CN115524569A - Fault diagnosis method, device and system - Google Patents
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Abstract
The invention discloses a fault diagnosis method, a fault diagnosis device and a fault diagnosis system. The fault diagnosis method comprises the following steps: acquiring vibration data of target equipment; judging whether the vibration data of the target equipment comprise steady-state waveform data or not according to the vibration data to obtain a first judgment result; under the condition that the first judgment result indicates yes, inputting the steady-state waveform data into a vibration fault mechanism model for analysis to obtain a first fault reason corresponding to the target equipment; under the condition that the first judgment result indicates that the first fault reason is not obtained, inputting the vibration data of the target equipment into a preset model for analysis, and judging whether a second fault reason corresponding to the vibration data is obtained or not; and generating a diagnosis report according to the first fault reason, or generating the first diagnosis report according to the second fault reason when the second fault reason is obtained. The method can diagnose the fault reason of the target equipment in time, and is beneficial to the troubleshooting and maintenance of the fault equipment by workers.
Description
Technical Field
The invention relates to the technical field of function testing, in particular to a fault diagnosis method, a fault diagnosis device and a fault diagnosis system.
Background
The fault diagnosis technology for the mechanical equipment can predict in advance and prepare for preventing the possible faults in advance. By applying the fault diagnosis technology of the mechanical equipment, the potential safety hazard can be effectively reduced or eliminated, and the occurrence of larger accidents is avoided. The time period of safe and stable operation of mechanical equipment is prolonged, and more economic benefits are created. The fault diagnosis system and the anti-interference detection method can conduct necessary guidance on the operation of equipment, and improve the reliability, safety and effectiveness of the operation of the equipment. The method utilizes new-generation information technologies such as intelligent sensors, edge computing, industrial internet, big data, artificial intelligence and the like to monitor the online operation of the equipment every week and establish the data management of the whole life cycle so as to realize the safety and reliability management of the equipment. With the rapid development of science and technology, the frequency converter is applied to various fields of industrial control due to the characteristics of electricity saving, energy saving, reliability and high efficiency, and higher harmonics generated during the operation of the frequency converter can interfere the operation of surrounding equipment.
The frequency converter can generate harmonic waves with larger power and has stronger interference on other equipment of the system. The device mainly divides electromagnetic radiation, conduction and inductive coupling interference. The method specifically comprises the following steps: 1. generating electromagnetic radiation to surrounding electronic and electrical equipment; 2. conducting interference to the power supply and conducting the interference to other equipment of the system through a power distribution network; 3. the frequency converter generates inductive coupling to other adjacent lines, and induces interference voltage or current.
At present, high-power equipment is mostly driven by a frequency converter, and higher harmonics generated when the frequency converter operates can interfere with the operation of surrounding equipment and influence the accuracy of data detection.
Disclosure of Invention
The invention mainly aims to provide a fault diagnosis method, a fault diagnosis device and a fault diagnosis system, and aims to solve the problem that high-order harmonics generated when a frequency converter operates in the prior art interfere with the operation of surrounding equipment and influence the accuracy of data detection.
In order to achieve the above object, according to one aspect of the present invention, there is provided a fault diagnosis method including: acquiring vibration data of target equipment; judging whether the vibration data of the target equipment comprises steady-state waveform data or not according to the vibration data to obtain a first judgment result; when the first judgment result indicates yes, inputting the steady-state waveform data into a vibration fault mechanism model for analysis to obtain a first fault reason corresponding to the target equipment, wherein the vibration fault mechanism model is used for representing a mapping relation between the steady-state waveform data and the fault reason; under the condition that the first judgment result indicates that the first fault reason is not obtained, inputting vibration data of the target device into a preset model to analyze, judging whether a second fault reason corresponding to the vibration data is obtained, wherein the preset model is obtained by training a plurality of groups of first data to be trained, and each group of first data to be trained in the plurality of groups of first data to be trained comprises: the sample vibration data and a label used for identifying a second fault reason corresponding to the sample vibration data are obtained; and generating a diagnosis report according to the first fault reason, or generating the first diagnosis report according to the second fault reason when the second fault reason is obtained.
Optionally, acquiring vibration data of the target device includes: receiving vibration waveform data of target equipment, which are acquired by a sensor module at a plurality of preset time points, wherein the sensor module is arranged on the target equipment; receiving vibration waveform data of target equipment, which is acquired by a sensor module at a plurality of preset time points, wherein the sensor module is arranged on the target equipment; judging whether the plurality of target waveforms conform to theoretical waveforms; sending an adjusting signal to a sensor module under the condition that any one of a plurality of target waveforms does not conform to a theoretical waveform, wherein the sensor module is used for acquiring vibration waveform data of target equipment within a preset time period according to a preset time interval under the condition that the adjusting signal is received, and the preset time period is a time interval between any two adjacent preset time points in the plurality of preset time points; and receiving vibration waveform data of the target equipment, which is acquired by the sensor module at a preset time interval.
Optionally, the fault diagnosis method further includes: acquiring historical fault information of target equipment, wherein the historical fault information comprises: the fault analysis method comprises the following steps of obtaining a plurality of historical fault reasons and a plurality of fault spectrum data corresponding to the historical fault reasons, wherein each historical fault reason corresponds to at least one part of target equipment; and establishing a vibration fault mechanism model according to a plurality of historical fault reasons and a plurality of fault frequency spectrum data.
Optionally, the vibration data of the target device includes: vibration speed, acceleration, temperature index, and vibration waveform data.
Optionally, the fault diagnosis method further includes: under the condition that the judgment result indicates that the second fault reason is not obtained, performing feature extraction on the vibration data to obtain target features; and matching the target characteristics with a fault characteristic library of the target equipment to generate a second diagnosis report, wherein the fault characteristic library comprises a plurality of fault characteristics, and the plurality of fault characteristics are obtained by extracting the characteristics of historical fault information.
Optionally, the fault diagnosis method further includes: judging whether to trigger an alarm signal or not according to the vibration data and the working threshold value of the target equipment; and under the condition of triggering the alarm signal, outputting the alarm signal.
According to another aspect of the embodiments of the present invention, there is also provided a fault diagnosis apparatus including: the acquisition module is used for acquiring vibration data of the target equipment; the judging module is used for judging whether the vibration data of the target equipment comprise steady-state waveform data or not to obtain a first judging result; the first determining module is used for inputting the steady-state waveform data into a vibration fault mechanism model for analysis under the condition that the first judging result indicates yes, so as to obtain a first fault reason corresponding to the target equipment, and the vibration fault mechanism model is used for representing the mapping relation between the steady-state waveform data and the fault reason; the second determining module is used for inputting the vibration data of the target equipment into a preset model for analysis under the condition that the first judgment result indicates no, judging whether a second fault reason corresponding to the vibration data is obtained, wherein the preset model is obtained by training a plurality of groups of first data to be trained, and each group of first data to be trained in the plurality of groups of first data to be trained comprises: the sample vibration data and a label used for identifying a second fault reason corresponding to the sample vibration data; and the generating module is used for generating a diagnosis report according to the first fault reason or generating a first diagnosis report according to the second fault reason under the condition of obtaining the second fault reason.
According to another aspect of the embodiments of the present invention, there is also provided a fault diagnosis system, including: the sensor module is arranged on the target equipment and used for acquiring vibration data of the target equipment, and the sensor module at least comprises a vibration sensor assembly; the processor is electrically connected with the sensor module and used for receiving vibration data; a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the fault diagnosis method as described above.
Optionally, the vibration sensor assembly comprises: a vibration sensor; the control circuit is electrically connected with the vibration sensor and used for driving the vibration sensor, and the control circuit comprises a filter circuit; the isolation gasket is arranged between the vibration sensor and the target equipment; and the shielding cover is covered outside the vibration sensor, the control circuit and the isolation gasket.
Optionally, the shielding case is a composite material layer, and the composite material layer includes a metal layer and a polymer layer stacked from inside to outside.
Optionally, the vibration sensor assembly further comprises a cable connected to the processor, the cable comprising: a plurality of cable cores, any one of which is grounded; at least one armor layer is arranged on the periphery of the cable cores.
The technical scheme of the invention is applied to provide the fault diagnosis method, wherein the vibration data of the target equipment is obtained; judging whether the vibration data of the target equipment comprises steady-state waveform data or not according to the vibration data to obtain a first judgment result, inputting the steady-state waveform data into a vibration fault mechanism model to analyze under the condition that the first judgment result indicates yes to obtain a first fault reason corresponding to the target equipment, inputting the vibration data of the target equipment into a preset model to analyze under the condition that the first judgment result indicates no to judge whether a second fault reason corresponding to the vibration data is obtained or not, and generating a diagnosis report according to the first fault reason or generating a first diagnosis report according to the second fault reason under the condition that the second fault reason is obtained. The method can diagnose the fault reason of the target equipment in time, is beneficial to the troubleshooting and maintenance of the fault equipment by workers, and effectively avoids the influence on the data detection accuracy caused by the interference of a frequency converter with surrounding equipment in the prior art, thereby being beneficial to diagnosing other fault types of the equipment except for vibration faults.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a block flow diagram showing a fault diagnosis method according to embodiment 1 of the present invention;
fig. 2 is a schematic flow chart of a fault diagnosis method according to embodiment 1 of the present invention;
fig. 3 is a block diagram of a failure diagnosis apparatus according to embodiment 2 of the present invention;
fig. 4 is a block diagram of a failure diagnosis system according to embodiment 3 of the present invention;
fig. 5 is a schematic structural view of a vibration sensor assembly in a failure diagnosis system according to embodiment 3 of the present invention;
fig. 6 is a schematic cross-sectional view of a shield case of the vibration sensor assembly according to fig. 5.
Detailed Description
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged under appropriate circumstances in order to facilitate the description of the embodiments of the invention herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
According to an embodiment of the present invention, an embodiment of a fault diagnosis method is provided, and fig. 1 is a flowchart of a fault diagnosis method according to embodiment 1 of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, obtaining vibration data of target equipment;
step S104, judging whether the vibration data of the target equipment comprises steady-state waveform data or not according to the vibration data to obtain a first judgment result;
step S106, under the condition that the first judgment result indicates yes, inputting the steady-state waveform data into a vibration fault mechanism model for analysis to obtain a first fault reason corresponding to the target equipment, wherein the vibration fault mechanism model is used for representing the mapping relation between the steady-state waveform data and the fault reason;
step S108, when the first determination result indicates that the first failure cause is not detected, inputting the vibration data of the target device into a preset model to analyze, and determining whether a second failure cause corresponding to the vibration data is obtained, where the preset model is obtained by training multiple sets of first data to be trained, and each set of first data to be trained in the multiple sets of first data to be trained includes: the sample vibration data and a label used for identifying a second fault reason corresponding to the sample vibration data;
and step S110, generating a diagnosis report according to the first fault reason, or generating the first diagnosis report according to the second fault reason when the second fault reason is obtained.
The method can diagnose the fault reason of the target equipment in time, is beneficial to the troubleshooting and maintenance of the fault equipment by workers, and effectively avoids the influence on the data detection accuracy caused by the interference of a frequency converter with surrounding equipment in the prior art, thereby being beneficial to diagnosing other fault types of the equipment except for the vibration fault.
In some optional embodiments, obtaining vibration data of the target device comprises: receiving vibration waveform data of target equipment, which is acquired by a sensor module at a plurality of preset time points, wherein the sensor module is arranged on the target equipment; receiving vibration waveform data of target equipment, which are acquired by a sensor module at a plurality of preset time points, wherein the sensor module is arranged on the target equipment; judging whether the plurality of target waveforms conform to theoretical waveforms; sending an adjusting signal to a sensor module under the condition that any one of a plurality of target waveforms does not conform to a theoretical waveform, wherein the sensor module is used for acquiring vibration waveform data of target equipment within a preset time period according to a preset time interval under the condition that the adjusting signal is received, and the preset time period is a time interval between any two adjacent preset time points in the plurality of preset time points; and receiving vibration waveform data of the target equipment, which is acquired by the sensor module at a preset time interval.
In the above alternative embodiment, the acquisition interval of the sensor module may be set appropriately, for example, data acquisition may be performed at any time interval, such as 5 minutes, 15 minutes, 120 minutes, and the like. The sensor module can acquire a group of waveform data within 5 minutes at the just-running stage, and after basic waveform data is acquired for a period of time, the acquisition interval time is prolonged in a form of on-site or remote issuing on the premise that no problem exists in equipment through data analysis.
In the above optional embodiment, after the monitoring device operates for a period of time, the data amount of data acquisition, transmission and storage is reduced by adjusting the frequency of acquiring the vibration data. Illustratively, the normal acquisition interval is set to 2 hours, namely, 2/4/6/8/10 of the collected data at the same time point, when abnormal vibration is collected at 2 points, 2. If the waveform of 2.
In the step S104, the obtained first determination result is used to characterize whether the vibration data of the target device includes the steady-state waveform data, when the vibration data includes the steady-state waveform data, it is preliminarily determined that the vibration data is a vibration fault, and the step S106 is executed; when the vibration data does not include the steady-state waveform data, it is preliminarily determined as not a vibration failure, and step S108 is performed.
In some optional embodiments, the fault diagnosis method further comprises: acquiring historical fault information of target equipment, wherein the historical fault information comprises: the fault diagnosis method comprises the following steps of obtaining a plurality of historical fault reasons and a plurality of fault spectrum data corresponding to the historical fault reasons, wherein each historical fault reason corresponds to at least one part of target equipment; and establishing a vibration fault mechanism model according to a plurality of historical fault reasons and a plurality of fault frequency spectrum data.
In the above embodiment, establishing a vibration fault mechanism model according to a plurality of historical fault causes and a plurality of fault spectrum data may include: extracting corresponding fault waveform data from each fault frequency spectrum data, and screening steady-state waveform data from the fault waveform data; and establishing a mechanism model based on the corresponding relation between a plurality of steady state waveform data corresponding to a plurality of fault frequency spectrum data and a plurality of historical fault reasons.
In the above embodiment, the historical failure information may be failure information recorded when the target device has failed before, or may be failure information collected when the target device is considered to have failed during manufacturing. Because the known conclusion or the known working condition is used for generating the fault to obtain the corresponding conclusion, the conclusion is correct and effective, and therefore, the mechanism model is established by using the experience to verify the unknown fault, and the fault diagnosis can be more accurate.
When the vibration data of the target device does not include the steady-state waveform data, a trained preset model is further adopted, the vibration data of the target device is input into the preset model to be analyzed, whether a second fault reason corresponding to the vibration data is obtained or not is judged, and the vibration data of the target device can include: vibration speed, acceleration, temperature index, and vibration waveform data.
Specifically, the data output from the preset model is also vibration data, but the data are chaotic and can include vibration data when the target device is started, when the target device is stopped, and when the target device is disturbed, the unsteady waveform data cannot be diagnosed by using a specific mechanism model, so that the neural network model training can be performed through a large amount of data to obtain the preset model, and the accuracy of diagnosis can be verified.
When the preset model obtained by training the neural network model cannot obtain the fault reason, fuzzy reasoning can be carried out, and on the premise that the fault cannot be determined, the vibration data of the target equipment are compared with a plurality of fault characteristics in the fault characteristic library to provide a general diagnosis conclusion.
In some optional embodiments, the fault diagnosis method further comprises: under the condition that the judgment result indicates that the second fault reason is not obtained, performing feature extraction on the vibration data to obtain target features; and matching the target characteristics with a fault characteristic library of the target equipment to generate a second diagnosis report, wherein the fault characteristic library comprises a plurality of fault characteristics, and the plurality of fault characteristics are obtained by extracting the characteristics of historical fault information.
In some optional embodiments, the fault diagnosis method further comprises: judging whether an alarm signal is triggered or not according to the vibration data and the working threshold value of the target equipment; and under the condition of triggering the alarm signal, outputting the alarm signal.
In the embodiment, by outputting the alarm signal, the early warning staff can perform troubleshooting in advance, and the influence caused by equipment failure is further avoided. The working threshold value of the target equipment can be set according to international or national industry standards, and can also be automatically calculated according to a fault alarm formula on the premise of normal operation according to the recent operating condition of the target equipment. The operating threshold values relate to metrics including, but not limited to: voltage, temperature, vibration acceleration, and vibration velocity.
As shown in fig. 2, which is a block flow diagram of a fault diagnosis method in this embodiment, the fault diagnosis method provided in this embodiment will be further described below with reference to fig. 2, and the fault diagnosis flow shown in fig. 2 may include the following steps:
carry out data acquisition through sensor module, gather vibration data, the temperature data etc. of target equipment key position, vibration data can include: vibration speed, acceleration, temperature index, and vibration waveform data. The vibration data that the sensor module detected transmit to the treater through long-range intelligent transmission unit, can accomplish the report and the transmission of vibration data with multiple mode (4G, WIFI, wired network), satisfy the requirement of actual installation environment, convey data simultaneously in order to satisfy the needs of analysis, early warning, also can insert transmission signals such as PLC, DCS.
And the processor calculates an alarm value according to a working threshold value or a fault alarm formula after acquiring the monitoring data, judges whether to perform alarm processing or not based on the alarm value, finishes diagnosis if the alarm processing is not performed, starts an alarm signal if the alarm processing is performed, and pushes the alarm to a system alarm service.
After the alarm signal is triggered, the processor judges whether the vibration data of the target device comprises the stable waveform data or not according to the vibration data, preliminarily judges the vibration fault when the vibration data comprises the stable waveform data, and preliminarily judges the non-vibration fault when the vibration data does not comprise the stable waveform data.
If the vibration fault is preliminarily judged, diagnosing the fault reason according to the vibration fault mechanism model, generating a diagnosis report according to the obtained fault reason, if the vibration fault is preliminarily judged to be a non-vibration fault, determining the fault reason according to neural network and fuzzy reasoning fault diagnosis, if the fault reason can be determined, generating the diagnosis report, if the fault reason cannot be determined, carrying out expert diagnosis analysis, further determining the fault reason, if the fault reason can be determined, generating the diagnosis report, and if the fault reason cannot be determined, generating information of more vibration data requested by an industry expert.
And if the diagnosis report is not generated, the information of more vibration data requested by the industry expert is pushed to the information system alarm platform.
Example 2
According to an embodiment of the present invention, there is also provided an apparatus for implementing the above fault diagnosis method, and fig. 3 is a block diagram of a test apparatus for an application program interface according to embodiment 2 of the present invention, as shown in fig. 3, the apparatus includes: the apparatus includes an obtaining module 202, a determining module 204, a first determining module 206, a second determining module 208, and a generating module 210, which are described in detail below.
An obtaining module 202, configured to obtain vibration data of a target device;
the judging module 204 is configured to judge whether the vibration data of the target device includes steady-state waveform data, so as to obtain a first judgment result;
a first determining module 206, configured to, when the first determination result indicates yes, input the steady-state waveform data into a vibration fault mechanism model for analysis to obtain a first fault cause corresponding to the target device, where the vibration fault mechanism model is used to represent a mapping relationship between the steady-state waveform data and the fault cause;
the second determining module 208 is configured to, when the first determination result indicates that the first failure cause is not obtained, input the vibration data of the target device into a preset model for analysis, and determine whether a second failure cause corresponding to the vibration data is obtained, where the preset model is obtained by training multiple sets of first data to be trained, and each set of the multiple sets of first data to be trained includes: the sample vibration data and a label used for identifying a second fault reason corresponding to the sample vibration data;
the generating module 210 is configured to generate a diagnosis report according to the first failure cause, or if a second failure cause is obtained, generate the first diagnosis report according to the second failure cause.
It should be noted here that the acquiring module 202, the determining module 20, the first determining module 206, the second determining module 208, and the generating module 210 correspond to steps S102 to S110 in embodiment 1, and a plurality of modules are the same as the corresponding steps in the implementation example and application scenario, but are not limited to the disclosure in embodiment 1.
Example 3
An embodiment of the present invention may provide a fault diagnosis system, and fig. 4 is a block diagram illustrating a structure of a fault diagnosis system according to an exemplary embodiment. As shown in fig. 4, the fault diagnosis system may include a sensor module, one or more processors 41 (only one shown), a memory 42 for storing processor-executable instructions, wherein: the sensor module is arranged on the target equipment and used for collecting vibration data of the target equipment, the sensor module at least comprises a vibration sensor assembly, and the processor is configured to execute instructions and receive the vibration data so as to realize the fault diagnosis method.
In some alternative embodiments, as shown in fig. 5 and 6, the vibration sensor assembly includes a vibration sensor 10, a control circuit (not shown), an isolation pad 20, and a shield can 30, wherein: the control circuit is electrically connected with the vibration sensor and used for driving the vibration sensor, and the control circuit comprises a filter circuit; a part of the spacer 20 is disposed between the vibration sensor 10 and the target device, and another part is disposed on the inner surface of the shield case 30; a shield 30 is housed outside the vibration sensor 10, the control circuit and the spacer 20.
The above embodiment can solve the interference problem from the aspects of isolation, filtering and the like, and has the function of physical isolation, thereby suppressing and eliminating an interference source, cutting off a coupling channel of interference to equipment, and reducing the sensitivity of the equipment to an interference signal. Specifically, the isolation gaskets are arranged at the bottoms of the vibration sensor and the circuit board, and the middle of the vibration sensor and the circuit board is fixed through the adhesive, so that the control circuit is not in physical contact with the shell 50, the interference source and the interfered parts are isolated from the circuit, the interference source and the interfered parts are not electrically connected, and the interference is isolated; the control circuit is provided with a filter circuit, and the filter circuit is used for inhibiting interference signals from being conducted from the frequency converter to the vibration sensor and the circuit board through a power line.
In the above alternative embodiment, the shielding case may be a composite material layer, and the composite material layer includes a metal layer and a polymer layer stacked from inside to outside. The shielding and blocking cover is made of composite materials, the inner part of the shielding and blocking cover is made of metal material layers (such as stainless steel 304), and the outer part of the shielding and blocking cover is made of composite material layers (such as nylon and abs), so that the shielding and blocking cover can play a role in shielding and blocking an interference source. The upper part of the shielding cover is provided with a wire outlet hole, and the thickness of the shielding cover can be more than or equal to 2mm, so that the shielding cover is favorable for preventing electromagnetic interference from entering.
In the above alternative embodiment, as shown in fig. 5, the vibration sensor assembly may further include a cable 40 connected to the processor, where the cable 40 includes a plurality of cable cores, any one of which is grounded, and at least one armor layer disposed on the outer periphery of the plurality of cable cores. Through making a cable inner core ground connection, can absorb the electromagnetic interference signal of penetrating, the good ground connection mode can restrain the coupling of internal noise to a great extent, prevents external disturbance's invasion, improves the interference killing feature of system. Above-mentioned armor can be the metal level, mainly plays the guard action, can also cover and hinder the interference, and the thickness of armor can be more than or equal to 1mm.
The memory may be configured to store software programs and modules, such as program instructions/modules corresponding to the method and apparatus for diagnosing a fault of underground water in a mine area in the embodiment of the present invention, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory, so as to implement the method for diagnosing a fault of underground water in a mine area. The memory may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include memory remotely located from the processor, which may be connected to the computer terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor can call the information and application program stored in the memory through the transmission device to execute the following steps: acquiring vibration data of target equipment; judging whether the vibration data of the target equipment comprises steady-state waveform data or not according to the vibration data to obtain a first judgment result; when the first judgment result indicates yes, inputting the steady-state waveform data into a vibration fault mechanism model for analysis to obtain a first fault reason corresponding to the target equipment, wherein the vibration fault mechanism model is used for representing a mapping relation between the steady-state waveform data and the fault reason; under the condition that the first judgment result indicates that the first fault reason is not obtained, inputting vibration data of the target device into a preset model to analyze, judging whether a second fault reason corresponding to the vibration data is obtained, wherein the preset model is obtained by training a plurality of groups of first data to be trained, and each group of first data to be trained in the plurality of groups of first data to be trained comprises: the sample vibration data and a label used for identifying a second fault reason corresponding to the sample vibration data; and generating a diagnosis report according to the first fault reason, or generating the first diagnosis report according to the second fault reason when the second fault reason is obtained.
Optionally, the processor may further execute the program code of the following steps: acquiring vibration data of a target device, comprising: receiving vibration waveform data of target equipment, which is acquired by a sensor module at a plurality of preset time points, wherein the sensor module is arranged on the target equipment; receiving vibration waveform data of target equipment, which is acquired by a sensor module at a plurality of preset time points, wherein the sensor module is arranged on the target equipment; judging whether the plurality of target waveforms conform to theoretical waveforms; sending an adjusting signal to a sensor module under the condition that any one of a plurality of target waveforms does not conform to a theoretical waveform, wherein the sensor module is used for acquiring vibration waveform data of target equipment within a preset time period according to a preset time interval under the condition that the adjusting signal is received, and the preset time period is a time interval between any two adjacent preset time points in the plurality of preset time points; and receiving vibration waveform data of the target equipment, which is acquired by the sensor module at a preset time interval.
Optionally, the processor may further execute the program code of the following steps: acquiring historical fault information of target equipment, wherein the historical fault information comprises: the fault analysis method comprises the following steps of obtaining a plurality of historical fault reasons and a plurality of fault spectrum data corresponding to the historical fault reasons, wherein each historical fault reason corresponds to at least one part of target equipment; and establishing a vibration fault mechanism model according to a plurality of historical fault reasons and a plurality of fault frequency spectrum data.
Optionally, the processor may further execute the program code of the following steps: the vibration data of the target device includes: vibration speed, acceleration, temperature index, and vibration waveform data.
Optionally, the processor may further execute the program code of the following steps: under the condition that the judgment result indicates that the second fault reason is not obtained, performing feature extraction on the vibration data to obtain target features; and matching the target characteristics with a fault characteristic library of the target equipment to generate a second diagnosis report, wherein the fault characteristic library comprises a plurality of fault characteristics, and the plurality of fault characteristics are obtained by extracting the characteristics of historical fault information.
Optionally, the processor may further execute the program code of the following steps: judging whether an alarm signal is triggered or not according to the vibration data and the working threshold value of the target equipment; and under the condition of triggering the alarm signal, outputting the alarm signal.
It will be understood by those skilled in the art that the structure shown in fig. 4 is only an illustration and is not intended to limit the structure of the fault diagnosis system. For example, it may also include more or fewer components (e.g., network interfaces, display devices, etc.) than shown in FIG. 4, or have a different configuration than shown in FIG. 4.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program instructing hardware associated with the fault diagnosis system, where the program may be stored in a computer-readable storage medium, and the storage medium may include: flash disks, read-Only memories (ROMs), random Access Memories (RAMs), magnetic or optical disks, and the like.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technical content can be implemented in other manners. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit is merely a division of a logic function, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk, and various media capable of storing program codes.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (11)
1. A fault diagnosis method, comprising:
acquiring vibration data of target equipment;
judging whether the vibration data of the target equipment comprises steady-state waveform data or not to obtain a first judgment result;
under the condition that the first judgment result indicates yes, inputting the steady-state waveform data into a vibration fault mechanism model for analysis to obtain a first fault reason corresponding to the target equipment, wherein the vibration fault mechanism model is used for representing a mapping relation between the steady-state waveform data and the fault reason;
under the condition that the first judgment result indicates that the first fault reason is not obtained, inputting the vibration data of the target device into a preset model for analysis, and judging whether a second fault reason corresponding to the vibration data is obtained, wherein the preset model is obtained by training a plurality of groups of first data to be trained, and each group of first data to be trained in the plurality of groups of first data to be trained comprises: the sample vibration data and a label used for identifying a second fault reason corresponding to the sample vibration data are obtained;
and generating a diagnosis report according to the first fault reason, or generating a first diagnosis report according to the second fault reason under the condition of obtaining the second fault reason.
2. The fault diagnosis method according to claim 1, wherein the acquiring vibration data of the target apparatus includes:
receiving vibration waveform data of the target equipment, which is acquired by a sensor module at a plurality of preset time points, wherein the sensor module is arranged on the target equipment;
generating a plurality of target waveforms according to the vibration waveform data of the target equipment corresponding to the preset time points;
judging whether the target waveforms conform to theoretical waveforms or not;
sending an adjustment signal to the sensor module when any one of the target waveforms does not conform to the theoretical waveform, wherein the sensor module is used for collecting vibration waveform data of the target device within a preset time period according to a preset time interval under the condition of receiving the adjustment signal, and the preset time period is a time interval between any two adjacent preset time points in the preset time points;
and receiving vibration waveform data of the target equipment, which is acquired by the sensor module at the preset time interval.
3. The fault diagnosis method according to claim 1, further comprising:
acquiring historical fault information of the target device, wherein the historical fault information comprises: a plurality of historical fault causes, and a plurality of fault spectrum data corresponding to the plurality of historical fault causes, wherein each of the historical fault causes corresponds to at least one portion of the target device;
and establishing the vibration fault mechanism model according to the plurality of historical fault reasons and the plurality of fault frequency spectrum data.
4. The fault diagnosis method according to claim 1, wherein the vibration data of the target device includes: vibration speed, acceleration, temperature index, and vibration waveform data.
5. The fault diagnosis method according to claim 3, further comprising:
under the condition that the judgment result indicates that the second fault reason is not obtained, performing feature extraction on the vibration data to obtain target features;
and matching the target characteristics with a fault characteristic library of the target equipment to generate a second diagnosis report, wherein the fault characteristic library comprises a plurality of fault characteristics, and the plurality of fault characteristics are obtained by performing characteristic extraction on the historical fault information.
6. The fault diagnosis method according to any one of claims 1 to 5, characterized by further comprising:
judging whether an alarm signal is triggered or not according to the vibration data and the working threshold value of the target equipment;
and under the condition of triggering the alarm signal, outputting the alarm signal.
7. A failure diagnosis device characterized by comprising:
the acquisition module is used for acquiring vibration data of the target equipment;
the judging module is used for judging whether the vibration data of the target equipment comprises steady-state waveform data or not to obtain a first judging result;
the first determining module is used for inputting the steady-state waveform data into a vibration fault mechanism model for analysis under the condition that the first judgment result indicates yes, so as to obtain a first fault reason corresponding to the target device, wherein the vibration fault mechanism model is used for representing a mapping relation between the steady-state waveform data and the fault reason;
a second determining module, configured to, when the first determination result indicates that the first failure cause is not detected, input the vibration data of the target device into a preset model for analysis, and determine whether a second failure cause corresponding to the vibration data is obtained, where the preset model is obtained by training multiple sets of first data to be trained, and each set of the multiple sets of first data to be trained includes: the sample vibration data and a label used for identifying a second fault reason corresponding to the sample vibration data are obtained;
and the generating module is used for generating a diagnosis report according to the first fault reason or generating a first diagnosis report according to the second fault reason under the condition of obtaining the second fault reason.
8. A fault diagnosis system, comprising:
the sensor module is arranged on target equipment and used for acquiring vibration data of the target equipment, and the sensor module at least comprises a vibration sensor assembly;
a processor electrically connected to the sensor module for receiving the vibration data;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the fault diagnosis method of any one of claims 1 to 6.
9. The fault diagnostic system of claim 8, wherein the vibration sensor assembly comprises:
a vibration sensor;
the control circuit is electrically connected with the vibration sensor and used for driving the vibration sensor, and the control circuit comprises a filter circuit;
an isolation pad disposed between the vibration sensor and the target device;
and the shielding cover is covered outside the vibration sensor, the control circuit and the isolation gasket.
10. The fault diagnosis system of claim 9, wherein the shielding cover is a composite material layer, and the composite material layer comprises a metal layer and a high polymer layer which are laminated from inside to outside.
11. The fault diagnosis system of claim 9 wherein the vibration sensor assembly further comprises a cable connected to the processor, the cable comprising:
a plurality of cable cores, any one of which is grounded;
and the armor layer is arranged on the peripheries of the cable cores.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116256179A (en) * | 2023-01-07 | 2023-06-13 | 深圳市超越科技开发有限公司 | Vehicle fault diagnosis method, system and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116256179A (en) * | 2023-01-07 | 2023-06-13 | 深圳市超越科技开发有限公司 | Vehicle fault diagnosis method, system and storage medium |
| CN116256179B (en) * | 2023-01-07 | 2023-10-27 | 深圳市超越科技开发有限公司 | Vehicle fault diagnosis method, system and storage medium |
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