Method for Operating a Hand-Held Power Tool

Abstract

A method is for operating a hand-held power tool that includes an electric motor. The method includes determining a signal of an operating parameter of the electric motor; determining an application class at least partly on the basis of the signal of the operating parameter; and providing comparative information at least partly on the basis of the application class including (i) providing at least one model-signal form, and (ii) providing a threshold value for correspondence. The model-signal form can be assigned to an established state in the progress of the work performed by the hand-held power tool. The method further includes comparing the signal of the operating parameter with the model-signal form and determining a correspondence evaluation from the comparison. The correspondence evaluation is at least partly based on the threshold value for correspondence.

Claims

1. A method for operating a handheld power tool comprising an electric motor, the method comprising: determining a signal of an operating variable of the electric motor; determining an application class at least partially based on the signal of the operating variable; providing comparison information at least partially based on the application class by (i) providing at least one model signal shape configured to be associated with a defined work status of the handheld power tool, and (ii) providing a threshold value of a match; comparing the signal of the operating variable with the at least one model signal shape and determining a match rating from the comparison, wherein the match rating takes place at least partially based on the threshold value of the match; and ascertaining the defined work status at least partially based on the determined match rating.

2. The method as claimed in claim 1, further comprising: executing a machine learning phase based on at least two or more exemplary applications, wherein the exemplary applications comprise reaching the defined work status; wherein the determining of the application class and the provision of the at least one model signal shape and/or the threshold value of the match takes place at least partially based on application classes generated in the machine learning phase and of the threshold values of the match and/or model signal shapes associated with the application classes.

3. The method as claimed in claim 2, the executing the machine learning phase further comprising: saving and classifying signals, associated with the exemplary applications, of the operating variable in at least one or more of the application classes.

4. The method as claimed in claim 3, the executing the machine learning phase further comprising: determining, saving, and classifying the model signal shapes, associated with the exemplary applications, at least partially based on a respective signal of the operating variable at a time the defined work status is reached.

5. The method as claimed in claim 2, the executing the machine learning phase further comprising: determining, saving, and classifying the threshold values, associated with the exemplary applications, of the match, at least partially based on a respective signal of the operating variable at a time the defined work status is reached.

6. The method as claimed in claim 2, the executing the machine learning phase further comprising: determining and saving threshold values, associated with the application classes, of the match, based on the saved threshold values of the match and the model signal shapes associated with the exemplary applications.

7. The method as claimed in claim 1, further comprising: executing a first routine of the handheld power tool at least partially based on the ascertained work status.

8. The method as claimed in claim 7, further comprising: collecting an assessment of a user of the handheld power tool relating to a quality of the executed first routine, and optimizing the first routine at least partially based on the assessment.

9. The method as claimed in claim 6, wherein a control unit of the handheld power tool and/or on a central computer determines, saves, and classifies the model signal shapes.

10. The method as claimed in claim 2, wherein the exemplary applications are executed by a user of the handheld power tool and/or read from a database.

11. The method as claimed in claim 7, wherein the first routine comprises: stopping the electric motor within a defined and/or presettable parameter, wherein the parameter is presettable by a user of the handheld power tool.

12. The method as claimed in claim 11, wherein the first routine further comprises: changing a speed of the electric motor.

13. The method as claimed in claim 12, wherein: the change in the speed of the electric motor takes place multiply and/or dynamically, successively in time, and/or along a characteristic curve of the change in speed and/or depending on the defined work status of the handheld power tool, and the change in the speed is determined at least partially via a learning operation based on the exemplary applications.

14. The method as claimed in claim 1, wherein the operating variable is a speed of the electric motor or an operating variable that correlates with the speed.

15. The method as claimed in claim 1, wherein the signal of the operating variable is determined as a time series of measured values of the operating variable, or as measured values of the operating variable as a variable of the electric motor that correlates with the time series.

16. The method as claimed in claim 1, wherein: the signal of the operating variable is determined as a time series of measured values of the operating variable, and the time series of the measured values of the operating variable is transformed into a series of the measured values of the operating variable as a variable of the electric motor that correlates with the time series.

17. The method as claimed in claim 1, wherein the handheld power tool is an impact driver, and a first operating state is impact operation.

18. A handheld power tool comprising: an electric motor; a measured-value pickup for an operating variable of the electric motor; and a control unit configured to operate the handheld power tool, the control unit configured to: determine a signal of the operating variable of the electric motor; determine an application class at least partially based on the signal of the operating variable; provide comparison information at least partially based on the application class by (i) providing at least one model signal shape configured to be associated with a defined work status of the handheld power tool, and (ii) providing a threshold value of a match; compare the signal of the operating variable with the at least one model signal shape and determining a match rating from the comparison, wherein the match rating takes place at least partially based on the threshold value of the match; and ascertain the defined work status at least partially based on the determined match rating.

Description

DRAWINGS

[0107] The invention is explained in more detail in the following text on the basis of preferred exemplary embodiments. In the schematic drawings:

[0108] FIG. 1 shows a schematic illustration of an electric handheld power tool;

[0109] FIG. 2(a) shows a work status of an exemplary application and an associated signal of an operating variable;

[0110] FIG. 2(b) shows a match of the signal, shown in FIG. 2(a), of the operating variable with a model signal;

[0111] FIG. 3 shows a work status of an exemplary application and two associated signals of operating variables;

[0112] FIG. 4 shows curves of signals of an operating variable according to two embodiments of the invention;

[0113] FIG. 5 shows curves of signals of an operating variable according to two embodiments of the invention;

[0114] FIG. 6 shows a work status of an exemplary application and two associated signals of operating variables;

[0115] FIG. 7 shows curves of signals of two operating variables according to two embodiments of the invention;

[0116] FIG. 8 shows curves of signals of two operating variables according to two embodiments of the invention;

[0117] FIG. 9 shows a schematic illustration of two different recordings of the signal of the operating variable;

[0118] FIG. 10(a) shows a signal of an operating variable;

[0119] FIG. 10(b) shows an amplitude function of a first frequency contained in the signal in FIG. 10(a);

[0120] FIG. 10(c) shows an amplitude function of a second frequency contained in the signal in FIG. 10(a);

[0121] FIG. 11 shows a joint illustration of a signal of an operating variable and an output signal of bandpass filtering, based on a model signal;

[0122] FIG. 12 shows a joint illustration of a signal of an operating variable and an output of a frequency analysis, based on a model signal;

[0123] FIG. 13 shows a joint illustration of a signal of an operating variable and of a model signal for the parameter estimation; and

[0124] FIG. 14 shows a joint illustration of a signal of an operating variable and of a model signal for cross-correlation.

[0125] FIG. 1 shows a handheld power tool 100 according to the invention, which has a housing 105 with a handle 115. According to the illustrated embodiment, to be supplied with power independently of the grid, the handheld power tool 100 is connectable mechanically and electrically to a battery pack 190. In FIG. 1, the handheld power tool 100 is in the form for example of a battery-powered rotary impact driver. However, it should be noted that the present invention is not limited to battery-powered rotary impact drivers, but can be used in principle in handheld power tools 100 in which it is necessary to ascertain a work status, for instance impact drills.

[0126] Arranged in the housing 105 are an electric motor 180, supplied with power by the battery pack 190, and a transmission 170. The electric motor 180 is connected to an input spindle via the transmission 170. Furthermore, a control unit 370 is arranged within the housing 105 in the region of the battery pack 190, said control unit 370, for the open-loop and/or closed-loop control of the electric motor 180 and the transmission 170, acting thereon for example by means of a set motor speed n, a selected angular momentum, a desired gear x or the like.

[0127] The electric motor 180 is actuable, i.e. able to be switched on and off, for example via a manual switch 195, and may be any desired type of motor, for example an electronically commutated motor or a DC motor. In principle, the electric motor 180 is able to be subjected to electronic open-loop and/or closed-loop control such that both reversing operation and specifications with regard to the desired motor speed n and the desired angular momentum are realizable. The manner of operation and the structure of a suitable electric motor are sufficiently well known from the prior art and so will not be described in detail here in order to keep the description concise.

[0128] Via an input spindle and an output spindle, a tool receptacle 140 is mounted rotatably in the housing 105. The tool receptacle 140 serves to receive a tool and can be integrally formed directly on the output spindle or connected thereto in the form of an attachment.

[0129] The control unit 370 is connected to a power source and is configured such that it can subject the electric motor 180 to electronic open-loop and/or closed-loop control by means of various current signals. The various current signals provide for different angular momentums of the electric motor 180, wherein the current signals are passed to the electric motor 180 via a control line. The power source may be in the form for example of a battery or, as in the illustrated exemplary embodiment, in the form of a battery pack 190 or of a connection to the grid.

[0130] Furthermore, control elements (not illustrated in detail) may be provided in order to set different operating modes and/or the direction of rotation of the electric motor 180.

[0131] According to one aspect of the invention, a method for operating a handheld power tool 100 is provided, by means of which a work status for example of the handheld power tool 100 illustrated in FIG. 1 can be established during use, for example a screwing-in or unscrewing operation.

[0132] As a consequence of the establishment of the work status, in embodiments of the invention, corresponding reactions or routines are initiated by the machine. As a result, reliably reproducible, high-quality screwing-in and unscrewing operations can be achieved. Aspects of the method are based, inter alia, on an investigation of signal shapes and a determination of a degree of matching of these signal shapes, which may correspond for example to an evaluation of onward rotation of an element, for instance a screw, driven by the handheld power tool 100.

[0133] FIG. 2 illustrates, in this regard, an example of a signal of an operating variable 200 of an electric motor 180 of a rotary impact driver, as occurs in this way or in a similar form when a rotary impact driver is used as intended. While the following statements relate to a rotary impact driver, in the context of the invention, they also apply, mutatis mutandis, to other handheld power tools 100, for example impact drills.

[0134] Time is plotted as reference variable on the abscissa x in the present example in FIG. 2. In an alternative embodiment, however, a variable correlated with time is plotted as reference variable, for example the rotational angle of the tool receptacle 140, the rotational angle of the electric motor 180, an acceleration, a jerk, in particular a higher order jerk, an output, or an energy. The motor speed n that applies at any time is plotted on the ordinate f(x) in the figure. Rather than the motor speed, it is also possible for some other operating variable that correlates with the motor speed to be chosen. In alternative embodiments of the invention, f(x) represents for example a signal of the motor current.

[0135] The motor speed and motor current are operating variables that are usually captured without additional effort by a control unit 370 in handheld power tools 100. The provision of a signal of an operating variable 200 of the electric motor 180 is referred to as method step S1 in the context of the present disclosure. “Providing” is understood in this context as making available the corresponding feature in an internal or external memory of the handheld power tool 100.

[0136] In preferred embodiments of the invention, a user of the handheld power tool 100 can select the operating variable on the basis of which the method according to the invention is intended to be carried out.

[0137] FIG. 2(a) shows an application involving a loose fastening element, for example a screw 900, in a fastening carrier 902, for example a wooden board. It is apparent from FIG. 2(a) that the signal comprises a first region 310 which is characterized by a monotonic increase in the motor speed, and by a region with a comparatively constant motor speed, which may also be referred to as a plateau. The intersection point between the abscissa x and ordinate f(x) in FIG. 2(a) corresponds, during the screwdriving operation, to the starting of the rotary impact driver.

[0138] In the first region 310, the screw 900 encounters relatively little resistance in the fastening carrier 902, and the torque required for screwing it in lies beneath the disengagement torque of the rotary impact mechanism. The curve of the motor speed in the first region 310 thus corresponds to the operating state of screwdriving without impact.

[0139] As is apparent from FIG. 2(a), the head of the screw 900 is not in contact with the fastening carrier 902 in the region 322, meaning that the screw 900 being driven by the rotary impact driver is rotated onward with each impact. This additional rotational angle can become smaller as the work operation continues, this being reflected in the figure by a decreasing period duration. Moreover, further screwing in can also be indicated by a speed that decreases on average.

[0140] If the head of the screw 900 subsequently reaches the substrate 902, an even higher torque and thus more impact energy is required for further screwing in. Since, however, the handheld power tool 100 does not supply any more impact energy, the screw 900 no longer rotates onward or rotates onward only through a significantly smaller rotational angle.

[0141] The rotary impact operation executed in the second 322 and third region 324 is characterized by an oscillating curve of the signal of the operating variable 200, wherein the shape of the oscillation can be for example trigonometric or other oscillation. In the present case, the oscillation has a curve that can be referred to as a modified trigonometric function. This characteristic shape of the signal of the operating variable 200 in impact screwdriving operation arises on account of the priming and releasing of the impact mechanism striker and the system chain, inter alia of the transmission 170, located between the impact mechanism and electric motor 180.

[0142] Using the circumstance that different cases of screwing each have characteristic shapes of the signals of the operating variables, in a step S2 of the method according to the invention, an application class is determined on the basis of the signal of the operating variable 200. In the case of a screwing process, the concept of the application class can in this case comprise, inter alia, one or more aspects such as screw size, screw type, screwing direction (screwing in or unscrewing), screw resistance, screwing speed, material of the screw substrate, and/or operating mode of the handheld power tool for the application executed by the user.

[0143] As can be gathered from the above, the individual work statuses, for example signal shapes associated with the starting of impact operation, are furthermore also characterized in principle by particular characteristic features, which are preset at least partially by the inherent properties of the rotary impact driver. In the method according to the invention, starting from this finding, in a step S3, comparison information is provided at least partially on the basis of the application class determined in step S2, wherein, in a step S3a, at least one model signal shape 240 is provided. The model signal shape 240 is in this case able to be associated with a work status, for example the achievement of the head of the screw 900 resting on the fastening carrier 902, and, in conjunction with some embodiments of the invention, the model signal shape 240 is also referred to as a state-typical model signal shape. In other words, the model signal shape 240 contains typical features for the work status, such as the existence of a waveform, vibration frequencies or amplitudes, or individual signal sequences in a continuous, quasi-continuous or discrete form.

[0144] In other applications, the work status to be detected can be characterized by other signal shapes than by vibrations, for instance by discontinuities or growth rates in the function f(x). In such cases, the state-typical model signal shape is characterized by these very parameters rather than by vibrations.

[0145] In a method step S3b, a further item of comparison information is provided, namely a threshold value of the match, which will be described in more detail below.

[0146] In a preferred configuration of the method according to the invention, in method step S3, the state-typical model signal shape 240 can be set by a user. The state-typical model signal shape 240 can likewise be stored or saved inside the device or provided by an external data device.

[0147] In a method step S4 of the method according to the invention, the signal of the operating variable 200 of the electric motor 180 is compared with the state-typical model signal shape 240. The feature “compare” should be understood to have a broad meaning in the context of the present invention and to be interpreted within the scope of signal analysis, such that a result of the comparison may in particular also be a partial or gradual match of the signal of the operating variable 200 of the electric motor 180 with the model signal shape 240, wherein the degree of matching of the two signals can be determined by different mathematical methods which will be described later.

[0148] In step S4, a match rating of the signal of the operating variable 200 of the electric motor 180 with the state-typical model signal shape 240 is moreover determined from the comparison and thus a statement can be made about the matching of the two signals. The match rating takes place in this case at least partially on the basis of the abovementioned threshold value of the match, which can thus also be understood as being the lower limit of the match of the signal of the operating variable 200 with the model signal shape 240 and is explained in more detail in the following text.

[0149] FIG. 2(b) shows a curve of a function q(x) of a match rating 201 that corresponds to the signal of the operating variable 200 in FIG. 2(a) and indicates, at every point on the abscissa x, a value of the match between the signal of the operating variable 200 of the electric motor 180 and the state-typical model signal shape 240.

[0150] In the present example of the screwing in of the screw 900, this rating is used to determine the amount of onward rotation upon an impact. The model signal shape 240 provided in step S3a corresponds in the example to an ideal impact without onward rotation, meaning the state in which the head of the screw 900 is in contact with the surface of the fastening carrier 902, as shown in the region 324 in FIG. 2(a). Accordingly, in region 324, there is a high match between the two signals, this being reflected by a constantly high value of the function q(x) of the match rating 201. By contrast, in the region 310, in which each impact is associated with large rotational angles of the screw 900, only small match values are achieved. The less the screw 900 rotates onward upon the impact, the higher this match is, this being discernible from the fact that the function q(x) of the match rating 201 already reproduces continuously increasing match values when the impact mechanism starts in the region 322, which is characterized by a rotational angle of the screw 200 that gets continuously smaller on each impact on account of the increasing screw-in resistance.

[0151] As is apparent from the example in FIG. 2, the match rating 201 of the signals for impact differentiation is highly suitable for this purpose on account of the more or less jumpy nature thereof, wherein this jumpy change is caused by the likewise more or less jumpy change in the onward rotational angle of the screw 900 at the end of the exemplary work operation. According to the invention, the ascertainment of the work status will take place at least partially on the basis of a comparison of the match rating 201 with the threshold value of the match provided in step S3b, which is indicated in FIG. 2(b) by a dashed line 202. In the present example of FIG. 2(b), the intersection point SP of the function q(x) of the match rating 201 with the line 202 is associated with the work status of the contact of the head of the screw 900 with the surface of the fastening carrier 902.

[0152] In a method step S5 of the method according to the invention, the work status is now ascertained at least partially on the basis of the match rating 201 determined in method step S4. It should be noted here that the function is not only limited to screwing-in applications but also includes a use in unscrewing applications.

[0153] The provision of the comparison information in step S3 can take place according to the invention at least partially on the basis of a machine learning phase. The machine learning phase includes, in embodiments of the invention, the execution or reading of at least two or more exemplary applications of the handheld power tool 100, wherein the at least one exemplary application comprises reaching a defined work status of the handheld power tool 100, for example reaching of the state in which the head of the screw 900 rests on the surface of the fastening carrier 902, as shown in region 324 of FIG. 2(a). The concept of the defined work status should nevertheless not be understood here as meaning that the work status absolutely has to be defined by a user. Rather, in advantageous embodiments of the invention, it is provided that the handheld power tool ascertains the defined work status automatically using data analysis methods on the basis of the exemplary applications, for example using the fact that, given a particular curve of the model signal shapes 200′ (corresponding for example to the head of the screw 900 resting on the fastening carrier 902), a reduction in the speed or switching off of the handheld power tool 100 takes place.

[0154] The method according to the invention accordingly comprises, in this embodiment, a step SM of executing a machine learning phase on the basis of at least two or more exemplary applications, wherein the exemplary applications comprise reaching the determined work status. In this embodiment, the determination of the application classes in step S2 and the provision of the model signal shape 240 and/or the threshold value of the match in step S3 takes place at least partially on the basis of application classes generated in the machine learning phase and of threshold values of the match and/or model signal shapes 240′ associated with the application classes.

[0155] The handheld power tool thus learns automatically or partially automatically the time at which, in different applications, a reaction to the curve of the match evaluation is desired, without the user needing to give a corresponding instruction.

[0156] In particular embodiments of the invention, the method step SM in this case advantageously comprises saving and classification of signals, associated with the exemplary applications, of the operating variable 200′ in at least one or more application classes.

[0157] Specific configurations of the method according to the invention can, for this purpose, contain one or more of the following method steps.

[0158] SMa determining, saving and classifying model signal shapes 240′, associated with the exemplary applications, at least partially on the basis of the respective signal of the operating variable 200′ at the time the defined work status is reached.

[0159] SMb determining, saving and classifying threshold values, associated with the exemplary applications, of the match, at least partially on the basis of the respective signal of the operating variable 200′ at the time the defined work status is reached.

[0160] SMc determining and saving threshold values, associated with the application classes, of the match, on the basis of the saved threshold values of the match and model signal shapes 240′ associated with the exemplary applications.

[0161] The steps SMa, SMb and SMc comprise different data analysis methods that are known per se, for example averaging or more advanced operation of explorative statistics, which generally provide a more accurate result the larger the set of exemplary applications. In this connection, it should be noted that the method steps SMa, SMb and SMc can take place selectively in a control unit of the handheld power tool 100 and/or on a central computer, in particular by transmitting the signals, determined in step S1 and associated with the exemplary applications, of the operating variable 200′ via an Internet connection. In this case, it is possible for particular steps of the method according to the invention, for example the above-mentioned data analysis for identifying the defined work status or the threshold values of the match not to be executed by the handheld power tool 100 but by a central computer node, and for the underlying set of exemplary applications to be maximized by combining exemplary applications received from different users and saved.

[0162] Conversely, such a procedure makes it possible for the exemplary applications to not necessarily need to be executed by a user of the handheld power tool 100. Rather, they can also be read directly from a database. In this case, the database can be both an external database connected for example via the Internet or an internal database, for example in the form of a database provided on the handheld power tool itself at the factory. Exemplary applications or data characterizing these exemplary applications and read from an external database are also referred to as “screw profiles” in connection with the present invention.

[0163] The basis of these embodiments is thus accumulation of the “wealth of experience” of the handheld power tool 100 by exemplary applications which are either executed by the handheld power tool 100 itself or are transmitted to the handheld power tool 100 in the form of datasets.

[0164] Put simply, in the first variant, the user carries out for example a multiplicity of screwing-in processes, wherein the handheld power tool 100 automatically and cumulatively executes data analyses to classify and categorize the applications, and to determine the model signal shapes 200′ and the threshold values of the match when the user carries out a repetitive routine, for example stops the handheld power tool 100 or reduces the speed. It should be noted here that this repetitive routine can itself likewise be used to classify and categorize the application. In subsequent applications which are likewise evaluated using this methodology, the handheld power tool 100 then automatically determines the application class, provides the comparison information associated with this application class, i.e. at least the model signal shape 240 and threshold value of the match, and, given a corresponding match evaluation of the currently existing signal of the operating variable 200 and of the model signal 240, automatically executes the routine carried out by the user in the particular application class, for example a reduction in the speed of the electric motor 180, as will be described in more detail below.

[0165] According to the invention, it is thus possible, by distinguishing and comparing signal shapes, to evaluate a work status of an element driven by a rotary impact driver and to initiate a routing following the work status, wherein particular signal shapes used here, namely the model signal shape 240, and a part of the evaluation criterion for matching the compared signal shapes, namely the threshold value of the match, are made available at least partially by a machine learning phase.

[0166] In one embodiment of the invention, it is provided that the machine learning phase in step SM comprises learning of the handheld power tool by way of images as part of “deep learning”. In this case, a suitable image capturing device and/or existing images of application sequences are used. In this case, the image capturing device can comprise an image sensor or a camera, with which the exemplary applications are optically captured, analyzed using the known image processing tools, and subsequently categorized. In a similar way, it is also possible, in step S2, to determine the application class with the aid of optical capturing by way of the image capturing device and subsequent image analysis. Conceivable image capturing devices may be internal image sensors or cameras, i.e. images sensors or cameras integrated in the handheld power tool, or external image sensors or cameras, for example the camera of a smartphone.

[0167] Advantageously, the establishment of the work status learned according to the above statements is supplemented by a further method step S6, in which a first routine of the handheld power tool 100 is executed at least partially on the basis of the work status ascertained in method step S5, as set out below. In this case, it is assumed in each case that the work status to be ascertained, as a result of which the handheld power tool executes the abovementioned first routine in method step S6, was defined by a machine learning phase as described above by way of the parameters of the model signal shape 240 and/or threshold value of the match. However, in alternative embodiments, it is likewise provided that the first routine is estimated, in unknown applications, with the aid of known applications with similar characteristics.

[0168] In spite of the resultant reduction in the speed on changing the operating state to impact operation, in the case for example of small wood screws or self-tapping screws, it is possible only with great difficulty to prevent the screw head from penetrating into the material. This is due to the fact that the impacts of the impact mechanism result in a high spindle speed, even with increasing torque.

[0169] This behavior is illustrated in FIG. 3. As in FIG. 2, time for example is plotted on the abscissa x, while a motor speed is plotted on the ordinate f(x) and the torque g(x) is plotted on the ordinate g(x). The graphs f and g accordingly indicate the curves of the motor speed f and of the torque g over time. In the lower region of FIG. 3, again similarly to the illustration in FIG. 2, different states during an operation of screwing a wood screw 900, 900′ and 900″ into a fastening carrier 902 are schematically illustrated.

[0170] In the “no impact” operating state, which is indicated by the reference sign 310 in the figure, the screw rotates at a high speed f and low torque g. In the “impact” operating state, indicated by the reference sign 320, the torque g increases rapidly, while the speed f decreases only slightly, as already noted above. The region 310′ in FIG. 3 indicates the region within which the impact ascertainment explained in connection with FIG. 2 takes place.

[0171] In order for example to prevent a screw head of the screw 900 from penetrating the fastening carrier 902, according to the invention, in the method step S6, an application-related, appropriate routine or reaction of the tool is executed at least partially on the basis of the work status ascertained in method step S5, for instance switching off of the machine, a change in the speed of the electric motor 180, and/or visual, audible and/or haptic feedback to the user of the handheld power tool 100.

[0172] In one embodiment of the invention, the first routine comprises the stopping of the electric motor 180 taking into consideration at least one defined and/or presettable parameter, in a particular a parameter that is presettable by a user of the handheld power tool.

[0173] As an example of this, stopping of the device immediately after the impact ascertainment 310′ is schematically shown in FIG. 4, with the result that the user is assisted in preventing the screw head from penetrating into the fastening carrier 902. In the figure, this is illustrated by the branch f′ of the graph f that drops rapidly after the region 310′.

[0174] An example of a defined and/or presettable parameter, in particular a parameter that is settable by a user of the handheld power tool 100, a time, defined by the user, after which the device stops, this being illustrated in FIG. 4 by the period T.sub.Stopp and the associated branch f″ of the graph f. Ideally, the handheld power tool 100 stops just such that the screw head is flush with the screw contact surface. Since the time until this case occurs is different from application to application, however, it is advantageous for the period T.sub.Stopp to be definable by the user.

[0175] Alternatively or in addition, in one embodiment of the invention, the first routine comprises a change, in particular a reduction and/or an increase, in a speed, in particular a setpoint speed, of the electric motor 180 and therefore also of the spindle speed after impact ascertainment. The embodiment in which a reduction in the speed is executed is illustrated in FIG. 5. Again, the handheld power tool 100 is initially operated in the “no impact” operating state 310, which is characterized by the curve, represented by the graph f, of the motor speed. After an impact has been ascertained in the region 310′, the motor speed is reduced in the example by a particular amplitude, this being illustrated by the graphs f′ and f″, respectively.

[0176] The amplitude or the level of the change in speed of the electric motor 180, characterized by Δ.sub.D for the branch f″ of the graph f in FIG. 5, can be set by the user in one embodiment of the invention. As a result of the reduction in the speed, the user has more time to react when the screw head approaches the surface of the fastening carrier 902. As soon as the user is of the opinion that the screw head is flush enough with the contact surface, they can stop the handheld power tool 100 with the aid of the switch. Compared to the stopping of the handheld power tool 100 after impact ascertainment, the change in motor speed, a reduction in the example of FIG. 5, has the advantage that, as a result of switching off being determined by the user, this routine is largely independent of the application.

[0177] In one embodiment of the invention, the amplitude Δ.sub.D of the change in speed of the electric motor 180 and/or a target value of the speed of the electric motor 180 is definable by a user of the handheld power tool 100, this increasing the flexibility of this routine further for the purposes of applicability for different applications.

[0178] The change in speed of the electric motor 180 takes place multiply and/or dynamically in embodiments of the invention. In particular provision may be made for the change in speed of the electric motor 180 to take place successively in time and/or along a characteristic curve of the change in speed, and/or depending on the work status of the handheld power tool 100.

[0179] Examples of this comprise, inter alia, combinations of a reduction in speed and an increase in speed. Moreover, different routines or combinations thereof can be executed in a time-offset manner for impact ascertainment. Furthermore, the invention also comprises embodiments in which there is a temporal offset between two or more routines. If, for example, the motor speed is reduced directly after impact ascertainment, the motor speed can also be increased again after a particular time value. Furthermore, embodiments are provided in which not only different routines themselves but also the time offset between the routines is preset by a characteristic curve.

[0180] As mentioned at the beginning, the invention comprises embodiments in which the work status is characterized by a change from an “impact” operating state in a region 320 to the “no impact” operating state in a region 310, this being illustrated in FIG. 6.

[0181] Such a transition of the operating states of the handheld power tool 100 is given for example in a work status in which a screw 900 is released from a fastening carrier 902, i.e. during an unscrewing operation, this being schematically illustrated in the lower region of FIG. 6. As also in FIG. 3, in FIG. 6 the graph f represents the speed of the electric motor 180 and the graph g represents the torque.

[0182] As already explained in connection with other embodiments of the invention, the operating state of the handheld power tool, in the present case the operating state of the impact mechanism, is also ascertained here with the aid of the discovery of characteristic signal shapes.

[0183] In the “impact” operating state, i.e. in the region 320 in FIG. 6, the screw 900 does not rotate and a high torque g is applied. In other words, the spindle speed is equal to zero in this state. In the “no impact” operating state, i.e. in the region 310 in FIG. 6, the torque g rapidly drops, this in turn providing for an equally rapid increase in the spindle and motor torque f. As a result of this rapid increase in the motor torque f, caused by the reduction in the torque g from the time at which the screw 900 is released from the fastening carrier 902, it is often difficult for a user to capture the screw 900 or nut being released and prevent it from dropping down.

[0184] The method according to the invention can be applied in order to prevent a threaded means, which may be a screw 900 or a nut, from being unscrewed so rapidly after being released from the fastening carrier 902 that it drops down. In this regard, reference is made to FIG. 7. FIG. 7 corresponds substantially to FIG. 6 in terms of the illustrated axes and graphs, and corresponding reference signs indicate corresponding features.

[0185] In one embodiment, the routine in step S6 comprises the stopping of the handheld power tool 100 immediately after it has been established that the handheld power tool 100 has ascertained the work status to be ascertained, in the example the “no impact” operating mode, this being illustrated in FIG. 7 by a steeply falling branch f′ of the graph f of the motor speed in the region 310. In alternative embodiments, the user can define a time T.sub.Stopp after which the device stops. In the figure, this is illustrated by the branch f″ of the graph f of the motor speed. A person skilled in the art recognizes that the motor speed, as also shown in FIG. 6, initially increases rapidly after the transition from the region 320 (“impact” operating state) to the region 310 (“no impact” operating state) and drops steeply after expiry of the time period T.sub.Stopp.

[0186] Given a suitable selection of the time period T.sub.Stopp, it is possible for the motor speed to drop to “zero” precisely when the screw 900 or the nut is still located in the thread. In this case, the user can remove the screw 900 or the nut by way of a few thread revolutions or alternatively leave it in the thread in order, for example, to open a clamp.

[0187] A further embodiment of the invention is described in the following text with reference to FIG. 8. In this case, after the transition from the region 320 (“impact” operating state) to the region 310 (“no impact” operating state), a reduction in the motor speed takes place. The amplitude or amount of the reduction is specified in the figure with Δ.sub.D as a measure between an average f″ of the motor speed in the region 320 and the reduced motor speed f′. This reduction can be set by the user in certain embodiments, in particular by specifying a target value of the speed of the handheld power tool 100, which lies at the level of the branch f′ in FIG. 8.

[0188] As a result of the reduction in the motor speed and thus also in the spindle speed, the user has more time to react when the head of the screw 900 is released from the screw contact surface. As soon as the user is of the opinion that the screw head or the nut has been screwed far enough, they can use the switch to stop the handheld power tool 100.

[0189] Compared with the embodiments described in connection with FIG. 7, in which the handheld power tool 100 is stopped immediately or with a delay after the transition from the region 320 (“impact” operating state) to the region 310 (“no impact” operating state), the reduction in speed has the advantage of greater independence from the application, since it is ultimately the user who determines when the handheld power tool is switched off after the reduction in speed. This can be helpful for example in the case of long threaded rods. Here, there are applications in which, after the releasing of the threaded rod and the associated stopping of the impact mechanism, a more or less long unscrewing process still needs to be carried out. Switching off the handheld power tool 100 after stopping the impact mechanism would thus not be appropriate in these cases.

[0190] It should be mentioned that, in some embodiments of the invention, it is provided that the parameters, used in method step S6, of the first routine as described above, for example curve and amplitude of a reduction or increase in speed, can also be defined by a machine learning phase on the basis of exemplary applications and/or screw profiles.

[0191] Furthermore, by way of a further method step S7, in which a quality evaluation of the user of the handheld power tool 100 relating to the first routine executed in step S6 is collected, the routine can be optimized at least partially on the basis of the evaluation.

[0192] In some embodiments of the invention, a work status is output to a user of the handheld power tool by means of an output device of the handheld power tool.

[0193] A number of technical relationships and embodiments relating to the execution of method steps S1-S5 are explained in the following text.

[0194] In practical applications, provision may be made for one or more of the method steps S1 to S4 to be executed repetitively during operation of the handheld power tool 100, in order to monitor the work status of the executed application. For this purpose, in method step S1, the determined signal of the operating variable 200 may be segmented such that method steps S2 and S4 are executed on signal segments, preferably always of an identical, fixed length.

[0195] For this purpose, the signal of the operating variable 200 can be stored as a sequence of measured values in a memory, preferably a ring memory. In this embodiment, the handheld power tool 100 comprises the memory, preferably the ring memory.

[0196] As already mentioned in connection with FIG. 2, in preferred embodiments of the invention, in method step S1, the signal of the operating variable 200 is determined as a time series of measured values of the operating variable, or as measured values of the operating variable as a variable of the electric motor 180 that correlates with the time series. In this case, the measured values may be discrete, quasi continuous or continuous.

[0197] In one embodiment, the signal of the operating variable 200 is captured in method step S1 as a time series of measured values of the operating variable, and in a method step S1a following the method step S1, the time series of the measured values of the operating variable is transformed into a series of the measured values of the operating variable as a variable of the electric motor 180 that correlates with the time series, for example a rotational angle of the tool receptacle 140, the motor rotational angle, an acceleration, a jerk, in particular a higher order jerk, an output, or an energy.

[0198] The advantages of this embodiment are described in the following text with reference to FIG. 9. Similarly to FIG. 2, FIG. 9a shows signals f(x) of an operating variable 200 over an abscissa x, in this case over time t. As in FIG. 2, the operating variable may be a motor speed or a parameter that correlates with the motor speed.

[0199] The depiction contains two signal curves of the operating variable 200, which can each be associated with a work status, thus for example the rotary impact screwdriving mode in the case of a rotary impact driver. In both cases, the signal comprises a wavelength of a waveform assumed to be sinusoidal under ideal conditions, wherein the signal with a shorter wavelength, T1 has a curve with a higher impact frequency, and the signal with a longer wavelength, T2 has a curve with a lower impact frequency.

[0200] Both signals can be generated with the same handheld power tool 100 at different motor speeds and are dependent, inter alia, on the speed of rotation that the user requests via the operating switch of the handheld power tool 100.

[0201] If, for example, the parameter “wavelength” is now used for the definition of the state-typical model signal shape 240, at least two different wavelengths T1 and T2 would have to be stored, in the present case, as possible parts of the state-typical model signal shape, in order that the comparison of the signal of the operating variable 200 with the state-typical model signal shape 240 results in both cases in the result of a “match”. Since the motor speed can change generally and significantly over time, this means that the desired wavelength also varies and as a result the methods for ascertaining this impact frequency would accordingly have to be set adaptively.

[0202] Given a large number of possible wavelengths, the complexity of the method and of the programming would accordingly increase rapidly.

[0203] Therefore, in the preferred embodiment, the time values of the abscissa are transformed into values that correlate with the time values, for example acceleration values, higher order jerk values, output values, energy values, frequency values, rotational angle values of the tool receptacle 140 or rotational angle values of the electric motor 180. This is possible because the fixed transmission ratio of the electric motor 180 to the impact mechanism and to the tool receptacle 140 results in a direct, known dependence of the motor speed with respect to the impact frequency. As a result of this standardization, a vibration signal, independent of the motor speed, of constant periodicity is achieved, this being illustrated in FIG. 3b by way of the two from the transformation of the signals belonging to T1 and T2, wherein the two signals now have the same wavelength P1=P2.

[0204] Accordingly, in this embodiment of the invention, the state-typical model signal shape 240 can be defined, valid for all speeds, by way of a single parameter of the wavelength over the variable that correlates with time, for example the rotational angle of the tool receptacle 140, the motor rotational angle, an acceleration, a jerk, in particular a higher order jerk, an output, or an energy.

[0205] In a preferred embodiment, the comparison of the signal of the operating variable 200 in method step S4 takes place using a comparison method, wherein the comparison method comprises at least a frequency-based comparison method and/or a comparative comparison method. The comparison method compares the signal of the operating variable 200 with the state-typical model signal shape 240 to determine whether at least the threshold value of the match has been fulfilled. The comparison method compares the measured signal of the operating variable 200 with the threshold value of the match. The frequency-based comparison method comprises at least the bandpass filtering and/or the frequency analysis. The comparative comparison method comprises at least the parameter estimation and/or the cross-correlation. The frequency-based comparison method and the comparative comparison method are described in more detail in the following text.

[0206] In embodiments with bandpass filtering, the input signal transformed, optionally as described, into a variable that correlates with time is filtered via one or more bandpasses, the pass bands of which match one or more state-typical model signal shapes. The pass band results from the state-typical model signal shape 240. It is also conceivable for the pass band to match a frequency stored in connection with the state-typical model signal shape 240. In the event that amplitudes of this frequency exceed a previously set limit value, as is the case upon reaching the work status to be ascertained, the comparison in method step S4 then leads to the result that the signal of the operating variable 200 is equal to the state-typical model signal shape 240 and that therefore the work status to be ascertained has been reached. The setting of an amplitude limit value can, in this embodiment, be understood as being the determination of the match rating of the state-typical model signal shape 240 with the signal of the operating variable 200, on the basis of which a decision is taken in method step S5 as to whether the work status to be ascertained exists or not.

[0207] With reference to FIG. 10, the embodiment is intended to be explained in which the frequency analysis is used as frequency-based comparison method. In this case, the signal of the operating variable 200, which is illustrated in FIG. 10(a) and corresponds for example to the curve of the speed of the electric motor 180 over time, is transformed, on the basis of the frequency analysis, for example the fast-Fourier transformation (FFT), from a time range into the frequency range with corresponding weighting of the frequencies. In this case, the term “time range” according to the above statements should be understood as meaning both “curve of the operating variable over time” and “curve of the operating variable as a variable that correlates with time”.

[0208] The frequency analysis in this form is sufficiently well known as a mathematical tool of signal analysis from many fields in the art and is used, inter alia, to approximate measured signals as series expansions of weighted periodic, harmonic functions of different wavelengths. In FIGS. 10(b) and 10(c), for example, weighting factors κ.sub.1(x) and κ.sub.2(x) indicate, as functional curves 203 and 204 over time, whether and to what extent the corresponding frequencies or frequency bands, which are not specified at this point for the sake of clarity, exist in the investigated signal, i.e. the curve of the operating variable 200.

[0209] With regard to the method according to the invention, it is thus possible, with the aid of the frequency analysis, to determine whether and with what amplitude the frequency associated with the state-typical model signal shape 240 exists in the signal of the operating variable 200. Furthermore, however, it is also possible for frequencies to be defined, the non-existence of which is a measure of the presence of the work status to be ascertained. As mentioned in connection with the bandpass filtering, a limit value of the amplitude can be set, which is a measure of the degree of matching of the signal of the operating variable 200 with the state-typical model signal shape 240.

[0210] In the example in FIG. 10(b) for instance, the amplitude κ.sub.1(x) of a first frequency, typically not to be found in the state-typical model signal shape 240, in the signal of the operating variable 200 drops, at the time t.sub.2 (point SP.sub.2), below an associated limit value 203(a), this being, in the example, a necessary but insufficient criterion for the presence of the work status to be ascertained. At the time t.sub.3 (point SP.sub.3), the amplitude κ.sub.2(x) of a second frequency, typically to be found in the state-typical model signal shape 240, in the signal of the operating variable 200 exceeds an associated limit value 204(a). In the associated embodiment of the invention, the common presence of the dropping below and exceeding of the limit values 203(a), 204(a) by the amplitude functions κ.sub.1(x) and κ.sub.2(x), respectively, is the decisive criterion for the match rating of the signal of the operating variable 200 with the state-typical model signal shape 240. Accordingly, in this case, it is established in method step S5 that the work status to be ascertained has been reached.

[0211] In alternative embodiments of the invention, only one of these criteria is used, or combinations of one of the criteria or of both criteria with other criteria, for example the reaching of a setpoint speed of the electric motor 180.

[0212] In embodiments in which the comparative comparison method is used, the signal of the operating variable 200 is compared with the state-typical model signal shape 240 in order to find out whether the measured signal of the operating variable 200 has an at least 50% match with the state-typical model signal shape 240 and thus the predefined threshold value has been reached. It is also conceivable for the signal of the operating variable 200 to be compared with the state-typical model signal shape 240 in order to determine a match of the two signals with one another.

[0213] In embodiments of the method according to the invention in which the parameter estimation is used as the comparative comparison method, the measured signal of the operating variables 200 is compared with the state-typical model signal shape 240, wherein parameters estimated for the state-typical model signal shape 240 are identified. With the aid of the estimated parameters, a measure of the matching of the measure signal of the operating variables 200 with the state-typical model signal shape 240 can be determined, to find out whether the work status to be ascertained has been reached. The parameter estimation is based in this case on curve fitting, which is a mathematical optimization method known to a person skilled in the art. The mathematical optimization method makes it possible, with the aid of the estimated parameters, to adapt the state-typical model signal shape 240 to a series of measurement data from the signal of the operating variable 200. Depending on the degree of matching of the state-typical model signal shape 240 parameterized by means of the estimated parameters and a limit value, the decision as to whether the work status to be ascertained has been reached can be taken.

[0214] With the aid of the curve fitting of the comparative method of parameter estimation, it is also possible to determine a degree of matching of the estimated parameters of the state-typical model signal shape 240 with respect to the measured signal of the operating variable 200.

[0215] In one embodiment of the method according to the invention, the cross-correlation method is used as comparative comparison method in method step S4. Like the mathematical methods described above, the cross-correlation method is known per se to a person skilled in the art. In the cross-correlation method, the state-signal model signal shape 240 is correlated with the measured signal of the operating variable 200.

[0216] Compared with the method, set out above, of parameter estimation, this result of the cross-correlation is again a signal sequence with a signal length added up from a length of the signal of the operating variable 200 and the state-typical model signal shape 240, which represents the similarity of the time-shifted input signals. In this case, the maximum of this output sequence represents the time of the greatest match of the two signals, i.e. of the signal of the operating variable 200 and the state-typical model signal shape 240, and is therefore also a measure for the correlation itself, which is used, in this embodiment, in method step S5, as a decision criterion for the reaching of the work status to be ascertained. In the implementation in the method according to the invention, a significant difference from the parameter estimation is that any desired state-typical model signal shapes can be used for the cross-correlation, while, in the parameter estimation, the state-typical model signal shape 240 has to be able to be represented by parameterizable mathematical functions.

[0217] FIG. 11 shows the measured signal of the operating variable 200 for the case in which bandpass filtering is used as the frequency-based comparison method. In this case, as the abscissa x, the time or a variable that correlates with time is plotted. FIG. 11a shows the measured signal of the operating variable, as an input signal of the bandpass filtering, wherein, in the first region 310, the handheld power tool 100 is operated in screwdriving operation. In the second region 320, the handheld power tool 100 is operated in rotary impact operation. FIG. 11b illustrates the output signal after the bandpass has filtered in the input signal.

[0218] FIG. 12 illustrates the measured signal of the operating variable 200 for the case in which frequency analysis is used as the frequency-based comparison method. In FIGS. 12a and b, the first region 310 is shown, in which the handheld power tool 100 is in screwdriving operation. The time t or a variable that is correlated with time is plotted on the abscissa x in FIG. 6a. In FIG. 12b, the signal of the operating variable 200 is illustrated in a transformed form, wherein it is possible to transform for example by means of a fast-Fourier transformation from a time range into a frequency range. Plotted on the abscissa x′ in FIG. 12b is for example the frequency f, such that the amplitudes of the signal of the operating variable 200 are illustrated. In FIGS. 12c and d, the second region 320 is illustrated, in which the handheld power tool 100 is in rotary impact operation. FIG. 12c shows the measured signal of the operating variable 200 plotted over time in rotary impact operation. FIG. 12d shows the transformed signal of the operating variable 200, wherein the signal of the operating variable 200 is plotted over the frequency f as abscissa x′. FIG. 12d shows characteristic amplitudes for rotary impact operation.

[0219] FIG. 13a shows a typical case of a comparison by means of the comparative comparison method of parameter estimation between the signal of an operating variable 200 and a state-typical model signal shape 240 in the first region 310 described in FIG. 2. While the state-typical model signal shape 240 has a substantially trigonometric curve, the signal of the operating variable 200 has a curve that differs greatly therefrom. Independently of the selection of one of the above-described comparison methods, the comparison, carried out in method step S4, between the state-typical model signal shape 240 and the signal of the operating variable 200 has in this case the result that the degree of matching of the two signals is so low that, in method step S5, the work status to be ascertained is not ascertained.

[0220] FIG. 13b, by contrast, illustrates the case in which the work status to be ascertained is present and therefore the state-typical model signal shape 240 and the signal of the operating variable 200 have overall a high degree of matching, even if deviations are able to be found at individual measuring points. Thus, in the comparative comparison method of parameter estimation, the decision can be taken as to whether the work status to be ascertained has been reached.

[0221] FIG. 14 shows the comparison of the state-typical model signal shape 240, see FIGS. 14b and 14e, with the measured signal of the operating variable 200, see FIGS. 14a and 14d, for the case in which cross-correlation is used as comparative comparison method. In FIGS. 14a-f, the time or a variable that correlates with time is plotted on the abscissa x. In FIGS. 14a-c, the first region 310, corresponding to screwdriving operation, is shown. In FIGS. 14d-f, the third region 324, corresponding to the work status to be ascertained, is shown. As described above, the measured signal of the operating variable, FIG. 14a and FIG. 14d, is correlated with the state-typical model signal shape, FIGS. 14b and 14e. In FIGS. 14c and 14f, respective results of the correlations are illustrated. In FIG. 14c, the result of the correlation during the first region 310 is shown, wherein it is apparent that there is a low match between the two signals. In the example in FIG. 14c, therefore, the decision is taken in method step S5 that the work status to be ascertained has not been reached. In FIG. 14f, the result of the correlation during the third region 324 is shown. It is apparent from FIG. 14f that there is a high match, and so the decision is taken in method step S5 that the work status to be ascertained has been reached.

[0222] The invention is not limited to the exemplary embodiment described and illustrated. Rather, it encompasses all developments that a person skilled in the art might make in the scope of the invention defined by the claims.

[0223] In addition to the embodiments described and depicted, further embodiments are conceivable, which may encompass further modifications and combinations of features.