CN115931319B - Fault diagnosis method, device, electronic equipment and storage medium - Google Patents
Fault diagnosis method, device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application relates to the field of industrial equipment, in particular to a fault diagnosis method, a fault diagnosis 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 candidate spectrograms corresponding to each vibration measuring point; according to the relation between the corresponding amplitudes of the candidate spectrograms, carrying out 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. According to the method, the faults corresponding to the equipment to be monitored can be determined only by analyzing the amplitude and the frequency in the target spectrogram without identifying and analyzing the spectrograms corresponding to the vibration measuring points, so that the time is saved, and the efficiency of determining the faults corresponding to the equipment to be monitored is improved.
Description
Technical Field
The application relates to the field of industrial equipment, in particular to a fault diagnosis method, a fault diagnosis device, electronic equipment and a storage medium.
Background
Vibration is an important factor affecting the safe operation of the rotary machine, and also directly reflects the operating state of the device. Most structural or mechanical faults of the rotating machinery can be represented by vibration signals, so that the vibration monitoring of the rotating machinery is an important work for monitoring the state of equipment.
In the prior art, for a system for monitoring single equipment online, in order to accurately analyze single fault points, a plurality of vibration measuring points are generally deployed on one single equipment, vibration data collected by each vibration measuring point are respectively subjected to a series of processing and transformation, a spectrogram is finally obtained, and further analysis is performed according to the spectrogram.
In the prior art, a spectrogram is generated aiming at a single measuring point. Therefore, if one single equipment part has a plurality of measuring points, the spectrograms corresponding to the plurality of measuring points respectively need to be checked to judge whether the single equipment fails. Therefore, the above method takes a long time and is inefficient.
Disclosure of Invention
In view of the above, the embodiment of the application provides a fault diagnosis method, which aims to solve the problems of long time spent and low efficiency of single equipment fault diagnosis in the prior art.
According to a first aspect, an embodiment of the present application 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 candidate spectrograms corresponding to each vibration measuring point;
according to the relation between the corresponding amplitudes of the candidate spectrograms, carrying out 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.
According to the fault diagnosis method provided by the embodiment of the application, 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 is 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. According to the relation between the corresponding amplitudes of the candidate spectrograms, fusion processing is carried out on the candidate spectrograms to generate a target spectrogram, so that the characteristics of the candidate spectrograms can be included in the generated target 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 faults corresponding to the equipment to be monitored can be determined only by analyzing the amplitude and the frequency in the target spectrogram without identifying and analyzing the spectrograms corresponding to the vibration measuring points, so that the time is saved, and the efficiency of determining the faults corresponding to the equipment to be monitored is improved.
With reference to the first aspect, in a first implementation manner of the first aspect, the vibration data is vibration acceleration data, the vibration data corresponding to each vibration measurement point is analyzed, and a candidate spectrogram corresponding to each vibration measurement point is generated, including
Integrating and calculating each vibration acceleration data to obtain time domain vibration speed data corresponding to each vibration acceleration data;
and analyzing the time domain vibration speed data to generate candidate spectrograms.
According to the fault diagnosis method provided by the embodiment of the application, 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 speed data to generate each candidate spectrogram, so that the accuracy of each generated candidate spectrogram 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:
performing Fourier transform on each time domain vibration speed data to generate frequency domain vibration speed 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 application, fourier transformation is carried out on each time domain vibration speed data to generate the frequency domain vibration speed data, so that the accuracy of the generated frequency domain vibration speed 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, according to a relationship between magnitudes corresponding to each candidate spectrogram, performing fusion processing on each candidate spectrogram to generate a target spectrogram, including:
analyzing each candidate spectrogram, and determining the amplitude corresponding to each frequency in each candidate spectrogram;
comparing the corresponding amplitude values of the candidate spectrograms under the same frequency aiming at each frequency, and determining the corresponding maximum amplitude value of the candidate spectrograms under 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 application, 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 comparing the corresponding amplitude values of the candidate spectrograms at the same frequency aiming at each frequency, determining the corresponding maximum amplitude value of the candidate spectrograms at the same frequency, and ensuring the accuracy of the determined corresponding maximum amplitude value of the candidate spectrograms at the same frequency. And then, taking the maximum amplitude as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram, thereby ensuring the accuracy of the generated target spectrogram.
With reference to the first aspect, in a fourth implementation manner of the first aspect, analyzing the amplitude and the frequency in the target spectrogram, determining a fault corresponding to the device to be monitored includes:
analyzing the target spectrogram, and determining the highest amplitude value in the target spectrogram;
according to the corresponding relation between the amplitude and the frequency, determining a target frequency corresponding to the highest amplitude in the target spectrogram;
and determining the component with the fault corresponding to the equipment to be monitored according to the corresponding relation between the frequency and the component.
According to the fault diagnosis method provided by the embodiment of the application, the target spectrogram is analyzed, the highest amplitude in the target spectrogram is determined, and the accuracy of the determined highest amplitude in the target spectrogram is ensured. 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, thereby ensuring the accuracy of the determined target frequency. According to the corresponding relation between the frequency and the components, the components with faults corresponding to the equipment to be monitored are determined, and the accuracy of the determined components with faults corresponding to the equipment to be monitored is ensured.
With reference to the first aspect, in a fifth implementation manner of the first aspect, obtaining 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 using a plurality of acquisition equipment connected to the same vibration data acquisition station, wherein acquisition parameters corresponding to the plurality of acquisition equipment are the same.
According to the fault diagnosis method provided by the embodiment of the application, the vibration data corresponding to the vibration measuring points corresponding to the equipment to be monitored are collected simultaneously by utilizing the plurality of collecting equipment connected to the same vibration data collecting station, wherein the collecting parameters corresponding to the plurality of collecting equipment are the same, and the accuracy of the vibration data corresponding to the vibration measuring points corresponding to the equipment to be monitored obtained by collecting is ensured.
According to a second aspect, an embodiment of the present application 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 generation 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 carrying out 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 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.
According to the fault diagnosis device provided by the embodiment of the application, 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 is 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. According to the relation between the corresponding amplitudes of the candidate spectrograms, fusion processing is carried out on the candidate spectrograms to generate a target spectrogram, so that the characteristics of the candidate spectrograms can be included in the generated target 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 fault diagnosis device, the frequency spectrograms corresponding to the vibration measuring points do not need to be identified and analyzed, but only the amplitude and the frequency in the target frequency spectrogram are needed to be analyzed, so that the faults corresponding to the equipment to be monitored can be determined, time is saved, and the efficiency of determining the faults 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: integrating and calculating each vibration acceleration data to obtain time domain vibration speed data corresponding to each vibration acceleration data; and analyzing the time domain vibration speed data to generate candidate spectrograms.
According to the fault diagnosis device provided by the embodiment of the application, the integration 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 speed data to generate each candidate spectrogram, so that the accuracy of each generated candidate spectrogram is ensured.
According to a third aspect, an embodiment of the present application provides an electronic device, including a memory and a processor, where the memory and the processor are communicatively connected to each other, and the memory stores computer instructions, and the processor executes the computer instructions, thereby executing the fault diagnosis method in the first aspect or any implementation manner of the first aspect.
According to a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing computer instructions for causing a computer to perform 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 application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a fault diagnosis method provided by an embodiment of the present application;
FIG. 2 is a flow chart of a fault diagnosis method provided by another embodiment of the present application;
FIG. 3 is a schematic illustration of an acquisition device according to another embodiment of the present application coupled to the same vibration data acquisition station;
FIG. 4 is a schematic diagram of a vibration acceleration time domain waveform provided by another embodiment of the present application;
FIG. 5 is a schematic diagram of a vibration acceleration time domain waveform provided by another embodiment of the present application;
FIG. 6 is a schematic diagram of a vibration acceleration time domain waveform provided by another embodiment of the present application;
FIG. 7 is a schematic diagram of a waveform diagram of vibration velocity in time domain provided by another embodiment of the present application;
FIG. 8 is a schematic diagram of a waveform diagram of vibration velocity in time domain provided by another embodiment of the present application;
FIG. 9 is a schematic diagram of a waveform diagram of vibration velocity in time domain provided by another embodiment of the present application;
FIG. 10 is a schematic diagram of a velocity spectrum waveform provided by another embodiment of the present application;
FIG. 11 is a schematic diagram of a velocity spectrum waveform provided by another embodiment of the present application;
FIG. 12 is a schematic diagram of a velocity spectrum waveform provided by another embodiment of the present application;
FIG. 13 is a flow chart of a fault diagnosis method provided by another embodiment of the present application;
FIG. 14 is a schematic diagram of a target spectrogram generated in a fault diagnosis method according to another embodiment of the present application;
fig. 15 is a functional block diagram of a fault diagnosis apparatus to which the embodiment of the present application is applied;
fig. 16 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that, in the fault diagnosis method provided by the embodiment of the present application, the 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 manner of 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 the device to be monitored, the electronic device may be a server or a terminal, where the server in the embodiment of the application may be a server or a server cluster formed by multiple servers, and the terminal in the embodiment of the application may be other intelligent hardware devices 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.
In one embodiment of the present application, as shown in fig. 1, a fault diagnosis method is provided, and the method is applied to an electronic device for illustration, and includes the following steps:
s11, vibration data corresponding to a plurality of vibration measuring points of the equipment to be monitored are obtained.
Specifically, the electronic device may receive vibration data corresponding to a plurality of vibration measuring points of the device to be monitored, which are transmitted by the acquisition device connected to the electronic device, may also receive vibration data corresponding to a plurality of vibration measuring points of the device to be monitored, which are input by a user, and may also receive vibration data corresponding to a plurality of vibration measuring points of the device to be monitored, which are sent by other devices. The mode of the electronic equipment for acquiring the vibration data corresponding to the vibration measuring points of the equipment to be monitored is not particularly limited.
This step will be described in detail below.
S12, analyzing the vibration data corresponding to each vibration measuring point, and generating a candidate spectrogram corresponding to each vibration measuring point.
In an optional embodiment of the present application, the electronic device may analyze the vibration data corresponding to each vibration measurement point, determine the frequency and the amplitude in the vibration data corresponding to each vibration measurement point, and then generate the candidate spectrogram corresponding to each vibration measurement point according to the determined correspondence between the frequency and the amplitude.
This step will be described in detail below.
S13, according to the relation between the amplitude values corresponding to the candidate spectrograms, fusion processing is carried out on the candidate spectrograms, and a target spectrogram is generated.
In an alternative embodiment, 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 the target spectrogram. Wherein the feature image may be an image comprising a maximum amplitude.
This step will be described in detail below.
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 the fault corresponding to the device to be monitored and the component with the fault.
This step will be described in detail below.
According to the fault diagnosis method provided by the embodiment of the application, 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 is 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. According to the relation between the corresponding amplitudes of the candidate spectrograms, fusion processing is carried out on the candidate spectrograms to generate a target spectrogram, so that the characteristics of the candidate spectrograms can be included in the generated target 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 faults corresponding to the equipment to be monitored can be determined only by analyzing the amplitude and the frequency in the target spectrogram without identifying and analyzing the spectrograms corresponding to the vibration measuring points, so that the time is saved, and the efficiency of determining the faults corresponding to the equipment to be monitored is improved.
In one embodiment of the present application, as shown in fig. 2, a fault diagnosis method is provided, and the method is applied to an electronic device for illustration, and includes the following steps:
s21, vibration data corresponding to a plurality of vibration measuring points of the equipment to be monitored are obtained.
In an optional embodiment of the present application, the step of 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 acquiring vibration data corresponding to a plurality of vibration measuring points corresponding to the equipment to be monitored by using a plurality of acquisition equipment connected to the same vibration data acquisition station.
Wherein, the collection parameters that a plurality of collection equipment correspond are the same.
Specifically, for all vibration measuring points of the same device to be monitored, the electronic device may connect the acquisition devices corresponding to each vibration measuring point to the same vibration data acquisition station, where the connection diagram is shown in fig. 3, and then set the same acquisition parameters for each acquisition device.
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 period is 1 second.
The electronic equipment can monitor the vibration condition of a transmission case in a high-speed wire finish rolling area of a certain steel mill, and 6 vibration measuring points are deployed on the transmission case, wherein the vibration measuring points 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, for example, the sampling frequency is 25600Hz, and the sampling time is 1 second.
For example, assuming that the vibration data is vibration acceleration data, every t is set a A batch of data is synchronously collected at all vibration measuring points in unit time, the sampling frequency of each batch of data is fs Hz, the number of sampling points is n, and the vibration acceleration data collected at 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 measurement points, the sampling frequency is set to 25600Hz, and 25600 data points are acquired for 1 second. The corresponding vibration acceleration time domain waveform diagrams of the 3 measuring points collected at the same moment 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 。
S22, analyzing the vibration data corresponding to each vibration measuring point, and generating a candidate spectrogram corresponding to each vibration measuring point.
In an optional embodiment of the present application, the vibration data is vibration acceleration data, and the step of analyzing the vibration data corresponding to each vibration measurement point to generate a candidate spectrogram corresponding to each vibration measurement point in the step S22 may generate the following steps:
s221, performing integral calculation on each vibration acceleration data to obtain time domain vibration speed data corresponding to each vibration acceleration data.
Specifically, the electronic device may perform integral calculation on each vibration acceleration data to obtain time domain vibration velocity data corresponding to each vibration acceleration data.
The vibration acceleration data corresponding to each vibration measuring point is an acceleration time domain waveform, N vibration measuring points have N acceleration time domain waveforms, and each acceleration time domain waveform can be converted into a speed time domain waveform through integration. The integral formula is:
where v (t) is time domain vibration velocity data, and a (u) is vibration acceleration data.
S222, analyzing the time domain vibration speed data to generate candidate spectrograms.
In an alternative 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. The generated candidate spectrograms can be velocity time domain waveform diagrams, and the velocity time domain waveform diagrams can be shown in fig. 7-9.
In another alternative embodiment of the present application, the "analyzing each time domain vibration velocity data to generate each candidate spectrogram" in S222 may generate the following steps:
(1) Fourier transforming 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.
Specifically, since the faults of the device to be monitored are often caused by one or more parts thereof, and different parts generally cause vibrations of different frequencies, the time domain waveform needs to be converted into the frequency domain waveform so as to be convenient for checking which frequency has high amplitude, so as to correspond to the matched device parts. Thus, after the electronic device acquires the respective time-domain vibration velocity data, the electronic device may perform discrete-time fourier transform on the respective time-domain vibration velocity data to generate frequency-domain vibration velocity data.
Then, the electronic device analyzes the frequency domain vibration velocity data to generate candidate spectrograms. 10-12, each candidate spectrogram generated may be a velocity spectrogram.
S23, according to the relation between the amplitude values corresponding to the candidate spectrograms, fusion processing is carried out on the candidate spectrograms, and a target spectrogram is generated.
For this step, please refer to the description of S13 in fig. 1, and a detailed description is omitted here.
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 the description of S14 in fig. 1, and a detailed description is omitted here.
According to the fault diagnosis method provided by the embodiment of the application, the vibration data corresponding to the vibration measuring points corresponding to the equipment to be monitored are collected simultaneously by utilizing the plurality of collecting equipment connected to the same vibration data collecting station, wherein the collecting parameters corresponding to the plurality of collecting equipment are the same, and the accuracy of the vibration data corresponding to the vibration measuring points corresponding to the equipment to be monitored obtained by collecting is ensured.
In addition, according to the fault diagnosis method provided by the embodiment of the application, the integration 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 carrying out Fourier transform on each time domain vibration speed data to generate frequency domain vibration speed data, thereby ensuring the accuracy of the generated frequency domain vibration speed data. 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 one embodiment of the present application, as shown in fig. 13, a fault diagnosis method is provided, which is described by taking the application of the method to an electronic device as an example, and includes the following steps:
s31, vibration data corresponding to a plurality of vibration measuring points of the equipment to be monitored are obtained.
For this step, please refer to the description of S21 in fig. 2, and a detailed description is omitted here.
S32, analyzing the vibration data corresponding to each vibration measuring point, and generating a candidate spectrogram corresponding to each vibration measuring point.
For this step, please refer to fig. 2 for description of S22, and detailed description thereof is omitted herein.
S33, according to the relation between the amplitude values corresponding to the candidate spectrograms, fusion processing is carried out on the candidate spectrograms, and a target spectrogram is generated.
In an optional embodiment of the present application, the step S33 "of performing fusion processing on each candidate spectrogram according to the relationship between the magnitudes corresponding to each candidate spectrogram to generate 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 to determine an amplitude corresponding to each frequency in each candidate spectrogram.
S332, comparing the corresponding amplitude values of the candidate spectrograms at the same frequency for each frequency, and determining the corresponding maximum amplitude value of the candidate spectrograms at the same frequency.
Specifically, for each frequency, the electronic device compares the corresponding amplitude values of each candidate spectrogram under the same frequency, and determines the corresponding maximum amplitude value of each candidate spectrogram under the same frequency.
For example, taking frequency 2000 as an example, the electronic device may obtain the corresponding amplitude values when the frequency is 2000 in each candidate spectrogram, and then compare the corresponding amplitude values when the frequency is 2000 to determine the corresponding 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 uses the maximum amplitude as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram.
The electronic device generates the target spectrogram according to the method, and the electronic device generates the target spectrogram according to the method, as shown in fig. 14, by way of example, the maximum amplitude corresponding to the frequency 2000 is used as the amplitude corresponding to the frequency 2000 in the target spectrogram.
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 embodiment of the present application, the step S34 "analyzing the amplitude and the frequency in the target spectrogram to determine the 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 the target spectrogram is generated, the electronic device may perform image recognition on the target spectrogram, and determine the highest amplitude in the target spectrogram.
S342, determining the target frequency corresponding to the highest amplitude in the target spectrogram according to the corresponding relation between the amplitude and the frequency.
Specifically, the electronic device determines a target frequency corresponding to the highest amplitude in the target spectrogram according to the corresponding relation between the amplitude and the frequency.
S343, determining the component with the fault 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, the component in which the fault corresponding to the device to be monitored occurs.
According to the fault diagnosis method provided by the embodiment of the application, 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 comparing the corresponding amplitude values of the candidate spectrograms at the same frequency aiming at each frequency, determining the corresponding maximum amplitude value of the candidate spectrograms at the same frequency, and ensuring the accuracy of the determined corresponding maximum amplitude value of the candidate spectrograms at the same frequency. And then, taking the maximum amplitude as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram, thereby ensuring the accuracy of the generated target spectrogram.
In addition, the fault diagnosis method provided by the embodiment of the application 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, thereby ensuring the accuracy of the determined target frequency. According to the corresponding relation between the frequency and the components, the components with faults corresponding to the equipment to be monitored are determined, and the accuracy of the determined components with faults corresponding to the equipment to be monitored is ensured.
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, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least a portion of the steps of fig. 1, 2, and 13 may include a plurality of steps or stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the execution of the steps or stages is not necessarily sequential, but may be performed in turn or alternately with at least a portion of the steps or stages of other steps or other steps.
As shown in fig. 15, the present embodiment provides a failure diagnosis apparatus including:
the acquisition module 41 is used for acquiring vibration data corresponding to a plurality of vibration measuring points of the equipment 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;
the fusion module 43 is configured to perform fusion processing on each candidate spectrogram according to the relationship between the magnitudes corresponding to each candidate spectrogram, so as to generate a target spectrogram;
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 one 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 speed data to generate candidate spectrograms.
In one 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 one 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; comparing the corresponding amplitude values of the candidate spectrograms under the same frequency aiming at each frequency, and determining the corresponding maximum amplitude value of the candidate spectrograms under 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 one embodiment of the present application, the determining module 44 is specifically configured to analyze the target spectrogram and determine the highest amplitude in the target spectrogram; according to the corresponding relation between the amplitude and the frequency, determining a target frequency corresponding to the highest amplitude in the target spectrogram; and determining the component with the fault corresponding to the equipment to be monitored according to the corresponding relation between the frequency and the component.
In one embodiment of the present application, the acquiring module 41 is specifically configured to simultaneously acquire, by using a plurality of acquisition devices connected to the same vibration data acquisition station, vibration data corresponding to a plurality of vibration measurement points corresponding to a device to be monitored, where the acquisition parameters corresponding to the plurality of acquisition devices are the same.
The specific limitations and beneficial effects of the fault diagnosis apparatus can be found in the above limitations of the fault diagnosis method, and will not be described in detail herein. The respective modules in the above-described fault diagnosis apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or independent of a processor in the electronic device, or may be stored in software in a memory in the electronic device, so that the processor may call and execute operations corresponding to the above modules.
The embodiment of the application also provides electronic equipment, which is provided with the fault diagnosis device shown in the figure 15.
Fig. 16 is a schematic structural diagram of an electronic device according to an alternative embodiment of the present application, as shown in fig. 16, where the electronic device may include: at least one processor 51, such as a CPU (Central Processing Unit ), at least one communication interface 53, a memory 54, at least one communication bus 52. Wherein the communication bus 52 is used to enable connected communication between these components. The communication interface 53 may include a Display screen (Display) and a Keyboard (Keyboard), and the selectable communication interface 53 may further include a standard wired interface and a wireless interface. The memory 54 may be a high-speed RAM memory (Random Access 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 aforementioned processor 51. Wherein the processor 51 may be as described in connection with fig. 15, the memory 54 stores an application program, and the processor 51 invokes the program code stored in the memory 54 for performing any of the method steps described above.
The communication bus 52 may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The communication bus 52 may be classified as an address bus, a data bus, a control bus, or the like. For ease of illustration, only one thick line is shown in fig. 16, but not only one bus or one type of bus.
Wherein the memory 54 may include volatile memory (english) such as random-access memory (RAM); the memory may also include a nonvolatile memory (english: non-volatile memory), such as a flash memory (english: flash memory), a hard disk (english: hard disk drive, abbreviated as HDD) or a solid state disk (english: solid-state drive, abbreviated as SSD); memory 54 may also include a combination of the types of memory described above.
The processor 51 may be a central processor (English: central processing unit, abbreviated: CPU), a network processor (English: network processor, abbreviated: NP) or a combination of CPU and NP.
The processor 51 may further include a hardware chip, among others. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof (English: programmable logic device). The PLD may be a complex programmable logic device (English: complex programmable logic device, abbreviated: CPLD), a field programmable gate array (English: field-programmable gate array, abbreviated: FPGA), a general-purpose array logic (English: generic array logic, abbreviated: GAL), or any combination thereof.
Optionally, the memory 54 is also used for storing program instructions. The processor 51 may invoke program instructions to implement the fault diagnosis method as shown in the embodiments of fig. 1, 2 and 13 of the present application.
The embodiment of the application also provides a non-transitory computer storage medium, which stores computer executable instructions that can execute the fault diagnosis method in any of the above method embodiments. Wherein the storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), or a Solid State Drive (SSD); the storage medium may also comprise a combination of memories of the kind described above.
Although embodiments of the present application have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the application, and such modifications and variations fall within the scope of the application as defined by the appended claims.
Claims (8)
1. A fault diagnosis method, the method comprising:
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, wherein the candidate spectrogram represents a generation result of the corresponding amplitude of each sampling point in each time domain vibration speed data;
analyzing each candidate spectrogram, and determining the amplitude corresponding to each frequency in each candidate spectrogram;
comparing the corresponding amplitude values of the candidate spectrograms under the same frequency aiming at each frequency, and determining the corresponding maximum amplitude value of each candidate spectrogram under the same frequency;
taking the maximum amplitude as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram;
analyzing the target spectrogram, and determining the highest amplitude value in the target spectrogram;
according to the corresponding relation between the amplitude and the frequency, determining a target frequency corresponding to the highest amplitude in a target spectrogram;
and determining the component with the fault corresponding to the equipment to be monitored according to the corresponding relation between the frequency and the component.
2. The method of claim 1, wherein the vibration data is vibration acceleration data, the analyzing the vibration data corresponding to each vibration measurement point generates a candidate spectrogram corresponding to each vibration measurement point, including
Integrating and calculating each vibration acceleration data to obtain time domain vibration speed data corresponding to each vibration acceleration data;
and analyzing the time domain vibration speed data to generate each candidate spectrogram.
3. The method of claim 2, wherein said analyzing each of said time domain vibration velocity data to generate each of said candidate spectrograms comprises:
performing Fourier transform on each time domain vibration speed data to generate frequency domain vibration speed data;
and analyzing the frequency domain vibration speed data to generate each candidate spectrogram.
4. The method according to claim 1, wherein the obtaining vibration data corresponding to a plurality of vibration measuring points of the device to be monitored includes:
and simultaneously acquiring vibration data corresponding to the vibration measuring points corresponding to the equipment to be monitored by using a plurality of acquisition equipment connected to the same vibration data acquisition station, wherein acquisition parameters corresponding to the plurality of acquisition equipment are the same.
5. A fault diagnosis apparatus 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 generation 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 analyzing each candidate spectrogram and determining the amplitude corresponding to each frequency in each candidate spectrogram; comparing the corresponding amplitude values of the candidate spectrograms under the same frequency aiming at each frequency, and determining the corresponding maximum amplitude value of each candidate spectrogram under the same frequency; taking the maximum amplitude as the amplitude of the corresponding frequency in the target spectrogram to generate the target spectrogram;
the determining module is used for analyzing the target spectrogram and determining the highest amplitude value in the target spectrogram;
according to the corresponding relation between the amplitude and the frequency, determining a target frequency corresponding to the highest amplitude in a target spectrogram;
and determining the component with the fault corresponding to the equipment to be monitored according to the corresponding relation between the frequency and the component.
6. The apparatus of claim 5, wherein the vibration data is vibration acceleration data; the generating module is used for carrying out integral calculation on each vibration acceleration data to obtain time domain vibration speed data corresponding to each vibration acceleration data; analyzing each time domain vibration speed data to generate each candidate spectrogram, wherein the candidate spectrogram represents a generation result of the corresponding amplitude of each sampling point in each time domain vibration speed data.
7. An electronic device comprising a memory having stored therein computer instructions and a processor that, upon execution of the computer instructions, performs the fault diagnosis method of any of claims 1-4.
8. A computer-readable storage medium storing computer instructions for causing a computer to execute the fault diagnosis method of any one of claims 1 to 4.
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