Method for Calculating an Excavation Volume

Abstract

A method calculates an excavation volume that was excavated by a construction machine using a tool. A motion trajectory of the tool over time is determined using one or more of the following sensors: inertial measurement unit, angle sensors, and linear sensors. At least part of the motion trajectory is classified based on machine load data as an excavation trajectory during which excavation occurs. The excavation volume is calculated using the excavation trajectory and dimensions of the tool.

Claims

1. A method for calculating an excavation volume, which was excavated by a construction machine using a tool, the method comprising: determining a motion trajectory of the tool over time using at least one of an inertial measuring unit, angle sensors, and linear sensors; classifying at least a part of the determined motion trajectory based on machine load data as an excavation trajectory, during which an excavation occurs; and calculating the excavation volume based on the excavation trajectory and dimensions of the tool.

2. The method as claimed in claim 1, wherein the motion trajectory is determined based on an algorithm for determining a kinematic chain of the construction machine.

3. The method as claimed in claim 1, wherein the machine load data comprise physical data of the construction machine and/or of the tool.

4. The method as claimed in claim 1, wherein the classifying takes place via static conditions.

5. The method as claimed in claim 1, wherein the classifying takes place via machine learning.

6. The method as claimed in claim 1, wherein during the classifying, a type of material to be excavated is considered.

7. The method as claimed in claim 1, wherein a measurement of quantities is calculated and includes summing the excavation volume for several operating procedures of the construction machine.

8. The method as claimed in claim 1, wherein a measurement of quantities is calculated and includes calculating a space integral for the excavation volumes between a first and a last operating cycle of the construction machine.

9. The method as claimed in claim 7, wherein the measurement of quantities is used for an automated billing of an amount of work for excavating an excavated material.

10. The method as claimed in claim 1, further comprising: outputting a control signal as a function of the calculated excavation volume.

11. The method as claimed in claim 1, wherein a computer program is configured to perform the method.

12. The method as claimed in claim 11, wherein the computer program is stored on a non-transitory machine-readable storage medium.

13. The method as claimed in claim 1, wherein an electronic control device, is configured to calculate the excavation volume using the method.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Exemplary embodiments of the invention are illustrated in the drawings and are described in more detail in the following description.

[0027] FIG. 1 shows a schematic illustration of a construction machine and of an excavation volume.

[0028] FIG. 2 shows a flow chart of an embodiment of the method according to the invention.

[0029] FIG. 3 shows a flow chart of a further embodiment of the method according to the invention.

[0030] FIG. 4 shows a flow chart according to an exemplary embodiment, which connects to one of the flow charts from FIG. 2 or FIG. 3.

[0031] FIG. 5 shows a further flow chart according to a further exemplary embodiment, which connects to one of the flow charts from FIG. 2 or FIG. 3.

EXEMPLARY EMBODIMENTS OF THE INVENTION

[0032] FIG. 1 shows a schematic illustration of a construction machine 1 in the form of an excavator comprising a tool 2, which is formed as a shovel. The tool 2 is movably connected to the construction machine 1 via a multi-member working arm 3. The construction machine 1, the working arm 3, and the tool 2 form a kinematic chain. An inertial sensor 4 of an inertial measuring unit is in each case arranged on each member of the kinematic chain. The inertial sensors are connected to an electronic control device 5 and send sensor signals to it.

[0033] The construction machine 1 uses the tool 2 to excavate an excavation pit BG. A tool center point of the tool 2 thereby moves along a motion trajectory BT. The tool center point is a cutting edge tool 2 and the position of the tool center point in space is determined and tracked by means of the sensors 4 over time. An excavation trajectory AT is part of the motion trajectory BT and is characterized in that an excavation occurs and material is received in the tool 2 during the movement of the tool 2 along the excavation trajectory AT.

[0034] Moreover, an excavation volume AV is illustrated, which is excavated by the tool 2 by means of the excavation along the excavation trajectory. The excavation pit BG is thus expanded by this excavation volume AV. The excavation volume AV is calculated by means of the method according to the invention, as shown below. In addition to the currently excavated AV, previous excavation volumes FAV are also shown, by means of which the excavation pit BG was created.

[0035] FIG. 2 shows a flow chart of a first embodiment of the method according to the invention. At the beginning and during the entire method, the position of the tool center point of the tool 2 is determined 10 as an algorithm for determining the kinematic chain by means of the tool center point estimation. The sensor data of the inertial sensors 4 along the kinematic chain are used for this purpose, and the position and the orientation of the tool in space are then determined from the orientation and the position of the members by means of so-called Denavit-Hartenberg parameters (see, for example, Spong et al. “Robot modeling and control”, Vol. 3. New York: Wiley, 2006). The position of the tool 2, thus of the tool center point, is recorded over time and a motion trajectory BT of the tool 2 is determined 11 therefrom.

[0036] This is followed by a classification 12 by means of machine load data MD, which, in this embodiment, takes place with the help of thresholds S. During the classification 12, a division of the motion trajectory BT into the excavation trajectory AT takes place, at which an excavation occurs, and into other trajectories ST, at which no excavation occurs, but the tool 2 is moved, for example, into the excavation pit BG or to an unloading point (not illustrated). The machine load data MD serve as a characteristic for the beginning, the duration, and the end of the excavation. Examples for the machine load data MD are a prevailing performance, a load variation, a torque profile, a point in time of the injection, and/or a pressure profile of valve pressures of consumers. On the one hand, the machine load data MD are determined by means of additional sensors (not shown here), e.g. in the case of valve pressures by means of pressure sensors in the consumers. On the other hand, the machine load data MD are determined by means of other methods, which are known per se, and are available in the electronic control device 5. In this exemplary embodiment for an excavator shovel, it is determined on the basis of the pressures and loads in the cylinder when the excavation took place. The processing of the machine load data MD is performed directly on the electronic control device 5.

[0037] The thresholds S are selected for the machine load data MD in such a way that an exceeding of the machine load data MD characterizes the excavation. The thresholds S can be selected here for absolute values of the machine load data MD or for gradients of the machine load data MD. As examples, one threshold S can in each case be selected for the pressure, the torque, and the injection volume of a combustion engine, as well as for the pressure gradient, the gradient of the torque, and the gradient of the injection volume. On the one hand, the differentiation can occur during the classification 12 when only one of the machine load data MD exceeds the corresponding threshold S. For example, the excavation trajectory AT is classified when the pressure in a consumer exceeds the threshold S. Additional conditions, such as, e.g., an active injection, can be considered in additional exemplary embodiments. On the other hand, the differentiation can take place during the classification when coupled conditions are met. For example, the excavation trajectory AT is classified when the pressure in a consumer exceeds the threshold S, a load variation is determined, and the injection is active at the same time. Since the machine load data MD are different during the excavation of different materials, e.g. top soil, sandy soil, gravel, etc., the thresholds S are selected as a function of the type of the material to be excavated.

[0038] The excavation trajectory AT is subsequently used in combination with dimensions MW of the tool 2 for the calculation 13 of the excavation volume AV, which was excavated along the excavation trajectory AT. The excavation trajectory AT here serves as length of the excavation volume AV, and the width as well as the height of the excavation volume AV correspond to the width and the height of the tool 2. Even though the excavation trajectory AT illustrated in FIG. 1 runs in a straight manner, it is mostly curved in practice. An integration can be performed in order to calculate the excavation volume AV.

[0039] FIG. 3 shows a flow chart of a second embodiment of the method according to the invention. Analogously to the first exemplary embodiment, the position of the tool center point of the tool 2 is determined 20 in the same way at the beginning and during the entire method by means of the tool center point estimation as an algorithm for determining the kinematic chain. The position of the tool 2, thus of the tool center point, is likewise recorded over time, and a motion trajectory BT of the tool 2 is determined 21 therefrom.

[0040] This is followed by a classification 22 by means of machine load data MD, which, in this example, takes place with the help of a classifier K by means of machine learning. Also here, during the classification 22, a division of the motion trajectory BT into the excavation trajectory AT takes place, at which an excavation occurs, and into other trajectories ST, at which no excavation occurs. The machine load data MD correspond to those of the first exemplary embodiment and reference is made to them. The classifier K is trained with reference situations recorded in advance. For this purpose, each operating procedure of the construction machine 1 is recorded, assessed, and divided into reference classes RK in advance. The motion trajectories BT are then classified 22 by means of the classifier K on the basis of the reference classes RK for the operating procedures. A beginning, an end, and a duration of the operating procedure are determined for the classification 22, wherein these points in time likewise serve as training data for the classifier K. Since the machine load data MD are different during the excavation of different materials, e.g. top soil, sandy soil, gravel, etc., additional reference situations with different materials Mat to be excavated are trained in advance. The reference classes comprise subclassifications, which consider the material Mat to be excavated, and the classifiers are activated as a function of the material Mat to be excavated. After the classification 22, the result is then used, in turn, in order to update the reference classes RK and to thus teach the classifier K.

[0041] Analogously to the first exemplary embodiment, the excavation trajectory AT is subsequently used in combination with dimensions MW of the tool 2 for the calculation 23 of the excavation volume AV. The excavation trajectory AT here serves as length of the excavation volume AV, and the width as well as the height of the excavation volume AV correspond to the width and the height of the tool 2. Even though the excavation trajectory AT illustrated in FIG. 1 runs in a straight manner, it is mostly curved in practice. An integration can be performed in order to calculate the excavation volume AV.

[0042] FIGS. 4 and 5 in each case show a flow chart, which connects to one of the flow charts from FIG. 2 or FIG. 3, and they relate to applications according to the invention of the calculated excavation volume AV. The applications described below can be performed alone or in combination with one another. In the exemplary embodiment of FIG. 4, the excavation volume AV is used in order to generate an invoice R in an automated manner. For this purpose, the excavation volume AV as well as previous excavation volumes FAV, which were determined by means of the same method, are summed 30, in order to obtain a measurement of quantities A. In the alternative, a space integral 31 for the excavation volume and the previous excavation volumes between the first and the last operation is calculated, in order to obtain the measurement of quantities A. The measurement of quantities A identifies the scope of the provided construction services. Since the above-mentioned data are stored, the measurement of quantities A can be calculated during the excavation on the one hand, directly after the excavation on the other hand, or afterwards. The measurement of quantities A is subsequently compared 35 to a schedule of services LV, in order to bill the provided construction services. The invoice R is generated based on the measurement of quantities A and the comparison 35 to the schedule of services LV.

[0043] In the exemplary embodiment of FIG. 5, the excavation volume AV is referenced 40 in a virtual map. The virtual map is then visualized 41 to an operator, for example at a terminal inside a driver's cab of the construction machine 1. A terrain geometry and additional relevant information, such as, e.g., the position of pipelines or other infrastructure located in the ground, are thereby illustrated in the virtual map.

[0044] The determined excavation volume AV is furthermore compared 50 to a planned excavation volume GAV, and the result is used for assessing the accuracy, the efficiency, and/or additional factors.