CN116292246B - Fault monitoring method and system for vacuum pump - Google Patents
Fault monitoring method and system for vacuum pump Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B51/00—Testing machines, pumps, or pumping installations
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Abstract
The application relates to the technical field of artificial intelligence, and provides a fault monitoring method and system for a vacuum pump. The method comprises the following steps: the multi-stage vacuum pump is monitored in real time, and multi-dimensional working operation data information is acquired; classifying and integrating the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information; performing operation effect evaluation on the multidimensional operation attribute data information based on the operation standard of the vacuum pump to obtain operation effect information of the vacuum pump; when the operation effect information of the vacuum pump does not reach the standard vacuum pump effect threshold value, marking unqualified operation data to obtain fault data information of the vacuum pump; inputting the vacuum pump fault data information into a vacuum pump fault analysis model, and outputting vacuum pump fault diagnosis information; and performing fault early warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information. By adopting the method, the early warning timeliness of the operation faults can be realized, and the technical effect of safe operation of the vacuum pump is further ensured.
Description
Technical Field
The application relates to the technical field of artificial intelligence, in particular to a fault monitoring method and system of a vacuum pump.
Background
The vacuum pump is a device or equipment for pumping air from a pumped container by using mechanical, physical, chemical or physicochemical methods to obtain vacuum, and is a device for improving, generating and maintaining vacuum in a certain enclosed space by using various methods, and is widely used in the industries of metallurgy, chemical industry, food, electronic coating and the like. The method has important application significance for ensuring the safe operation of the vacuum pump, and carrying out real-time monitoring and timely fault treatment on the vacuum pump.
However, the prior art has the technical problems that the intelligent degree of the operation fault diagnosis is low, the operation fault cannot be early warned in time, and the safe operation of the vacuum pump is influenced.
Disclosure of Invention
Based on the above, it is necessary to provide a fault monitoring method and system for a vacuum pump, which can realize early warning timeliness of operation faults and further ensure safe operation of the vacuum pump.
A method of fault monitoring of a vacuum pump, the method comprising: the multi-stage vacuum pump is monitored in real time through a sensor group, and multi-dimensional working operation data information is acquired; carrying out attribute marking on the multidimensional working operation data information to obtain operation data attribute information; classifying and integrating the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information; obtaining a vacuum pump operation standard, and performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain vacuum pump operation effect information; when the vacuum pump operation effect information does not reach the standard vacuum pump effect threshold value, marking unqualified operation data to obtain vacuum pump fault data information; inputting the vacuum pump fault data information into a vacuum pump fault analysis model, and outputting to obtain vacuum pump fault diagnosis information; and performing fault early warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information.
A fault monitoring system for a vacuum pump, the system comprising: the data monitoring and collecting module is used for monitoring the multi-stage vacuum pump in real time through the sensor group and collecting and obtaining multidimensional working operation data information; the attribute marking module is used for marking the attribute of the multidimensional working operation data information to obtain operation data attribute information; the classification integration module is used for classifying and integrating the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information; the operation effect evaluation module is used for obtaining a vacuum pump operation standard, and performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain vacuum pump operation effect information; the fault data marking module is used for marking unqualified operation data when the operation effect information of the vacuum pump does not reach the standard vacuum pump effect threshold value, so as to obtain fault data information of the vacuum pump; the fault diagnosis information obtaining module is used for inputting the vacuum pump fault data information into a vacuum pump fault analysis model and outputting and obtaining the vacuum pump fault diagnosis information; and the fault early warning processing module is used for carrying out fault early warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
the multi-stage vacuum pump is monitored in real time through a sensor group, and multi-dimensional working operation data information is acquired;
carrying out attribute marking on the multidimensional working operation data information to obtain operation data attribute information;
Classifying and integrating the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information;
obtaining a vacuum pump operation standard, and performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain vacuum pump operation effect information;
when the vacuum pump operation effect information does not reach the standard vacuum pump effect threshold value, marking unqualified operation data to obtain vacuum pump fault data information;
Inputting the vacuum pump fault data information into a vacuum pump fault analysis model, and outputting to obtain vacuum pump fault diagnosis information;
And performing fault early warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
the multi-stage vacuum pump is monitored in real time through a sensor group, and multi-dimensional working operation data information is acquired;
carrying out attribute marking on the multidimensional working operation data information to obtain operation data attribute information;
Classifying and integrating the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information;
obtaining a vacuum pump operation standard, and performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain vacuum pump operation effect information;
when the vacuum pump operation effect information does not reach the standard vacuum pump effect threshold value, marking unqualified operation data to obtain vacuum pump fault data information;
Inputting the vacuum pump fault data information into a vacuum pump fault analysis model, and outputting to obtain vacuum pump fault diagnosis information;
And performing fault early warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information.
The fault monitoring method and the fault monitoring system for the vacuum pump solve the technical problems that the intelligent degree of operation fault diagnosis is low, the operation fault cannot be early-warned in time in the prior art, and the safe operation of the vacuum pump is affected, achieve the technical effects of acquiring the operation data of the multi-dimensional vacuum pump through real-time monitoring, comprehensively and accurately analyzing the operation fault, intelligently diagnosing the cause of the fault, realizing the early warning timeliness of the operation fault, and further guaranteeing the safe operation of the vacuum pump.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
FIG. 1 is a flow chart of a method for monitoring faults of a vacuum pump according to an embodiment;
FIG. 2 is a schematic flow chart of acquiring multidimensional working operation data information in a fault monitoring method of a vacuum pump according to an embodiment;
FIG. 3 is a block diagram of a fault monitoring system for a vacuum pump in one embodiment;
FIG. 4 is an internal block diagram of a computer device in one embodiment;
Reference numerals illustrate: the system comprises a data monitoring and collecting module 11, an attribute marking module 12, a classification and integration module 13, an operation effect evaluation module 14, a fault data marking module 15, a fault diagnosis information obtaining module 16 and a fault early warning processing module 17.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
As shown in fig. 1, the present application provides a fault monitoring method for a vacuum pump, the method comprising:
Step S100: the multi-stage vacuum pump is monitored in real time through a sensor group, and multi-dimensional working operation data information is acquired;
In one embodiment, as shown in fig. 2, the acquiring obtains multidimensional working operation data information, and step S100 of the present application further includes:
Step S110: the method comprises the steps of monitoring the multistage vacuum pump in real time through a sensor group, wherein the sensor group comprises a temperature and humidity sensor, an acoustic sensor, a flow sensor and a current sensor;
step S120: acquiring operation temperature and humidity information, operation current information and vacuum flow information of the multistage vacuum pump respectively through the temperature and humidity sensor, the flow sensor and the current sensor;
Step S130: acquiring sound vibration signal data information of the multistage vacuum pump based on the acoustic sensor;
Step S140: performing signal characteristic analysis on the sound vibration signal data information to obtain sound vibration characteristic information;
Step S150: and acquiring the multidimensional working operation data information based on the operation temperature and humidity information, the operation current information, the vacuum flow information and the sound vibration characteristic information.
In one embodiment, the obtaining the sound vibration characteristic information, step S140 of the present application further includes:
Step S141: carrying out signal noise reduction on the sound vibration signal data information to obtain standard sound vibration signal data information;
Step S142: constructing a vacuum pump fault sound characteristic database;
Step S143: performing signal matching on the standard sound vibration signal data information and the vacuum pump fault sound characteristic database to obtain sound fault type characteristics;
Step S144: obtaining a fault signal amplitude of the sound fault type characteristic;
step S145: and obtaining the sound vibration characteristic information based on the sound fault type characteristic and the fault signal amplitude.
In one embodiment, the step S141 of the present application further includes:
step S1411: performing wavelet decomposition on the data information of the sound vibration signals to obtain wavelet coefficients of the sound signals;
Step S1412: performing threshold quantization according to the wavelet coefficient of the sound signal, and determining a wavelet selection threshold of the sound signal;
step S1413: intercepting the wavelet coefficient of the sound signal according to the wavelet selection threshold of the sound signal to obtain noise signal information smaller than the wavelet selection threshold of the sound signal;
step S1414: and carrying out filtering reconstruction on the noise signal information to obtain the standard sound vibration signal data information.
Specifically, the vacuum pump is a device or equipment for extracting air from an extracted container by using a mechanical, physical, chemical or physicochemical method to obtain vacuum, and is a device for improving, generating and maintaining vacuum in a certain enclosed space by using various methods, and is widely used in industries such as metallurgy, chemical industry, food, electronic coating and the like. The method has important application significance for ensuring the safe operation of the vacuum pump, and carrying out real-time monitoring and timely fault treatment on the vacuum pump.
The multi-stage vacuum pump is monitored in real time through the sensor group, and consists of a plurality of types of vacuum pumps, and various vacuum pumps are combined according to the performance requirements of the multi-stage vacuum pump so as to realize the requirements of convenient use and various vacuum technological processes, wherein the common vacuum pumps comprise a dry screw vacuum pump, a water ring pump, a reciprocating pump, a slide valve pump, a rotary vane pump, a Roots pump, a diffusion pump and the like. The sensor group mainly comprises a temperature and humidity sensor, an acoustic sensor, a flow sensor, a current sensor and the like, the temperature and humidity sensor, the flow sensor and the current sensor are used for monitoring in real time to respectively obtain data such as operation temperature and humidity information, operation current information and suction vacuum flow information of the multistage vacuum pump, and the data information of sound vibration signals of the multistage vacuum pump is acquired and obtained based on the acoustic sensor.
And carrying out signal characteristic analysis on the collected data information of the sound vibration signal, wherein the data information is influenced by on-site environmental noise in an actual working environment, fault characteristic information in the vibration signal is often submerged in the noise signal, and the extraction of sound fault characteristics is influenced. Therefore, the signal noise reduction is firstly carried out on the voice vibration signal data information, specifically, the wavelet decomposition is carried out on the voice vibration signal data information, and the useful waveform can be left and the waveform irrelevant to stripping. The wavelet decomposition means that the signals are gradually subjected to multi-scale refinement through telescopic translation operation, and finally useful waveforms are separated according to the difference of wavelet coefficients generated by decomposing useful signals and irrelevant signals, so that the wavelet coefficients of sound signals generated after the wavelet decomposition are obtained. And setting a threshold range, screening out useful wavelet coefficients, wherein the wavelet coefficients generated by useful signals are larger than those generated by useless/noise signals, carrying out threshold quantization according to the wavelet coefficients of the sound signals, and determining the wavelet selection threshold of the sound signals. Intercepting the wavelet coefficients of the sound signal according to the wavelet selection threshold of the sound signal, namely selecting a proper threshold, wherein the wavelet coefficients larger than the threshold are considered to be generated by the useful signal, and meanwhile, the wavelet coefficients of the useful signal are reserved to the maximum extent; wavelet coefficients less than a threshold are considered noise generated, so that noise signal information less than the wavelet selection threshold of the sound signal is obtained, and useless signals can be screened out. Further, the noise signal information is subjected to filtering reconstruction, and the waveform generated by the useless signal can be screened out by setting the wavelet coefficient corresponding to the useless signal to be 0, so that the standard sound vibration signal data information is obtained.
And constructing a vacuum pump fault sound characteristic database, wherein the vacuum pump fault sound characteristic database is a history vacuum pump various fault sound signals obtained in a big data mode, and the standard sound vibration signal data information is subjected to signal matching with the vacuum pump fault sound characteristic database to obtain corresponding sound fault type characteristics, and the vacuum pump fault sound characteristic database is exemplified by abnormal low noise generated when the vacuum pump capacity is overlarge. And obtaining the amplitude of the fault signal generating the sound fault type characteristic, wherein the larger the amplitude is, the larger the influence degree of the type fault is, and the sound vibration characteristic information is determined based on the sound fault type characteristic and the amplitude of the fault signal to be used as a vacuum pump fault diagnosis reference. And finally, acquiring multidimensional working operation data information by combining the operation temperature and humidity information, the operation current information, the vacuum flow information and the sound vibration characteristic information. The technical effects of acquiring the operation data of the multi-dimensional vacuum pump through real-time monitoring, comprehensively and accurately analyzing the operation faults and further improving the fault analysis accuracy of the vacuum pump are achieved.
Step S200: carrying out attribute marking on the multidimensional working operation data information to obtain operation data attribute information;
step S300: classifying and integrating the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information;
specifically, attribute marking is performed on the multidimensional working operation data information, namely, the multidimensional data is classified and marked according to the data acquisition type, so that corresponding operation data attribute information including temperature and humidity attribute data, acoustic attribute data, flow attribute data, current attribute data and the like is obtained. And then classifying and integrating the multidimensional operation data information according to the operation data attribute information, namely integrating data according to the data attribute type to obtain multidimensional operation attribute data information so as to improve the subsequent operation data processing efficiency.
Step S400: obtaining a vacuum pump operation standard, and performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain vacuum pump operation effect information;
in one embodiment, the step S400 of obtaining the vacuum pump operation effect information further includes:
step S410: performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain a vacuum pump operation scoring matrix;
step S420: constructing an operation scoring mesh map according to the operation data attribute information;
step S430: projecting element values in the vacuum pump operation scoring matrix into the operation scoring mesh map to obtain a vacuum pump operation scoring mesh map;
step S440: and obtaining the vacuum pump operation effect information based on the area value of the vacuum pump operation grading reticulate diagram.
Specifically, the operation standard of the vacuum pump is an industry standard of each performance parameter when the vacuum pump works normally, the operation effect evaluation is performed on the multidimensional operation attribute data information based on the operation standard of the vacuum pump, and the operation effect evaluation can be performed by adopting an expert group evaluation method or a set evaluation rule to obtain a corresponding operation scoring matrix of the vacuum pump, wherein the operation scoring matrix of the vacuum pump is a scoring set corresponding to each operation attribute data. And constructing an operation scoring mesh map according to the operation data attribute information, namely, each distribution map edge of the operation scoring mesh map corresponds to the operation data attribute content. And respectively projecting the element values in the vacuum pump operation scoring matrix into the operation scoring mesh map according to the content of the distribution map edge, and obtaining the vacuum pump operation scoring mesh map by projection drawing. And then taking the area value surrounded by the vacuum pump operation scoring reticular graph as the information of the vacuum pump operation effect, wherein the larger the area value surrounded by the reticular graph is, the better the vacuum pump operation effect is. Visual display is carried out on the operation effect of the vacuum pump by drawing a scoring reticular chart of the operation of the vacuum pump, so that the operation precision analysis of the vacuum pump is realized, and the fault analysis accuracy of the vacuum pump is further improved.
Step S500: when the vacuum pump operation effect information does not reach the standard vacuum pump effect threshold value, marking unqualified operation data to obtain vacuum pump fault data information;
Specifically, the standard vacuum pump effect threshold is an effect scoring threshold when the vacuum pump is in normal operation, when the vacuum pump operation effect information does not reach the standard vacuum pump effect threshold, the vacuum pump is indicated to be in abnormal operation, faults occur, unqualified operation data in a vacuum pump operation scoring network chart are marked, and corresponding vacuum pump fault data information is obtained.
Step S600: inputting the vacuum pump fault data information into a vacuum pump fault analysis model, and outputting to obtain vacuum pump fault diagnosis information;
In one embodiment, the outputting obtains vacuum pump failure diagnosis information, and the applying step S600 further includes:
Step S610: building a vacuum pump fault analysis model, wherein the vacuum pump fault analysis model comprises a fault type analysis model and a fault grade analysis model;
Step S620: inputting the vacuum pump fault data information into the vacuum pump fault analysis model, and respectively obtaining fault type analysis information and fault grade analysis information based on the vacuum pump fault analysis model;
step S630: and outputting the vacuum pump fault diagnosis information based on the fault type analysis information and the fault grade analysis information.
Specifically, a vacuum pump fault analysis model is built, the vacuum pump fault analysis model is a neural network model and is used for carrying out cause analysis on vacuum pump fault data, and the vacuum pump fault analysis model can be obtained through historical data training and consists of a fault type analysis model and a fault grade analysis model. And inputting the vacuum pump fault data information into the vacuum pump fault analysis model, and respectively obtaining fault type analysis information and fault grade analysis information which are trained and output by the fault type analysis model and the fault grade analysis model based on the vacuum pump fault analysis model. Based on the fault type analysis information and the fault grade analysis information, the vacuum pump fault diagnosis information is obtained by combining output, and fault causes are intelligently diagnosed through a sub-vacuum pump fault analysis model, so that the early warning timeliness of operation faults is realized, and the safe operation of the vacuum pump is further ensured.
Step S700: and performing fault early warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information.
In one embodiment, the step S700 of the present application further includes:
Step S710: based on the vacuum pump fault diagnosis information, a fault early warning instruction is obtained;
step S720: constructing a vacuum pump operation and maintenance knowledge base;
Step S730: performing matching analysis on the vacuum pump operation and maintenance knowledge base and the vacuum pump fault diagnosis information to obtain a vacuum pump fault operation and maintenance scheme;
Step S740: and carrying out fault early warning operation and maintenance on the multistage vacuum pump based on the fault early warning instruction and the vacuum pump fault operation and maintenance scheme.
Specifically, fault early warning processing is carried out on the multistage vacuum pump based on the vacuum pump fault diagnosis information, specifically, a fault early warning instruction is obtained based on the vacuum pump fault diagnosis information so as to be used for timely early warning of vacuum pump faults. And constructing a vacuum pump operation and maintenance knowledge base in a big data mode, wherein the vacuum pump operation and maintenance knowledge base is a vacuum pump fault operation and maintenance scheme database, carrying out matching analysis on the vacuum pump operation and maintenance knowledge base and the vacuum pump fault diagnosis information to obtain a vacuum pump fault operation and maintenance scheme, and when the vacuum pump is very noisy and noisy in operation, the operation temperature of an air-pumped body is too high, the air is cooled and then enters the vacuum pump, or a vacuum pump cavity, a shaft and a shaft sleeve are overtightened together, and the vacuum pump cavity, the shaft sleeve and the shaft sleeve are tightly and poorly formed, so that a new device is used for dredging and conditioning an oil path, and smoothness is enhanced. And carrying out fault early warning operation and maintenance on the multistage vacuum pump based on the fault early warning instruction and the vacuum pump fault operation and maintenance scheme, so as to achieve the technical effects of intelligently diagnosing fault causes and quickly generating and matching the fault operation and maintenance scheme, realizing the early warning timeliness of operation faults and further ensuring the safe operation of the vacuum pump.
In one embodiment, as shown in fig. 3, there is provided a fault monitoring system of a vacuum pump, comprising: the system comprises a data monitoring and collecting module 11, an attribute marking module 12, a classification and integration module 13, an operation effect evaluation module 14, a fault data marking module 15, a fault diagnosis information obtaining module 16 and a fault early warning processing module 17, wherein:
The data monitoring and collecting module 11 is used for monitoring the multi-stage vacuum pump in real time through a sensor group and collecting and obtaining multidimensional working operation data information;
The attribute marking module 12 is configured to perform attribute marking on the multidimensional operation data information to obtain operation data attribute information;
The classification integration module 13 is configured to integrate the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information;
the operation effect evaluation module 14 is configured to obtain a vacuum pump operation standard, and perform operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain vacuum pump operation effect information;
The fault data marking module 15 is configured to mark unqualified operation data when the vacuum pump operation effect information does not reach a standard vacuum pump effect threshold value, so as to obtain vacuum pump fault data information;
The fault diagnosis information obtaining module 16 is configured to input the vacuum pump fault data information into a vacuum pump fault analysis model, and output and obtain vacuum pump fault diagnosis information;
And the fault early-warning processing module 17 is used for carrying out fault early-warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information.
In one embodiment, the data monitoring and acquisition module further comprises:
The sensor group monitoring unit is used for monitoring the multistage vacuum pump in real time through a sensor group, wherein the sensor group comprises a temperature and humidity sensor, an acoustic sensor, a flow sensor and a current sensor;
The operation information obtaining unit is used for obtaining operation temperature and humidity information, operation current information and vacuum flow information of the multistage vacuum pump through the temperature and humidity sensor, the flow sensor and the current sensor respectively;
a sound vibration signal data obtaining unit for obtaining sound vibration signal data information of the multistage vacuum pump based on the acoustic sensor;
the signal characteristic analysis unit is used for carrying out signal characteristic analysis on the sound vibration signal data information to obtain sound vibration characteristic information;
the multidimensional working operation data obtaining unit is used for obtaining multidimensional working operation data information based on the operation temperature and humidity information, the operation current information, the vacuum flow information and the sound vibration characteristic information.
In one embodiment, the signal characteristic analysis unit further comprises:
the signal noise reduction unit is used for carrying out signal noise reduction on the sound vibration signal data information to obtain standard sound vibration signal data information;
The fault sound characteristic database construction unit is used for constructing a vacuum pump fault sound characteristic database;
The characteristic signal matching unit is used for carrying out signal matching on the standard sound vibration signal data information and the vacuum pump fault sound characteristic database to obtain sound fault type characteristics;
The fault signal amplitude unit is used for obtaining the fault signal amplitude of the sound fault type characteristics;
And the sound vibration characteristic obtaining unit is used for obtaining the sound vibration characteristic information based on the sound fault type characteristic and the fault signal amplitude.
In one embodiment, the signal noise reduction unit further comprises:
The wavelet decomposition unit is used for carrying out wavelet decomposition on the data information of the sound vibration signal to obtain a wavelet coefficient of the sound signal;
The threshold value quantization unit is used for carrying out threshold value quantization according to the wavelet coefficient of the sound signal and determining a wavelet selection threshold value of the sound signal;
The sound signal interception unit is used for intercepting the sound signal wavelet coefficient according to the sound signal wavelet selection threshold value to obtain noise signal information smaller than the sound signal wavelet selection threshold value;
and the filtering reconstruction unit is used for carrying out filtering reconstruction on the noise signal information to obtain the standard sound vibration signal data information.
In one embodiment, the operation effect evaluation module further includes:
The effect evaluation unit is used for evaluating the operation effect of the multidimensional operation attribute data information based on the operation standard of the vacuum pump to obtain an operation scoring matrix of the vacuum pump;
The scoring mesh map construction unit is used for constructing a scoring mesh map according to the operation data attribute information;
the element value projection unit is used for projecting element values in the vacuum pump operation scoring matrix into the operation scoring mesh map to obtain a vacuum pump operation scoring mesh map;
And the operation effect information obtaining unit is used for obtaining the operation effect information of the vacuum pump based on the area value of the vacuum pump operation grading mesh chart.
In one embodiment, the fault diagnosis information obtaining module further includes:
The analysis model building unit is used for building a vacuum pump fault analysis model, wherein the vacuum pump fault analysis model comprises a fault type analysis model and a fault grade analysis model;
the fault analysis unit is used for inputting the vacuum pump fault data information into the vacuum pump fault analysis model, and respectively obtaining fault type analysis information and fault grade analysis information based on the vacuum pump fault analysis model;
And the model output unit is used for outputting the vacuum pump fault diagnosis information based on the fault type analysis information and the fault grade analysis information.
In one embodiment, the fault pre-warning processing module further comprises:
the fault early warning instruction obtaining unit is used for obtaining a fault early warning instruction based on the vacuum pump fault diagnosis information;
the operation and maintenance knowledge base construction unit is used for constructing a vacuum pump operation and maintenance knowledge base;
The fault matching analysis unit is used for carrying out matching analysis on the vacuum pump operation and maintenance knowledge base and the vacuum pump fault diagnosis information to obtain a vacuum pump fault operation and maintenance scheme;
and the fault early-warning operation and maintenance unit is used for carrying out fault early-warning operation and maintenance on the multistage vacuum pump based on the fault early-warning instruction and the vacuum pump fault operation and maintenance scheme.
For a specific embodiment of a fault monitoring system for a vacuum pump, reference may be made to the above embodiment of a fault monitoring method for a vacuum pump, which is not described herein. Each module in the fault monitoring device of a vacuum pump may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing news data, time attenuation factors and other data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a method of fault monitoring of a vacuum pump.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 4 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of: the multi-stage vacuum pump is monitored in real time through a sensor group, and multi-dimensional working operation data information is acquired; carrying out attribute marking on the multidimensional working operation data information to obtain operation data attribute information; classifying and integrating the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information; obtaining a vacuum pump operation standard, and performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain vacuum pump operation effect information; when the vacuum pump operation effect information does not reach the standard vacuum pump effect threshold value, marking unqualified operation data to obtain vacuum pump fault data information; inputting the vacuum pump fault data information into a vacuum pump fault analysis model, and outputting to obtain vacuum pump fault diagnosis information; and performing fault early warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of: the multi-stage vacuum pump is monitored in real time through a sensor group, and multi-dimensional working operation data information is acquired; carrying out attribute marking on the multidimensional working operation data information to obtain operation data attribute information; classifying and integrating the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information; obtaining a vacuum pump operation standard, and performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain vacuum pump operation effect information; when the vacuum pump operation effect information does not reach the standard vacuum pump effect threshold value, marking unqualified operation data to obtain vacuum pump fault data information; inputting the vacuum pump fault data information into a vacuum pump fault analysis model, and outputting to obtain vacuum pump fault diagnosis information; and performing fault early warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information. The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (5)
1. A method of fault monitoring of a vacuum pump, the method comprising:
the multi-stage vacuum pump is monitored in real time through a sensor group, and multi-dimensional working operation data information is acquired;
Carrying out attribute marking on the multidimensional working operation data information to obtain operation data attribute information, wherein the operation data attribute information is classification information for classifying and marking multidimensional data according to data acquisition types, and comprises temperature and humidity attribute data, acoustic attribute data, flow attribute data and current attribute data;
Classifying and integrating the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information;
obtaining a vacuum pump operation standard, and performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain vacuum pump operation effect information;
when the vacuum pump operation effect information does not reach the standard vacuum pump effect threshold value, marking unqualified operation data to obtain vacuum pump fault data information;
Inputting the vacuum pump fault data information into a vacuum pump fault analysis model, and outputting to obtain vacuum pump fault diagnosis information;
performing fault early warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information;
Wherein, the acquisition obtains multidimensional work operation data information, including:
The method comprises the steps of monitoring the multistage vacuum pump in real time through a sensor group, wherein the sensor group comprises a temperature and humidity sensor, an acoustic sensor, a flow sensor and a current sensor;
acquiring operation temperature and humidity information, operation current information and vacuum flow information of the multistage vacuum pump respectively through the temperature and humidity sensor, the flow sensor and the current sensor;
acquiring sound vibration signal data information of the multistage vacuum pump based on the acoustic sensor;
Performing signal characteristic analysis on the sound vibration signal data information to obtain sound vibration characteristic information;
Acquiring the multidimensional working operation data information based on the operation temperature and humidity information, the operation current information, the vacuum flow information and the sound vibration characteristic information;
the method for obtaining the operation effect information of the vacuum pump comprises the following steps:
performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain a vacuum pump operation scoring matrix;
constructing an operation scoring mesh map according to the operation data attribute information;
Projecting element values in the vacuum pump operation scoring matrix into the operation scoring mesh map to obtain a vacuum pump operation scoring mesh map;
Obtaining the vacuum pump operation effect information based on the area value of the vacuum pump operation grading reticulate diagram;
The obtaining the sound vibration characteristic information comprises the following steps:
carrying out signal noise reduction on the sound vibration signal data information to obtain standard sound vibration signal data information;
Constructing a vacuum pump fault sound characteristic database;
performing signal matching on the standard sound vibration signal data information and the vacuum pump fault sound characteristic database to obtain sound fault type characteristics;
Obtaining a fault signal amplitude of the sound fault type characteristic;
acquiring the sound vibration characteristic information based on the sound fault type characteristic and the fault signal amplitude;
The output obtains vacuum pump fault diagnosis information, including:
Building a vacuum pump fault analysis model, wherein the vacuum pump fault analysis model comprises a fault type analysis model and a fault grade analysis model;
inputting the vacuum pump fault data information into the vacuum pump fault analysis model, and respectively obtaining fault type analysis information and fault grade analysis information based on the vacuum pump fault analysis model;
Outputting the vacuum pump fault diagnosis information based on the fault type analysis information and the fault level analysis information;
the fault early warning processing for the multistage vacuum pump based on the vacuum pump fault diagnosis information comprises the following steps:
based on the vacuum pump fault diagnosis information, a fault early warning instruction is obtained;
Constructing a vacuum pump operation and maintenance knowledge base;
performing matching analysis on the vacuum pump operation and maintenance knowledge base and the vacuum pump fault diagnosis information to obtain a vacuum pump fault operation and maintenance scheme;
and carrying out fault early warning operation and maintenance on the multistage vacuum pump based on the fault early warning instruction and the vacuum pump fault operation and maintenance scheme.
2. The method of claim 1, wherein the obtaining standard acoustic vibration signal data information comprises:
performing wavelet decomposition on the data information of the sound vibration signals to obtain wavelet coefficients of the sound signals;
performing threshold quantization according to the wavelet coefficient of the sound signal, and determining a wavelet selection threshold of the sound signal;
Intercepting the wavelet coefficient of the sound signal according to the wavelet selection threshold of the sound signal to obtain noise signal information smaller than the wavelet selection threshold of the sound signal;
and carrying out filtering reconstruction on the noise signal information to obtain the standard sound vibration signal data information.
3. A fault monitoring system for a vacuum pump, the system comprising:
the data monitoring and collecting module is used for monitoring the multi-stage vacuum pump in real time through the sensor group and collecting and obtaining multidimensional working operation data information;
The attribute marking module is used for carrying out attribute marking on the multidimensional working operation data information to obtain operation data attribute information, wherein the operation data attribute information is classification information for classifying and marking multidimensional data according to data acquisition types, and comprises temperature and humidity attribute data, acoustic attribute data, flow attribute data and current attribute data;
The classification integration module is used for classifying and integrating the multidimensional operation data information according to the operation data attribute information to obtain multidimensional operation attribute data information;
The operation effect evaluation module is used for obtaining a vacuum pump operation standard, and performing operation effect evaluation on the multidimensional operation attribute data information based on the vacuum pump operation standard to obtain vacuum pump operation effect information;
the fault data marking module is used for marking unqualified operation data when the operation effect information of the vacuum pump does not reach the standard vacuum pump effect threshold value, so as to obtain fault data information of the vacuum pump;
the fault diagnosis information obtaining module is used for inputting the vacuum pump fault data information into a vacuum pump fault analysis model and outputting and obtaining the vacuum pump fault diagnosis information;
The fault early warning processing module is used for carrying out fault early warning processing on the multistage vacuum pump based on the vacuum pump fault diagnosis information;
the data monitoring and collecting module further comprises:
The sensor group monitoring unit is used for monitoring the multistage vacuum pump in real time through a sensor group, wherein the sensor group comprises a temperature and humidity sensor, an acoustic sensor, a flow sensor and a current sensor;
The operation information obtaining unit is used for obtaining operation temperature and humidity information, operation current information and vacuum flow information of the multistage vacuum pump through the temperature and humidity sensor, the flow sensor and the current sensor respectively;
a sound vibration signal data obtaining unit for obtaining sound vibration signal data information of the multistage vacuum pump based on the acoustic sensor;
the signal characteristic analysis unit is used for carrying out signal characteristic analysis on the sound vibration signal data information to obtain sound vibration characteristic information;
the multidimensional working operation data obtaining unit is used for obtaining multidimensional working operation data information based on the operation temperature and humidity information, the operation current information, the vacuum flow information and the sound vibration characteristic information;
the operation effect evaluation module further comprises:
The effect evaluation unit is used for evaluating the operation effect of the multidimensional operation attribute data information based on the operation standard of the vacuum pump to obtain an operation scoring matrix of the vacuum pump;
The scoring mesh map construction unit is used for constructing a scoring mesh map according to the operation data attribute information;
the element value projection unit is used for projecting element values in the vacuum pump operation scoring matrix into the operation scoring mesh map to obtain a vacuum pump operation scoring mesh map;
The operation effect information obtaining unit is used for obtaining the operation effect information of the vacuum pump based on the area value of the vacuum pump operation grading mesh map;
the signal characteristic analysis unit further includes:
the signal noise reduction unit is used for carrying out signal noise reduction on the sound vibration signal data information to obtain standard sound vibration signal data information;
The fault sound characteristic database construction unit is used for constructing a vacuum pump fault sound characteristic database;
The characteristic signal matching unit is used for carrying out signal matching on the standard sound vibration signal data information and the vacuum pump fault sound characteristic database to obtain sound fault type characteristics;
The fault signal amplitude unit is used for obtaining the fault signal amplitude of the sound fault type characteristics;
A sound vibration characteristic obtaining unit configured to obtain the sound vibration characteristic information based on the sound fault type characteristic and the fault signal amplitude;
the failure diagnosis information obtaining module further includes:
The analysis model building unit is used for building a vacuum pump fault analysis model, wherein the vacuum pump fault analysis model comprises a fault type analysis model and a fault grade analysis model;
the fault analysis unit is used for inputting the vacuum pump fault data information into the vacuum pump fault analysis model, and respectively obtaining fault type analysis information and fault grade analysis information based on the vacuum pump fault analysis model;
A model output unit for outputting the vacuum pump fault diagnosis information based on the fault type analysis information and the fault level analysis information;
the fault early warning processing module further comprises:
the fault early warning instruction obtaining unit is used for obtaining a fault early warning instruction based on the vacuum pump fault diagnosis information;
the operation and maintenance knowledge base construction unit is used for constructing a vacuum pump operation and maintenance knowledge base;
The fault matching analysis unit is used for carrying out matching analysis on the vacuum pump operation and maintenance knowledge base and the vacuum pump fault diagnosis information to obtain a vacuum pump fault operation and maintenance scheme;
and the fault early-warning operation and maintenance unit is used for carrying out fault early-warning operation and maintenance on the multistage vacuum pump based on the fault early-warning instruction and the vacuum pump fault operation and maintenance scheme.
4. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 2 when the computer program is executed.
5. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 2.
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