CN111610038B

CN111610038B - Fault diagnosis system, method, device, equipment and storage medium thereof

Info

Publication number: CN111610038B
Application number: CN202010443501.2A
Authority: CN
Inventors: 唐杰; 任晓斌
Original assignee: Huawei Digital Power Technologies Co Ltd
Current assignee: Huawei Digital Power Technologies Co Ltd
Priority date: 2020-05-22
Filing date: 2020-05-22
Publication date: 2022-05-13
Anticipated expiration: 2040-05-22
Also published as: CN111610038A

Abstract

The application provides a fault diagnosis system, a method, a device, equipment and a storage medium thereof, which are used for improving the accuracy of a fault diagnosis result, and the fault diagnosis system can comprise: the device comprises a noise receiving module, a processing module, an electric signal receiving module and a fault diagnosis module. The processing module is connected with the noise receiving module, and the fault diagnosis module is respectively connected with the electric signal receiving module and the processing module. The noise receiving module is used for being connected with the power system and receiving a first sound wave signal of the power system; the processing module is used for receiving the sound wave signal and processing the sound wave signal to obtain a second sound wave signal; the electric signal receiving module is used for being connected with the power system and receiving electric signal parameters of the power system; and the fault diagnosis module is used for receiving the second acoustic signal and the electric signal parameter and diagnosing the power system by using the second acoustic signal and the electric signal parameter to obtain a fault diagnosis result of the power system.

Description

Fault diagnosis system, method, device, equipment and storage medium thereof

Technical Field

The present application relates to the field of power electronics technologies, and in particular, to a fault diagnosis system, method, apparatus, device, and storage medium thereof.

Background

With the rapid development of the automobile industry and the large application of Battery Electric Vehicles (BEV), the automobile fault diagnosis technology is also rapidly promoted, which plays an irreplaceable role in automobile safety and maintenance.

The power system of the electric automobile at least comprises a driving motor, a speed reducer and an inverter. Specifically, the inverter is an electric control component, the reducer is a mechanical component, the driving motor is an electric control component and a mechanical component, the inverter can convert received electric energy into a supply voltage of the driving motor, the driving motor can rotate under the action of the supply voltage and output torque to the reducer, and the reducer can convert the output torque of the driving motor into the rotating speed of the wheel to drive the wheel to rotate.

In practical application, whether the electric automobile breaks down or not is mostly judged by detecting electric parameters of the inverter and the driving motor, and faults such as bearing failure of the driving motor, aging of the driving motor, gear abrasion, abnormal lubrication of the speed reducer and the like are difficult to detect, so that the detection result is inaccurate.

Therefore, the conventional fault diagnosis method has the problem of inaccurate diagnosis results.

Disclosure of Invention

The application provides a fault diagnosis system, a fault diagnosis method, a fault diagnosis device, equipment and a storage medium thereof, which are used for improving the accuracy of a fault diagnosis result.

In a first aspect, embodiments of the present application provide a fault diagnosis system, which may be connected to a power system of a device to be detected, and is used to detect whether the power system has a fault. The device to be detected can be an electric automobile.

Specifically, the fault diagnosis system may include: the device comprises a noise receiving module, a processing module, an electric signal receiving module and a fault diagnosis module. The processing module can be connected with the noise receiving module, and the fault diagnosis module can be respectively connected with the electric signal receiving module and the processing module.

The noise receiving device can be arranged near the power system and can be used for receiving a first sound wave signal of the power system; the processing module may be configured to receive the first acoustic signal and process the first acoustic signal to obtain a second acoustic signal; the electric signal receiving module can be used for being connected with the power system and receiving electric signal parameters of the power system; the fault diagnosis module can be used for receiving the second acoustic signal and the electric signal parameter, and detecting the power system by using the second acoustic signal and the electric signal parameter to obtain a fault diagnosis result of the power system.

By adopting the system structure, the first sound wave signal representing the fault state of the mechanical component and the electric signal parameter representing the fault state of the electric control component in the power system are received, and the two parts of data are utilized to carry out fault diagnosis on the power system, so that the fault diagnosis mode comprehensively diagnoses whether the power system has faults or not through the electric control component and the mechanical component, and the accuracy of the fault diagnosis result of the power system is improved.

In one possible design, the noise receiving device includes: a microphone sensor and/or a vibration sensor. Wherein the microphone sensor and the vibration sensor may be connected to a power system of the device to be detected.

Wherein the microphone sensor may be configured to receive a noise signal of the power system. The vibration sensor may be configured to receive a vibration signal of the power system. Wherein the first acoustic signal or the second acoustic signal may include: a noise signal and/or a vibration signal.

By adopting the system structure, for an application scene with low requirement on the accuracy of a power system diagnosis result, in order to reduce the energy loss, a microphone sensor or a vibration sensor can be adopted to obtain a first sound wave signal. For an application scene with a high requirement on the accuracy of the diagnosis result of the power system, the microphone sensor and the vibration sensor are used for acquiring the first sound wave signal, and when the first sound wave signal is used for fault diagnosis of the power system in the later period, the accuracy of the fault diagnosis result is improved, and the requirement of the application scene on the accuracy of the diagnosis result is met.

In one possible design, the processing module includes: the device comprises a filtering module, an amplifying module, an analog-to-digital converter and a memory.

The noise diagnosis device comprises a noise receiving module, an amplifying module, an analog-to-digital converter, a memory and a filtering module, wherein the filtering module is connected with the noise receiving module, the amplifying module is connected with the filtering module and the digital-to-analog conversion module, the analog-to-digital converter is connected with the memory, and the memory is connected with the fault diagnosis module.

The filtering module is used for receiving the first sound wave signal and filtering the first sound wave signal. The amplifying module may be configured to receive the filtered first sound wave signal, and amplify the filtered first sound wave signal. The analog-to-digital converter may be configured to perform analog-to-digital conversion on the amplified first acoustic signal to obtain a second acoustic signal, and store the second acoustic signal in the memory. The memory may be configured to store the second acoustic signal transmitted by the module converter and transmit the second acoustic signal to the fault diagnosis module.

By adopting the system structure, the first sound wave signal representing the running state of the mechanical component of the power system can be converted into a format required by the fault diagnosis module through the processing unit, namely a second sound wave signal, and the second sound wave signal is stored in the memory, so that the fault diagnosis module can directly use the signal to carry out fault diagnosis in the later period.

In a second aspect, embodiments of the present application provide an electric vehicle, which may include: a power system and a fault diagnosis system provided by the first aspect of the embodiment of the application. Wherein, the power system and the fault diagnosis system can be connected through an interface.

The power system can be used for providing power for the electric automobile. The fault diagnosis device can be used for carrying out fault diagnosis on the power system to obtain a fault diagnosis result.

By adopting the electric automobile structure, when a power system (comprising an electric control part and a mechanical part) of the electric automobile breaks down, early warning can be timely carried out, and the operation safety and the later-stage operation cost of the electric automobile are ensured.

In one possible design, the power system may include: the device comprises an inverter, a driving motor and a speed reducer.

Wherein, the driving motor can be respectively connected with the inverter and the reducer.

The inverter may be configured to be connected to a power supply and convert a voltage output by the power supply into a power supply voltage for driving the motor. The driving motor can be used for rotating under the action of the power supply voltage so as to drive the speed reducer to rotate. The speed reducer can be used for being connected with wheels of the electric automobile and driving the wheels to rotate through rotation of the speed reducer.

By adopting the electric automobile structure, in the running process of the electric automobile, the fault diagnosis can be carried out on the power system periodically or in real time through the fault diagnosis system, and when the fault of the power system is diagnosed, early warning can be carried out in advance so as to ensure the running safety of the electric automobile.

In a third aspect, an embodiment of the present application provides a fault diagnosis method, which may be executed by a fault diagnosis module in the fault diagnosis system provided in the first aspect of the embodiment of the present application. The method may specifically comprise the steps of:

acquiring a second sound wave signal of a power system of a device to be detected; acquiring electrical signal parameters of a power system; and carrying out fault diagnosis on the power system by utilizing the second acoustic wave signal and the electric signal parameter to obtain a fault diagnosis result of the power system. Wherein the second acoustic signal may be acquired by a memory in a processing module of the fault diagnosis system.

By adopting the method, whether the power system has faults can be comprehensively diagnosed by utilizing the second sound wave signal representing the fault state of the mechanical component of the power system and the electric signal parameter representing the electric control component of the power system, so that the accuracy of the fault diagnosis result of the power system is improved.

In one possible design, the fault diagnosis of the power system is performed by using the second acoustic signal and the electric signal parameter which represents the fault state of the electric control component of the power system, and the fault diagnosis result of the power system is obtained, and the fault diagnosis method comprises the following steps:

and inputting the second acoustic wave signal and the electric signal parameters into a pre-established power fault diagnosis model, and obtaining a fault diagnosis result and a fault type of the power system according to an output result of the diagnosis model. The power failure diagnosis model is established based on historical sound wave signals, historical electric signal parameters, fault type labels corresponding to the historical sound wave signals and fault type labels corresponding to the historical electric signal parameters of the power system.

By adopting the method, the electric signal parameter for representing the fault state of the power system and the second acoustic wave signal can be input into the pre-established power fault diagnosis model, the fault state of the power system can be directly obtained, and the operation is simple, convenient and quick.

In one possible design, diagnosing the power system by using the second acoustic signal and the electric signal parameter to obtain a fault diagnosis result of the power system, including:

extracting spectral information of the second acoustic signal; decomposing the second sound wave signal by utilizing the frequency spectrum information and the electric signal parameters to obtain corresponding sub sound wave signals of a plurality of different components in the power system; comparing the electric signal parameters and the sub sound wave signals corresponding to the different assemblies with data in a fault diagnosis library corresponding to the different assemblies respectively; and when the sub sound wave signals of the electric signal parameters corresponding to the target assembly are determined to be beyond the data range in the fault diagnosis library corresponding to the target assembly, determining that the target assembly is in fault. Wherein the fault diagnosis library corresponding to each of the plurality of different components is determined based on historical electrical signal parameters and historical acoustic signals of the power system.

By adopting the method, the fault diagnosis library of each component in the different components can be established through the numerical fluctuation range of the second acoustic signal and the electric signal parameter of the different components of the power system in the historical state in the normal state, the second acoustic signal and the electric signal parameter of each component in the current state are detected, and the fault state of each component in the different components is accurately diagnosed according to the current second acoustic signal and the electric signal parameter of the target component.

In one possible design, the failure diagnosis library corresponding to each of the plurality of different components may be established by: acquiring historical electric signal parameters of each of a plurality of different assemblies and corresponding historical sub-acoustic signals of each of the plurality of different assemblies in a normal state of the power system; and establishing a fault diagnosis library corresponding to each of the plurality of different power assemblies according to the sub-acoustic wave signal corresponding to each of the plurality of different assemblies and the electric signal parameter associated with each of the plurality of different assemblies. The fault diagnosis library corresponding to each of the plurality of different power assemblies may be configured as a fault diagnosis library of the power system.

By adopting the method, a plurality of components in the power system can be electric control components, mechanical components and mechanical and electric control combined components, when a fault diagnosis library of the target component is established by utilizing the second sound wave signal and electric signal parameters, the factors (the sub sound wave signal and the electric signal parameters) influencing the target component need to be determined firstly, the fault diagnosis library of the target component is established by utilizing the factors, and when the fault diagnosis library is utilized to carry out fault diagnosis on the target component in the later period, the accuracy of the diagnosis result is ensured.

In one possible design, decomposing the second acoustic signal using the spectral information and the electrical signal parameters to obtain corresponding sub-acoustic signals for a plurality of different components in the power system includes:

determining frequency information of the power system by using the electric signal parameters;

determining acoustic coefficients corresponding to a plurality of different components;

and decomposing the second acoustic signal according to the frequency information, the acoustic wave coefficients corresponding to the different assemblies and the frequency spectrum information to obtain a sub-acoustic signal corresponding to each assembly in the different assemblies in the power system.

By adopting the method, the received second acoustic signal can contain acoustic signals of a plurality of components, when the fault state of the target component is determined based on the second acoustic signal, the sub acoustic signal corresponding to the target component needs to be split from the second acoustic signal, and fault diagnosis is performed on the target component based on the split sub acoustic signal, so that the influence of the acoustic signals of other components on the diagnosis result of the target component is avoided, and the accuracy of the fault diagnosis result of the target component is improved.

In one possible design, the electrical signal parameters may include one or more of: speed, current, torque, voltage, frequency, and temperature.

In a fourth aspect, an embodiment of the present application provides a fault diagnosis apparatus, which may include: an acquisition unit and a processing unit.

The acquisition unit can be used for acquiring a second sound wave signal of the dynamic system of the device to be detected and acquiring an electric signal parameter of the dynamic system. The processing unit can be used for carrying out fault diagnosis on the power system by utilizing the second acoustic wave signal and the electric signal parameter to obtain a fault diagnosis result of the power system.

In one possible design, the processing unit may be specifically configured to: and inputting the second acoustic wave signal and the electric signal parameters into a pre-established power fault diagnosis model, and obtaining a fault diagnosis result and a fault type of the power system according to an output result of the diagnosis model. The power failure diagnosis model is established based on historical sound wave signals, historical electric signal parameters, fault type labels corresponding to the historical sound wave signals and fault type labels corresponding to the historical electric signal parameters of the power system.

In one possible design, the processing unit may be specifically configured to: extracting spectral information of the second acoustic signal; decomposing the second sound wave signal by utilizing the frequency spectrum information and the electric signal parameters to obtain corresponding sub sound wave signals of a plurality of different components in the power system; comparing the electric signal parameters and the sub sound wave signals corresponding to the different assemblies with data in a fault diagnosis library corresponding to the different assemblies respectively; and when the sub sound wave signals of the electric signal parameters corresponding to the target assembly are determined to be beyond the data range in the fault diagnosis library corresponding to the target assembly, determining that the target assembly is in fault. Wherein the fault diagnosis library corresponding to each of the plurality of different components is determined based on historical electrical signal parameters and historical acoustic signals of the power system.

In one possible design, the processing unit may be further configured to build a fault diagnosis library corresponding to each of the plurality of different components by:

acquiring historical electric signal parameters of each component in a plurality of different components and historical sub-sound wave signals corresponding to each component in the plurality of different components in a normal state of the power system; and establishing a fault diagnosis library corresponding to each of the plurality of different assemblies according to the sub sound wave signals corresponding to each of the plurality of different assemblies and the electric signal parameters related to each of the plurality of different assemblies. The fault diagnosis library corresponding to each of the plurality of different components can constitute a fault diagnosis library of the power system.

In one possible design, the processing unit is specifically configured to:

determining frequency information of the power system by using the electric signal parameters; determining acoustic coefficients corresponding to a plurality of different components; and decomposing the second sound wave signal according to the frequency information, the sound wave coefficients corresponding to the different assemblies and the frequency spectrum information to obtain sub sound wave signals corresponding to the different assemblies in the power system.

In one possible design, the electrical signal parameters include one or more of: speed, current, torque, voltage, frequency, and temperature.

In addition, the technical effect brought by any possible design manner in the fourth aspect can be referred to the technical effect brought by any possible design manner in the third aspect and the third aspect, and is not described herein again.

In a fifth aspect, an embodiment of the present application provides a fault diagnosis device, where the fault diagnosis device may be a fault diagnosis module in the diagnosis system provided in the first aspect of the embodiment of the present application, and the fault diagnosis device may include: a processor and a memory. Wherein the memory has stored therein a computer program; the processor is adapted to invoke the computer program in the memory to cause the control device to perform the method of the third aspect and any one of the possible designs of the third aspect.

In addition, the technical effect brought by any possible design manner in the fifth aspect can be referred to the technical effect brought by any possible design manner in the third aspect and the third aspect, and is not described herein again.

In a sixth aspect, embodiments of the present application provide a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to perform the method of the third aspect and any possible design of the third aspect.

In addition, the technical effect brought by any possible design manner in the sixth aspect can be referred to the technical effect brought by any possible design manner in the third aspect and the third aspect, and is not described herein again.

Drawings

Fig. 1 is a schematic diagram of an application scenario according to an embodiment of the present application;

fig. 2 is a schematic structural diagram of a fault diagnosis system according to an embodiment of the present application;

FIG. 3 is a schematic structural diagram of a processing module according to an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of an electric vehicle according to an embodiment of the present application;

FIG. 5 is a schematic structural diagram of a powertrain according to an embodiment of the present disclosure;

fig. 6 is a first flowchart illustrating a fault diagnosis method according to an embodiment of the present application;

fig. 7 is a second flowchart illustrating a fault diagnosis method according to an embodiment of the present application;

fig. 8 is a schematic flow chart of a sub-acoustic signal acquisition process according to an embodiment of the present application;

fig. 9 is a flowchart illustrating a process of establishing a fault diagnosis library according to an embodiment of the present application;

fig. 10 is a third flowchart illustrating a fault diagnosis process according to an embodiment of the present application;

FIG. 11 is a schematic structural diagram of a fault diagnosis apparatus according to an embodiment of the present application;

fig. 12 is a schematic structural diagram of a fault diagnosis device according to an embodiment of the present application.

Detailed Description

In the embodiment of the present application, "and/or" describes an association relationship of associated objects, which means that three relationships may exist, for example, a and/or B may mean: a alone, B alone, and both a and B, wherein A, B may be singular or plural.

The term "connection" referred to in this application, describing a connection relationship of two objects, may mean two connection relationships, for example, a and B connection, may mean: a is directly connected with B, and A is connected with B through C.

The "plurality" in the embodiment of the present application means two or more.

In the present application embodiments, "exemplary," "in some embodiments," "in another embodiment," and the like are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, the term using examples is intended to present concepts in a concrete fashion.

It should be noted that the terms "first," "second," and the like in the embodiments of the present application are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or order. The terms equal to or greater than or equal to in the embodiments of the present application may be used with greater than or equal to, and are applicable to the technical solutions adopted when greater than or equal to, and may also be used with less than or equal to, and are applicable to the technical solutions adopted when less than or equal to, it should be noted that when equal to or greater than or equal to, it is not used with less than; when the ratio is equal to or less than the combined ratio, the ratio is not greater than the combined ratio.

The fault diagnosis system provided by the embodiment of the application can be applied to electric vehicles, numerical control machines, ship propellers and wind power generation systems, fig. 1 exemplarily shows an application scenario of an electric vehicle, and as shown in fig. 1, the electric vehicle at least comprises: the components 1 to N form a power system of the electric automobile. Wherein N is a natural number.

The fault diagnosis system can be connected with a power system of the electric automobile to detect whether the power system of the electric automobile has a fault.

At present, a fault diagnosis system judges whether a power system fails by acquiring electric signal parameters representing the fault state of an electric control component in the power system of an electric automobile, but a plurality of components forming the power system of the electric automobile do not only comprise the electric control component, but also comprise a mechanical component and a component combining electric control and machinery, and whether the mechanical component fails or not can not be diagnosed only by detecting the electric signal parameters of the power system.

Therefore, the current fault diagnosis mode has the problem of low accuracy of fault diagnosis results, and the operation safety of the electric automobile is seriously influenced.

In view of the foregoing problems, embodiments of the present application provide a fault diagnosis system, method, apparatus, device, and storage medium thereof, which can improve accuracy of a fault diagnosis result.

Referring to fig. 2, in the structural schematic diagram of the fault diagnosis system provided by the present application, the fault diagnosis system 200 may be connected to a power system of a device to be detected, and perform fault diagnosis on the power system by sampling a signal representing a fault state of the power system on the power system to obtain the fault state of the power system, so as to ensure the operation safety of the device to be detected. The device to be detected can be an electric automobile, a photovoltaic power generation system and a wind power generation system.

As shown in fig. 2, the fault diagnosis system 200 may include: the device comprises a noise receiving module 201, a processing module 202, an electric signal receiving module 203 and a fault diagnosis module 204.

Wherein, the processing module 202 can be connected with the noise receiving module 201, and the fault diagnosis module 204 can be connected with the electric signal receiving module 203 and the processing module 202, respectively.

The noise receiving module 201 may be configured to be connected to a power system and configured to receive a first sound wave signal of the power system. The processing module 202 may be configured to receive the first acoustic signal and process the first acoustic signal to obtain a second acoustic signal. The electrical signal receiving module 203 may be configured to interface with a power system and receive an electrical signal parameter of the power system. The fault diagnosis module 204 may be configured to receive the second acoustic signal and the electrical signal parameter, and perform fault diagnosis on the power system by using the second acoustic signal and the electrical signal parameter, so as to obtain a fault diagnosis result of the power system.

When the fault diagnosis system 200 shown in fig. 2 is used for fault diagnosis of a power system, an input end of the noise receiving module 201 may be used as a first acquisition point of the fault diagnosis system 200 to acquire a first acoustic signal representing a fault state of a mechanical component, and an input end of the electrical signal receiving module 203 may be used as a second acquisition point of the fault diagnosis system 200 to acquire an electrical signal parameter representing a fault state of an electrical control component, and output the acquired first acoustic signal and the electrical signal parameter together to the fault diagnosis module 204 to perform fault diagnosis of the power system, so as to obtain a fault diagnosis result of the power system.

It should be understood that the first acoustic wave signal received by the noise receiving module 201 and representing the fault state of the mechanical component is an analog signal, and it may be difficult for the fault diagnosing module 204 to directly process the first acoustic wave signal, so that before the first acoustic wave signal is output to the fault diagnosing module 204, the second acoustic wave signal that can be directly processed by the fault diagnosing module 204 may be output after the first acoustic wave signal is processed by the processing module 203, and then the second acoustic wave signal is output to the fault diagnosing module 204.

It should be understood that, when the fault diagnosis system 200 provided in the embodiment of the present application is used to perform fault diagnosis on a power system of a device to be detected, fault diagnosis may be performed on the power system through the first acoustic signal representing a fault state of a mechanical component of the power system and the electrical signal parameter representing a fault state of an electrical control component of the power system, that is, the fault diagnosis method provided in the embodiment of the present application comprehensively considers the influence of two factors, namely, the electrical control component and the mechanical component, on the fault of the power system, and the fault diagnosis result obtained after fault diagnosis is performed in this way has higher accuracy.

In practical applications, for example, an electric vehicle, the fault diagnosis system 200 may be fixed on the electric vehicle. In another implementation manner, the fault diagnosis system 200 may also be configured to be flexibly detachable, that is, a fixed interface is provided on the electric vehicle, so as to implement connection between the fault diagnosis system 200 and the electric vehicle. In this case, the failure diagnosis system 200 may be regarded as a device independent of the electric vehicle.

Alternatively, the noise receiving module 201, the processing module 202, the electrical signal receiving module 203, and the fault diagnosing module 204 in the fault diagnosing system 200 may be connected in the form of an integrated circuit.

Alternatively, the noise receiving module 201, the processing module 202, the electrical signal receiving module 203, and the fault diagnosing module 204 in the fault diagnosing system 200 may be connected by transmission lines.

Next, specific configurations of the noise receiving module 201, the processing module 202, the electric signal receiving module 203, and the fault diagnosing module 204 in the fault diagnosing system 200 will be described.

Noise receiving module 201

The noise receiving module 201 may be connected to a power system of the device to be detected, and may be configured to sample a first acoustic signal indicative of a fault condition of the power system. Wherein the power system may comprise a plurality of different components.

Specifically, the noise receiving module 201 may include: a microphone sensor and/or a vibration sensor.

Wherein, the microphone sensor is arranged to function as: a noise signal of the power system is received. The vibration sensor is arranged to function as: and receiving a vibration signal of the power system. Wherein the vibration signal may comprise a vibration frequency of the plurality of components.

The specific types of the microphone sensor and the vibration sensor are not described in detail herein.

For example, the vibration sensor is disposed on a plurality of components of the power system and is used for directly acquiring vibration signals of the plurality of components in the power system during operation. Wherein the number of vibration sensors is the same as the number of components in the power system.

For example, the microphone sensor may be disposed near the power system, and may collect noise signals generated in the air during the operation of a plurality of components in the power system, so that the noise signals of the entire power system may be obtained by one microphone sensor.

It should be understood that if the vibration sensor is used for receiving the first sound wave signal, the first sound wave signal corresponding to the power system can be accurately obtained, but a plurality of sensors need to be arranged; if the microphone sensor is used for acquiring the first sound wave signal, the acquisition of the first sound wave signal can be realized by only arranging one sensor, but sound wave signals of other parts close to the power system may exist in the sampled first sound wave signal, namely interference signals may exist in the first sound wave signal. In practical applications, the selection may be performed according to an application scenario of the fault diagnosis system 200, which is not described in detail herein.

In some embodiments, in an application scenario where the accuracy of the fault diagnosis result is not high, in order to reduce the energy consumption, the first acoustic wave signal may be acquired by using a microphone sensor or a vibration sensor. Wherein the first acoustic signal comprises a noise signal or a vibration signal.

In other embodiments, in an application scenario where the requirement on the accuracy of the fault diagnosis result is high, the microphone sensing and the vibration sensor may be used to acquire the first sound wave signal, and when the fault diagnosis is performed on the power system based on the first sound wave signal, the accuracy of the fault diagnosis result is guaranteed.

For example, the noise receiving module 201 may collect the first acoustic signal and the electrical signal parameter at fixed time intervals or in real time. The specific setting of the time interval value is not limited in this embodiment of the present application.

Of course, the above description of the reception of the noise receiving module 201 is only an example, and in practical applications, the noise receiving module 201 may employ a pressure sensor for acquiring the first acoustic signal by detecting the pressure difference generated in the air by the acoustic signal during the operation of the power system.

Second, the processing module 202

The processing module 202 may be connected to the noise receiving module 201, and configured to receive the first acoustic signal and process the first acoustic signal to obtain a second acoustic signal. The first sound wave signal is an analog signal, and the second sound wave signal is a digital signal.

Specifically, the processing module 202 may include: a filtering module 2021, an amplifying module 2022, an analog-to-digital converter 2023, and a memory 2024.

As shown in fig. 3, the filtering module 2021 may be connected to the noise receiving module 201. The amplifying module 2022 is connected to the filtering module 2021 and the analog-to-digital converter 2023. The analog-to-digital converter 2023 may be connected to the memory 2024. The memory 2024 is connected to the fault diagnosis module 204.

The filtering module 2021 is configured to: and receiving the first sound wave signal, and filtering the first sound wave signal to filter out interference signals in the first sound wave signal. The amplification module 2022 is arranged to: and receiving the first sound wave signal after filtering processing, and amplifying the first sound wave signal after filtering processing so as to process the first sound wave signal at a later stage. The analog-to-digital converter 2023 is arranged to function as: the amplified first acoustic signal is subjected to analog-to-digital conversion to obtain a second acoustic signal, and the second acoustic signal is stored in the memory 2024. The memory 2024 is set to function as: the memory module converter 2023 sends the second acoustic signal, and sends the second acoustic signal to the fault diagnosis module 204.

It should be understood that if the fault diagnosis system 200 collects the first acoustic signal and the electrical signal parameter in real time, when the fault diagnosis module 204 performs fault diagnosis by using the second acoustic signal and the electrical signal parameter and the processing speed of the fault diagnosis module 204 is limited, the second acoustic signal fault diagnosis module 204 converted by the analog-to-digital converter 2023 may not receive the first acoustic signal and the electrical signal parameter, so as to avoid a diagnosis fault, the second acoustic signal and the electrical signal parameter may be temporarily stored in the memory 2024, and when the fault diagnosis module 204 is idle, the second acoustic signal and the electrical signal parameter stored in the memory 2024 are directly called to perform fault diagnosis on the power system.

Third, the electric signal receiving module 203

The electric signal receiving module 203 is connected with a power system which can be connected with the device to be detected and is used for receiving electric signal parameters which represent the fault state of electric control components of the power system. Wherein the electrical signal parameters may include: current, voltage, rotational speed, frequency, temperature, etc.

In one example, the powered system is provided with a monitoring system that can acquire operating parameters of a plurality of devices (powered systems and non-powered systems) in the device to be tested to monitor the operating state of the device to be tested. Specifically, the electric signal receiving module 203 can be connected with a monitoring system of the device to be detected to acquire electric signal parameters representing fault states of electric control components of the power system in the power system.

In another example, the electrical signal receiving module 203 may communicate with a powertrain of the device to be detected to obtain electrical signal parameters in the powertrain that are indicative of a fault condition of an electrical control component.

Fourth, fault diagnosis module 204

The fault diagnosis module 204 may be connected to the electrical signal receiving module 203 and the processing module 202, respectively, and the fault diagnosis module 204 may be configured to receive the second acoustic signal and the electrical signal parameter, and diagnose the power system by using the second acoustic signal and the electrical signal parameter, so as to obtain a power assembly fault diagnosis result of the power system.

In one example, since a plurality of components are included in the power system, each component is a part of the power system, when the fault diagnosis system 200 in the embodiment of the present application is used to diagnose a fault of the power system, it is possible to diagnose whether each power component has a fault by using the second acoustic signal and the electrical signal parameter, and when it is determined that any one of the plurality of components has a fault, it is determined that the power system has a fault.

In some embodiments, when it is determined that the power system has a fault, a warning is given by a monitoring system of the device to be detected, and the name of the component with the fault is displayed on a display panel of the monitoring system.

In other embodiments, upon determining that the power system is malfunctioning, the power system is controlled to stop operating and the name of the malfunctioning component is displayed on a display panel of the monitoring system.

In an example, the fault diagnosis module 204 may further be configured to receive the first acoustic wave signal from the noise receiving module 201, and control the electrical signal receiving module 203 to receive the electrical signal parameter.

For example, the fault diagnosis module 204 may be any one of a Micro Control Unit (MCU), a Central Processing Unit (CPU), and a Digital Signal Processor (DSP). Of course, the specific form of the fault diagnosis module 204 is not limited to the above example.

Based on the same inventive concept, as shown in fig. 4, an embodiment of the present application further provides an electric vehicle, where the electric vehicle 400 may include: a power system 401 and a fault diagnosis system 200 provided by the embodiment of the application. Wherein the powertrain 401 may be coupled to the fault diagnostic system 200 via a socket.

The power system 401 may be connected to a power supply and configured to provide power to the electric vehicle 400 through the power supply. The fault diagnosis system 200 may be configured to perform fault diagnosis on the power system 401, and obtain a fault diagnosis result of the power system 401.

Specifically, as shown in fig. 5, the power system 401 may include: an inverter 4011, a drive motor 4012, and a decelerator 4013.

The drive motor 4012 may be connected to an inverter 4011 and a reducer 4013.

The inverter 4011 may be configured to be connected to a power supply, and configured to convert a voltage output by the power supply into a supply voltage of the drive motor 4012; the driving motor 4012 can be used for rotating under the action of the power supply voltage so as to drive the speed reducer 4013 to rotate; the speed reducer 4013 is used to connect with a wheel of the electric vehicle 400, and is used to drive the wheel to rotate through the rotation of the speed reducer 4013.

Optionally, the electric vehicle 400 may further include a power supply, which may supply power to the power system 401. The power supply is a direct current power supply and outputs a first voltage. The first voltage is the working voltage of the driving motor 4012.

Optionally, the electric vehicle 400 further includes a monitoring system, which can monitor the operation of the electric vehicle and obtain the electrical signal parameters during the operation of the electric vehicle 200. Wherein the electrical signal parameters may include at least: current, voltage, speed, torque, and current.

It should be understood that, with the above-mentioned structure of the electric vehicle 400, during the operation of the electric vehicle 400, the fault diagnosis system 200 may periodically or in real time perform fault diagnosis on the power system 401, and when it is diagnosed that the power system 401 has a fault, an early warning may be performed in advance to ensure the operation safety of the electric vehicle 400.

Based on the same inventive concept, the embodiment of the present application further provides a fault diagnosis method, which can be executed by the fault diagnosis module provided by the embodiment of the present application, and performs fault diagnosis on the power system of the device to be detected through the second acoustic signal and the electrical signal parameter to obtain a fault diagnosis result of the power system.

For example, as shown in fig. 6, a schematic flow chart of a fault diagnosis method according to an embodiment of the present application is shown, where the method may include the following steps:

s601: the fault diagnosis module acquires a second acoustic signal of the power system of the device to be detected. The power system may include a plurality of components, and the second acoustic signal may include information indicative of a fault diagnosis status of the plurality of components. Wherein, the second acoustic signal is a digital acoustic signal.

In one example, the second acoustic signal may be received by a processing module provided by an embodiment of the present application.

S602: the fault diagnosis module obtains electrical signal parameters of the power system. Wherein the electrical signal parameters may include one or more of: speed, current, torque, voltage, frequency, and temperature.

In some embodiments, an electrical signal parameter indicative of a fault condition of an electrical control component of a powertrain system may be received by an electrical signal receiving module provided by an embodiment of the present application.

In other embodiments, the electrical signal parameters indicative of the fault condition of the electrical control components of the powertrain system may be obtained directly by interfacing with a monitoring system of the device under test.

S603: and the fault diagnosis module diagnoses the power system by utilizing the second sound wave signal and the electric signal parameter to obtain a fault diagnosis result of the power system. The fault diagnosis result may include whether the power system is faulty or not.

In some embodiments, when it is determined that the power system has a fault, an early warning may be performed by a monitoring system of the device to be detected, and a fault warning message and a name of the component having the fault are displayed on a display panel of the monitoring system.

In other embodiments, upon determining that the power system is malfunctioning, the power system may be controlled to stop operating by displaying a malfunction warning message and the name of the malfunctioning component on a display panel of the monitoring system.

Specifically, the present application may perform fault diagnosis on the power system by using two ways, namely, a fault diagnosis model and a fault diagnosis library, which are established in advance, based on the second acoustic wave signal and the electrical signal parameter, and the following two ways are described in detail with reference to the embodiments.

The first method is as follows: and carrying out fault diagnosis on the power system through a pre-established power fault diagnosis model. Specifically, a second acoustic signal and an electric signal parameter are input into a fault diagnosis model established in advance, and a fault diagnosis result and a fault type of the power system are obtained according to an output result of the fault diagnosis model.

The fault diagnosis result may include whether the power system is in fault, and the fault type may include a name of a component in fault.

Specifically, a fault diagnosis model of the power system is established by utilizing deep network learning based on historical sound wave signals, historical electric signal parameters, fault type labels corresponding to the historical sound wave signals and fault type labels corresponding to the historical electric signal parameters of the power system. Wherein the failure type tag may contain the name of the failed component. The fault type label corresponding to the historical sound wave signal comprises fault state information of a plurality of different components corresponding to the historical sound wave signal.

And secondly, performing fault diagnosis on the power system by adopting a pre-established fault database. The following describes a process of performing fault diagnosis on a power system by using a fault database with reference to an embodiment, as shown in fig. 7, the process may specifically include the following steps:

s701: the fault diagnosis module extracts spectrum information of the second acoustic signal.

Specifically, a spectrogram of the second acoustic signal may be extracted using Fast Fourier Transform (FFT).

S702: the fault diagnosis module decomposes the second sound wave signal by using the frequency spectrum information and the electric signal parameters to obtain corresponding sub-sound wave information of a plurality of different components in the power system.

It should be understood that, since the obtained second acoustic signal includes acoustic signals of a plurality of power components in the power system, when performing fault diagnosis on the target component using the second acoustic signal, it is necessary to first obtain a sub-acoustic signal corresponding to the target component from the second acoustic signal to perform fault diagnosis on the target signal. Wherein, the sound wave signals generated in the operation process of a plurality of components in the power system are all related to the frequency.

Specifically, as shown in fig. 8, frequency information of the power system is determined by using electrical signal parameters; determining acoustic coefficients corresponding to a plurality of different components; and decomposing the second acoustic signal according to the frequency information, the acoustic wave coefficients corresponding to the different assemblies and the frequency spectrum information to obtain sub-acoustic wave information corresponding to each assembly in the different assemblies in the power system.

For example, taking a driving motor assembly in a power system as an example, if the frequency of the power system is determined to be 50Hz through the parameters of the electric signals, and the driving motor is a motor with 48 slots, the sound wave signal corresponding to the frequency of 50 multiplied by 48 in the frequency spectrum information is the sub sound wave signal corresponding to the driving motor. It should be noted that, the sub-acoustic signals corresponding to other components in the power system can be obtained by the above method.

In addition, in the above manner, the second acoustic signal can be decomposed to obtain a plurality of sub-acoustic signals corresponding to different components.

S703: and the fault diagnosis module compares the electric signal parameters and the sub sound wave signals corresponding to the different assemblies with data in a fault diagnosis library corresponding to the different assemblies respectively. Wherein the fault diagnosis library corresponding to each of the plurality of different components is determined based on historical electrical signal parameters and historical acoustic information of the power system.

It should be understood that when a component in the power system is in a non-fault state (i.e., a normal state), the values of the sub-acoustic signals corresponding to the component and the electrical signal parameters associated with the component fluctuate within a certain range, and a fault diagnosis library corresponding to a plurality of components in the power system can be established according to the fluctuation range.

S704: and the fault diagnosis module determines that the target assembly has a fault when the sub sound wave signals of the electric signal parameters corresponding to the target assembly exceed the data range in the fault diagnosis library corresponding to the target assembly.

Next, with reference to fig. 9, a process of establishing a fault diagnosis library corresponding to each of the plurality of components provided in S703 of the present application will be described in detail. It should be noted that the following steps may be adopted to establish a fault diagnosis library corresponding to each of the plurality of components.

S901: the fault diagnosis module acquires historical electric signal parameters of each of the plurality of different components and historical sub-acoustic signals corresponding to each of the plurality of different components in a normal state of the power system.

Specifically, the numerical fluctuation range of the component in the normal state can be determined through the sub-acoustic wave signal and the historical electric signal parameter corresponding to the component.

S902: the fault diagnosis module establishes a fault diagnosis library corresponding to each of the plurality of different components according to the electrical signal parameters associated with each of the plurality of different components and the sub-acoustic wave signals corresponding to each of the plurality of different components.

Specifically, taking the assembly as an example of a driving motor, the driving motor is an electric control and mechanical combination component, therefore, whether the driving motor fails or not is related to the corresponding sub sound wave signal and the electric signal parameters (rotating speed, current, voltage and torque), so when a fault diagnosis library corresponding to the driving motor is established, the fluctuation range of the sub sound wave signal of the driving motor when the rotating speed, the current, the voltage and the rotating speed are specific values can be established, the fluctuation range of the sound wave signal when the related electric signal parameters are different values is calculated by using the method, and the calculated multiple sound wave fluctuation ranges are stored, so that the fault diagnosis library of the driving motor is obtained.

Next, by taking fig. 10 as an example, the fault diagnosis process provided in the second embodiment of the present invention is described in detail, and the specific process is as follows:

s1001: a second acoustic signal is acquired.

The second acoustic signal comprises acoustic signals of a plurality of different components.

S1002: and acquiring electrical signal parameters.

The electrical signal parameters may include: current, voltage, rotational speed, torque, frequency, torque, temperature, and the like.

Note that, in the present application, the data acquisition order of S1001 and S1002 is not particularly limited.

S1003: spectral information of the second acoustic signal is extracted.

S1004: and decomposing the second sound wave signal by utilizing the frequency information, the frequency spectrum information and the power coefficients of a plurality of different assemblies in the power system to obtain the sub sound wave signals corresponding to the plurality of different assemblies.

For example, taking a driving motor assembly in a power system as an example, if the frequency of the power system is determined to be 50Hz through the parameters of the electric signals, and the driving motor is a motor with 48 slots, the sound wave signal corresponding to the frequency of 50 multiplied by 48 in the frequency spectrum information is the sub sound wave signal corresponding to the driving motor. It should be noted that, the sub-acoustic signals corresponding to other components in the power system can be obtained by the above method. Wherein, 48 slots are the power coefficient of the driving motor.

Wherein the frequency information can be directly obtained from the electrical signal parameters. The corresponding power coefficients of a plurality of different components can be obtained according to a production manual of the components, and the obtained power coefficients are directly stored in a fault diagnosis module so as to be directly used when the sub sound wave signals are decomposed.

S1005: and respectively inputting the sub sound wave signal corresponding to each of the plurality of different assemblies and the related electric signal parameters into the corresponding fault diagnosis library.

S1006: the sub-acoustic signals and associated electrical signal parameters for each of the plurality of different components are compared to data in a corresponding fault diagnosis library.

Specifically, taking the target assembly as an example, when the sub acoustic wave signal corresponding to the target assembly and the electrical signal parameter associated with the target assembly are received, a value fluctuation interval corresponding to the sub acoustic wave signal corresponding to the value of the associated electrical signal parameter is found, and the sub acoustic wave signal corresponding to the target assembly is compared with the found value fluctuation interval.

S1007: and obtaining the fault diagnosis result of each component according to the comparison result.

Specifically, taking a target component as an example, when the sub acoustic wave signal and the associated electrical signal parameter corresponding to the target exceed the data in the fault diagnosis library corresponding to the target component, it is determined that the component has a fault.

S1008: and obtaining a fault diagnosis result of the power system according to the fault diagnosis result of each component.

Specifically, a power system failure is determined when any one of a plurality of different components in the power system fails.

The fault diagnosis method according to the embodiment of the present application is described in detail above with reference to fig. 6 and 10. The following describes the failure diagnosis device according to the embodiment of the present application in detail with reference to fig. 11.

It is to be understood that, in order to implement the above functions, the fault diagnosis apparatus 1100 may include a corresponding hardware structure and/or software module that performs each function. Those of skill in the art will readily appreciate that the present invention can be implemented in hardware or a combination of hardware and computer software, with the exemplary elements and algorithm steps described in connection with the embodiments disclosed herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

Fig. 11 shows a possible exemplary block diagram of a fault diagnosis apparatus according to an embodiment of the present application, and the diagnosis apparatus 1100 may be in the form of software, or hardware, or a combination of software and hardware. The fault diagnosis apparatus 1100 may include: an acquisition unit 1101 and a processing unit 1102. The obtaining unit 1101 can be used for obtaining a second acoustic signal of the power system of the device to be detected, and obtaining an electrical signal parameter of the power system. The processing unit 1102 may be configured to perform fault diagnosis on the power system by using the second acoustic signal and the electrical signal parameter, so as to obtain a fault diagnosis result of the power system.

In an embodiment, the processing unit 1102 may be specifically configured to: and inputting the second acoustic wave signal and the electric signal parameters into a pre-established power fault diagnosis model, and obtaining a fault diagnosis result and a fault type of the power system according to an output result of the diagnosis model. The power failure diagnosis model is established based on historical sound wave signals, historical electric signal parameters, fault type labels corresponding to the historical sound wave signals and fault type labels corresponding to the historical electric signal parameters of the power system.

In an embodiment, the processing unit 1102 may be specifically configured to: extracting spectral information of the second acoustic signal; decomposing the second sound wave signal by utilizing the frequency spectrum information and the electric signal parameters to obtain corresponding sub sound wave signals of a plurality of different components in the power system; comparing the electric signal parameters and the sub sound wave signals corresponding to the different assemblies with data in a fault diagnosis library corresponding to the different assemblies respectively; and when the sub sound wave signals of the electric signal parameters corresponding to the target assembly are determined to be beyond the data range in the fault diagnosis library corresponding to the target assembly, determining that the target assembly is in fault. Wherein the fault diagnosis library corresponding to each of the plurality of different components is determined based on historical electrical signal parameters and historical acoustic information of the power system.

In an embodiment, the processing unit 1102 may be further configured to establish a fault diagnosis library corresponding to each of the plurality of components by: acquiring historical electric signal parameters of each component in a plurality of different components and historical sub-sound wave information corresponding to each component in the plurality of different components in a normal state of the power system; and establishing a fault diagnosis library corresponding to each of the plurality of different assemblies according to the sub sound wave signals corresponding to each of the plurality of different assemblies and the electric signal parameters related to each of the plurality of different assemblies.

In an embodiment, the processing unit 1102 may be specifically configured to: determining frequency information of the power system by using the electric signal parameters; determining acoustic coefficients corresponding to a plurality of different components; and decomposing the second sound wave signal according to the frequency spectrum information, the sound wave coefficients corresponding to the different assemblies and the frequency spectrum information to obtain sub sound wave signals corresponding to the different assemblies in the power system.

In an embodiment, the electrical signal parameters include one or more of: speed, current, torque, voltage, speed, and temperature.

It should be noted that the failure diagnosis apparatus 1100 shown in fig. 11 can be used to execute the failure diagnosis method shown in fig. 6. The implementation of the fault diagnosis apparatus 1100 that is not described in detail can be referred to the related description of the fault diagnosis method shown in fig. 6.

Referring to fig. 12, a schematic diagram of a fault diagnosis device provided in the present application, which may be a fault diagnosis module in the fault diagnosis system in the above embodiment, is shown. As shown in fig. 12, the apparatus 1200 includes: a processor 1201 and a memory 1202.

Optionally, the apparatus 1200 may also include a bus 1203. The processor 1201 and the memory 1202 may be connected to each other via a bus 1203; the bus 1203 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus 1203 may be divided into an address bus, a data bus, a control bus, and so on. For ease of illustration, only one thick line is shown in FIG. 12, but this is not intended to represent only one bus or type of bus.

The processor 1201 may be a CPU, microprocessor, ASIC, or one or more integrated circuits configured to control the execution of the programs of the present application.

Memory 1202 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory may be separate and coupled to the processor via a communication line 1203. The memory may also be integral to the processor.

The memory 1202 is used for storing computer-executable instructions for executing the present invention, and is controlled by the processor 1201 to execute. The processor 1201 is configured to execute computer-executable instructions stored in the memory 1202, thereby implementing the optical fault diagnosis method provided by the above-described embodiment of the present application.

Optionally, the computer-executable instructions in the embodiments of the present application may also be referred to as application program codes, which are not specifically limited in the embodiments of the present application.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various changes and modifications may be made in the embodiments of the present application without departing from the spirit and scope of the embodiments of the present application. Thus, if such modifications and variations of the embodiments of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to encompass such modifications and variations.

Claims

1. A fault diagnosis system, comprising: the device comprises a noise receiving module, a processing module, an electric signal receiving module and a fault diagnosis module;

the noise receiving module is used for being connected with a power system and receiving a first sound wave signal of the power system;

the processing module is connected with the noise receiving module and is used for receiving the first sound wave signal and processing the first sound wave signal to obtain a second sound wave signal;

the electric signal receiving module is used for being connected with the power system and receiving electric signal parameters of the power system;

the fault diagnosis module is respectively connected with the electric signal receiving module and the processing module, and is used for receiving the second acoustic signal and the electric signal parameter and diagnosing the power system by using the second acoustic signal and the electric signal parameter to obtain a fault diagnosis result of the power system;

the power system includes a plurality of components, and the fault diagnosis module diagnoses each of the components using the second acoustic signal and the electrical signal parameter, each of the components including any one of: an electrically controlled component, a mechanical component, or an electrically controlled and mechanically coupled component;

the fault diagnosis module is used for:

extracting spectral information of the second acoustic signal;

decomposing the second sound wave signal by utilizing the frequency spectrum information and the electric signal parameters to obtain corresponding sub sound wave signals of a plurality of different components in the power system;

comparing the electrical signal parameters and the sub-acoustic signals corresponding to the plurality of different components with data in a fault diagnosis library corresponding to the plurality of different components respectively;

when the sub sound wave signals of the electric signal parameters and corresponding to the target assembly are determined to exceed the data range in the fault diagnosis library corresponding to the target assembly, determining that the target assembly has a fault;

wherein the fault diagnosis library corresponding to each of the plurality of different components is determined based on historical electrical signal parameters and historical acoustic signals of the power system.

2. The system of claim 1, wherein the noise receiving means comprises: a microphone sensor and/or a vibration sensor;

the microphone sensor is used for receiving a noise signal of the power system;

the vibration sensor is used for receiving a vibration signal of the power system;

the first or second acoustic signal comprises: the noise signal and/or the vibration signal.

3. The system of claim 1 or 2, wherein the processing module comprises: the device comprises a filtering module, an amplifying module, an analog-to-digital converter and a memory;

the filtering module is connected with the noise receiving module and is used for receiving the first sound wave signal and filtering the first sound wave signal;

the amplifying module is connected with the filtering module and the analog-to-digital converter, and is used for receiving the first sound wave signal after filtering processing and amplifying the first sound wave signal after filtering processing;

the analog-to-digital converter is connected with the memory, and the analog-to-digital conversion unit is used for performing analog-to-digital conversion on the amplified first sound wave signal to obtain a second sound wave signal and storing the second sound wave signal to the memory;

the memory is connected with the fault diagnosis module and used for storing the second sound wave signal sent by the module converter and sending the second sound wave signal to the fault diagnosis module.

4. An electric vehicle, comprising: a power system and a fault diagnosis system as claimed in any one of claims 1 to 3;

the power system is used for providing power for the electric automobile;

the fault diagnosis system is used for carrying out fault diagnosis on the power system to obtain a fault diagnosis result.

5. The electric vehicle of claim 4, characterized in that the power system comprises: an inverter, a drive motor and a reducer;

the inverter is used for being connected with a power supply and converting the voltage output by the power supply into the power supply voltage of the driving motor;

the driving motor is respectively connected with the inverter and the speed reducer and is used for rotating under the action of the power supply voltage so as to drive the speed reducer to rotate;

the speed reducer is used for being connected with wheels of the electric automobile and driving the wheels to rotate through rotation of the speed reducer.

6. A fault diagnosis method, comprising:

acquiring a second sound wave signal of a power system of a device to be detected;

acquiring an electric signal parameter of the power system;

carrying out fault diagnosis on the power system by utilizing the second acoustic wave signal and the electric signal parameter to obtain a fault diagnosis result of the power system;

the diagnosing the power system by using the second acoustic wave signal and the electric signal parameter to obtain the fault diagnosis result of the power system comprises the following steps:

extracting spectral information of the second acoustic signal;

7. The method of claim 6, wherein said decomposing the second acoustic signal using the spectral information and the electrical signal parameters to obtain corresponding sub-acoustic signals for a plurality of different components in the powered system comprises:

determining acoustic coefficients corresponding to the plurality of different components;

and decomposing the second sound wave signal according to the frequency information, the sound wave coefficients corresponding to the different assemblies and the frequency spectrum information to obtain a sub sound wave signal corresponding to each assembly in the different assemblies in the power system.

8. The method of claim 7, wherein the fault diagnosis library corresponding to each of the plurality of different components is established using:

acquiring historical electric signal parameters of each component in the plurality of different components and historical sub-sound wave signals corresponding to each component in the plurality of different components in a normal state of the power system;

establishing a fault diagnosis library corresponding to each of the plurality of different assemblies according to the sub-acoustic wave signal corresponding to each of the plurality of different assemblies according to the electrical signal parameter associated with each of the plurality of different assemblies.

9. The method of any one of claims 6-8, wherein the electrical signal parameters include one or more of: speed, current, torque, voltage, and temperature.

10. A failure diagnosis device characterized by comprising: an acquisition unit and a processing unit;

the acquisition unit is used for acquiring a second sound wave signal of the dynamic system of the device to be detected; and

acquiring an electric signal parameter of the power system;

the processing module is used for carrying out fault diagnosis on the power system by utilizing the second sound wave signal and the electric signal parameter to obtain a fault diagnosis result of the power system;

the power system includes a plurality of components, and the processing module diagnoses each of the components using the second acoustic signal and the electrical signal parameter, each of the components including any one of: an electrically controlled component, a mechanical component, or a combination of electrically and mechanically controlled components;

the processing unit is specifically configured to:

extracting spectral information of the second acoustic signal;

11. The apparatus as claimed in claim 10, wherein said processing unit is specifically configured to:

and decomposing the second sound wave signal according to the frequency spectrum information, the sound wave coefficients corresponding to the different components and the frequency spectrum information to obtain sub sound wave signals corresponding to the different components in the power system.

12. The apparatus of claim 10 or 11, wherein the processing unit is further configured to build a library of fault diagnoses corresponding to each of the plurality of different power assemblies using:

acquiring historical electric signal parameters of each of the plurality of different components and historical sound wave signals of each of the plurality of different components in a normal state of the power system;

13. The apparatus of any one of claims 10-12, wherein the electrical signal parameters include one or more of: speed, current, torque, voltage, and temperature.

14. A fault diagnosis apparatus characterized by comprising:

a memory and a processor;

a memory for storing program instructions;

a processor for invoking program instructions stored in the memory to perform the method of any of claims 6-9.

15. A computer-readable storage medium having stored thereon computer instructions which, when executed on a computer, cause the computer to perform the method of any one of claims 6-9.