CN116147910A - Method and device for detecting running state of slewing mechanism, controller and working machine - Google Patents

Abstract

The method comprises the steps of after operation information related to rotation movement of a rotation mechanism is obtained, constructing a sampling signal sample based on the operation information, carrying out Fourier transform on the sampling signal sample to obtain a spectrum sample, further taking a gear or a bearing in the rotation mechanism as a target component, extracting the amplitude of a plurality of spectral lines in the spectrum sample based on a fault characteristic spectrum number of the target component to obtain a constructed spectrum, carrying out inverse Fourier transform on the constructed spectrum to obtain an inverse transformation signal sample, and determining the operation state of the target component based on the inverse transformation signal sample. The detection method provided by the invention can realize the detection of the running state of the slewing mechanism based on the running information of the slewing mechanism, is beneficial to timely finding out the fault of the slewing mechanism and timely taking corresponding operation and maintenance measures, and further improves the operation safety of the operation machine.

Description

Method and device for detecting running state of slewing mechanism, controller and working machine

Technical Field

The application relates to the technical field of power electronics, in particular to a method and a device for detecting the running state of a slewing mechanism, a controller and a working machine.

Background

In practical application, many working machines are provided with a swing mechanism, and engineering operations of different angles at the same position are realized through the swing mechanism. Taking an excavator as an example, the excavator comprises an upper automobile body and a lower automobile body, wherein the upper automobile body is arranged on the lower automobile body through a rotation mechanism, when the excavator is used for excavating, the operation position of the lower automobile body is relatively fixed, and the upper automobile body can rotate in a certain rotation angle range through the rotation mechanism, so that the excavator can realize excavating operations at different angles.

In general, the slewing mechanism comprises three major parts of a driving device, a transmission device and a slewing bearing, wherein the transmission device mainly comprises a transmission gear and a supporting bearing. In the operation process of the working machine, if a transmission gear or a supporting bearing in the slewing mechanism breaks away, for example, the inner ring and the outer ring of the supporting bearing are separated, the overall rotation efficiency of the slewing mechanism can be reduced, and even the slewing mechanism is loosened or falls off, so that the working safety is affected.

Therefore, how to detect the operation state of the swing mechanism during the operation of the working machine to ensure the operation safety is one of the technical problems to be solved urgently by those skilled in the art.

Disclosure of Invention

In view of the foregoing, the present application has been made in an effort to provide a method and apparatus for detecting an operating state of a swing mechanism, a controller, and a work machine, which detect an operating state of a swing mechanism, thereby contributing to improvement of work safety.

In a first aspect, the present application provides a method for detecting an operating state of a swing mechanism, including:

acquiring operation information related to the rotary motion of the rotary mechanism;

constructing a sampling signal sample based on the operation information;

performing Fourier transform on the sampling signal sample to obtain a spectrum sample;

extracting the amplitude values of a plurality of spectral lines based on a fault characteristic spectrum number of a target component in the spectrum sample to obtain a constructed spectrum, wherein the target component comprises a gear or a bearing in the slewing mechanism;

performing inverse Fourier transform on the constructed spectrum to obtain an inverse transformed signal sample;

an operating state of the target component is determined based on the inverse transformed signal samples.

Optionally, the operation information includes: vibration signals and rotation signals corresponding to the same time stamp;

the constructing a sampling signal sample based on the operation information includes:

extracting a vibration signal corresponding to a target frequency from the vibration signals, and performing envelope processing on the vibration signal corresponding to the target frequency to obtain a processed vibration signal;

Sampling the processed vibration signal at equal angular intervals based on the rotation signal and a preset sampling frequency to obtain an initial signal sample;

the initial signal sample comprises a plurality of vibration signal amplitudes which are arranged according to time sequence, wherein any vibration signal amplitude corresponds to a rotation angle of the slewing mechanism;

and processing the initial signal sample according to a preset sample processing rule to obtain a sampling signal sample.

Optionally, the processing the initial signal sample according to a preset sample processing rule to obtain a sampled signal sample includes:

dividing the initial signal sample into a plurality of initial signal sub-samples according to each rotation angle, wherein any initial signal sub-sample comprises at least one vibration signal amplitude;

retaining a target signal sub-sample comprising impact vibration characteristics in each initial signal sub-sample;

and constructing a sampling signal sample based on each target signal sub-sample.

Optionally, the dividing the initial signal sample into a plurality of initial signal sub-samples according to each rotation angle includes:

determining the extreme point angle in each rotation angle;

and dividing the initial signal sample into a plurality of initial signal sub-samples by taking the moment corresponding to any two adjacent extreme point angles as a boundary.

Optionally, the constructing a sampling signal sample based on each target signal sub-sample includes:

processing each target signal sub-sample according to a preset processing rule, and arranging the processed target signal sub-samples in time sequence to obtain a sampling signal sample;

wherein, the preset processing rule comprises:

performing reverse sequence processing on the target signal subsamples corresponding to the reversing process;

for a target signal sub-sample that does not include a preset number of vibration signal amplitudes, the number of vibration signal amplitudes in the target signal sub-sample is supplemented to the preset number using a zero value.

Optionally, the arranging the processed target signal sub-samples in time sequence to obtain a sampled signal sample includes:

and if the number of the vibration signal amplitudes included in the target signal sub-samples arranged according to the time sequence is larger than the preset sample length, cutting the target signal sub-samples arranged according to the time sequence according to the preset sample length to obtain sampling signal samples.

Optionally, in the spectrum sample, extracting the amplitude of a plurality of spectral lines based on the fault characteristic spectrum number of the target component to obtain a constructed spectrum, including:

and extracting a fault characteristic clef of the target component and the amplitude of a spectral line corresponding to the clef of the integral multiple of the fault characteristic clef from the spectrum sample to obtain a constructed spectrum.

Optionally, determining the operating state of the target component based on the inverse transformed signal samples includes:

dividing the inverse transformed signal samples into a plurality of inverse transformed signal sub-samples;

calculating the average value of the maximum vibration signal amplitude in each inverse transformation signal sub-sample to obtain a vibration signal average value;

calculating a target decibel value corresponding to the vibration signal mean value;

determining the running state of the target component corresponding to the target decibel value according to a preset mapping relation;

and the corresponding relation between different decibel values and different motion states of the target part is recorded in the preset mapping relation.

Optionally, dividing the inverse transformed signal samples into a plurality of inverse transformed signal sub-samples comprises:

determining a sub-sample length based on a sample length of the inverse transformed signal samples and a fault signature of the target component;

dividing the inverse transformed signal samples into a plurality of inverse transformed signal sub-samples according to the sub-sample length.

In a second aspect, the present invention provides a rotating structure operation state detection device, including:

an acquisition unit configured to acquire operation information related to a turning motion of the turning mechanism;

A construction unit for constructing a sampling signal sample based on the operation information;

the transformation unit is used for carrying out Fourier transformation on the sampling signal samples to obtain spectrum samples;

the extraction unit is used for extracting the amplitude values of a plurality of spectral lines based on the fault characteristic spectrum number of the target component in the spectrum sample to obtain a constructed spectrum, wherein the target component comprises a gear or a bearing in the slewing mechanism;

an inverse transformation unit, configured to perform inverse fourier transformation on the constructed spectrum, to obtain inverse transformed signal samples;

a determining unit for determining an operating state of the target component based on the inverse transformed signal samples.

In a third aspect, the present invention provides a controller comprising: a memory and a processor; the memory stores a program adapted to be executed by the processor to implement the swing mechanism operation state detection method according to any one of the first aspects of the present invention.

In a fourth aspect, the present disclosure provides a work machine comprising: a swing mechanism and a controller according to a third aspect of the present invention, wherein,

the controller is connected with the rotary structure.

Based on the above, according to the method for detecting the running state of the slewing mechanism, after the running information related to the slewing motion of the slewing mechanism is obtained, a sampling signal sample is constructed based on the running information, fourier transformation is performed on the sampling signal sample to obtain a spectrum sample, a gear or a bearing in the slewing mechanism is further used as a target component, in the spectrum sample, the amplitude values of a plurality of spectral lines are extracted based on the fault characteristic spectral number of the target component to obtain a constructed spectrum, and then inverse fourier transformation is performed on the constructed spectrum to obtain an inverse transformation signal sample and the running state of the target component is determined based on the inverse transformation signal sample. The detection method provided by the invention can realize the detection of the running state of the slewing mechanism based on the running information of the slewing mechanism, is beneficial to timely finding out the fault of the slewing mechanism and timely taking corresponding operation and maintenance measures, and further improves the operation safety of the operation machine.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic view of a prior art swing mechanism.

Fig. 2 is a flowchart of a method for detecting an operation state of a swing mechanism according to an embodiment of the present invention.

Fig. 3 is a schematic diagram of the sampling effect of equally spaced sampling of a vibration signal.

Fig. 4 is a schematic diagram of the sampling effect of sampling vibration signals at equal angular intervals.

Fig. 5 is a schematic diagram of a sample signal provided by an embodiment of the present invention.

Fig. 6 is a schematic diagram of a spectrum sample provided by an embodiment of the present invention.

Fig. 7 is a flow chart of constructing a sample signal sample provided by an embodiment of the present invention.

Fig. 8 a-8 d are schematic diagrams of the construction of correlated sampling effects in sampled signal samples.

Fig. 9 is a block diagram of a detection device for running state of a swing mechanism according to an embodiment of the present invention.

Detailed Description

The following description of the technical solutions in the embodiments of the present application will be made clearly and completely with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.

Referring to fig. 1, fig. 1 is a schematic structural view of a swing mechanism in the prior art, and as shown in fig. 1, the swing mechanism includes a swing speed reducer, a driving gear, a transition gear, a driven gear, a swing support bearing and other main components, and meanwhile, fig. 1 also shows a protection cover for preventing foreign matters from entering and ensuring the safety of the internal operation environment of the swing support bearing. It should be noted that the configuration of the swing mechanism shown in fig. 1 is only an alternative configuration, and in practical application, the swing mechanism may also include various other implementations, and the specific implementation of the swing mechanism is not limited by the present invention. Of course, as for the structural mode shown in fig. 1 alone, various other structural parts may be required to be provided in the swing mechanism, and the present invention is specifically realized by referring to the related art, and is not specifically exemplified herein.

As described above, if the transmission gear or the support bearing in the swing mechanism is broken, for example, the inner ring and the outer ring of the support bearing are separated, the overall rotation efficiency of the swing mechanism is reduced, and even the swing mechanism is loosened or the arm is dropped, which affects the operation safety. In order to solve the problem, the invention provides a detection method for the running state of the slewing mechanism, which is used for detecting the running state of the slewing mechanism based on the running information of the slewing mechanism, is beneficial to timely finding out faults of the slewing mechanism and timely taking corresponding operation and maintenance measures, and further improves the operation safety of the operation machine.

The detection method provided by the invention can be applied to a controller, wherein the controller can be a controller arranged on the swing mechanism, and can also be other controllers independent of the swing mechanism on the working machine, such as a whole vehicle controller of the working machine or other auxiliary controllers arranged on the working machine. Of course, in some cases, it may also be applied to a server on the network side. Referring to fig. 2, fig. 2 is a flowchart of a method for detecting an operation state of a swing mechanism according to an embodiment of the present invention, where the flowchart may include:

s100, acquiring operation information related to the rotary motion of the rotary mechanism.

In the actual operation of the slewing mechanism, there are often various kinds of operation information related to the slewing motion of the slewing mechanism, and in this embodiment, the operation information mainly includes a vibration signal and a rotation signal of the slewing mechanism, and the rotation signal is further subdivided into a rotation speed signal and a rotation angle signal.

In practical application, the vibration signal can be acquired by a vibration sensor, the rotation speed signal can be acquired by a rotation speed sensor, and the rotation angle signal can be acquired by an angle sensor. Of course, the above operation information may also be acquired by other manners, which are not specifically limited herein.

It should be noted that, in combination with practical operation experience, vibration caused by gear or bearing faults during operation of the slewing mechanism is often related to rotation process of the slewing mechanism, and the vibration signal and the rotation signal have a direct correlation in time, so that the method requires synchronous acquisition of the vibration signal and the rotation signal, that is, the vibration signal, the rotation speed signal and the rotation angle signal correspond to the same time stamp.

S110, constructing a sampling signal sample based on the operation information.

It will be appreciated that the operating environment of the work machine is often harsh and the environmental noise is very loud, and that vibration signals collected by the vibration sensor often include a lot of noise that is not useful in detecting the operating condition of the swing mechanism and that needs to be removed. Also, for a certain swing mechanism, the frequency of the vibration signal generated in the fault state of the swing mechanism may be predetermined, for example, the frequency of the vibration signal generated in the fault state of most swing mechanisms is typically between 12k±2 KHz.

Based on the above, after the vibration signal is acquired, the vibration signal corresponding to the target frequency in the obtained vibration signal may be first extracted, and envelope processing may be performed on the vibration signal corresponding to the target frequency, to obtain a processed vibration signal. As mentioned above, the target frequency corresponds to the frequency of the vibration signal generated in the fault state of the swing mechanism, and may be determined based on the design parameters and the mechanism characteristics of the swing mechanism in practical application. Further, the process of extracting the vibration signal of the target frequency may be implemented based on a band-pass filtering technique, and the process of performing envelope processing on the vibration signal corresponding to the target frequency may be implemented based on a hilbert or low-pass filtering technique, which is not limited in the present invention.

After the processed vibration signal is obtained, the processed vibration signal is sampled at equal angular intervals based on the rotation signal and a preset sampling frequency, and an initial signal sample is obtained. As described above, the rotation signal includes a rotation speed signal and a rotation angle signal, and the process of sampling at equal angular intervals may be performed based on the rotation speed signal or the rotation angle signal, and the sampling at equal angular intervals is performed with the same number of sampling points for one rotation of the component.

If the rotation speed signal is used for sampling at equal angle intervals, analog pulses are generated according to a preset sampling frequency, for example, 200 times of rotation frequency, and the vibration signal is sampled at equal angle intervals. Meanwhile, in order to facilitate subsequent data processing, sampling is also required to be completed according to the analog pulse synchronization rotation angle signal, so that the sampled vibration signal corresponds to the rotation angle signal one by one, and the consistency of the sampling points of one circle of component rotation is ensured, for example, 200 points of one circle of rotation are sampled when the component rotates at 200 times of rotation frequency.

Further, if the rotation angle signal is utilized to complete the sampling at equal angular intervals, a circle of sampling points are required to be determined according to a preset sampling frequency, so that a corresponding angle value to be sampled is determined according to the rotation angle signal, an analog pulse is generated to complete the sampling at equal angles of the processed vibration signal, and if the vibration signal rotates for 200 points at a circle, the vibration signal is sampled at 1.8 degrees, 3.6 degrees, … degrees and 360 degrees respectively. It is to be understood that when the processed vibration signal is sampled at equal angular intervals based on the rotation angle signal, the rotation angle signal is first divided to obtain angular values at equal intervals, and therefore, as with the equiangular interval sampling using the rotation speed signal, the vibration signal and the rotation angle signal can be obtained in one-to-one correspondence based on the rotation angle signal.

It should be noted that the foregoing is merely a general description of a process of sampling a vibration signal at equal angle intervals based on a rotation speed signal or a rotation angle signal, and a specific implementation process thereof may be implemented with reference to a related art, and the present invention is not limited to a specific implementation process of sampling a vibration signal at equal angle intervals.

Comparing fig. 3 and fig. 4, in which fig. 3 is a schematic diagram of sampling effects after sampling the vibration signal at equal intervals, and fig. 4 is a schematic diagram of sampling effects after sampling the vibration signal at equal intervals, comparing it can be seen that the spectrum component of the vibration signal obtained after sampling the vibration signal at equal intervals is more complex, which is not beneficial to subsequent data analysis, and conversely, the spectrum component of the vibration signal obtained after sampling the vibration signal at equal intervals is more single, which can effectively reduce the data volume of subsequent fault detection.

After the processed vibration signals are sampled at equal angle intervals according to the above, an initial signal sample is obtained, wherein the initial signal sample comprises a plurality of vibration signal amplitudes which are arranged according to time sequence, any vibration signal amplitude corresponds to the rotation angle of a rotation mechanism, and certainly, the vibration signals and the rotation angles which correspond to each other also correspond to the same time stamp.

And finally, processing the initial signal sample according to a preset sample processing rule to obtain a sampling signal sample, wherein the sampling signal sample comprises a plurality of sampling signal sub-samples, and any sampling signal sub-sample comprises a plurality of vibration signal amplitudes. The specific process of processing the initial signal samples according to the preset sample processing rule to finally obtain the sampled signal samples meeting the above requirements will be specifically developed in the following, and will not be described in detail here.

S120, carrying out Fourier transform on the sampling signal sample to obtain a spectrum sample.

The sampled signal samples are assumed to be Xcon, the sample length is M, that is, the samples include M vibration signal amplitudes, fourier transform is performed on the sampled signal samples on the basis of the M vibration signal amplitudes, and the transform result, that is, the spectrum samples, may be labeled Yori for convenience of subsequent description. It will be appreciated that a spectrum sample Yori is a sequence of data, e.g. [0,0.03,1.2], meaning line magnitude 0, line magnitude 0.03, line magnitude 1.2.

For example, referring to fig. 5, a schematic waveform of the sampled signal sample shown in fig. 5, and a waveform of the spectrum sample obtained after fourier transforming the sampled signal sample may be shown in fig. 6.

S130, extracting the amplitude values of a plurality of spectral lines in the spectrum sample based on the fault characteristic spectrum number of the target component to obtain a constructed spectrum.

As described above, for the swing mechanism, the components that have the greatest influence on its safe operation are the gears and the bearings, and thus, the target component mentioned in the present embodiment may be the gears or the bearings in the swing mechanism. In practical application, the detection method provided by the invention can be applied to detect the states of the slewing mechanism and the bearing respectively, which is also feasible, and the invention is not limited to the detection method.

After the target component is determined, the fault characteristic clef of the target component and the amplitude of the spectral line corresponding to the clef of the integral multiple of the fault characteristic clef are extracted from the obtained spectrum sample, and the constructed spectrum is obtained.

For a target component determined in a swing mechanism, the fault signature can be calculated according to the following formula:

Np＝(M /Nc)×(f1/ f2) (1)

wherein Np represents a fault signature;

nc represents the number of sampling points per sampling period;

f1 represents a failure characteristic frequency of the target component;

f2 represents the frequency of rotation of the target component.

It should be noted that, for the determined target component, the own fault characteristic frequency may be explicitly calculated, and may be specifically implemented with reference to the related art, where the specific calculation process of the fault characteristic frequency of the target fault is not limited, and when the method is applied to the determined slewing mechanism, the fault characteristic frequency of the target component may be stored in advance in the memory, and when the step is executed, the fault characteristic frequency may be directly called.

Further, taking the target component as an example of a gear, assuming that the fault characteristic spectrum number is 5, the spectrum sample yori= [0,0.01,0.03,0.06,0.07,1.5,0.04,0.02,0.06,0.07,1.1,0.01,0.03] is obtained by calculation according to the above formula, the spectrum corresponding to the integer multiple spectrum number of the spectrum number 5 and the spectrum corresponding to the integer multiple spectrum number of the spectrum number 5 are extracted, and the rest spectrum line amplitudes are all set to zero values, so that the construction spectrum ycon= [0,0,0,0,0,1.5,0,0,0,0,1.1,0,0] is obtained.

S140, performing inverse Fourier transform on the constructed spectrum to obtain an inverse transformed signal sample.

The constructed spectrum Ycon is subjected to an inverse fourier transform to obtain inverse transformed signal samples, denoted Xinv. In practical applications, different inverse transformed signal samples may be obtained after inverse fourier transformation of different structured spectra. As for a specific implementation procedure of performing inverse fourier transform on the constructed spectrum, it can be implemented with reference to the related art, which is not limited by the present invention.

S150, determining the operation state of the target component based on the inverse transformation signal sample.

After obtaining the inverse transformed signal sample, the sub-sample length is first determined based on the obtained sample length of the inverse transformed signal sample and the fault signature of the target component, and as an alternative implementation, the product obtained by rounding the quotient of the sample length of the inverse transformed signal sample and the fault signature of the target component may be used as the sub-sample length, for example, the sample length is 12000, and the gear fault signature is 60, and then the sub-sample length is 12000/60=200. Further, the inverse transformed signal samples are divided into a plurality of inverse transformed signal sub-samples according to the sub-sample lengths.

Further, the maximum vibration signal amplitude in each inverse transformation signal subsamples is respectively determined to obtain a maximum amplitude value, then the average value of all the obtained maximum amplitude values is calculated to obtain a vibration signal average value, and a target decibel value corresponding to the vibration signal average value is calculated according to the following formula:

Db＝20 × log( C × J / Fspe) (2)

db represents a target decibel value corresponding to the mean value of the vibration signal;

c represents a preset coefficient, and can be set according to actual detection requirements in actual application;

j represents the mean value of the vibration signal;

fspe represents the frequency of rotation of the target component.

After the target decibel value is obtained, the operating state of the target component can be determined according to the target decibel value. As a preferred implementation manner, the embodiment of the present invention provides a preset mapping relationship, where the preset mapping relationship records the correspondence between different db values and different motion states of the target component, so after obtaining the target db value, the running state of the target component corresponding to the target db value can be determined by querying the preset mapping relationship. In general, the greater the target decibel value obtained, the higher the failure level of the target component and the more serious the failure.

In summary, by the detection method provided by the invention, the detection of the running state of the slewing mechanism can be realized based on the running information of the slewing mechanism, thereby being beneficial to timely finding out the fault of the slewing mechanism and timely taking corresponding operation and maintenance measures, and further improving the operation safety of the working machine.

According to practical experience, the slewing mechanism usually rotates aperiodically when in operation, and because of operation requirements, the rotation angle of the slewing mechanism in each rotation is often different and can be any angle within the maximum rotation angle range, so that a fault point is likely to pass in the rotation process, and the fault point is likely to not pass in the rotation process, and correspondingly, vibration signals generated by passing the fault point are sometimes not, so that the vibration signals usually acquired are quite different, the fault frequency is difficult to capture, and the real-time monitoring of the operation state of the slewing mechanism is quite difficult. Therefore, how to process according to the preset sample processing rule based on the collected operation information, so as to obtain the sample of the sampling signal which can be used for detecting the operation state finally is very important. Next, a specific implementation of constructing the sample signal sample in the foregoing embodiment S110 will be described with reference to fig. 7.

The specific process of constructing the sampling signal sample provided by the invention can comprise the following steps:

s200, dividing the initial signal sample into a plurality of initial signal sub-samples according to each rotation angle.

In combination with the foregoing related content in step S110, it is known that the initial signal sample obtained after the equal angle interval sampling is performed on the processed vibration signal includes a plurality of vibration signal amplitudes arranged according to time sequence, more importantly, any vibration signal amplitude corresponds to a rotation angle of a rotation mechanism, the vibration signal amplitudes and the rotation angles have a one-to-one correspondence, and the vibration signal amplitudes and the rotation angles having the correspondence also correspond to the same time stamp.

Based on the above, the division of the initial signal samples may be achieved based on the rotation angle. Specifically, assuming that the initial signal sample is denoted by Xsam, the rotation angles corresponding to the amplitudes of the vibration signals are arranged according to the same time sequence, a set of rotation angles can be obtained, and the initial signal sample is denoted by Asam, and it can be understood that the number of elements in the initial signal sample and the set of rotation angles are the same.

Firstly, determining the extreme point angle in each rotation angle in the rotation angle set, namely determining the extreme point in Asam, and further dividing an initial signal sample into a plurality of initial signal subsamples by taking the moment corresponding to any two adjacent extreme point angles as a boundary. Through the extreme point angle combination, xsam can be divided into a plurality of periods, and the boundary of each period is a timestamp corresponding to the extreme point angle, and meanwhile, because the rotation angle and the vibration signal amplitude are in one-to-one correspondence, the initial signal sample can be divided into a plurality of initial signal subsamples based on the obtained timestamp corresponding to the extreme point angle.

For example: asam= [0 °,10 °,20 °,30 °,20 °,10 ° ], the 4 th point of Asam is the extremum, asam is divided into two periods, while the number of elements in the periods is 4 and 2, respectively. The initial signal sample can be divided into a plurality of initial signal sub-samples according to the extreme angle obtained by the method, and any initial signal sub-sample comprises at least one vibration signal amplitude.

S210, reserving target signal subsamples which comprise impact vibration characteristics in the initial signal subsamples.

As described above, the operation characteristics of the slewing mechanism make the vibration signal triggered by the fault point sometimes be absent, if the period in which the impact vibration does not occur is not removed from the collected samples, the continuity is destroyed, which is not beneficial to the spectrum analysis, so that the subsamples in each initial signal subsample, which do not include the impact vibration feature, need to be removed, and the target signal subsamples including the impact vibration feature are reserved.

And (3) according to the previous example, respectively determining the maximum vibration signal amplitude in each initial signal sub-sample according to each initial signal sub-sample obtained after division, if the maximum vibration signal amplitude in any initial signal sub-sample does not exceed a preset amplitude threshold, confirming that the initial signal sub-sample does not comprise impact vibration characteristics, removing the initial signal sub-sample, and so on, and only retaining the initial signal sub-sample with the maximum vibration signal amplitude greater than the preset amplitude threshold in each initial signal sub-sample, thereby obtaining the target signal sub-sample.

S220, constructing sampling signal samples based on the target signal sub-samples.

Based on the actual running condition of the slewing mechanism, the slewing mechanism has two conditions of forward rotation and reverse rotation, so that the vibration signals collected under the condition of reversing the slewing mechanism are required to be overturned, impact vibration caused by faults is ensured to be at the same angle, meanwhile, the number of data points in each period is consistent, and the reliability of a spectrum analysis result is improved.

In order to complete the construction of the sampled signal samples, the embodiment of the invention provides the following preset processing rules, which specifically include: and performing reverse sequence processing on the target signal sub-samples corresponding to the reversing process, and supplementing the number of the vibration signal amplitudes in the target signal sub-samples to the preset number by using zero values aiming at the target signal sub-samples which do not comprise the preset number of the vibration signal amplitudes.

In the previous example, the minimum rotation angle of the slewing mechanism is Amin, the maximum rotation angle of the slewing mechanism is Amax, and any target signal sub-sample can be processed according to the following process:

firstly, differential processing is carried out on a rotation angle set Asam to obtain angle intervals corresponding to all rotation angles, if all the angle intervals corresponding to the target signal sub-samples are negative values, the target signal sub-samples correspond to an inversion process, and then the target sampling sub-samples need to be processed in an inverted sequence. For example, the target sample sub-sample is [0.01,1,2,3,1,0.01,0.01], which is obtained after the reverse processing [0.01,0.01,1,3,2,1,0.01].

Further, if the minimum angle included in any target sampled signal sub-sample is not Amin, and/or the maximum angle in the target sampled sub-sample is not Amax, then the target sampled signal sub-sample needs to be supplemented, for example, the target sampled signal sub-sample is [0.01,1,2,3,1,0.01,0.01], the corresponding rotation angle set is [10 °,20 °,30 °,40 °,50 °,60 °,70 ° ], amin=0 °, amax=100 °, the corresponding angle interval is 10 °,4 data points need to be supplemented, namely, 4 zero values need to be supplemented, and the result after supplementation is [0,0.01,1,2,3,1,0.01,0.01,0,0,0].

It will be appreciated that the preset processing rules described in the foregoing may be used alone or simultaneously, and if any target signal sub-sample needs to be processed in reverse order and the number of vibration signal amplitudes is to be supplemented, the reverse order processing may be performed first, and then the number of vibration signal amplitudes in the target signal sub-sample may be supplemented to the preset number. Of course, it can be understood from the foregoing that the preset number is the number of vibration signal amplitudes corresponding to the case that all vibration signal amplitudes are included in the sub-samples of the sampling signal.

After each target sampling signal sub-sample is processed according to the above, each target sampling signal sub-sample can be further arranged according to the time sequence, if the number of vibration signal amplitudes included in the vibration signal amplitude set after arrangement is greater than the preset sample length, the target sampling signal sub-sample after arrangement according to the time sequence is cut according to the preset sample length to obtain the sampling signal sample, and thus the construction process of the sampling signal sample is completed.

As shown in fig. 8a to 8d, the processed vibration signal is shown in fig. 8a, and includes 5 periods (with broken lines as a boundary), and the number of sampling points in each complete period is 200 points, because of the operation characteristics of the slewing mechanism, some periods are less than 200 points, and some periods are inversions. After the processed vibration signal is subjected to Fourier transformation, spectral lines are disordered, and the effect is as shown in fig. 8b, so that fault identification is not facilitated. After the sampled signal samples are obtained according to the foregoing, each target sampled signal sub-sample includes 200 vibration signal amplitudes, and the inverted signals are inverted, so that the effect thereof can be as shown in fig. 8c, the spectrum obtained by fourier transforming the most sampled signal sample can be as shown in fig. 8d, and compared with fig. 8b, the spectrum obtained in fig. 8d is clear and ordered, which is beneficial to fault identification.

The invention provides a rotation mechanism running state detection device, which belongs to the same application conception as the rotation mechanism running state detection method provided by the embodiment of the application, can execute the rotation mechanism running state detection method provided by any embodiment of the application, and has corresponding functional modules and beneficial effects for executing the rotation mechanism running state detection method. Technical details not described in detail in the present embodiment may be referred to the method for detecting the running state of the swing mechanism provided in the embodiment of the present application, and will not be described herein again.

Referring to fig. 9, fig. 9 is a block diagram of a detection device for detecting an operation state of a swing mechanism according to an embodiment of the present invention, where the detection device provided in the embodiment includes:

an acquisition unit 10 for acquiring operation information related to a turning motion of the turning mechanism;

a construction unit 20 for constructing a sample signal sample based on the operation information;

a transforming unit 30, configured to perform fourier transform on the sampled signal samples to obtain spectrum samples;

an extraction unit 40, configured to extract, in a spectrum sample, magnitudes of a plurality of spectral lines based on a fault signature of a target component, to obtain a constructed spectrum, where the target component includes a gear or a bearing in a slewing mechanism;

An inverse transform unit 50 for performing inverse fourier transform on the constructed spectrum to obtain inverse transformed signal samples;

a determining unit 60 for determining an operating state of the target component based on the inverse transformed signal samples.

Optionally, the operation information includes: vibration signals and rotation signals corresponding to the same time stamp;

a construction unit 20 for constructing a sample signal sample based on the operation information, comprising:

extracting a vibration signal corresponding to a target frequency from the vibration signals, and performing envelope processing on the vibration signal corresponding to the target frequency to obtain a processed vibration signal;

sampling the processed vibration signal at equal angular intervals based on the rotation signal and a preset sampling frequency to obtain an initial signal sample;

the initial signal sample comprises a plurality of vibration signal amplitudes which are arranged according to time sequence, and any vibration signal amplitude corresponds to the rotation angle of one slewing mechanism;

and processing the initial signal sample according to a preset sample processing rule to obtain a sampling signal sample.

Optionally, the construction unit 20 is configured to process the initial signal samples according to a preset sample processing rule to obtain sampled signal samples, and includes:

dividing an initial signal sample into a plurality of initial signal sub-samples according to each rotation angle, wherein any initial signal sub-sample comprises at least one vibration signal amplitude;

Preserving target signal subsamples including impact vibration characteristics in each initial signal subsample;

a sampled signal sample is constructed based on each target signal subsamples.

Optionally, the constructing unit 20 is configured to divide the initial signal sample into a plurality of initial signal sub-samples according to each rotation angle, and includes:

determining the extreme point angle in each rotation angle;

and dividing the initial signal sample into a plurality of initial signal sub-samples by taking the moment corresponding to any two adjacent extreme point angles as a boundary.

Optionally, the construction unit 20 is configured to construct a sampled signal sample based on each target signal sub-sample, including:

processing each target signal sub-sample according to a preset processing rule, and arranging the processed target signal sub-samples in time sequence to obtain a sampling signal sample;

the preset processing rules comprise:

performing reverse sequence processing on the target signal subsamples corresponding to the reversing process;

for a target signal sub-sample that does not include a preset number of vibration signal amplitudes, the number of vibration signal amplitudes in the target signal sub-sample is supplemented to the preset number using a zero value.

Optionally, the construction unit 20 is configured to arrange the processed target signal sub-samples in a time sequence to obtain a sampled signal sample, and includes:

And if the number of the vibration signal amplitudes included in the target signal sub-samples arranged according to the time sequence is larger than the preset sample length, cutting the target signal sub-samples arranged according to the time sequence according to the preset sample length to obtain sampling signal samples.

An extracting unit 40, configured to extract, in a spectrum sample, magnitudes of a plurality of spectral lines based on a fault signature of a target component, to obtain a constructed spectrum, including:

and extracting the fault characteristic clef of the target component and the amplitude of the spectral line corresponding to the clef of the integral multiple of the fault characteristic clef from the spectrum sample to obtain a constructed spectrum.

Optionally, the determining unit 60 is configured to determine an operation state of the target component based on the inverse transformed signal samples, and includes:

dividing the inverse transformed signal samples into a plurality of inverse transformed signal sub-samples;

calculating the average value of the maximum vibration signal amplitude in each inverse transformation signal sub-sample to obtain a vibration signal average value;

calculating a target decibel value corresponding to the vibration signal mean value;

determining the running state of a target component corresponding to the target decibel value according to a preset mapping relation;

the corresponding relation between different decibel values and different motion states of the target part is recorded in the preset mapping relation.

Optionally, the determining unit 60 is configured to divide the inverse transformed signal sample into a plurality of inverse transformed signal sub-samples, including:

determining a sub-sample length based on a sample length of the inverse transformed signal samples and a fault signature of the target component;

the inverse transformed signal samples are divided into a plurality of inverse transformed signal sub-samples according to the sub-sample lengths.

Optionally, an embodiment of the present invention further provides a controller, including: a memory and a processor; the memory stores a program suitable for execution by the processor to implement the swing mechanism operation state detection method provided in any of the above embodiments.

Optionally, an embodiment of the present invention further provides a working machine, including: the swing mechanism and the controller provided by the foregoing embodiment, wherein,

the controller is connected with the rotary structure.

In some embodiments, the present embodiment further provides a computer readable storage medium, such as a floppy disk, an optical disk, a hard disk, a flash memory, a usb disk, an SD (Secure Digital Memory Card, secure digital Card) Card, an MMC (Multimedia Card) Card, or the like, in which one or more instructions for implementing the foregoing steps are stored, where the one or more instructions are executed by one or more processors, and cause the processors to perform the foregoing method for detecting an operating state of a swing mechanism. For a related implementation, refer to the foregoing description, which is not repeated herein.

In addition to the methods and apparatus described above, embodiments of the present application may also be a computer program product comprising computer program instructions which, when executed by a processor, cause the processor to perform the steps in the swing mechanism operation state detection method according to various embodiments of the present application described in the foregoing description.

The computer program product may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.

Those skilled in the art will appreciate that various modifications and improvements can be made to the disclosure. For example, the various devices or components described above may be implemented in hardware, or may be implemented in software, firmware, or a combination of some or all of the three.

Further, while the present disclosure makes various references to certain elements in a system according to embodiments of the present disclosure, any number of different elements may be used and run on a client and/or server. The units are merely illustrative and different aspects of the systems and methods may use different units.

A flowchart is used in this disclosure to describe the steps of a method according to an embodiment of the present disclosure. It should be understood that the steps that follow or before do not have to be performed in exact order. Rather, the various steps may be processed in reverse order or simultaneously. Also, other operations may be added to these processes.

Those of ordinary skill in the art will appreciate that all or a portion of the steps of the methods described above may be performed by a computer program that instructs associated hardware, and that the program may be stored on a computer readable storage medium, such as a read only memory, etc. Alternatively, all or part of the steps of the above embodiments may be implemented using one or more integrated circuits. Accordingly, each module/unit in the above embodiment may be implemented in the form of hardware, or may be implemented in the form of a software functional module. The present disclosure is not limited to any specific form of combination of hardware and software.

Unless defined otherwise, all terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

The foregoing is illustrative of the present disclosure and is not to be construed as limiting thereof. Although a few exemplary embodiments of this disclosure have been described, those skilled in the art will readily appreciate that many modifications are possible in the exemplary embodiments without materially departing from the novel teachings and advantages of this disclosure. Accordingly, all such modifications are intended to be included within the scope of this disclosure as defined in the claims. It is to be understood that the foregoing is illustrative of the present disclosure and is not to be construed as limited to the specific embodiments disclosed, and that modifications to the disclosed embodiments, as well as other embodiments, are intended to be included within the scope of the appended claims. The disclosure is defined by the claims and their equivalents.

Claims (12)

1. The method for detecting the running state of the slewing mechanism is characterized by comprising the following steps of:

Acquiring operation information related to the rotary motion of the rotary mechanism;

constructing a sampling signal sample based on the operation information;

performing Fourier transform on the sampling signal sample to obtain a spectrum sample;

extracting the amplitude values of a plurality of spectral lines based on a fault characteristic spectrum number of a target component in the spectrum sample to obtain a constructed spectrum, wherein the target component comprises a gear or a bearing in the slewing mechanism;

performing inverse Fourier transform on the constructed spectrum to obtain an inverse transformed signal sample;

an operating state of the target component is determined based on the inverse transformed signal samples.

2. The method of claim 1, wherein the operation information comprises: vibration signals and rotation signals corresponding to the same time stamp;

the constructing a sampling signal sample based on the operation information includes:

extracting a vibration signal corresponding to a target frequency from the vibration signals, and performing envelope processing on the vibration signal corresponding to the target frequency to obtain a processed vibration signal;

sampling the processed vibration signal at equal angular intervals based on the rotation signal and a preset sampling frequency to obtain an initial signal sample;

The initial signal sample comprises a plurality of vibration signal amplitudes which are arranged according to time sequence, wherein any vibration signal amplitude corresponds to a rotation angle of the slewing mechanism;

and processing the initial signal sample according to a preset sample processing rule to obtain a sampling signal sample.

3. The method of claim 2, wherein processing the initial signal samples according to a predetermined sample processing rule results in sampled signal samples, comprising:

dividing the initial signal sample into a plurality of initial signal sub-samples according to each rotation angle, wherein any initial signal sub-sample comprises at least one vibration signal amplitude;

retaining a target signal sub-sample comprising impact vibration characteristics in each initial signal sub-sample;

and constructing a sampling signal sample based on each target signal sub-sample.

4. A method according to claim 3, wherein said dividing said initial signal samples into a plurality of initial signal subsamples according to each said rotation angle comprises:

determining the extreme point angle in each rotation angle;

and dividing the initial signal sample into a plurality of initial signal sub-samples by taking the moment corresponding to any two adjacent extreme point angles as a boundary.

5. A method according to claim 3, wherein said constructing a sampled signal sample based on each of said target signal subsamples comprises:

processing each target signal sub-sample according to a preset processing rule, and arranging the processed target signal sub-samples in time sequence to obtain a sampling signal sample;

wherein, the preset processing rule comprises:

performing reverse sequence processing on the target signal subsamples corresponding to the reversing process;

for a target signal sub-sample that does not include a preset number of vibration signal amplitudes, the number of vibration signal amplitudes in the target signal sub-sample is supplemented to the preset number using a zero value.

6. The method of claim 5, wherein the arranging the processed target signal subsamples in time order results in the sampled signal samples, comprising:

and if the number of the vibration signal amplitudes included in the target signal sub-samples arranged according to the time sequence is larger than the preset sample length, cutting the target signal sub-samples arranged according to the time sequence according to the preset sample length to obtain sampling signal samples.

7. The method of claim 1, wherein extracting magnitudes of a plurality of spectral lines based on a fault signature of a target component in the spectrum sample to obtain a constructed spectrum comprises:

And extracting a fault characteristic clef of the target component and the amplitude of a spectral line corresponding to the clef of the integral multiple of the fault characteristic clef from the spectrum sample to obtain a constructed spectrum.

8. The method of claim 1, wherein determining the operational state of the target component based on the inverse transformed signal samples comprises:

dividing the inverse transformed signal samples into a plurality of inverse transformed signal sub-samples;

calculating the average value of the maximum vibration signal amplitude in each inverse transformation signal sub-sample to obtain a vibration signal average value;

calculating a target decibel value corresponding to the vibration signal mean value;

determining the running state of the target component corresponding to the target decibel value according to a preset mapping relation;

and the corresponding relation between different decibel values and different motion states of the target part is recorded in the preset mapping relation.

9. The method of claim 8, wherein dividing the inverse transformed signal samples into a plurality of inverse transformed signal sub-samples comprises:

determining a sub-sample length based on a sample length of the inverse transformed signal samples and a fault signature of the target component;

Dividing the inverse transformed signal samples into a plurality of inverse transformed signal sub-samples according to the sub-sample length.

10. The utility model provides a revolution mechanic running state detection device which characterized in that includes:

an acquisition unit configured to acquire operation information related to a turning motion of the turning mechanism;

a construction unit for constructing a sampling signal sample based on the operation information;

the transformation unit is used for carrying out Fourier transformation on the sampling signal samples to obtain spectrum samples;

the extraction unit is used for extracting the amplitude values of a plurality of spectral lines based on the fault characteristic spectrum number of the target component in the spectrum sample to obtain a constructed spectrum, wherein the target component comprises a gear or a bearing in the slewing mechanism;

an inverse transformation unit, configured to perform inverse fourier transformation on the constructed spectrum, to obtain inverse transformed signal samples;

a determining unit for determining an operating state of the target component based on the inverse transformed signal samples.

11. A controller, comprising: a memory and a processor; the memory stores a program adapted to be executed by the processor to implement the swing mechanism operation state detecting method according to any one of claims 1 to 9.

12. A work machine, comprising: the swing mechanism and the controller of claim 11, wherein,

the controller is connected with the rotary structure.

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