Method and device for fault diagnosis, diagnostic device, electronic device and storage medium

Abstract

The present disclosure provides a method for fault diagnosis, which can include: listening to an environmental sound of a target element; in response to an action sound of the target element being included in the environmental sound, generating a target sound including the action sound; and using a diagnostic device to analyze the target sound and output a diagnosis result for characterizing an operating state of the target element. The present disclosure also provides a device for fault diagnosis, a diagnostic device, an electronic device, and a storage medium.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to a fault diagnosis technology, and in particular, to a fault diagnosis method and device, a diagnosis apparatus, an electronic device, and a storage medium. BACKGROUND

[0002] A switch cabinet is an electrical device capable of controlling and protecting electrical equipment by turning on and off the circuit during the process of power generation, power transmission, power distribution, and power conversion in a power system. The switch cabinet is built-in with a circuit breaker, which is the main component of turning on and off the circuit. Since the operation of the circuit breaker is very frequent, it often fails. It is very important to find the failure of the circuit breaker in time for the protection of electrical equipment.

[0003] The circuit breaker has a certain action frequency in the normal working state, and each action produces a certain action sound. At present, the action sound of the circuit breaker is mainly detected by a sound pressure meter by a technician, and then the action frequency is obtained, and finally the state of the circuit breaker is judged by the technician subjectively.

[0004] However, all the detection data involved in the above method cannot be exported, and only the technician can make a subjective judgment according to experience, which has a large subjective and no credibility. In addition, the technician can only detect the fault at the specified time point according to the inspection plan, and cannot monitor in real time, so it is difficult to find the fault in time. SUMMARY

[0005] In order to solve at least one of the above technical problems, the present disclosure provides a fault diagnosis method and device, a diagnosis apparatus, an electronic device, and a storage medium.

[0006] One aspect of the present disclosure provides a fault diagnosis method, which can include: listening to an environmental sound of a target element; generating a target sound including an action sound of the target element in response to the action sound included in the environmental sound; and analyzing the target sound by a diagnosis apparatus to output a diagnosis result for representing a working state of the target element.

[0007] In some embodiments, generating a target sound including an action sound of a target element in response to the action sound included in the environmental sound can include: when the action sound of the target element is included in the environmental sound, buffering a prelude sound recorded by a recording element for a first preset time; triggering the recording element to record the action sound for a second preset time; and integrating the prelude sound and the action sound to generate a target sound for representing the environmental sound of the target element.

[0008] In some embodiments, the analyzing the target sound by the diagnostic device and outputting a diagnostic result for representing a working state of the target element comprises: analyzing the target sound to generate frequency response data for representing an action frequency of the target element; comparing the frequency response data with an expected frequency response to generate a frequency response difference value; and in response to a determination that the frequency response difference value is greater than an error threshold, generating a diagnostic result of an abnormal working state, or in response to a determination that the frequency response difference value is less than or equal to the error threshold, generating a diagnostic result of a normal working state.

[0009] In some embodiments, after listening to the ambient sound of the target element, the method further comprises: determining whether a volume of the ambient sound exceeds a target volume, wherein the target volume is a volume standard of the action sound; and in response to the volume of the ambient sound exceeding the target volume, generating a determination result that the action sound of the target element is included in the ambient sound.

[0010] In some embodiments, before generating the target sound including the action sound in response to the action sound of the target element being included in the ambient sound, the method further comprises: using the recording element to record a prelude sound in a first preset time cycle, wherein the prelude sound occurs before the action sound.

[0011] In some embodiments, before analyzing the target sound by the diagnostic device and outputting a diagnostic result for representing a working state of the target element, the method further comprises: training an initial diagnostic element to generate the diagnostic device.

[0012] Another aspect of the present disclosure provides a device for fault diagnosis, which can include: a listening module configured to listen to an ambient sound of a target element; a target sound generation module configured to generate a target sound including an action sound of the target element in response to the action sound of the target element being included in the ambient sound; and a diagnostic result acquisition module configured to analyze the target sound by a diagnostic device and output a diagnostic result for representing a working state of the target element.

[0013] Yet another aspect of the present disclosure provides a device for fault diagnosis, which can include: a listening element disposed on one side of a target element and configured to listen to an ambient sound of the target element; a plurality of recording elements respectively disposed on at least two sides of the target element and configured to record a target sound, the target sound including an action sound of the target element and a prelude sound; a communication element configured to transmit the target sound to a diagnostic device according to a listening result of the listening element on the presence of the action sound in the ambient sound; a diagnostic device configured to process the target sound to generate a diagnostic result for representing a working state of the target element; and a power supply element including an external power supply and a built-in battery and configured to supply power to at least one of the listening element, the recording elements, the communication element, and the diagnostic device.

[0014] Still another aspect of the present disclosure provides an electronic device, which can include a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, a method for fault diagnosis according to any one of the above embodiments is implemented.

[0015] Still another aspect of the present disclosure provides a readable storage medium, which stores a computer program, and the computer program is adapted to be loaded by a processor to execute a method for fault diagnosis according to any one of the above embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings, which are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the present disclosure and together with the description serve to explain the principles of the present disclosure.

[0017] Figure 1 A flow chart of a method for fault diagnosis according to an exemplary embodiment of the present disclosure.

[0018] Figure 2 A block diagram of an apparatus for fault diagnosis according to an exemplary embodiment of the present disclosure.

[0019] Figure 3 A hardware schematic diagram of a fault diagnosis device according to an exemplary embodiment of the present disclosure.

[0020] Reference numerals

[0021] 1000 Apparatus for fault diagnosis

[0022] 1002 Training unit listening module

[0023] 1004 Target sound generation module

[0024] 1006 Diagnosis result acquisition module

[0025] 1100 Bus

[0026] 1200 Processor

[0027] 1300 Memory

[0028] 1400 Other circuit

[0029] 2000 Fault diagnosis device

[0030] 2100 Listening element

[0031] 2200 Recording element

[0032] 2300 Communication element

[0033] 2500 power supply components. Detailed Implementation

[0034] The present disclosure will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the disclosure. Furthermore, it should be noted that, for ease of description, only the parts relevant to the present disclosure are shown in the accompanying drawings.

[0035] It should be noted that, where there is no conflict, the embodiments and features described in this disclosure can be combined with each other. The technical solutions of this disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0036] Unless otherwise stated, the exemplary implementations / embodiments shown are to be understood as providing exemplary features of various details that provide ways in which the technical concepts of this disclosure can be implemented in practice. Therefore, unless otherwise stated, the features of various implementations / embodiments may be additionally combined, separated, interchanged and / or rearranged without departing from the technical concepts of this disclosure.

[0037] The terminology used herein is for the purpose of describing particular embodiments and is not restrictive. As used herein, unless the context clearly indicates otherwise, the singular forms “a” and “the” are intended to include the plural forms as well. Furthermore, when the terms “comprising” and / or “including” and variations thereof are used in this specification, it indicates the presence of the stated features, integrals, steps, operations, parts, components, and / or groups thereof, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, parts, components, and / or groups thereof. It should also be noted that, as used herein, the terms “substantially,” “about,” and other similar terms are used as approximate terms rather than as terms of degree, thus explaining the inherent biases in measurements, calculated values, and / or provided values ​​that would be recognized by one of ordinary skill in the art.

[0038] Figure 1 This is a flowchart of a fault diagnosis method according to an exemplary embodiment of this disclosure. The following will be combined with... Figure 1 The specific implementation method of each step of the fault diagnosis method S100 is explained in detail.

[0039] Step S102: Listen to the ambient sound of the target component.

[0040] The target element is the equipment whose operating status needs to be monitored, such as the circuit breaker in a switchgear. The circuit breaker is the main component in the switchgear for connecting and disconnecting circuits. Because its operation is very frequent, it is prone to failure; therefore, it is used as the target element in this disclosure. The target element produces corresponding operating sounds when it performs its actions. When the target element is operating normally, the frequency and intensity of its operating sounds will remain within a certain range; therefore, the operating status of the target element can be determined based on the state of its operating sounds.

[0041] Ambient sound refers to the sound signals generated by the target component and its surrounding environment during the monitoring process. It may include the sound of the target component's movement or noise signals in the environment.

[0042] If no action sounds are detected in the ambient sound, it means that the target component is not in operation. In this case, you can continue to monitor.

[0043] If motion sounds are present in the ambient sound, it means that the target element is in a working state. At this time, the recording element will be triggered to record the motion sounds and to buffer the preceding sounds of the recording element.

[0044] Therefore, recognizing motion sounds in environmental sounds is very important.

[0045] In some implementations, after listening to the ambient sound of the target element, the method further includes: identifying motion sounds in the ambient sound, specifically: determining whether the volume of the ambient sound exceeds a target volume, wherein the target volume is a volume standard for motion sounds; and in response to the ambient sound volume exceeding the target volume, generating a determination result that the ambient sound includes motion sounds of the target element.

[0046] More specifically, upon detecting ambient sound, a threshold is triggered to determine if the ambient sound contains action sounds. The threshold is essentially a volume comparator used to compare the volume of the ambient sound with a target volume. When the ambient sound volume exceeds the target volume, the recording element is triggered to record the action sounds, and operations such as buffering preceding sounds are also initiated. If the ambient sound volume is less than or equal to the target volume, the triggering mechanism is not activated, and continuous monitoring continues.

[0047] In some implementations, a preceding sound recording mechanism is also set up simultaneously during the process of monitoring the ambient sound of the target component, that is, the preceding sound is recorded in a loop using a recording element at a first preset time, wherein the preceding sound occurs before the action sound.

[0048] The recording element is used to record ambient sounds around the target element, including the target element's movement sounds and noise signals. The aforementioned monitoring mechanism is executed by the monitoring element, which does not have recording capabilities, while the recording element can record sound. However, since this disclosure continuously monitors the target element's operating status in real time, to reduce power consumption and save storage space, the recording element does not store all recorded sounds; it only triggers a buffering mechanism after the monitoring element detects movement sounds in the ambient sound.

[0049] The first preset time is the recording time for each preceding audio segment, which can be 6 seconds or set according to needs; there are no restrictions here.

[0050] Prelude audio is the sound that precedes the action sound; it can be noise or a mixture of noise and action sound. Recording prelude audio aims to prevent untimely recording triggering due to time differences between the monitoring and recording components. In short, recording prelude audio ensures complete capture of the action sound, preventing its loss. Furthermore, including ambient noise preceding the action sound facilitates accurate noise signal extraction, which is beneficial for noise reduction processing of action sounds mixed with noise.

[0051] Step S104: In response to the ambient sound including the motion sound of the target element, generate a target sound including the motion sound.

[0052] The target sound is the complete sound of the switching action, which is formed by integrating the action sound and the preceding sound. Its main purpose is to make the action sound more complete and prevent the loss of action sound due to the recording element's untimely response to the monitoring element's commands. The target sound is actually a sound segment within the ambient sound, and it is named separately in this disclosure to distinguish the processing objects of the monitoring element and the recording element.

[0053] Specifically, when the ambient sound includes the motion sound of the target element, the preceding sound recorded by the recording element for a first preset time is buffered; the recording element is triggered to record the motion sound for a second preset time; and the preceding sound and the motion sound are integrated to generate a target sound that represents the ambient sound of the target element.

[0054] The second preset time is the time required to record the action sound, and it is mainly set according to the time required for the target component to perform the action. When the target component is a circuit breaker, the second preset time can be set to 30 seconds. The duration of the second preset time should be longer than the length of time required for the target component to perform the action to ensure that the action sound can be recorded completely.

[0055] Step S106: Analyze the target sound using a diagnostic tool and output diagnostic results to characterize the working state of the target component.

[0056] A diagnostic tool, a type of neural network, utilizes deep learning mechanisms to analyze and process target sound, accurately outputting diagnostic results that characterize the working state of the target components. Diagnostic results obtained using the machine learning principles of a diagnostic tool offer higher accuracy and reliability compared to results obtained through subjective judgment by technicians in related technologies.

[0057] Specifically, the target sound is analyzed to generate frequency response data that characterizes the operating frequency of the target component; the frequency response data is compared with the expected frequency response to generate a frequency response difference value; and in response to the judgment result that the frequency response difference value is greater than the error threshold, a diagnostic result of abnormal working state is generated, or in response to the judgment result that the frequency response difference value is less than or equal to the error threshold, a diagnostic result of normal working state is generated.

[0058] Among them, the operating frequency can characterize the operating frequency of the target component. For example, when a circuit breaker connects and disconnects the circuit, it will produce an operating sound. The operating frequency of the circuit breaker can be inferred from the frequency of the operating sound. When the circuit breaker is in normal working condition, its operating frequency is within a reasonable frequency range. If the circuit breaker is aging, its frequency of connecting and disconnecting the circuit will decrease, and the operating frequency will also decrease accordingly.

[0059] Frequency response data is used to record the operating frequency of the target component. The desired frequency response is the reasonable frequency range data of the target component under normal operating conditions. The frequency response difference value is the difference between the frequency response data and the desired frequency response, used to characterize the difference between the operating frequency of the target component and the operating frequency of the target component under normal operating conditions.

[0060] In some implementations, prior to step S106, the method further includes: training the initial diagnostic element to generate a diagnostic tool.

[0061] The initial diagnostic element is a preliminary neural network consisting of multiple intermediate layers. The weights of each intermediate layer are initialized, therefore it cannot accurately output a diagnostic result based on the target sound. However, based on the learnable nature of neural networks, it can be trained into a diagnostic device capable of outputting diagnostic results based on the target sound using a large number of training samples.

[0062] Specifically, multiple sample sounds are acquired, including motion sounds; the sample sounds are analyzed by an initial diagnostic element to generate an estimation result; in response to the prediction error between the estimation result and the expected result, the weights of each intermediate element in the initial diagnostic element are adjusted; and when the prediction error is less than the error threshold, a diagnostic is generated.

[0063] In some implementations, noise reduction processing of the target audio is also included. Because the target audio contains preceding audio segments, which include a large proportion of pure noise, noise signal features can be extracted from the preceding audio. Based on these noise signal features, a mask extractor can accurately generate a noise mask for noise suppression. Using the noise mask, action sounds in the target audio can be extracted. The inclusion of preceding audio improves the accuracy of noise signal extraction, resulting in better noise reduction and easier analysis by the diagnostic tool.

[0064] The fault diagnosis method disclosed herein includes a pre-recording audio recording process, which facilitates accurate noise reduction and ensures complete acquisition of action sounds. Simultaneously, using a monitoring element to trigger the pre-recording audio buffer avoids wasting power and storage space on continuous buffering. Furthermore, the diagnostic results generated by the diagnostic tool using machine learning principles are more reliable than manual diagnosis. Storing the action sounds also provides data support for subsequent processing of abnormal operating states of target components.

[0065] Figure 2 This is a block diagram of a fault diagnosis apparatus according to an exemplary embodiment of the present disclosure. Figure 2 As shown, another aspect of this disclosure provides a fault diagnosis apparatus 1000, which may include: a monitoring module 1002 for monitoring ambient sounds of a target component; a target sound generation module 1004 for generating a target sound including the motion sound of the target component in response to ambient sounds; and a diagnostic result acquisition module 1006 for analyzing the target sound using a diagnostic tool and outputting diagnostic results characterizing the operating state of the target component.

[0066] The device 1000 may include corresponding units that perform one or more steps in the flowchart described above. Therefore, each or more steps in the flowchart can be performed by a corresponding unit, and the device 1000 may include one or more of these units. A unit may be one or more hardware modules specifically configured to perform a corresponding step, or implemented by a processor configured to perform a corresponding step, or stored in a computer-readable storage medium for implementation by a processor, or implemented through some combination thereof.

[0067] This hardware architecture can be implemented using a bus architecture. The bus architecture can include any number of interconnect buses and bridges, depending on the specific application of the hardware and bus design constraints. Bus 1100 will connect various circuits, including one or more processors 1200, memory 1300, and / or hardware modules. Bus 1100 can also connect various other circuits 1400, such as peripherals, voltage regulators, power management circuits, external antennas, etc.

[0068] Bus 1100 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Component (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, this diagram uses only one connection line, but it does not imply that there is only one bus or one type of bus.

[0069] Any process or method description in the flowcharts or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of this disclosure includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of this disclosure pertain. The processor performs the various methods and processes described above. For example, the method embodiments of this disclosure may be implemented as software programs tangibly contained in a machine-readable medium, such as memory. In some embodiments, part or all of the software program may be loaded and / or installed via memory and / or a communication interface. When the software program is loaded into memory and executed by the processor, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the processor may be configured to perform one of the methods described above by any other suitable means (e.g., by means of firmware).

[0070] The logic and / or steps represented in the flowchart or otherwise described herein may be specifically implemented in any readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus or device (such as a computer-based system, a processor-included system or other system that can fetch and execute instructions from, an instruction execution system, apparatus or device).

[0071] The fault diagnosis device disclosed herein includes a pre-recording audio recording process, which facilitates accurate noise reduction and ensures complete acquisition of action sounds. Simultaneously, the use of a monitoring element to trigger the pre-recording audio buffer avoids the waste of power and storage space associated with continuous buffering. Furthermore, the diagnostic results generated by the diagnostic tool using machine learning principles are more reliable than manual diagnosis. The storage of action sounds also provides data support for subsequent processing of abnormal operating states of target components.

[0072] Figure 3This is a hardware schematic diagram of a fault diagnosis device according to an exemplary embodiment of this disclosure. Figure 3 As shown, another aspect of this disclosure provides a fault diagnosis device 2000, which may include: a monitoring element 2100 disposed on one side of a target element for monitoring ambient sounds of the target element; a plurality of recording elements 2200 disposed on at least two sides of the target element for recording target sounds, the target sounds including movement sounds of the target element and preceding sounds; a communication element 2300 for transmitting the target sounds to a diagnostic device based on the monitoring results of the monitoring elements regarding the presence of movement sounds in the ambient sounds; and a diagnostic device for processing the target sounds to generate diagnostic results characterizing the operating state of the target element; and a power supply element 2500, including an external power supply and a built-in battery, for powering at least one of the monitoring element 2100, the recording elements 2200, the communication elements 2300, and the diagnostic device.

[0073] The listening element 2100 can be an analog microphone and can be placed on the side of the target element.

[0074] The recording element 2200 can be a digital microphone, and two can be arranged, either on the side or the back of the target element.

[0075] The communication element 2300 can be composed of a low-power MCU (Microcontroller Unit), a WIFI (Wireless Fidelity) unit, a 4G mobile communication unit, a 485 bus, and an Ethernet unit to support various transmission methods for the target sound from the recording element 2200 to the diagnostic device, including WIFI communication, 4G mobile signal communication, bus transmission, and Ethernet communication. The communication element 2300 also includes a Bluetooth BLE unit to support configuration requirements of the communication module 2300 via Bluetooth. The MCU unit, WIFI unit, 4G mobile communication unit, 485 bus, and Bluetooth BLE unit are connected via UART (Universal Asynchronous Receiver / Transmitter). A PHY (Physical) interface is provided between the MCU unit and the Ethernet unit to convert the target sound into Ethernet audio data. The MCU unit is connected to the PHY interface via RMII (Reduced Media Independent Interface), and the PHY interface is connected to the Ethernet unit via MDI (Medium Dependent Interface).

[0076] The monitoring element 2100 is connected to the MCU unit via a low-power wake-up circuit.

[0077] The recording element 2200 is connected to the MCU unit via a low-power recording circuit. A switching switch and PDM (Pulse Density Modulation) are respectively provided between the two monitoring elements 2100 and the low-power recording circuit.

[0078] A PDM is provided between the low-power recording circuit and the MCU unit.

[0079] The external power supply is equipped with an AC / AD (Alternating Current and Direct Current) power module, which converts the external 220V AC power into DC power.

[0080] It has a built-in 3800mAh lithium-ion battery. Two power supply options are available to increase installation flexibility.

[0081] This device is also equipped with a Bluetooth antenna (BT), a Wi-Fi antenna, a 4G mobile signal antenna, and an Ethernet interface.

[0082] This equipment is equipped with a PE (protected earth) wire, which is used to ground the entire equipment casing. When the fault diagnosis equipment is short-circuited, it can form a circuit with the ground to protect the equipment user.

[0083] This device is also equipped with multiple status indicator lights and switches.

[0084] The fault diagnosis device disclosed herein includes a pre-recording audio recording process, which facilitates accurate noise reduction and ensures complete acquisition of action sounds. Simultaneously, the use of a monitoring element to trigger the pre-recording audio buffer avoids the waste of power and storage space associated with continuous buffering. Furthermore, the diagnostic results generated by the diagnostic tool using machine learning principles are more reliable than manual diagnosis. The storage of action sounds also provides data support for subsequent processing of abnormal operating states of target components.

[0085] For the purposes of this specification, a "readable storage medium" can be any means capable of containing, storing, communicating, propagating, or transmitting a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable read-only memory (CDROM). Furthermore, a readable storage medium can even be paper or other suitable media on which a program can be printed, since a program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in memory.

[0086] It should be understood that various parts of this disclosure can be implemented in hardware, software, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0087] Those skilled in the art will understand that all or part of the steps of the methods described above can be implemented by a program instructing related hardware, and the program can be stored in a readable storage medium. When executed, the program includes one or a combination of the steps of the method implementation.

[0088] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into a single processing module, or each unit can exist physically separately, or two or more units can be integrated into a single module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a readable storage medium. The storage medium can be a read-only memory, a disk, or an optical disk, etc.

[0089] This disclosure also provides an electronic device, including: a memory storing execution instructions; and a processor or other hardware module executing the execution instructions stored in the memory, causing the processor or other hardware module to perform the above-described method.

[0090] This disclosure also provides a readable storage medium storing executable instructions, which, when executed by a processor, are used for a fault diagnosis method, including: listening to ambient sounds of a target component; generating a target sound including the action sounds of the target component in response to ambient sounds including the action sounds of the target component; and analyzing the target sound using a diagnostic tool to output a diagnostic result characterizing the operating state of the target component.

[0091] In the description of this specification, the references to terms such as "one embodiment / mode," "some embodiments / modes," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment / mode or example is included in at least one embodiment / mode or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment / mode or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments / modes or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments / modes or examples described in this specification, as well as the features of different embodiments / modes or examples.

[0092] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0093] Those skilled in the art should understand that the above embodiments are merely for illustrating the present disclosure and are not intended to limit the scope of the disclosure. Those skilled in the art can make other changes or modifications based on the above disclosure, and these changes or modifications still fall within the scope of the present disclosure.

Claims

1. A method for fault diagnosis, characterized in that, include: Listen to ambient sounds around the target component; In response to the ambient sound including the motion sound of the target element, a target sound including the motion sound is generated; as well as The target sound is analyzed using a diagnostic tool, and diagnostic results are output to characterize the working state of the target component. The step of generating a target sound including the action sound of the target element in response to the ambient sound includes: When the ambient sound includes the action sound of the target element, the preceding sound recorded by the recording element for a first preset time is buffered; The recording element is triggered to record the sound of the action for a second preset time; and Integrate the preceding sound and the action sound to generate the target sound, which is used to characterize the ambient sound of the target element; The step of analyzing the target sound using a diagnostic tool and outputting diagnostic results characterizing the operating state of the target component includes: The target sound is analyzed to generate frequency response data characterizing the operating frequency of the target component; The frequency response data is compared with the desired frequency response to generate a frequency response difference value; and In response to the judgment result that the frequency response difference value is greater than the error threshold, a diagnostic result of abnormal working state is generated; or in response to the judgment result that the frequency response difference value is less than or equal to the error threshold, a diagnostic result of normal working state is generated. Before generating a target sound including the motion sound of the target element in response to the ambient sound, the method further includes: The preceding sound is recorded in a loop using a recording element at a first preset time, wherein the preceding sound occurs before the action sound.

2. The fault diagnosis method according to claim 1, characterized in that, Following the ambient sound of the target component being monitored, the following is also included: Determine whether the volume of the ambient sound exceeds a target volume, wherein the target volume is a volume standard for the action sound; and In response to the ambient sound volume exceeding the target volume, a judgment result is generated that the ambient sound includes the action sound of the target element.

3. The fault diagnosis method according to claim 1, characterized in that, Before analyzing the target sound using a diagnostic tool and outputting diagnostic results characterizing the operating state of the target component, the method further includes: The initial diagnostic element is trained to generate the diagnostic tool.

4. A fault diagnosis device, characterized in that, include: The monitoring module is used to monitor the ambient sound of the target component. A target sound generation module is used to generate a target sound including the action sound of the target element in response to the action sound of the ambient sound. as well as The diagnostic result acquisition module is used to analyze the target sound using a diagnostic tool and output diagnostic results to characterize the working state of the target component. The step of generating a target sound including the action sound of the target element in response to the ambient sound includes: when the ambient sound includes the action sound of the target element, buffering the preceding sound recorded by the recording element for a first preset time; triggering the recording element to record the action sound for a second preset time; and integrating the preceding sound and the action sound to generate the target sound for characterizing the ambient sound of the target element. The step of analyzing the target sound using a diagnostic instrument and outputting a diagnostic result characterizing the working state of the target component includes: analyzing the target sound to generate frequency response data characterizing the operating frequency of the target component; comparing the frequency response data with a desired frequency response to generate a frequency response difference value; and generating a diagnostic result of abnormal working state in response to a judgment result that the frequency response difference value is greater than an error threshold, or generating a diagnostic result of normal working state in response to a judgment result that the frequency response difference value is less than or equal to the error threshold. Before generating a target sound including the action sound of the target element in response to the ambient sound, the method further includes: using a recording element to cyclically record a preceding sound at a first preset time, wherein the preceding sound occurs before the action sound.

5. A fault diagnosis device, characterized in that, include: A monitoring element is disposed on one side of the target element and is used to monitor the ambient sound of the target element; Multiple recording elements are respectively disposed on at least two sides of the target element for recording target sound, the target sound including the action sound of the target element and preceding sound; A communication element is used to transmit the target sound to a diagnostic device based on the monitoring result of the monitoring element that detects the presence of the action sound in the ambient sound. The diagnostic tool is used to process the target sound and generate diagnostic results to characterize the working state of the target component. as well as The power supply component includes an external power supply and a built-in battery for powering at least one of the listening component, the recording component, the communication component, and the diagnostic device; The fault diagnosis device is used to perform the fault diagnosis method according to any one of claims 1 to 3.

6. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the fault diagnosis method as described in any one of claims 1 to 3.

7. A readable storage medium, characterized in that, The readable storage medium stores a computer program adapted for loading by a processor to perform the fault diagnosis method as described in any one of claims 1 to 3.

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