CN115931319A - Fault diagnosis method, fault diagnosis device, electronic equipment and storage medium - Google Patents
Fault diagnosis method, fault diagnosis device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the field of industrial equipment, in particular to a fault diagnosis method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining vibration data corresponding to a plurality of vibration measuring points of equipment to be monitored; analyzing the vibration data corresponding to each vibration measuring point to generate a candidate spectrogram corresponding to each vibration measuring point; performing fusion processing on each candidate spectrogram according to the relation between the amplitude values corresponding to each candidate spectrogram to generate a target spectrogram; and analyzing the amplitude and the frequency in the target spectrogram, and determining the fault corresponding to the equipment to be monitored. According to the method, the fault corresponding to the equipment to be monitored can be determined without identifying and analyzing the spectrogram corresponding to the vibration measuring points, but only by analyzing the amplitude and the frequency in the target spectrogram, so that the time is saved, and the efficiency of determining the fault corresponding to the equipment to be monitored is improved.
Description
Technical Field
The invention relates to the field of industrial equipment, in particular to a fault diagnosis method and device, electronic equipment and a storage medium.
Background
The vibration is an important factor influencing the safe operation of the rotary machine, and simultaneously, the running state of the equipment is directly reflected. Most structural or mechanical faults of the rotary machine can be presented through vibration signals, and therefore, the vibration monitoring of the rotary machine is an important work for monitoring the state of equipment.
In the prior art, for a system for monitoring a single device on line, in order to accurately analyze a single fault point, a plurality of vibration measurement points are usually deployed on a single device, and then a series of processing and transformation are performed on vibration data collected by each vibration measurement point, so as to obtain a spectrogram finally, and further analysis is performed according to the spectrogram.
In the prior art, a spectrogram is generated for a single measuring point. Therefore, if one single equipment part has a plurality of measuring points, the single equipment part can be judged whether to have a fault by checking the frequency spectrogram corresponding to each of the plurality of measuring points. Therefore, the above method takes a long time and is inefficient.
Disclosure of Invention
In view of this, an embodiment of the present invention provides a fault diagnosis method, which aims to solve the problems in the prior art that the fault diagnosis of a single device takes long time and is low in efficiency.
According to a first aspect, an embodiment of the present invention provides a fault diagnosis method, including:
obtaining vibration data corresponding to a plurality of vibration measuring points of equipment to be monitored;
analyzing the vibration data corresponding to each vibration measuring point to generate a candidate frequency spectrogram corresponding to each vibration measuring point;
performing fusion processing on each candidate spectrogram according to the relation between the corresponding amplitude values of each candidate spectrogram to generate a target spectrogram;
and analyzing the amplitude and the frequency in the target spectrogram, and determining the fault corresponding to the equipment to be monitored.
According to the fault diagnosis method provided by the embodiment of the invention, the vibration data corresponding to the plurality of vibration measuring points of the equipment to be monitored are obtained, then the vibration data corresponding to each vibration measuring point are analyzed, the candidate spectrogram corresponding to each vibration measuring point is generated, and the accuracy of the generated candidate spectrogram corresponding to each vibration measuring point is ensured. And performing fusion processing on each candidate spectrogram according to the relation between the corresponding amplitude values of each candidate spectrogram to generate a target spectrogram, so that the generated target spectrogram can comprise the characteristics of each candidate spectrogram, and the accuracy of the generated target spectrogram is further ensured. And then, analyzing the amplitude and the frequency in the target spectrogram, determining the fault corresponding to the equipment to be monitored, and ensuring the accuracy of the determined fault corresponding to the equipment to be monitored. According to the method, the fault corresponding to the equipment to be monitored can be determined without identifying and analyzing the spectrogram corresponding to the vibration measuring points, but only by analyzing the amplitude and the frequency in the target spectrogram, so that the time is saved, and the efficiency of determining the fault corresponding to the equipment to be monitored is improved.
With reference to the first aspect, in the first implementation manner of the first aspect, the vibration data is vibration acceleration data, and the vibration data corresponding to each vibration measurement point is analyzed to generate a candidate spectrogram corresponding to each vibration measurement point, which includes
Performing integral calculation on each vibration acceleration data to obtain time domain vibration speed data corresponding to each vibration acceleration data;
and analyzing the time-domain vibration velocity data to generate candidate spectrograms.
According to the fault diagnosis method provided by the embodiment of the invention, the integral calculation is carried out on each vibration acceleration data to obtain the time domain vibration speed data corresponding to each vibration acceleration data, so that the accuracy of the time domain vibration speed data corresponding to each vibration acceleration data obtained through calculation is ensured. And analyzing the time domain vibration velocity data to generate candidate spectrograms, so that the accuracy of the generated candidate spectrograms is ensured.
With reference to the first implementation manner of the first aspect, in a second implementation manner of the first aspect, analyzing each time-domain vibration velocity data to generate each candidate spectrogram, includes:
carrying out Fourier transform on each time domain vibration velocity data to generate frequency domain vibration velocity data;
and analyzing the vibration speed data of each frequency domain to generate each candidate spectrogram.
According to the fault diagnosis method provided by the embodiment of the invention, fourier transform is carried out on each time domain vibration velocity data to generate frequency domain vibration velocity data, so that the accuracy of the generated frequency domain vibration velocity data is ensured. And then, analyzing the vibration speed data of each frequency domain to generate each candidate spectrogram, thereby ensuring the accuracy of each generated candidate spectrogram.
With reference to the first aspect, in a third implementation manner of the first aspect, performing fusion processing on each candidate spectrogram according to a relationship between corresponding amplitude values of each candidate spectrogram, and generating a target spectrogram, includes:
analyzing each candidate spectrogram, and determining the amplitude corresponding to each frequency in each candidate spectrogram;
for each frequency, comparing the corresponding amplitude values of each candidate spectrogram at the same frequency, and determining the corresponding maximum amplitude value of each candidate spectrogram at the same frequency;
and taking the maximum amplitude as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram.
According to the fault diagnosis method provided by the embodiment of the invention, each candidate spectrogram is analyzed, the amplitude corresponding to each frequency in each candidate spectrogram is determined, and the accuracy of the determined amplitude corresponding to each frequency in each candidate spectrogram is ensured. And aiming at each frequency, comparing the corresponding amplitude values of each candidate spectrogram at the same frequency, and determining the corresponding maximum amplitude value of each candidate spectrogram at the same frequency, so that the accuracy of the determined corresponding maximum amplitude value of each candidate spectrogram at the same frequency is ensured. And then, the maximum amplitude is taken as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram, so that the accuracy of the generated target spectrogram is ensured.
With reference to the first aspect, in a fourth implementation manner of the first aspect, analyzing an amplitude and a frequency in a target spectrogram, and determining a fault corresponding to a device to be monitored includes:
analyzing the target spectrogram and determining the highest amplitude value in the target spectrogram;
determining a target frequency corresponding to the highest amplitude in the target spectrogram according to the corresponding relation between the amplitude and the frequency;
and determining the part with the fault corresponding to the equipment to be monitored according to the corresponding relation between the frequency and the part.
The fault diagnosis method provided by the embodiment of the invention analyzes the target spectrogram, determines the highest amplitude in the target spectrogram, and ensures the accuracy of the determined highest amplitude in the target spectrogram. And then, according to the corresponding relation between the amplitude and the frequency, determining the target frequency corresponding to the highest amplitude in the target spectrogram, so that the accuracy of the determined target frequency is ensured. And determining the fault-occurring component corresponding to the equipment to be monitored according to the corresponding relation between the frequency and the component, thereby ensuring the accuracy of the determined fault-occurring component corresponding to the equipment to be monitored.
With reference to the first aspect, in a fifth implementation manner of the first aspect, acquiring vibration data corresponding to a plurality of vibration measurement points of a device to be monitored includes:
and simultaneously acquiring vibration data corresponding to a plurality of vibration measuring points corresponding to the equipment to be monitored by utilizing a plurality of acquisition equipment connected to the same vibration data acquisition station, wherein the acquisition parameters corresponding to the plurality of acquisition equipment are the same.
According to the fault diagnosis method provided by the embodiment of the invention, a plurality of acquisition devices connected to the same vibration data acquisition station are used for simultaneously acquiring the vibration data corresponding to a plurality of vibration measurement points corresponding to the device to be monitored, wherein the acquisition parameters corresponding to the plurality of acquisition devices are the same, so that the accuracy of the acquired vibration data corresponding to the plurality of vibration measurement points corresponding to the device to be monitored is ensured.
According to a second aspect, an embodiment of the present invention further provides a fault diagnosis apparatus, including:
the acquisition module is used for acquiring vibration data corresponding to a plurality of vibration measuring points of the equipment to be monitored;
the generating module is used for analyzing the vibration data corresponding to each vibration measuring point and generating a candidate spectrogram corresponding to each vibration measuring point;
the fusion module is used for performing fusion processing on each candidate spectrogram according to the relation between the amplitude values corresponding to each candidate spectrogram to generate a target spectrogram;
and the determining module is used for analyzing the amplitude and the frequency in the target spectrogram and determining the fault corresponding to the equipment to be monitored.
The fault diagnosis device provided by the embodiment of the invention obtains the vibration data corresponding to the plurality of vibration measuring points of the equipment to be monitored, analyzes the vibration data corresponding to each vibration measuring point, generates the candidate spectrogram corresponding to each vibration measuring point, and ensures the accuracy of the generated candidate spectrogram corresponding to each vibration measuring point. And performing fusion processing on each candidate spectrogram according to the relation between the corresponding amplitude values of each candidate spectrogram to generate a target spectrogram, so that the generated target spectrogram can comprise the characteristics of each candidate spectrogram, and the accuracy of the generated target spectrogram is further ensured. And then, the amplitude and the frequency in the target spectrogram are analyzed to determine the fault corresponding to the equipment to be monitored, so that the accuracy of the determined fault corresponding to the equipment to be monitored is ensured. According to the fault diagnosis device, the fault corresponding to the equipment to be monitored can be determined without identifying and analyzing the spectrograms corresponding to the vibration measuring points but only by analyzing the amplitude and the frequency in the target spectrograms, so that the time is saved, and the efficiency of determining the fault corresponding to the equipment to be monitored is improved.
With reference to the second aspect, in a first embodiment of the second aspect, the generating module is specifically configured to: performing integral calculation on each vibration acceleration data to obtain time domain vibration speed data corresponding to each vibration acceleration data; and analyzing the vibration speed data of each time domain to generate each candidate spectrogram.
The fault diagnosis device provided by the embodiment of the invention performs integral calculation on each vibration acceleration data to obtain time domain vibration speed data corresponding to each vibration acceleration data, and ensures the accuracy of the time domain vibration speed data corresponding to each vibration acceleration data obtained by calculation. And analyzing the time-domain vibration velocity data to generate candidate spectrograms, so that the accuracy of the generated candidate spectrograms is ensured.
According to a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory and a processor, where the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions, so as to execute the fault diagnosis method in the first aspect or any one of the implementation manners of the first aspect.
According to a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the fault diagnosis method of the first aspect or any one of the implementation manners of the first aspect.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a fault diagnosis method provided by an embodiment of the invention;
FIG. 2 is a flow chart of a fault diagnosis method provided by another embodiment of the invention;
FIG. 3 is a schematic illustration of another embodiment of the present invention providing a collection device connected to the same vibration data collection station;
FIG. 4 is a schematic diagram of a time domain waveform of vibration acceleration provided by another embodiment of the present invention;
FIG. 5 is a schematic diagram of a time domain waveform of vibration acceleration provided by another embodiment of the present invention;
FIG. 6 is a schematic diagram of a time domain waveform of vibration acceleration provided by another embodiment of the present invention;
FIG. 7 is a schematic diagram of a time domain waveform of vibration velocity provided by another embodiment of the present invention;
FIG. 8 is a schematic diagram of a time domain waveform of vibration velocity provided by another embodiment of the present invention;
FIG. 9 is a schematic diagram of a time domain waveform of vibration velocity provided by another embodiment of the present invention;
FIG. 10 is a schematic diagram of a velocity spectrum waveform plot provided by another embodiment of the present invention;
FIG. 11 is a schematic diagram of a velocity spectrum waveform plot provided by another embodiment of the present invention;
FIG. 12 is a schematic diagram of a velocity spectrum waveform plot provided by another embodiment of the present invention;
FIG. 13 is a flow chart of a fault diagnosis method provided by another embodiment of the invention;
FIG. 14 is a schematic diagram of a target spectrum generated by a fault diagnosis method according to another embodiment of the present invention;
fig. 15 is a functional block diagram of a failure diagnosis apparatus provided by applying an embodiment of the present invention;
fig. 16 is a schematic diagram of a hardware structure of an electronic device to which an embodiment of the present invention is applied.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
It should be noted that, in the method for fault diagnosis provided in the embodiment of the present application, the main execution body may be a fault diagnosis device, and the fault diagnosis device may be implemented as part or all of a computer device in a software, hardware, or a combination of software and hardware, where the electronic device may be a controller in a device to be monitored, or may be an electronic device independent of the device to be monitored. When the electronic device is independent of a device to be monitored, the electronic device may be a server or a terminal, where the server in this embodiment of the present application may be one server or a server cluster composed of multiple servers, and the terminal in this embodiment of the present application may be another intelligent hardware device such as a smart phone, a personal computer, a tablet computer, a wearable device, and an intelligent robot. In the following method embodiments, the execution subject is an electronic device as an example.
In an embodiment of the present application, as shown in fig. 1, a fault diagnosis method is provided, which is described by taking an example that the method is applied to an electronic device, and includes the following steps:
s11, obtaining vibration data corresponding to a plurality of vibration measuring points of the equipment to be monitored.
Specifically, the electronic device may receive vibration data corresponding to a plurality of vibration measurement points of the device to be monitored, which is transmitted by the acquisition device connected to the electronic device, may also receive vibration data corresponding to a plurality of vibration measurement points of the device to be monitored, which is input by a user, and may also receive vibration data corresponding to a plurality of vibration measurement points of the device to be monitored, which is sent by other devices. The embodiment of the application does not specifically limit the way in which the electronic device acquires the vibration data corresponding to the multiple vibration measurement points of the device to be monitored.
Details regarding this step will be described below.
And S12, analyzing the vibration data corresponding to each vibration measuring point to generate a candidate spectrogram corresponding to each vibration measuring point.
In an optional implementation manner of the present application, the electronic device may analyze the vibration data corresponding to each vibration measurement point, determine a frequency and an amplitude in the vibration data corresponding to each vibration measurement point, and then generate a candidate spectrogram corresponding to each vibration measurement point according to a correspondence between the determined frequency and amplitude.
Details regarding this step will be described below.
And S13, performing fusion processing on each candidate spectrogram according to the relation between the amplitude values corresponding to each candidate spectrogram to generate a target spectrogram.
In an optional implementation manner, the electronic device may perform image recognition on each candidate spectrogram, determine a feature image in each candidate spectrogram, and then perform fusion processing on the feature images in each candidate spectrogram to generate a target spectrogram. Wherein the characteristic image may be an image including a maximum magnitude.
Details regarding this step will be described below.
And S14, analyzing the amplitude and the frequency in the target spectrogram, and determining the fault corresponding to the equipment to be monitored.
Specifically, the electronic device may analyze the amplitude and the frequency in the target spectrogram, and determine a fault corresponding to the device to be monitored and a component having the fault.
Details regarding this step will be described below.
According to the fault diagnosis method provided by the embodiment of the invention, the vibration data corresponding to the vibration measuring points of the equipment to be monitored are obtained, then the vibration data corresponding to each vibration measuring point are analyzed, the candidate spectrogram corresponding to each vibration measuring point is generated, and the accuracy of the generated candidate spectrogram corresponding to each vibration measuring point is ensured. And performing fusion processing on each candidate spectrogram according to the relation between the corresponding amplitude values of each candidate spectrogram to generate a target spectrogram, so that the generated target spectrogram can comprise the characteristics of each candidate spectrogram, and the accuracy of the generated target spectrogram is further ensured. And then, analyzing the amplitude and the frequency in the target spectrogram, determining the fault corresponding to the equipment to be monitored, and ensuring the accuracy of the determined fault corresponding to the equipment to be monitored. According to the method, the fault corresponding to the equipment to be monitored can be determined without identifying and analyzing the spectrogram corresponding to the vibration measuring points, but only by analyzing the amplitude and the frequency in the target spectrogram, so that the time is saved, and the efficiency of determining the fault corresponding to the equipment to be monitored is improved.
In an embodiment of the present application, as shown in fig. 2, a fault diagnosis method is provided, which is described by taking an example that the method is applied to an electronic device, and includes the following steps:
s21, obtaining vibration data corresponding to a plurality of vibration measuring points of the equipment to be monitored.
In an optional implementation manner of this application, the step S21 "obtaining vibration data corresponding to a plurality of vibration measurement points of the device to be monitored" may include the following steps:
s211, simultaneously collecting vibration data corresponding to a plurality of vibration measuring points corresponding to the equipment to be monitored by using a plurality of collecting equipment connected to the same vibration data collecting station.
Wherein, the corresponding acquisition parameters of a plurality of acquisition equipment are the same.
Specifically, for all vibration measurement points of the same device to be monitored, the electronic device may connect the acquisition devices corresponding to the vibration measurement points to the same vibration data acquisition station, the connection diagram is as shown in fig. 3, and then set the same acquisition parameters for the acquisition devices.
Wherein, the vibration data acquisition station is a sensor data acquisition box, and the acquisition equipment can be an acceleration vibration sensor. The sampling parameters may include sampling duration and sampling frequency. For example, the sampling frequency is 25600Hz, and the sampling time is 1 second.
For example, the electronic device can monitor the vibration condition of a transmission case in a high-speed wire finishing area of a certain steel mill, and 6 vibration measuring points are deployed on the transmission case and comprise an input end vertical direction, an input end horizontal direction, an input end axial direction, an output end vertical direction, an output end horizontal direction and an output end axial direction. The 6 vibration measuring points are all connected with the same vibration data acquisition station, and the same acquisition parameters are set, such as the sampling frequency of 25600Hz and the sampling time of 1 second.
For example, assume that the vibration data is vibration acceleration data, set at intervals of t a Synchronously acquiring a batch of data by all vibration measuring points in unit time, wherein the sampling frequency of each batch of data is fs Hz, the number of sampling points is n, and the vibration acceleration data acquired by the ith measuring point is A i ＝{a 1 ,a 2 ,a 3 ,...,a n-1 ,a n }. For example, assuming that the device to be monitored is a transmission case, the device has 3 measuring points, and the device is arranged to be monitoredThe sample frequency was 25600Hz, and 25600 data points were collected for 1 second. The corresponding vibration acceleration time domain oscillograms of the 3 measuring points collected at the same time are shown in fig. 4-6, wherein the abscissa is a sampling point, the ordinate is vibration acceleration, and the unit is m/s 2 。
And S22, analyzing the vibration data corresponding to each vibration measuring point to generate a candidate spectrogram corresponding to each vibration measuring point.
In an alternative embodiment of the present application, the vibration data is vibration acceleration data, and the step of "analyzing the vibration data corresponding to each vibration measuring point and generating a candidate spectrogram corresponding to each vibration measuring point" in S22 may include:
and S221, performing integral calculation on each vibration acceleration data to obtain time domain vibration velocity data corresponding to each vibration acceleration data.
Specifically, the electronic device may perform integral calculation on the respective vibration acceleration data to obtain time-domain vibration velocity data corresponding to the respective vibration acceleration data.
The vibration acceleration data corresponding to each vibration measuring point is an acceleration time domain waveform, N acceleration time domain waveforms exist in N vibration measuring points, and each acceleration time domain waveform can be converted into a velocity time domain waveform through integration. The integral formula is:
wherein v (t) is time-domain vibration velocity data, and a (u) is vibration acceleration data.
And S222, analyzing the time-domain vibration speed data to generate candidate spectrograms.
In an optional embodiment of the present application, the electronic device may analyze each time-domain vibration velocity data, determine a corresponding amplitude of each sampling point, and then generate each candidate spectrogram according to the corresponding amplitude of each sampling point in each time-domain vibration velocity data.
Illustratively, the electronic device analyzes the respective time-domain vibration velocity data to generate respective candidate spectrograms. Each candidate spectrogram generated therein may be a velocity-time domain oscillogram, which may be as shown in fig. 7 to 9.
In another optional embodiment of the present application, in the step S222, "analyzing each time-domain vibration velocity data to generate each candidate spectrogram", the following steps may be generated:
(1) And performing Fourier transform on each time domain vibration velocity data to generate frequency domain vibration velocity data.
(2) And analyzing the vibration speed data of each frequency domain to generate each candidate spectrogram.
In particular, since the failure of the device to be monitored is often caused by one or more components therein, and different components usually cause vibration at different frequencies, it is necessary to convert the time domain waveform into the frequency domain waveform to see which frequency has a high amplitude so as to correspond to the matched device component. Therefore, after the electronic device acquires each time-domain vibration velocity data, the electronic device may perform discrete-time fourier transform on each time-domain vibration velocity data to generate frequency-domain vibration velocity data.
Then, the electronic equipment analyzes the vibration speed data of each frequency domain to generate each candidate spectrogram. As an example, as shown in fig. 10-12, each of the generated candidate spectrograms may be a velocity spectrogram.
And S23, performing fusion processing on each candidate spectrogram according to the relation between the amplitude values corresponding to each candidate spectrogram to generate a target spectrogram.
For this step, please refer to fig. 1 for description of S13, which is not described herein.
And S24, analyzing the amplitude and the frequency in the target spectrogram, and determining the fault corresponding to the equipment to be monitored.
For this step, please refer to fig. 1 for the description of S14, which is not described herein.
According to the fault diagnosis method provided by the embodiment of the invention, the vibration data corresponding to the vibration measuring points corresponding to the equipment to be monitored are simultaneously acquired by utilizing the plurality of acquisition equipment connected to the same vibration data acquisition station, wherein the acquisition parameters corresponding to the plurality of acquisition equipment are the same, so that the accuracy of the acquired vibration data corresponding to the plurality of vibration measuring points corresponding to the equipment to be monitored is ensured.
In addition, according to the fault diagnosis method provided by the embodiment of the invention, the integral calculation is performed on each vibration acceleration data to obtain the time domain vibration velocity data corresponding to each vibration acceleration data, so that the accuracy of the time domain vibration velocity data corresponding to each vibration acceleration data obtained through calculation is ensured. Fourier transform is carried out on each time domain vibration velocity data to generate frequency domain vibration velocity data, and accuracy of the generated frequency domain vibration velocity data is guaranteed. And then, analyzing the vibration speed data of each frequency domain to generate each candidate spectrogram, thereby ensuring the accuracy of each generated candidate spectrogram.
In an embodiment of the present application, as shown in fig. 13, a fault diagnosis method is provided, which is described by taking an example that the method is applied to an electronic device, and includes the following steps:
s31, obtaining vibration data corresponding to a plurality of vibration measuring points of the equipment to be monitored.
For this step, please refer to fig. 2 for description of S21, which is not described herein.
And S32, analyzing the vibration data corresponding to each vibration measuring point to generate a candidate spectrogram corresponding to each vibration measuring point.
Please refer to fig. 2 for an introduction of S22 for this step, which is not described herein.
And S33, performing fusion processing on each candidate spectrogram according to the relation between the corresponding amplitude values of each candidate spectrogram to generate a target spectrogram.
In an optional embodiment of the present application, in the step S33, "performing fusion processing on each candidate spectrogram according to a relationship between corresponding amplitude values of each candidate spectrogram, and generating the target spectrogram", may include the following steps:
s331, analyzing each candidate spectrogram, and determining the amplitude corresponding to each frequency in each candidate spectrogram.
Specifically, the electronic device may analyze each candidate spectrogram, and determine a magnitude corresponding to each frequency in each candidate spectrogram.
S332, comparing the corresponding amplitude values of the candidate spectrograms at the same frequency aiming at the frequencies, and determining the corresponding maximum amplitude value of the candidate spectrograms at the same frequency.
Specifically, for each frequency, the electronic device compares corresponding amplitudes of each candidate spectrogram at the same frequency, and determines a corresponding maximum amplitude of each candidate spectrogram at the same frequency.
For example, taking the frequency 2000 as an example, the electronic device may obtain the corresponding amplitude value when the frequency in each candidate spectrogram is 2000, and then compare the corresponding amplitude values when the frequency is 2000 to determine the maximum amplitude value when the frequency is 2000.
S333, taking the maximum amplitude as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram.
Specifically, the electronic device takes the maximum amplitude as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram.
Illustratively, the electronic device uses the maximum amplitude corresponding to the frequency of 2000 as the amplitude corresponding to the frequency of 2000 in the target spectrogram, and according to the above method, the electronic device generates the target spectrogram, which is exemplarily shown in fig. 14 and is a schematic diagram of the target spectrogram generated by the electronic device.
And S34, analyzing the amplitude and the frequency in the target spectrogram, and determining the fault corresponding to the equipment to be monitored.
In an optional implementation manner of the present application, in step S34, "analyzing the amplitude and the frequency in the target spectrogram, and determining a fault corresponding to the device to be monitored", may include the following steps:
s341, analyzing the target spectrogram, and determining the highest amplitude value in the target spectrogram.
Specifically, after generating the target spectrogram, the electronic device may perform image recognition on the target spectrogram, and determine the highest amplitude in the target spectrogram.
And S342, determining a target frequency corresponding to the highest amplitude in the target spectrogram according to the corresponding relation between the amplitudes and the frequencies.
Specifically, the electronic device determines a target frequency corresponding to the highest amplitude in the target spectrogram according to the correspondence between the amplitudes and the frequencies.
And S343, determining the fault component corresponding to the equipment to be monitored according to the corresponding relation between the frequency and the component.
Specifically, the electronic device may determine, according to the correspondence between the frequency and the component, a component in which a fault corresponding to the device to be monitored occurs.
According to the fault diagnosis method provided by the embodiment of the invention, each candidate spectrogram is analyzed, the amplitude corresponding to each frequency in each candidate spectrogram is determined, and the accuracy of the determined amplitude corresponding to each frequency in each candidate spectrogram is ensured. And aiming at each frequency, comparing the corresponding amplitude values of each candidate spectrogram at the same frequency, and determining the corresponding maximum amplitude value of each candidate spectrogram at the same frequency, so that the accuracy of the determined corresponding maximum amplitude value of each candidate spectrogram at the same frequency is ensured. And then, the maximum amplitude is taken as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram, so that the accuracy of the generated target spectrogram is ensured.
In addition, the fault diagnosis method provided by the embodiment of the invention analyzes the target spectrogram, determines the highest amplitude in the target spectrogram, and ensures the accuracy of the determined highest amplitude in the target spectrogram. And then, according to the corresponding relation between the amplitude and the frequency, determining the target frequency corresponding to the highest amplitude in the target spectrogram, so that the accuracy of the determined target frequency is ensured. And determining the fault component corresponding to the equipment to be monitored according to the corresponding relation between the frequency and the component, thereby ensuring the accuracy of the determined fault component corresponding to the equipment to be monitored.
It should be understood that although the steps in the flowcharts of fig. 1, 2 and 13 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not limited to being performed in the exact order illustrated and, unless explicitly stated herein, may be performed in other orders. Moreover, at least some of the steps in fig. 1, 2, and 13 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least some of the other steps.
As shown in fig. 15, the present embodiment provides a failure diagnosis apparatus including:
the obtaining module 41 is configured to obtain vibration data corresponding to a plurality of vibration measuring points of the device to be monitored;
the generating module 42 is configured to analyze the vibration data corresponding to each vibration measurement point, and generate a candidate spectrogram corresponding to each vibration measurement point;
a fusion module 43, configured to perform fusion processing on each candidate spectrogram according to a relationship between the amplitudes corresponding to each candidate spectrogram, so as to generate a target spectrogram;
and the determining module 44 is configured to analyze the amplitude and the frequency in the target spectrogram, and determine a fault corresponding to the device to be monitored.
In an embodiment of the present application, the vibration data is vibration acceleration data, and the generating module 42 is specifically configured to perform integral calculation on each vibration acceleration data to obtain time-domain vibration velocity data corresponding to each vibration acceleration data; and analyzing the time-domain vibration velocity data to generate candidate spectrograms.
In an embodiment of the present application, the generating module 42 is specifically configured to perform fourier transform on each time-domain vibration velocity data to generate frequency-domain vibration velocity data; and analyzing the vibration speed data of each frequency domain to generate each candidate spectrogram.
In an embodiment of the present application, the fusion module 43 is specifically configured to analyze each candidate spectrogram, and determine an amplitude corresponding to each frequency in each candidate spectrogram; for each frequency, comparing the corresponding amplitude values of each candidate spectrogram at the same frequency, and determining the corresponding maximum amplitude value of each candidate spectrogram at the same frequency; and taking the maximum amplitude as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram.
In an embodiment of the present application, the determining module 44 is specifically configured to analyze the target spectrogram and determine a highest amplitude value in the target spectrogram; determining a target frequency corresponding to the highest amplitude in the target spectrogram according to the corresponding relation between the amplitude and the frequency; and determining the part with the fault corresponding to the equipment to be monitored according to the corresponding relation between the frequency and the part.
In an embodiment of the present application, the obtaining module 41 is specifically configured to simultaneously acquire, by using a plurality of acquiring devices connected to the same vibration data acquiring station, vibration data corresponding to a plurality of vibration measuring points corresponding to a device to be monitored, where the acquiring parameters corresponding to the plurality of acquiring devices are the same.
For specific limitations and beneficial effects of the fault diagnosis device, reference may be made to the above limitations on the fault diagnosis method, which are not described herein again. The modules in the fault diagnosis device can be wholly or partially realized by software, hardware and a combination thereof. The modules may be embedded in a hardware form or may be independent of a processor in the electronic device, or may be stored in a memory in the electronic device in a software form, so that the processor calls and executes operations corresponding to the modules.
An embodiment of the present invention further provides an electronic device, which includes the fault diagnosis apparatus shown in fig. 15.
As shown in fig. 16, fig. 16 is a schematic structural diagram of an electronic device according to an alternative embodiment of the present invention, and as shown in fig. 16, the electronic device may include: at least one processor 51, such as a CPU (Central Processing Unit), at least one communication interface 53, memory 54, at least one communication bus 52. Wherein a communication bus 52 is used to enable the connection communication between these components. The communication interface 53 may include a Display (Display) and a Keyboard (Keyboard), and the optional communication interface 53 may also include a standard wired interface and a standard wireless interface. The Memory 54 may be a high-speed RAM Memory (volatile Random Access Memory) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The memory 54 may alternatively be at least one memory device located remotely from the processor 51. Wherein the processor 51 may be in connection with the apparatus described in fig. 15, the memory 54 stores an application program, and the processor 51 calls the program code stored in the memory 54 for performing any of the above-mentioned method steps.
The communication bus 52 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 52 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 16, but this is not intended to represent only one bus or type of bus.
The memory 54 may include a volatile memory (RAM), such as a random-access memory (RAM); the memory may also include a non-volatile memory (english: flash memory), such as a Hard Disk Drive (HDD) or a solid-state drive (SSD); the memory 54 may also comprise a combination of the above types of memories.
The processor 51 may be a Central Processing Unit (CPU), a Network Processor (NP), or a combination of a CPU and an NP.
The processor 51 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a field-programmable gate array (FPGA), a General Array Logic (GAL), or any combination thereof.
Optionally, the memory 54 is also used to store program instructions. The processor 51 may call program instructions to implement the fault diagnosis method as shown in the embodiments of fig. 1, fig. 2 and fig. 13 of the present application.
An embodiment of the present invention further provides a non-transitory computer storage medium, where a computer-executable instruction is stored in the computer storage medium, and the computer-executable instruction may execute the fault diagnosis method in any of the above method embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk Drive (Hard Disk Drive, abbreviated as HDD), or a Solid State Drive (SSD); the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.
Claims (10)
1. A fault diagnosis method, characterized in that the method comprises:
obtaining vibration data corresponding to a plurality of vibration measuring points of equipment to be monitored;
analyzing the vibration data corresponding to each vibration measuring point to generate a candidate spectrogram corresponding to each vibration measuring point;
according to the relation between the corresponding amplitudes of the candidate spectrograms, performing fusion processing on the candidate spectrograms to generate a target spectrogram;
and analyzing the amplitude and the frequency in the target spectrogram, and determining the fault corresponding to the equipment to be monitored.
2. The method of claim 1, wherein the vibration data is vibration acceleration data, and the analyzing the vibration data corresponding to each vibration measurement point to generate a candidate spectrogram corresponding to each vibration measurement point comprises
Performing integral calculation on each vibration acceleration data to obtain time domain vibration speed data corresponding to each vibration acceleration data;
and analyzing each time domain vibration velocity data to generate each candidate spectrogram.
3. The method of claim 2, wherein said analyzing each of said time-domain vibroseis velocity data to generate each of said candidate spectrograms comprises:
carrying out Fourier transform on each time domain vibration velocity data to generate frequency domain vibration velocity data;
and analyzing the frequency domain vibration speed data to generate the candidate spectrogram.
4. The method according to claim 1, wherein the generating the target spectrogram by fusing each of the candidate spectrograms according to the relationship between the amplitudes corresponding to the candidate spectrograms comprises:
analyzing each candidate spectrogram, and determining the amplitude corresponding to each frequency in each candidate spectrogram;
for each frequency, comparing corresponding amplitudes of the candidate spectrograms at the same frequency, and determining the corresponding maximum amplitude of the candidate spectrograms at the same frequency;
and taking the maximum amplitude as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram.
5. The method according to claim 1, wherein the analyzing the amplitude and the frequency in the target spectrogram to determine the fault corresponding to the device to be monitored comprises:
analyzing the target spectrogram and determining the highest amplitude value in the target spectrogram;
determining a target frequency corresponding to the highest amplitude in the target spectrogram according to the corresponding relation between the amplitude and the frequency;
and determining the part with the fault corresponding to the equipment to be monitored according to the corresponding relation between the frequency and the part.
6. The method of claim 1, wherein obtaining vibration data corresponding to a plurality of vibration measurement points of the equipment to be monitored comprises:
and simultaneously acquiring vibration data corresponding to the vibration measuring points corresponding to the equipment to be monitored by utilizing a plurality of acquisition equipment connected to the same vibration data acquisition station, wherein the acquisition parameters corresponding to the plurality of acquisition equipment are the same.
7. A failure diagnosis device characterized by comprising:
the acquisition module is used for acquiring vibration data corresponding to a plurality of vibration measuring points of the equipment to be monitored;
the generating module is used for analyzing the vibration data corresponding to each vibration measuring point to generate a candidate spectrogram corresponding to each vibration measuring point;
the fusion module is used for performing fusion processing on each candidate spectrogram according to the relation between the amplitude values corresponding to the candidate spectrograms to generate a target spectrogram;
and the determining module is used for analyzing the amplitude and the frequency in the target spectrogram and determining the fault corresponding to the equipment to be monitored.
8. The apparatus according to claim 7, wherein the generating module is configured to perform an integral calculation on each of the vibration acceleration data to obtain time-domain vibration velocity data corresponding to each of the vibration acceleration data; and analyzing each time domain vibration velocity data to generate each candidate spectrogram.
9. An electronic device comprising a memory and a processor, wherein the memory stores computer instructions, and the processor executes the computer instructions to perform the fault diagnosis method according to any one of claims 1 to 6.
10. A computer-readable storage medium storing computer instructions for causing a computer to execute the fault diagnosis method according to any one of claims 1 to 6.
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