Method and system for non-invasive vibration-based condition monitoring of a machine

Abstract

A method and a device for non-invasive vibration-based condition monitoring of a machine placed on a physical frame of reference, using a time-domain broadband magnetoresistive sensor having a sensor transfer function of electric resistance versus magnetic field intensity, said machine comprising an attached magnet or a magnetic part; comprising the steps of: placing the magnetic sensor on said physical frame of reference at a distance from the machine and at a predetermined distance from the magnet or magnetic part, such that the magnetoresistive sensor is operating in a dynamic part of the sensor transfer function in respect of the magnetic field produced by the magnet or a magnetic part; capturing a time-domain magnetic field signal transduced by the sensor; and using an electronic data processor to process the captured signal to obtain a vibration-based indicator of the machine's condition.

Claims

1. A method for non-invasive vibration-based condition monitoring of a machine placed on a physical frame of reference, using a time-domain broadband magnetoresistive sensor having a sensor transfer function of electric resistance versus magnetic field intensity, said machine comprising an attached magnet or a magnetic part, comprising the steps of: placing the magnetic sensor on said physical frame of reference, externally and mechanically uncoupled from said machine, at a distance from the machine and at a predetermined distance from the magnet or magnetic part, such that the magnetoresistive sensor is operating in a dynamic part of the sensor transfer function in respect of the magnetic field produced by the magnet or a magnetic part; capturing a time-domain magnetic field signal transduced by the sensor, including a broadband response that includes 0 Hz or a DC component; and using an electronic data processor to process the captured signal to obtain a vibration-based indicator of the machine's condition; wherein the broadband magnetoresistive sensor has a broadband response that includes 0 Hz or a DC component, and wherein the magnet is previously attached on an exterior surface of the machine or to the machine frame or to an internal part of the machine.

2. The method for non-invasive condition monitoring of a machine according to claim 1, wherein the internal part of the machine is the specific part to be monitored.

3. The method for non-invasive condition monitoring of a machine according to claim 1, wherein said parts are mechanically coupled to the machine frame.

4. The method for non-invasive condition monitoring of a machine according to claim 1, further comprising operating the magnetoresistive sensor in a linear part of the sensor transfer function in respect of the magnetic field produced by the magnet or a magnetic part, wherein the magnetoresistive sensor is selected from the group consisting of: a magnetic tunnel junction, MTJ, sensor; a tunnel magnetoresistance, TMR, sensor; a giant magnetoresistance, GMR, sensor; and an anisotropic magnetoresistive, AMR, sensor.

5. The method for non-invasive condition monitoring of a machine according to claim 1, further comprising arranging the predetermined distance and the MTJ sensor such that the MTJ sensor is being operated within a linear response portion of the MTJ sensor input-output function.

6. The method for non-invasive condition monitoring of a machine according to claim 1, wherein the physical frame of reference is fixed relative to the ground.

7. The method for non-invasive condition monitoring of a machine according to claim 6, further comprising placing the magnetic sensor on a vibration-dampening or mechanically-decoupled stand which is placed on said physical frame of reference.

8. A system for non-invasive vibration-based condition monitoring of a machine placed on a physical frame of reference, said machine comprising an attached magnet or a magnetic part, the system comprising: a time-domain wideband magnetoresistive sensor having a sensor transfer function of electric resistance versus magnetic field intensity, wherein the broadband magnetoresistive sensor has a broadband response that includes 0 Hz or a DC component, said machine comprising an attached magnet or a magnetic part, wherein the magnet is previously attached on an exterior surface of the machine or to a machine frame or to an internal part of the machine, for placing on said physical frame of reference, externally and mechanically uncoupled from said machine, at a distance from the machine and at a reference distance from the magnet or magnetic part, wherein the magnetoresistive sensor is operating in a dynamic part of the sensor transfer function in respect of the magnetic field produced by the magnet or a magnetic part; and an electronic data processor configured for: capturing a time-domain magnetic field signal transduced by the sensor including a broadband response that includes 0 Hz or a DC component; and processing the captured signal to obtain a vibration-based indicator of the machine's condition.

9. The system for non-invasive condition monitoring of a machine according to claim 8, wherein the wideband comprises 0 Hz or a DC component, wherein the broadband magnetoresistive sensor has a broadband response that includes a lower limit of 0 Hz and an upper limit of 1 KHz to 1 GHz.

10. System according to claim 8, wherein the magnetoresistive sensor is selected from the group consisting of: a magnetic tunnel junction, MTJ, sensor; a tunnel magnetoresistance, TMR, sensor; a giant magnetoresistance, GMR, sensor; and an anisotropic magnetoresistive, AMR, sensor.

11. The system for non-invasive condition monitoring of a machine according to claim 8, wherein the magnetoresistive sensor comprises a magnetic tunnel junction, MTJ, sensor, and wherein the electronic data processor is configured for processing the captured signal which is obtained when the MTJ sensor operates within a linear response portion of the MTJ sensor input-output function.

12. The system for non-invasive condition monitoring of a machine according to claim 8, wherein the magnet is a compound magnet comprising an assembly of a plurality of magnets arranged for increasing the gradient of the produced magnetic field.

13. A method for using a time-domain wideband magnetoresistive sensor having a sensor transfer function of electric resistance versus magnetic field intensity, for non-invasive vibration-based condition monitoring of a machine placed on a physical frame of reference, said machine comprising an attached magnet or a magnetic part, wherein the magnet is previously attached on an exterior surface of the machine or a machine frame or to an internal part of the machine, wherein the broadband magnetoresistive sensor has a broadband response that includes 0 Hz or a DC component, said method comprising: placing the magnetic sensor on said physical frame of reference, externally and mechanically uncoupled from said machine, at a distance from the machine and at a predetermined distance from the magnet or magnetic part, such that the magnetoresistive sensor is operating in a dynamic part of the sensor transfer function in respect of the magnetic field produced by the magnet or a magnetic part; capturing a time-domain magnetic field signal transduced by the sensor, including a broadband response that includes 0 Hz or a DC component; and using an electronic data processor to process the captured signal to obtain a vibration-based indicator of the machine's condition.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The following figures provide preferred embodiments for illustrating the disclosure and should not be seen as limiting the scope of invention.

[0063] FIG. 1 is a schematic illustration of a setup describing the conventional method to monitor moving parts inside a machine.

[0064] FIG. 2 is a schematic illustration of a setup according to an embodiment of the disclosure for non-invasive monitoring of a machine.

[0065] FIG. 3 shows an example of a time-domain signal obtained from a test machine using the sensor according to an embodiment of the disclosure during three time periods (all machinery off, main machine part on and pump off, main machine part off and pump on).

[0066] FIG. 4 shows an example of a time-domain signal obtained from a test machine using the sensor according to an embodiment of the disclosure during machine start up.

[0067] FIG. 5 is an example of a spectrogram obtained from a test machine.

[0068] FIG. 6 is an example of a segment of data obtained in a complex machine made of many different parts and illustrating how information about particular internal components and failure conditions can be extracted from the data collected by the sensor, where (a) shows a normal period of operation, (b) shows an abnormal period of operation where a motor is abnormally inoperative (note the absence of the repeating time-domain pattern around the 16 Hz-17 Hz mark), (c) shows an abnormal period of operation where there is a compressed air failure (note the repeating dwindling time-domain pattern around the 16 Hz-17 Hz mark).

DETAILED DESCRIPTION

[0069] The present disclosure relates to a method and a device for non-invasive condition monitoring of machines.

[0070] Current conditional monitoring methods and devices are often expensive, unsafe, delicate, requires precise alignment, requires highly skilled operators to perform, requires exposing the internal parts of the machine in order to install the monitoring device and, may be unreliable in dusty and dirty environments.

[0071] Monitoring the condition of existing machines requires some level of knowledge of the machine details and functional principles, such as where are the critical moving parts located, how can they be accessed, where can foreign sensors be installed safely, how to safely install the extra cables required by wired sensors, etc. As a consequence, different machines end up being monitored by different sets of sensors, placed in different numbers in order to monitor the different types of machine parts.

[0072] FIG. 1 is a schematic illustration of the conventional method for condition monitoring of a machine with several internal moving parts. Conventionally, each moving part is monitored by a sensor or set of sensors placed in contact or even inside the part being monitored. This is an invasive solution which requires foreign sensors and wires to be added to the machine, which is not always possible or safe. Furthermore, a prior knowledge of the moving parts location, nature of the motion and nature of the moving part itself is required to install appropriate sensors in the appropriate positions in order to extract useful information.

[0073] As such, there is a need for a cheaper, simpler and non-invasive method for condition monitoring of machines that can be applied more universally, i.e., regardless of the nature of the machine and its internal parts.

[0074] The present disclosure relates to a method and a device for non-invasive monitoring of machine that is cheaper, simpler and does not require installing wires on/in the machine, or opening up the machine to expose the internal moving parts. Therefore, this method can be used to monitor any machine with internal moving parts, regardless of the nature of the machine.

[0075] In an embodiment, the method and device of the present disclosure include the use of a magnet placed on the machine frame. This magnet is solidary with the frame and creates a magnetic field with a magnitude that decays in space with the distance from the magnet. A magnet placed in a position {right arrow over (r.sub.0)}, generates a magnetic field {right arrow over (H)}({right arrow over (r)}−{right arrow over (r.sub.0)}) that will change with respect to the placement of the magnet and the position in space considered.

[0076] In an embodiment, the method and device of the present disclosure include the use of a magnetic field sensor placed in the vicinity of the magnet, without contact and at a distance which is generally of the order from 0.1 cm to 10 cm, but can be further away, for example 1 cm-1 m or 1 m-10 m. This distance is preferably large enough for the magnetic field created by the magnet in the position occupied by the magnetic field sensor to fall within the dynamic range of the magnetic field sensor. If this condition is met, the magnetic field sensor will operate as a transducer which will convert the magnetic field in the position occupied by the sensor, {right arrow over (r.sub.s)}, into a voltage which can be read and digitized by an appropriate electronics circuit. The transduction of magnetic field into voltage is determined by the sensitivity of the magnetic field sensor, dV/dH, which depends on the nature of the magnetic field sensor.

[0077] As shown in FIG. 2, any mechanical motion of any moving part of the machine that is mechanically coupled to the machine frame is transmitted to such frame that acts as a mechanical waveguide collecting mechanical energy from all different sources. Such motion in the frame results in a motion of the magnet, which is attached, for instance, to the tool frame. As a result, the position of the magnet changes with time {right arrow over (r.sub.0)}={right arrow over (r.sub.0)}(t) and so does the magnetic field in the fixed location where the magnet is placed {right arrow over (H)}({right arrow over (r.sub.s)},t)={right arrow over (H)}({right arrow over (r.sub.a)}−{right arrow over (r.sub.0)}(t)). As a result, a displacement of the tool frame Δ{right arrow over (r)} generates a change of the magnetic field in the location of the magnetic field sensor which is given by

[00001]$\Delta \stackrel{.fwdarw.}{r}\frac{d\stackrel{.fwdarw.}{H}}{d\stackrel{.fwdarw.}{r}}\left(\stackrel{.fwdarw.}{r_s}\right)$

which in turn is converted to a change in the output voltage of the magnetic field sensor as a result of the intrinsic sensitivity of the sensor:

[00002]$\Delta V=\Delta \stackrel{.fwdarw.}{r}\frac{d\stackrel{.fwdarw.}{H}}{d\stackrel{.fwdarw.}{r}}\left(\stackrel{.fwdarw.}{r_s}\right)\frac{\mathrm{dV}}{d\stackrel{.fwdarw.}{H}}.$

[0078] The magnetic field sensor and the magnetic field gradient may be arranged such that the magnetic field gradient at the position of installation of the magnetic field sensor is large enough to generate a voltage variation across the sensor that is above the noise level of the electronics circuit used to monitor said voltage for displacements of the frame in the nanometer range.

[0079] The magnetic field sensor and the electronics circuit used to monitor the magnetic field sensor output may operate over a large frequency range (DC-10 MHz), allowing the motion of the frame to be monitored across a large range of time scales.

[0080] Due to the rapidly decreasing intensity of the magnetic field across space, the magnetic field sensor selectively may detect the motion of the frame at the point of contact or installation of the magnet. The magnet may form part of the machine to be monitored or, alternatively, may be permanently or detachably mounted onto the machine at a contact point. The mechanical motion in neighbouring machines will have negligible disturbance as compared with the displacement signal generated at the tool where the device is installed.

[0081] In an embodiment, the device comprises a data acquisition apparatus capable of acquiring and digitizing the data collected by the magnetic field sensor. The acquiring and digitizing the data may be at very fast rates (up to 10 Msps) with a noise level comparable to the intrinsic noise of the magnetic field sensor.

[0082] In an embodiment, the device comprises a data analysis software capable of analyzing the data collected, namely by producing a dynamic spectrograph that can be used to characterize different machine part's operational modes.

[0083] In an embodiment, operating in the time domain, the data acquisition apparatus together with the data analysis software will generate an output which will depend on the motion of the different moving parts in the machine.

[0084] In an embodiment, as an example, moving parts in the machine with periodic mechanical motions with different characteristic frequencies can be identified as different Fourier components along the time trace. Additionally, parts operating at similar frequencies will generate different time traces that depend on the magnitude of the movements, relative phase difference between them, distance between the parts and the permanent magnet and type of mechanical coupling between these parts and the machine's exterior frame.

[0085] In an embodiment, the device comprises a data processing software which correlates the data collected with critical failures (reactive maintenance needs) as well as with the aging process of different moving parts in the machine for the purpose of predictive maintenance.

[0086] FIG. 3 shows an example of a time-domain signal obtained from a test machine using the magnetic field sensor according to an embodiment of the disclosure during three time periods (all machinery off, main machine part on and pump off, main machine part off and pump on).

[0087] FIG. 4 shows an example of a time-domain signal obtained from a test machine using the magnetic field sensor according to an embodiment of the disclosure during machine start up, with zoomed in excerpts.

[0088] FIG. 5 is an example of a spectrogram obtained from a test machine for a duration of 16 minutes.

[0089] FIG. 6 is an example illustrating how information about particular internal components and failure conditions can be extracted from the data collected by the sensor monitoring a very complex machine made of many different parts. The data in FIG. 6 was collected in a machine operating in a real environment. The data was collected with the sensor placed outside the tool, in the physical reference frame (the ground) and with a magnet placed in the external surface of the tool frame at a distance of 10 cm from the sensor. The data was collected in a factory with other machines operating in the vicinity of the machine being monitored. The top inset spectrogram shows the data collected with the machine operating in normal conditions and executing a repetitive task. In this spectrogram a data feature is seen to occur about every 2 minutes with a signature in the frequency range between 16-17 Hz made of 4 pulses. In the bottom left-figure the data was acquired in the same machine and under the same conditions except that the cable powering a particular motor was removed. The effect of this change is that the data feature mentioned above is no longer visible in the spectrum. This experiment allows the feature previously identified to be labelled as identifying this particular motor that makes part of the machine operating normally. The absence of this data pattern is identified as signalling an abnormal operation where this particular motor is not mechanically moving when it is expected to do so. But this is not the only possible fault mode that can be detected. The bottom right figure shows a spectrogram that was collected in the same machine and under the same conditions as the normal operation, except that a compressed air cable supplying a mechanism associated with the same motor was disconnected. The result of this action is that the pattern labelled as signalling the particular motor operating normally is still present, but no longer looks the same as under normal operation. In this particular case, the signal is still present in the same frequency range as before (16-17 Hz), it is still repeating every 2 minutes and it is still made of four bursts. However, the amplitude of the signal collected with the sensor is fading from burst to bursts and from event to event. This modified pattern is identified as signalling an abnormal operation where this particular motor is mechanically powered, but the associated compressed air mechanism is not receiving enough compressed air pressure. This example illustrates the main points of this invention disclosure with a data pattern that is simple enough to be visually identified and that can be identified easily without the mediation of any data analysis algorithm. Of course, a data analysis method will be able to extract meaningful assessments from much less evident data patterns from the collected data. The Spectrograms in FIG. 6 show a very small fraction of the data collected in the tool. In particular, the frequency window plotted is limited at 20 Hz to focus on the particular event discussed here in the frequency range of 16-17 Hz.

[0090] The disclosure should not be seen in any way restricted to the embodiments described and a person with ordinary skill in the art will foresee many possibilities to modifications thereof.

[0091] The above described embodiments are combinable.