CN102270829B - Apparatus and calculating method for early warning on health of servo motor - Google Patents
Apparatus and calculating method for early warning on health of servo motor Download PDFInfo
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- CN102270829B CN102270829B CN201010188164.3A CN201010188164A CN102270829B CN 102270829 B CN102270829 B CN 102270829B CN 201010188164 A CN201010188164 A CN 201010188164A CN 102270829 B CN102270829 B CN 102270829B
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Abstract
The invention discloses an apparatus and a calculating method for early warning on health of a servo motor; and the apparatus and the method are applied to estimation on a vibration state of a computer numerical control machine tool. First, a vibration signal is generated by a vibration sensing unit; second, the vibration signal is transmitted sequentially to a data buffer; third, time and frequency domains conversion is carried out on the vibration signal by a time-frequency domain conversion unit; fourth, a deterioration index is calculated by a deterioration index calculation unit and a health index is obtained by a health index calculation unit. Therefore, the utilization of the built-in vibration sensing unit enables installation and wiring for an extra added sensor to be saved; moreover, according to the health index size, the vibration state of operation of the servo motor on the computer numerical control machine tool can be estimated and thus good parses on nonlinear and nonstationary vibration characteristics can be provided.
Description
Technical field
The present invention, about a kind of healthy early warning device and computational methods thereof of servomotor, provides healthy early warning device and the computational methods thereof of the servomotor of vibration signal time-frequency domain conversion.
Background technology
In recent years, along with the lifting of high efficiency, high quality of production technology, therefore, comprehensive by plant equipment towards maximizing, rapid, systematization, complicated and automation direction development.Also increasing because of equipment scale in factory, the relevance of each system is also more and more closer, and itself also becomes increasingly complex equipment.If so cannot predict in early days possible fault and occur, equipment is overhauled to maintenance, once break down, cause economic loss by considerable.
With the example that is operating as of Computerized numerical control machine tool, host computer is passed to multiple-axis servo driver with position command, in order to drive servomotor to rotate.By the action of drive system (as guide screw pipe, slide rail etc.), platform can be moved.But operation for a long time, mechanical consume, lubricating condition, can affect the fluency of board running on problems such as the heart walk.Also therefore, board produces irregular vibrations and energy dissipation, is unavoidable.In the process of equipment operation, if having abnormal vibrations long-term existence in equipment, do not improve immediately, although the short time still can maintain regular event, be bound to for a long time cause the infringement of equipment, affect its task performance.
For overall servomotor health index estimation is carried out in systematization computing, collect voltage, electric current, empty consume and the acceleration from board of driver with the calculator of PC-based and advise the shock value being passed.These time domain datas can pass through fast fourier transform (Fast Fourier transform, FFT) or wavelet conversion (Wavelet Transform, WT) changes frequency domain or time-frequency domain into.But these time-frequency domain switch technologies, though the statistical mathematics of utilization and pattern learning can obtain health status desired value up till now.But, because amount of calculation is large, so need independently calculator to carry out, so, will increase cost and the space of those calculators of installing.Be limited to the difference of the driver functions of different labels, signal source and the real-time of fechtable will be restricted simultaneously.
The research and development of rotary machinery fault diagnosis a lot of year, up to the present, the method that detects vibration signal has a variety of, process and data analysis for signal, fast fourier transform (FFT) is the method the most generally using at present, and is most representative one in frequency domain analysis method.Traditional Fourier analysis (Fourier spectral analysis) can provide method easily to analyze the Energy distribution of data at frequency domain (frequency domain), its principle is that the composition based on signal is done linear superposition combination by sine or the cosine function of different frequency, amplitude and phase place, the signal characteristic that makes to be difficult to performance in time domain can clearly show in frequency domain.Distribute and linear (linear) time series as long as signal is stable state (stationary), can effectively present the characteristic of signal by spectral conversion.But, for the data of non-linear (nonlinear) and unstable state (nonstationary), Fourier analysis mainly can cause following shortcoming:
1, in the process of integration, be easy to some information to erase, and may produce energy dissipation is caused to wave spectrum illusion to the part of high frequency because of integration, allow correct frequency ambiguity, cause the mistake in interpretation.
2, in the time that signal converts frequency domain to, the information of time-domain just can disappear, and that is to say, cannot in frequency domain, determine the time that characteristic frequency occurs, and increases the inconvenience on analytic signal.
For wavelet conversion (WT), can analytic signal in the three-dimensional distribution of energy-frequency-time, it can resolve into the mixed signal of different frequency composition the signal of different frequency composition, separation signal and noise effectively.But, because wavelet conversion is to be come by fourier transform correction, still exist energy to disperse, the shortcoming that frequency range increases, and lack adaptability.And, before decomposed signal, must first select suitable wavelet basis function, once and this basic function is selected, just must go to analyze all data with it, thereby limit applicable scope.
Therefore, how to design a kind of healthy early warning device and computational methods thereof of servomotor, can be to reduce installing and the distribution of additional sensor, and provide preferably parsing for non-linear and astable vibrant characteristic, be to want for the application a large problem that overcomes and solve.
Summary of the invention
In order to address the above problem, the invention provides a kind of healthy early warning device of servomotor, be applied to the shock conditions estimation of Computerized numerical control machine tool.
The healthy early warning device of servomotor comprises servomotor and servo-driver.The built-in at least one vibratory sensation measurement unit of servomotor, to sense the operating parameters of servomotor, and produces vibration signal.
Servo-driver connects servomotor, and comprises microprocessor.Microprocessor comprises time-frequency domain converting unit, resolution unit, deterioration index computing unit and health index computing unit.Time-frequency domain converting unit receives vibration signal, and the conversion of vibration signal between time-domain and frequency domain is provided.Resolution unit connects time-frequency domain converting unit, to receive vibration signal and to decompose vibration signal as multiple decomposed signals.Deterioration index computing unit connects resolution unit, according to selected decomposed signal and the comparison of criticism curve, to calculate deterioration index.Health index computing unit connects deterioration index computing unit, calculates health index according to deterioration index.
By this, utilize built-in vibratory sensation measurement unit, can save the installing and the distribution that additionally install transducer additional, and, according to health index size, run on the shock conditions on Computerized numerical control machine tool with estimation servomotor, and provide preferably and resolve for non-linear and astable vibrant characteristic.
In order to address the above problem, the invention provides a kind of healthy early warning computational methods of servomotor, be applied to the shock conditions estimation of Computerized numerical control machine tool.
The step of the healthy early warning computational methods of servomotor comprises: first, produce vibration signal by vibratory sensation measurement unit; Then, sequentially transmit vibration signal to data buffer; Then, by time-frequency domain converting unit, vibration signal is carried out to time-frequency domain conversion; Finally, calculate deterioration index by deterioration index computing unit, and utilize health index computing unit to try to achieve health index.
Technology, means and effect of taking for reaching predetermined object in order further to understand the present invention, refer to following about detailed description of the present invention and accompanying drawing, believe object of the present invention, feature and feature, when obtaining thus one deeply and concrete understanding, but accompanying drawing only provides reference and explanation use, is not used for the present invention to be limited.
Brief description of the drawings
Figure 1A is the schematic diagram that the present invention's one servomotor is connected with a servo-driver;
Figure 1B is the stereogram that this servomotor of the present invention is applied to a Computerized numerical control machine tool;
Fig. 2 is the calcspar of this servomotor of the present invention and this servo-driver;
Fig. 3 is the flow chart of the healthy early warning computational methods of the present invention's one servomotor;
Fig. 4 is the flow chart of the time-frequency domain switch process of healthy early warning computational methods of the present invention;
Fig. 5 A is the oscillogram of the original time domain vibration signal of the present invention one and multiple Time Domain Decomposition signals;
Fig. 5 B is amplitude-frequency-time three-dimensional distribution map of those Time Domain Decomposition signals of the present invention; And
Fig. 6 is the schematic diagram of those Time Domain Decomposition signals of the present invention and a criticism curve comparison.
Wherein, Reference numeral:
10 servomotors
102 vibratory sensation measurement units
20 servo-drivers
202 high-speed serial communication interfaces
204 data buffers
206 microprocessors
2062 time-frequency domain converting units
2064 resolution unit
2066 deterioration index computing units
2068 health index computing units
S100～S400 step
S310～S340 step
Sv time domain vibration signal
St1～St9 Time Domain Decomposition signal
Δ g1～Δ g9 intensity difference
Embodiment
Relevant the technical content and a detailed description, coordinate brief description of the drawings as follows:
Refer to Figure 1A and Figure 1B, be respectively schematic diagram that the present invention's one servomotor is connected with a servo-driver and this servomotor and be applied to the stereogram of a Computerized numerical control machine tool.Board with Computerized numerical control machine tool is applied as example, is needing the occasion of angle location, and motor need to have encoder to carry out detection rotor angle, and then estimation angular speed and angular acceleration values.In practical operation, sometimes, with motor rotor direct-drive, sometimes carry out transmission with shaft coupling.And movement or the vibrations of shaft coupling before and after the more flexible reply of rotor axis direction (Z direction), and the vibrations meeting major part of the X-Y plane vertical with axis direction passes to encoder from the origination point of mechanism.Therefore, install a vibratory sensation measurement unit 102 in the encoder of this servomotor 10, wherein, this vibratory sensation measurement unit 102 can be an acceleration transducer (G-sensor).This vibratory sensation measurement unit 102 can detect vibrations and the noise of this servomotor 10, screw rod, slide rail, workbench running.In addition, be fixedly mounted with another vibratory sensation measurement unit 102 in the stator slot of this servomotor 10, because this servomotor 10 is paid in mechanism with screwed lock, therefore, the vibrations of all platforms can be detected by this vibratory sensation measurement unit 102 full and accurately.That is to say, be fixed on this vibratory sensation measurement unit 102 on encoder in order to detect the shock wave of drive system; And be fixed on this vibratory sensation measurement unit 102 in stator slot in order to detect the shock wave on upper lower platform.
Referring to Fig. 2, is the calcspar of this servomotor of the present invention and this servo-driver.The servo drive system of this Computerized numerical control machine tool mainly comprises a servomotor 10 and a servo-driver 20.This servomotor 10 mainly comprises a rotor (not shown), a stator (not shown), is installed in this epitrochanterian encoder (not shown), and at least one vibratory sensation measurement unit 102.Wherein, this vibratory sensation measurement unit 102 can be installed in this encoder of this servomotor 10, to estimate the drive system shock conditions of this Computerized numerical control machine tool; Or, can be installed in this stator slot of this servomotor 10, to estimate the board shock conditions of this Computerized numerical control machine tool.
In practical operation, servomotor 10 simultaneously built-in multiple these vibratory sensation measurement units 102 in encoder with stator slot in, the shock conditions in order to the drive system of testing tool machine respectively and board in X, Y, Z direction.But, for convenience of description, in the present embodiment, illustrate with a vibratory sensation measurement unit 102.This vibratory sensation measurement unit 102 to be to sense the operating parameters of this servomotor 10, and produces a vibration signal Sv.This servo-driver 20 connects this servomotor 10.And this servo-driver 20 comprises a high-speed serial communication interface 202, a data buffer 204 and a microprocessor 206.This data buffer 204 connects this high-speed serial communication interface 202, this vibration signal Sv producing in order to receive and to store this vibratory sensation measurement unit 102, and wherein, this data buffer 204 is a queue buffer (queuebuffer).
This microprocessor 206 connects this data buffer 204.This microprocessor 206 comprises frequency domain converting unit 2062, a resolution unit 2064, a deterioration index computing unit 2066 and a health index computing unit 2068 for the moment.This time-frequency domain converting unit 2062 receives this vibration signal Sv that this data buffer 204 is exported, and the conversion of this vibration signal Sv between time-domain and frequency domain is provided.This resolution unit 2064 connects this time-frequency domain converting unit 2062, to receive this vibration signal Sv and to decompose this vibration signal Sv as multiple decomposed signal St1～St9 (referring to Fig. 5 A).This deterioration index computing unit 2066 connects this resolution unit 2064, according to selected those decomposed signals St1～St9 and a criticism curve comparison, to calculate a deterioration index.Wherein, this criticism curve can be obtained by the rule of thumb of Practical Operation.This health index computing unit 2068 connects this deterioration index computing unit 2066, calculates a health index according to this deterioration index.As for the calculating of this deterioration index and this health index, describe in detail as after.By this, according to this health index size, run on the shock conditions on Computerized numerical control machine tool to estimate this servomotor 10.
Referring to Fig. 3, is the flow chart of the healthy early warning computational methods of the present invention's one servomotor.The step of the healthy early warning computational methods of this servomotor comprises: first, obtain an original vibration signal S100.Then, this vibration signal is orderly sent to a data buffer S200.Then, this vibration signal is carried out to time-frequency domain conversion S300.Wherein, the time-frequency domain conversion of this vibration signal can adopt Hilbert-Huang conversion (Hilbert-Huang Transform, HHT), fast fourier transform (Fast Fourier Transform, FFT), wavelet conversion (Wavelet Transform, WT) or other time-frequency domain switch technology obtain.Finally, calculate a deterioration index, and try to achieve a health index S400.As for, the healthy early warning computational methods more detailed description of this servomotor, refers to hereinafter.
Referring to Fig. 4, is the flow chart of the time-frequency domain switch process of healthy early warning computational methods of the present invention.Change (HHT) into example with Hilbert-Huang, this step S300 is described in further detail, that is this vibration signal is carried out to time-frequency domain conversion S300.After this vibration signal is read via this data buffer, carry out empirical mode decomposition (Empirical Mode Decomposition, EMD) decompose, in the hope of multiple intrinsic mode functions (Intrinsic Mode Function, IMF) component S310.Then, select main those intrinsic mode functions (IMF) component S320, and those main intrinsic mode function (IMF) components are carried out to Hilbert-Huang conversion (HHT) conversion, to obtain multiple instantaneous decomposed signal S330.Finally, combine those instantaneous decomposed signals, to obtain a Hilbert spectrum (Hilbert Spectrum) S340.Wherein, this Hilbert spectrum (Hilbert Spectrum) is amplitude-frequency-time three-dimensional distribution map, mainly be that the spectral content of describing signal changes in time, to can represent energy or the intensity of signal on time and frequency spectrum simultaneously.
Coordinate referring to Fig. 5 A and Fig. 5 B, be respectively the oscillogram of the original time domain vibration signal of the present invention one and multiple Time Domain Decomposition signals and amplitude-frequency-time three-dimensional distribution map of those Time Domain Decomposition signals.An original time domain vibration signal Sv as shown in Figure 5A, can obtain corresponding multiple Time Domain Decomposition signal St1～St9 by Hilbert-Huang conversion (HHT), make complicated original time domain vibration signal Sv be decomposed into the signal resolution of limited multiple different time yardsticks with it.That is to say, after Time Domain Decomposition signal St1～St9 superposition of these main (association is large), almost with regard to reducible be this original time domain vibration signal Sv.Coordinate Figure 1B, the explanation as an example of servomotor 10 shock detection example, and suppose that these servomotor 10 rotating speeds are w (t).The original time domain vibration signal Sv that this vibratory sensation measurement unit 102 is passed back, by Hilbert-Huang conversion (HHT), can obtain corresponding those Time Domain Decomposition signals St1～St9.(referring to Fig. 5 A) from below to up, this first Time Domain Decomposition signal St1 is that 200Hz, this second Time Domain Decomposition signal St2 are that 100Hz, the 3rd Time Domain Decomposition signal St3 are that the two frequency multiplication harmonic waves of servomotor 10 rotating speed w (t), the 4th Time Domain Decomposition signal St4 are a frequency multiplication harmonic wave of w (t).Be amplitude-frequency-time three-dimensional distribution map of Time Domain Decomposition signal St1～St9 as shown in Figure 5 B, be corresponding Hilbert spectrum (HilbertSpectrum), the height in figure shows the intensity (or energy) of those Time Domain Decomposition signals St1～St9.
Referring to Fig. 6, is the schematic diagram of those Time Domain Decomposition signals of the present invention and a criticism curve comparison.This Hilbert spectrum (Hilbert Spectrum) producing according to this time-frequency domain converting unit 2062, captures the intensity of those Time Domain Decomposition signals St1～St9 under a certain instantaneous time.Taking the present embodiment as example, there are 9 instantaneous strength values to be captured (as the circular stain on figure), and, those instantaneous strength values and this criticism curve compare, to obtain intensity difference Δ g1～Δ g9 of relative populations, that is those instantaneous strength values that are calculated as under institute's respective frequencies of those intensity difference Δ g1～Δs g9 deduct corresponding this criticism curve.Wherein, the value of this criticism curve can be considered the boundary of weighing this servomotor running health status.By finding out significantly on figure, this first intensity difference Δ g1 and this second intensity difference Δ g2 be all on the occasion of, also reflect in this original vibration signal Sv, be 1 in frequency, this first Time Domain Decomposition signal St1 under 200rps and frequency be the shockproofness of this second Time Domain Decomposition signal St2 under 800rps and the value of this criticism curve by comparison, be the operational situation that worsens (extremely).In addition, remaining those intensity difference Δ g3～Δs g9 is all negative value, similarly, also reflect that in this original vibration signal Sv, the shockproofness of those Time Domain Decomposition signals St3～St9 and the value of this criticism curve by comparison, are the operational situation of normal (health).Be worth mentioning, adopt with a deterioration index Di and quantize about this servomotor vibrations deterioration degree.Wherein, definition one maximum permissible value Tm, and the calculating of this deterioration index Di be those on the occasion of intensity difference (in this example for this first intensity difference Δ g1 and this second intensity difference Δ g2) with, then with the ratio of this maximum permissible value Tm.Wherein, maximum permissible value Tm can be obtained by the rule of thumb of Practical Operation.That is:
Deterioration index Di=(on the occasion of intensity difference Δ g1～Δ g9)/maximum permissible value Tm.
Wherein, if this deterioration index Di exceedes at 1 o'clock, look it with 1.And a health index Hi can be defined as:
Health index Hi=1-deterioration index Di.
So can learn intuitively, when this servomotor 10, to shake deterioration degree more acute, and those intensity difference Δ g1～Δs g9 summation of value that exceedes this criticism curve is larger, makes calculated this deterioration index Di larger, and relatively, Hi is also less for this health index.
In sum, the present invention has advantages of following:
1, utilize this built-in vibratory sensation measurement unit, can save the installing and the distribution that additionally install transducer additional.
2, can this vibratory sensation measurement unit (G-sensor) be set respectively at the stator slot of this servomotor and encoder, can be completed separately by corresponding driver and servomotor the estimation of board vibrations and drive system vibrations.
3, the healthy early warning device of this servomotor can provide the different health indicators of multidirectional board vibrations from drive system shake.
The above; be only detailed description and the accompanying drawing of preferred embodiment of the present invention; feature of the present invention is not limited to this; not in order to limit the present invention; all scopes of the present invention should be as the criterion with following claims, and all closing in the embodiment of the spirit variation similar with it of protection range of the present invention, all should be contained in category of the present invention; any those skilled in the art in the field of the invention, can think easily and variation or amendment all can be encompassed in the scope of the claims of following this case.
Claims (14)
1. a healthy early warning device for servomotor, is applied to the shock conditions estimation of a Computerized numerical control machine tool, it is characterized in that, the healthy early warning device of this servomotor comprises:
One servomotor, built-in at least one vibratory sensation measurement unit, to sense the operating parameters of this servomotor, and produces a vibration signal; And
One servo-driver, connects this servomotor, and this servo-driver comprises a microprocessor;
This microprocessor comprises:
Frequency domain converting unit, receives this vibration signal, and the conversion of this vibration signal between time-domain and frequency domain is provided for the moment;
One resolution unit, connects this time-frequency domain converting unit, to receive this vibration signal and to decompose this vibration signal as multiple decomposed signals;
One deterioration index computing unit, connect this resolution unit, by the instantaneous strength value of those captured decomposed signals deduct with a criticism curve of instantaneous strength value institute respective frequencies on value, obtain multiple difference in signal strength, according on the occasion of those difference in signal strength and with the ratio of a maximum permissible value, calculate a deterioration index; And
One health index computing unit, connects this deterioration index computing unit, calculates a health index according to this deterioration index;
By this, utilize this built-in vibratory sensation measurement unit, can save the installing and the distribution that additionally install transducer additional, and, according to this health index size, run on the shock conditions on Computerized numerical control machine tool to estimate this servomotor, and provide preferably and resolve for non-linear and astable vibrant characteristic.
2. the healthy early warning device of servomotor as claimed in claim 1, is characterized in that, this servo-driver also comprises a high-speed serial communication interface, its communication interface for transmitting for this vibration signal.
3. the healthy early warning device of servomotor as claimed in claim 2, it is characterized in that, this servo-driver also comprises a data buffer, connects respectively this high-speed serial communication interface and this microprocessor, this vibration signal being produced to receive and to store this vibratory sensation measurement unit.
4. the healthy early warning device of servomotor as claimed in claim 1, is characterized in that, this vibratory sensation measurement unit is installed in an encoder of this servomotor, to estimate the drive system shock conditions of this Computerized numerical control machine tool.
5. the healthy early warning device of servomotor as claimed in claim 1, is characterized in that, this vibratory sensation measurement unit is installed in a stator slot of this servomotor, to estimate the board shock conditions of this Computerized numerical control machine tool.
6. the healthy early warning device of servomotor as claimed in claim 3, is characterized in that, this data buffer is a queue buffer.
7. the healthy early warning device of servomotor as claimed in claim 1, is characterized in that, this vibratory sensation measurement unit is an acceleration transducer (G-sensor).
8. the healthy early warning device of servomotor as claimed in claim 1, is characterized in that, this criticism curve is for to obtain with the rule of thumb.
9. the healthy early warning device of servomotor as claimed in claim 1, is characterized in that, this deterioration index obtains by these those decomposed signals of deterioration index computing unit comparison and this criticism curve calculation.
10. healthy early warning computational methods for servomotor, are applied to the shock conditions estimation of a Computerized numerical control machine tool; The step of the healthy early warning computational methods of this servomotor comprises:
(a) produce a vibration signal by a vibratory sensation measurement unit;
(b) sequentially transmit this vibration signal to one data buffer;
(c) by a period of time frequency domain converting unit this vibration signal is carried out to time-frequency domain conversion;
(c ') received this vibration signal and decomposed this vibration signal by a resolution unit is multiple decomposed signals; And
(d) by a deterioration index computing unit by the instantaneous strength value of those captured decomposed signals deduct with a criticism curve of instantaneous strength value institute respective frequencies on value, obtain multiple difference in signal strength, according on the occasion of those difference in signal strength sums and the ratio of a maximum permissible value, calculate a deterioration index, and utilize a health index computing unit to try to achieve a health index.
11. healthy early warning computational methods as claimed in claim 10, is characterized in that, this step (c) also comprises:
(c1) carry out empirical mode decomposition, in the hope of multiple intrinsic mode function components;
(c2) select this main intrinsic mode function component;
(c3) this main intrinsic mode function component is carried out to the conversion of Hilbert-Huang, to obtain multiple instantaneous decomposed signals; And
(c4) combine this instantaneous decomposed signal, to obtain a Hilbert spectrum.
12. healthy early warning computational methods as claimed in claim 10, is characterized in that, the time-frequency domain conversion of this vibration signal can be the conversion of a Hilbert-Huang.
13. healthy early warning computational methods as claimed in claim 10, is characterized in that, the time-frequency domain conversion of this vibration signal can be a fast fourier transform.
14. healthy early warning computational methods as claimed in claim 10, is characterized in that, the time-frequency domain conversion of this vibration signal can be a wavelet conversion.
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| CN108390517B (en) * | 2018-03-29 | 2019-08-13 | 苏州晟贝科动力科技有限公司 | A kind of electric vehicle motor controller assembly having security alarm function |
| CN109916624B (en) * | 2019-03-22 | 2020-11-06 | 南京理工大学 | Hilbert yellow-based fatigue failure diagnosis method for ball screw pair |
| TWI741366B (en) * | 2019-09-10 | 2021-10-01 | 英業達股份有限公司 | System and method for estimating transportation risk |
| CN111060192B (en) * | 2019-10-21 | 2022-02-15 | 张国基 | Calculation chip system for abnormal vibration of mechanical equipment |
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| US7308322B1 (en) * | 1998-09-29 | 2007-12-11 | Rockwell Automation Technologies, Inc. | Motorized system integrated control and diagnostics using vibration, pressure, temperature, speed, and/or current analysis |
| CN101592712A (en) * | 2008-05-28 | 2009-12-02 | 罗伯特·博世有限公司 | Move a kind of method of device |
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| DE102005008586A1 (en) * | 2005-02-24 | 2006-09-07 | Wago Verwaltungsgesellschaft Mbh | Electric drive device with structure-borne sound sensor |
| US7346461B2 (en) * | 2005-09-30 | 2008-03-18 | The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration | System and method of analyzing vibrations and identifying failure signatures in the vibrations |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US7308322B1 (en) * | 1998-09-29 | 2007-12-11 | Rockwell Automation Technologies, Inc. | Motorized system integrated control and diagnostics using vibration, pressure, temperature, speed, and/or current analysis |
| CN101592712A (en) * | 2008-05-28 | 2009-12-02 | 罗伯特·博世有限公司 | Move a kind of method of device |
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