WO2023093919A2 - 一种洗衣机异音检测方法、装置、电子设备及存储介质 - Google Patents

一种洗衣机异音检测方法、装置、电子设备及存储介质 Download PDF

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WO2023093919A2
WO2023093919A2 PCT/CN2023/073311 CN2023073311W WO2023093919A2 WO 2023093919 A2 WO2023093919 A2 WO 2023093919A2 CN 2023073311 W CN2023073311 W CN 2023073311W WO 2023093919 A2 WO2023093919 A2 WO 2023093919A2
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Prior art keywords
washing machine
data
sound
vibration data
tested
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PCT/CN2023/073311
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English (en)
French (fr)
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WO2023093919A3 (zh
Inventor
张成龙
黄雯瑶
董琪
周靖超
孙明
李志远
周邦国
Original Assignee
卡奥斯工业智能研究院(青岛)有限公司
海尔卡奥斯物联科技有限公司
海尔数字科技(青岛)有限公司
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Publication of WO2023093919A2 publication Critical patent/WO2023093919A2/zh
Publication of WO2023093919A3 publication Critical patent/WO2023093919A3/zh

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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
    • G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering

Definitions

  • the embodiments of the present application relate to the technical field of abnormal sound detection, for example, to a method, device, electronic equipment, and storage medium for detecting abnormal sound of a washing machine.
  • Abnormal sound is an important indicator to measure the quality of washing machine.
  • most of the abnormal sound detection on the washing machine production line adopts the method of manual detection and manual recording.
  • Manual abnormal sound detection is easily affected by subjective factors, and the detection accuracy is low. After a long time of detection, the staff is prone to auditory fatigue, resulting in false detection. And problems such as missed inspections seriously affect the production efficiency and automation level of the production line.
  • some abnormal sound detection systems are applied. Due to the influence of the noise generated by the vibration of the washing machine on the abnormal sound detection system, the detection accuracy of the current abnormal sound detection system is not high.
  • the abnormal sound detection system can detect the abnormal sound of washing machine products, it cannot analyze the cause of the abnormal sound, and manual assistance is needed to guide unqualified products to carry out follow-up maintenance and other work.
  • Embodiments of the present application provide a washing machine abnormal sound detection method, device, electronic equipment, and storage medium, combining the results of sound detection and vibration detection to determine the location and cause of abnormal sound, and improve the accuracy of abnormal sound detection.
  • the embodiment of the present application provides a method for detecting abnormal noise of a washing machine, including:
  • the embodiment of the present application also provides a device for detecting abnormal noise of a washing machine, including:
  • the data acquisition module is configured to acquire target sound data and target vibration data of the washing machine to be detected
  • the data analysis module is configured to select a matching sound analysis algorithm and vibration analysis algorithm based on the equipment identification information of the washing machine to be detected, so as to analyze the target sound data and target vibration data;
  • the module for determining the position and cause of the abnormal sound is configured to determine the location of the abnormal sound produced by the washing machine to be detected and the cause of the abnormal sound based on the analysis results of the sound data and the analysis results of the vibration data.
  • the embodiment of the present application also provides an electronic device, the electronic device includes:
  • processors one or more processors
  • memory for storing one or more programs
  • the one or more processors When the one or more programs are executed by the one or more processors, the one or more processors implement the method for detecting abnormal noise of a washing machine described in any embodiment of the present application.
  • the embodiment of the present application further provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the method described in any embodiment of the present application. Method for detecting abnormal sound of washing machine.
  • FIG. 1 is a flow chart of a method for detecting abnormal noise of a washing machine provided in Embodiment 1 of the present application;
  • Fig. 2 is a flow chart of a method for detecting abnormal noise of a washing machine provided in Embodiment 2 of the present application;
  • Fig. 3 is a flow chart of a method for detecting abnormal noise of a washing machine provided in Embodiment 3 of the present application;
  • Fig. 4 is a schematic structural diagram of a washing machine abnormal sound detection device provided in Embodiment 4 of the present application.
  • FIG. 5 is a schematic structural diagram of an electronic device provided in Embodiment 5 of the present application.
  • Figure 1 is a flowchart of a method for detecting abnormal noise of a washing machine provided in Embodiment 1 of the present application.
  • This embodiment is applicable to the detection of abnormal noise of a washing machine, and the method of this embodiment can be performed by a device for detecting abnormal noise of a washing machine , the device may be implemented in hardware and/or software.
  • the device can be configured in a server for abnormal noise detection of washing machines. The method comprises the steps of:
  • the target sound data may refer to the sound data emitted by the washing machine after it is started, for example, the sound emitted by the motor after the washing machine is started.
  • the target vibration data may refer to the data generated by the vibration after the washing machine is started, for example, the vibration data generated when the drum of the washing machine rotates.
  • Each part of the washing machine contains at least one sensor to collect target vibration data and target sound data of the washing machine in real time.
  • the device identification information may refer to a mark used to identify different models or batches of the washing machine.
  • the image acquisition device is used to acquire the equipment identification information of the washing machine, and the equipment identification information includes at least the model of the washing machine and the batch number of the washing machine.
  • the image acquisition device is used to obtain the equipment identification information of the washing machine, the collected image is transmitted to the machine vision system to obtain the product model of the washing machine, and the matching sound analysis algorithm and vibration analysis algorithm are selected according to different models of the washing machine, the said The sound analysis algorithm and the vibration analysis algorithm are automatically matched by the abnormal sound detection algorithm platform; the abnormal sound detection algorithm platform matches different sound analysis algorithms and vibration analysis algorithms according to different models of the washing machine, and the target sound data and the target vibration analysis of moving data.
  • the image acquisition device is used to obtain the equipment identification information of the washing machine, and the collected image is transmitted to the machine vision system to obtain the product batch number of the washing machine.
  • the abnormal sound detection algorithm platform according to Different batch numbers of washing machines are matched with different sound analysis algorithms and vibration analysis algorithms to analyze the target sound data and target vibration data.
  • analyzing the target sound data and target vibration data may refer to performing time-frequency analysis on the collected target sound data and target vibration data, for example, using a sound analysis algorithm to analyze the chromatogram of the target sound data , using the vibration analysis algorithm to perform envelope analysis on the target vibration data.
  • the unqualified washing machine to be tested According to the sound data analysis results, vibration data analysis results and the mechanism model of the washing machine to be tested, determine the position where the washing machine to be tested produces abnormal sound and the cause of the abnormal sound, and according to the abnormal sound generated The cause of the abnormal sound and the location of the abnormal sound remind the maintenance personnel to repair the unqualified washing machine to be tested.
  • the embodiment of the present application provides a washing machine abnormal sound detection method, by obtaining the target sound data and target vibration data of the washing machine to be detected; according to the equipment identification information of the washing machine to be detected, a matching sound analysis algorithm and vibration analysis algorithm are selected to detect The target sound data and the target vibration data are analyzed; according to the sound data analysis results and the vibration data analysis results, the position and the cause of the abnormal sound of the washing machine to be detected are determined.
  • the abnormal sound detection algorithm platform automatically matches the sound analysis algorithm and the vibration analysis algorithm to analyze the target sound data and target vibration data, and determine the location of the abnormal sound produced by the washing machine to be detected and the cause of abnormal sound, improve the accuracy of abnormal sound detection; and guide the maintenance personnel to repair the unqualified washing machine to be tested according to the mechanism model of the washing machine to be tested.
  • the application embodiment of the present invention determines the location and cause of the abnormal sound, and improves the accuracy of abnormal sound detection.
  • FIG. 2 is a flow chart of a method for detecting abnormal noise of a washing machine provided in Embodiment 2 of the present application.
  • this application Embodiments The foregoing embodiments are optimized on the basis of the foregoing embodiments, and the embodiments of the present application may be combined with various optional solutions in one or more of the foregoing embodiments.
  • the method for detecting abnormal noise of a washing machine provided in the embodiment of the present application may include the following steps:
  • the device identification information of the washing machine to be detected is obtained through the machine vision system, and the data collection environment of the washing machine to be detected is configured according to the obtained device identification information. Judging whether the currently configured data collection environment meets the collection conditions, the judgment criteria include parameters such as sampling frequency, number of sampling bits, number of bits, and environmental noise.
  • the judgment criteria include parameters such as sampling frequency, number of sampling bits, number of bits, and environmental noise.
  • an image acquisition device is used to obtain the barcode image of the washing machine, the barcode image is transmitted to a machine vision system, and the device identification information of the washing machine to be detected is obtained;
  • the obtained equipment identification information of the washing machine to be detected configure the data collection environment of the washing machine to be detected, and judge whether the currently configured data collection environment meets the collection conditions;
  • the judging whether the currently configured data collection environment satisfies the collection conditions includes: judging whether the sampling frequency, the number of sampling bits and the environmental noise of the washing machine to be tested meet the preset collection conditions.
  • the image acquisition device uses the image acquisition device to obtain the equipment identification information of the washing machine to be detected, configuring the data acquisition environment of the washing machine to be detected according to the equipment identification information, and judging whether the currently configured data acquisition environment meets the acquisition conditions.
  • the data collection environment is configured because the parameters of the washing machines to be tested are different, and different collection environments are determined according to different equipment identification information of the washing machines to be tested.
  • S220 Collect sound data and vibration data of the washing machine to be tested under the data collection environment, and obtain target sound data and vibration data of the washing machine to be tested.
  • vibration detection is performed on the base of the washing machine to be detected using a hydraulic device to obtain vibration data of the base of the washing machine to be detected, and the base model information of the washing machine to be detected is obtained through radio frequency identification technology;
  • the base vibration data In response to the matching of the collected base vibration data with the historical base vibration data, the base vibration data to analyze;
  • the base vibration data is eliminated, and the historical base vibration data is used as new base vibration data to obtain target vibration data of the washing machine to be detected.
  • a hydraulic device is used to fix the base of the washing machine, and the model of the base of the washing machine to be detected is collected through radio frequency identification technology.
  • Analyze the target vibration data in response to the mismatch between the collected base vibration data and the historical base vibration data, eliminate the collected base vibration data as noise data, and determine whether the noise data has been eliminated.
  • the noise data Analyze the vibration data of the base, and continue to eliminate the noise data when the noise data has not been eliminated.
  • the embodiment of the present application provides a washing machine abnormal sound detection method.
  • the equipment identification information of the washing machine to be tested is obtained through the machine vision system, and the data collection environment of the washing machine to be tested is configured according to the obtained equipment identification information; the washing machine to be tested is fixed by using a hydraulic device
  • the base uses radio frequency identification technology to obtain the equipment identification information of the washing machine to be tested. According to the matching degree between the collected base vibration data and the historical base vibration data, the generated vibration noise is eliminated, and the impact of vibration noise on abnormal sound detection is improved.
  • the accuracy rate of abnormal sound detection according to the equipment identification information of the washing machine to be detected, select the matching sound analysis algorithm and vibration analysis algorithm to analyze the target sound data and target vibration data; according to the sound data analysis results and vibration data analysis
  • the position and the cause of the abnormal sound of the washing machine to be tested are determined, and the maintenance personnel are promptly instructed to repair the unqualified washing machine to be tested.
  • FIG. 3 is a flow chart of a method for detecting abnormal noise of a washing machine provided in Embodiment 3 of the present application.
  • the embodiments of the present application optimize the foregoing embodiments on the basis of the foregoing embodiments, and the embodiments of the present application may be combined with various optional solutions in the foregoing one or more embodiments.
  • the abnormal sound detection method of the washing machine provided in the embodiment of the present application may include the following steps:
  • the abnormal sound detection algorithm platform automatically matches the sound analysis algorithm and vibration analysis algorithm of the corresponding model; Frequency analysis; the sound analysis algorithm analyzes the chromatogram of the collected sound data to generate abnormal sound detection results, and the vibration analysis algorithm performs envelope analysis on the collected vibration data to generate abnormal sound detection results.
  • a matching vibration analysis algorithm is selected to perform envelope analysis on the target vibration data to generate a vibration data analysis result.
  • the abnormal sound usually has certain characteristics
  • the data-driven deep learning training model is used to perform training and feature extraction on various sound data collected, and establish a voiceprint database.
  • the sound data includes friction sound and resonance sound, etc., so that
  • the voiceprint database includes chromatograms. Compare the collected sound data chromatogram with the chromatogram in the voiceprint database to find out whether there is abnormal sound, and based on the characteristics of different abnormal sound chromatograms, delineate the frequency of abnormal sound within a certain range, and then get The type of abnormal sound.
  • the noise frequency range of the bearing of the washing machine to be tested is 2000 Hz to 5000 Hz. If the noise frequency of the collected target sound data of the bearing itself is not in the range of 2000 Hz to 5000 Hz, the bearing of the washing machine to be tested has abnormal noise.
  • the analysis of the target vibration data envelope is also to compare the signal characteristics of the normal envelope and the abnormal envelope, and judge whether there is abnormal sound by judging the sound pressure of the envelope. For example, under normal circumstances, the sound pressure of the envelope curve is -0.3 ⁇ 0.3Pa, if the sound pressure of the envelope curve of the target vibration data is not within the range of -0.3 ⁇ 0.3Pa, it is determined that the target vibration data exists Abnormal, and the abnormal sound is a scratching sound.
  • the sound data analysis results and the vibration data analysis results are judged, and the following conditions are regarded as unqualified washing machines to be tested: the sound data analysis results are unqualified but the vibration data analysis results are qualified, the sound data analysis results are qualified but the vibration data The data analysis results are unqualified, and the sound data analysis results and vibration data analysis results are unqualified.
  • the analysis results of the vibration data and the mechanism model of the washing machine to be tested determine the position where the washing machine to be tested produces the abnormal sound and the cause of the abnormal sound;
  • the mechanism model of the washing machine to be detected includes the precise distribution of multiple structures of the washing machine
  • the information of the unqualified washing machine to be tested includes at least: equipment identification information, data collection environment information, target sound data, target vibration data, sound data analysis results, and vibration data analysis results.
  • the washing machine to be tested is unqualified, and the equipment identification information and the collected target vibration data of the unqualified washing machine to be tested are , target sound data, sound data analysis results, and vibration data analysis results are uploaded to the manufacturing execution system and database for storage of data information, and the location of the abnormal sound is determined according to the mechanism model of the washing machine to be tested.
  • the washing machine to be tested is qualified. And upload the information of the qualified washing machines to be tested to the manufacturing execution system and database, and store the information of the qualified washing machines to be tested; the information of the qualified washing machines to be tested at least includes: equipment identification information, data collection Environmental information, target sound data, target vibration data, sound data analysis results, and vibration data analysis results.
  • the embodiment of the present application provides a washing machine abnormal sound detection method, by obtaining the target sound data and target vibration data of the washing machine to be detected; according to the equipment identification information of the washing machine to be detected, the abnormal sound detection algorithm platform automatically matches the sound analysis algorithm of the corresponding model and vibration analysis algorithm; the sound analysis algorithm and vibration analysis algorithm perform time-frequency analysis on the collected sound data and vibration data; the sound analysis algorithm analyzes the chromatogram of the collected sound data, and the vibration analysis algorithm packages the collected vibration data Analyzing the network line to generate abnormal sound detection results; in response to both the sound data analysis results and the vibration data analysis results being qualified, it is determined that the washing machine to be tested is qualified; in response to at least one of the sound data analysis results and the vibration data analysis results being unqualified, Determine that the washing machine to be tested is unqualified, and according to the sound data analysis results, vibration data analysis results, and the mechanism model of the washing machine to be tested, determine the position where the washing machine to be tested produces abnormal noise and the cause of the abnormal sound, and promptly remind maintenance personnel Carry out repairs to
  • Fig. 4 is a schematic structural diagram of a washing machine abnormal noise detection device provided in Embodiment 4 of the present application, the device includes: a data acquisition module 410, a data analysis module 420 and a module for determining the location and cause of abnormal noise 430. in:
  • the data acquisition module 410 is configured to acquire target sound data and target vibration data of the washing machine to be detected;
  • the data analysis module 420 is configured to select a matching sound analysis algorithm and vibration analysis algorithm according to the equipment identification information of the washing machine to be detected, so as to analyze the target sound data and target vibration data;
  • the location and cause determination module 430 of the abnormal sound is configured to determine the location and the cause of the abnormal sound of the washing machine to be detected according to the sound data analysis results and the vibration data analysis results.
  • the data acquisition module 410 is configured to acquire target sound data and target vibration data of the washing machine to be detected in the following manner:
  • the sound data and vibration data of the washing machine to be tested are collected to obtain the target sound data and vibration data of the washing machine to be tested.
  • the acquiring the device identification information of the washing machine to be detected, and configuring the data collection environment of the washing machine to be detected according to the device identification information includes:
  • Adopt image acquisition equipment to obtain the barcode image of the washing machine, transmit the barcode image to the machine vision system, and obtain the equipment identification information of the washing machine to be detected;
  • the obtained equipment identification information of the washing machine to be detected configure the data collection environment of the washing machine to be detected, and judge whether the currently configured data collection environment meets the collection conditions;
  • the judging whether the currently configured data collection environment satisfies the collection conditions includes: judging whether the sampling frequency, the number of sampling bits and the environmental noise of the washing machine to be tested meet the preset collection conditions.
  • the data acquisition module 420 is configured to select a matching sound analysis algorithm and a vibration analysis algorithm according to the equipment identification information of the washing machine to be detected in the following manner, so as to analyze the target sound data And target vibration data for analysis:
  • the base vibration data is eliminated, and the historical base vibration data is used as new base vibration data to obtain target vibration data of the washing machine to be detected.
  • the analyzing the target sound data and target vibration data includes:
  • a matching vibration analysis algorithm is selected to perform envelope analysis on the target vibration data to generate a vibration data analysis result.
  • the abnormal sound location and cause determination module 430 is configured to determine the location where the abnormal sound is generated by the washing machine to be detected and the abnormal sound generated according to the sound data analysis results and the vibration data analysis results in the following manner: The reason for the sound:
  • the analysis result of the vibration data and the mechanism model of the washing machine to be tested determine the position where the washing machine to be tested produces the abnormal sound and the cause of the abnormal sound;
  • the mechanism model of the washing machine to be detected includes the precise distribution of multiple structures of the washing machine.
  • determining that the washing machine to be tested is unqualified includes:
  • the information of the unqualified washing machine to be tested at least includes: equipment identification information, data collection Environmental information, target sound data, target vibration data, sound data analysis results, and vibration data analysis results;
  • the abnormal sound location and cause determination module 430 is also configured to determine the location of the abnormal sound and the abnormal sound generated by the washing machine to be detected according to the analysis results of the sound data and the analysis results of the vibration data in the following manner s reason:
  • the information of the qualified washing machines at least includes: equipment identification information, data collection environment information, Target sound data, target vibration data, sound data analysis results, and vibration data analysis results;
  • the above-mentioned device can execute the abnormal sound detection method of the washing machine provided in any embodiment of the present application, and has corresponding functional modules and beneficial effects for executing the abnormal sound detection method of the washing machine.
  • FIG. 5 is a schematic structural diagram of an electronic device provided in Embodiment 5 of the present application.
  • the embodiment of the present application provides an electronic device, which can integrate the interactive device for detecting abnormal noise of the washing machine provided in the embodiment of the present application.
  • this embodiment provides an electronic device 500, which includes: one or more processors 520; a storage device 510 for storing one or more programs, when the one or more programs are executed The one or more processors 520 execute, so that the one or more processors 520 implement the method for detecting abnormal noise of a washing machine provided in the embodiment of the present application, and the method includes:
  • processor 520 can also implement the implementation of the method for detecting abnormal noise of a washing machine provided in any embodiment of the present application.
  • the electronic device 500 shown in FIG. 5 is only an example
  • the electronic device 500 includes a processor 520, a storage device 510, an input device 540, and an output device 540; the number of processors 520 in the electronic device can be one or more, and one processor 520 As an example; the processor 520, the storage device 510, the input device 540 and the output device 540 in the electronic device may be connected through a bus or in other ways. In FIG. 5, the connection through the bus 550 is taken as an example.
  • the storage device 510 can be used to store software programs, computer-executable programs and module units, such as program instructions corresponding to the method for detecting abnormal noise of a washing machine in the embodiment of the present application.
  • the storage device 510 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application program required by at least one function; the data storage area may store data created according to the use of the terminal, and the like.
  • the storage device 510 may include a high-speed random access memory, and also Non-volatile memory may be included, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device.
  • the storage device 510 may include memory located remotely from the processor 520, and these remote memories may be connected through a network. Examples of such networks include the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
  • the input device 540 can be used to receive input numbers, character information or voice information, and generate key signal input related to user settings and function control of the electronic device.
  • the output device 540 may include electronic equipment such as a display screen and a speaker.
  • the electronic device provided in the embodiment of the present application can determine the location and cause of the abnormal sound, and improve the accuracy of abnormal sound detection.
  • Embodiment 6 of the present application also provides a storage medium containing computer-executable instructions, the computer-executable instructions are used to execute a method for detecting abnormal noise of a washing machine when executed by a computer processor, the method comprising:
  • the program when executed by the processor, it can also be used to execute the method for detecting abnormal noise of the washing machine provided in any embodiment of the present application.
  • the computer storage medium in the embodiments of the present application may use any combination of one or more computer-readable media.
  • the computer readable medium may be a computer readable signal medium or a computer readable storage medium.
  • a computer-readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof.
  • Computer-readable storage media can include: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (Random Access Memory, RAM), read-only memory (Read Only Memory, ROM), erasable Programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), flash memory, optical fiber, portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), optical storage device, magnetic storage device, or any of the above the right combination.
  • a computer readable storage medium may be any tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device.
  • a computer readable signal medium may include a data signal carrying computer readable program code in baseband or as part of a carrier wave. Such propagated data signals may take various forms, including: electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • a computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. .
  • Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wires, optical cables, radio frequency (Radio Frequency, RF), etc., or any suitable combination of the above.
  • any appropriate medium including but not limited to: wireless, wires, optical cables, radio frequency (Radio Frequency, RF), etc., or any suitable combination of the above.
  • Computer program code for performing the operations of the present application may be written in one or more programming languages or combinations thereof, including object-oriented programming languages—such as Java, Smalltalk, C++, and conventional Procedural Programming Language - such as "C" or a similar programming language.
  • the program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server.
  • the remote computer can be connected to the user computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or it can be connected to an external computer (e.g. using an Internet Service Provider to connect via the Internet).
  • LAN Local Area Network
  • WAN Wide Area Network
  • Internet Service Provider to connect via the Internet

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  • Audiology, Speech & Language Pathology (AREA)
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Abstract

本申请实施例公开了一种洗衣机异音检测方法、装置、电子设备及存储介质。该方法包括：获取待检测洗衣机的目标声音数据以及目标振动数据；依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析；依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因

Description

一种洗衣机异音检测方法、装置、电子设备及存储介质
本申请要求在2021年11月26日提交中国专利局、申请号为202111423244.7的中国专利申请的优先权，该申请的全部内容通过引用结合在本申请中。
技术领域
本申请实施例涉及异音检测技术领域，例如涉及一种洗衣机异音检测方法、装置、电子设备及存储介质。
背景技术
异音是衡量洗衣机品质的一个重要指标。然而，洗衣机生产线上的异音检测大都采用人工检测以及人工记录的方法，人工异音检测易受主观因素影响，检测准确率较低，并且长时间检测，工作人员容易产生听觉疲劳，导致误检以及漏检等问题，严重影响产线生产效率和自动化水平。为了实现洗衣机的异音自动化检测，一些异音检测***应用而生，受洗衣机工作时由振动产生的噪声对异音检测***的影响，当前异音检测***的检测准确率并不高。此外，异音检测***虽然能够检测出洗衣机产品的异音，但无法分析异音产生原因，需要人工辅助才能指导不合格的产品进行后续的维修等工作。
发明内容
本申请实施例提供一种洗衣机异音检测方法、装置、电子设备及存储介质，结合声音检测和振动检测的结果，确定异音位置及原因，提高异音检测的准确率。
第一方面，本申请实施例提供了一种洗衣机异音检测方法，包括：
获取待检测洗衣机的目标声音数据以及目标振动数据；
依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析；
依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因。
第二方面，本申请实施例还提供了一种洗衣机异音检测装置，包括：
数据获取模块，设置为获取待检测洗衣机的目标声音数据以及目标振动数据；
数据分析模块，设置为依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析；
异音位置及原因确定模块，设置为依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因。
第三方面，本申请实施例还提供了一种电子设备，该电子设备包括：
一个或多个处理器；
存储器，用于存储一个或多个程序；
当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现本申请任意实施例所述的洗衣机异音检测方法。
第四方面，本申请实施例还提供了一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序，所述计算机程序被处理器执行时实现本申请任意实施例所述的洗衣机异音检测方法。
附图说明
图1是本申请实施例一提供的一种洗衣机异音检测方法的流程图；
图2是本申请实施例二提供的一种洗衣机异音检测方法的流程图；
图3是本申请实施例三提供的一种洗衣机异音检测方法的流程图；
图4是本申请实施例四提供的一种洗衣机异音检测装置的结构示意图；
图5是本申请实施例五提供的一种电子设备的结构示意图。
具体实施方式
下面结合附图和实施例对本申请作详细说明。可以理解的是，此处所描述的具体实施例仅仅用于解释本申请。另外还需要说明的是，为了便于描述，附图中仅示出了与本申请相关的部分而非全部结构。
在更加详细地讨论示例性实施例之前，应当提到的是，一些示例性实施例被描述成作为流程图描绘的处理或方法。虽然流程图将各项操作(或步骤)描述成顺序的处理，但是其中的许多操作(或步骤)可以被并行地、并发地或者同时实施。此外，各项操作的顺序可以被重新安排。当其操作完成时所述处理可以被终止，但是还可以具有未包括在附图中的附加步骤。所述处理可以对应于方法、函数、规程、子例程、子程序等等。
实施例一
图1是本申请实施例一提供的一种洗衣机异音检测方法的流程图，本实施例可适用于对洗衣机异音进行检测的情况，本实施例的方法可以由洗衣机异音检测装置来执行，该装置可以采用硬件和/或软件的方式来实现。该装置可以配置于洗衣机异音检测的服务器中。该方法包括如下步骤：
S110、获取待检测洗衣机的目标声音数据以及目标振动数据。
本实施例中，目标声音数据可以是指洗衣机在启动后发出的声音数据，例如，启动洗衣机后电机发出的声音。
目标振动数据可以是指洗衣机在启动后由于振动产生的数据，例如，在洗衣机桶转动时产生的振动数据。
在洗衣机的每个部位下都含有至少一个传感器，实时采集洗衣机的目标振动数据以及目标声音数据。
S120、依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析。
本实施例中，设备标识信息可以是指用来识别洗衣机不同型号或不同批次的一种记号。例如利用图像采集设备获取洗衣机的设备标识信息，所述设备标识信息至少包括洗衣机型号以及洗衣机的批次号。
在一种示例中，利用图像采集设备获取洗衣机的设备标识信息，将采集的图像传输至机器视觉***获取洗衣机的产品型号，根据洗衣机的不同型号选取匹配的声音分析算法以及振动分析算法，所述声音分析算法以及振动分析算法由异音检测算法平台自动匹配；所述异音检测算法平台根据洗衣机的不同型号匹配不同的声音分析算法以及振动分析算法，对所述目标声音数据以及目标振 动数据进行分析。
在一种示例中，利用图像采集设备获取洗衣机的设备标识信息，将采集的图像传输至机器视觉***获取洗衣机的产品批次号，对于属于同一批次的洗衣机，在异音检测算法平台内根据洗衣机的不同批次号匹配不同的声音分析算法以及振动分析算法，对所述目标声音数据以及目标振动数据进行分析。
本实施例中，对所述目标声音数据以及目标振动数据进行分析可以是指对采集到的目标声音数据以及目标振动数据进行时频分析，例如采用声音分析算法对目标声音数据进行色谱图的分析，采用振动分析算法对目标振动数据进行包络线分析。
S130、依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因。
本实施例中，判断声音数据分析结果以及振动数据分析结果是否都合格，响应于声音数据分析结果以及振动数据分析结果都合格时，确定待检测洗衣机合格；响应于声音数据分析结果以及振动数据分析结果中存在至少一项不合格，确定待检测洗衣机不合格。
对于检测不合格的待检测洗衣机，依据所述声音数据分析结果、振动数据分析结果以及待检测洗衣机的机理模型，确定待检测洗衣机产生异音的位置以及产生异音的原因，并根据产生异音的原因以及产生异音的位置提醒维修人员对检测不合格的待检测洗衣机进行维修。
本申请实施例提供了一种洗衣机异音检测方法，通过获取待检测洗衣机的目标声音数据以及目标振动数据；依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析；依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因。通过采用图像采集设备采集待检测洗衣机的设备标识信息，由异音检测算法平台自动匹配声音分析算法以及振动分析算法对目标声音数据以及目标振动数据进行数据分析，确定待检测洗衣机产生异音的位置及产生异音的原因，提高异音检测的准确率；并根据待检测洗衣机的机理模型指导维修人员对不合格的待检测洗衣机进行维修工作。本发明申请实施例依据声音数据分析结果、振动数据分析结果以及洗衣机的机理模型，确定异音位置及原因，提高异音检测的准确率。
实施例二
图2为本申请实施例二提供的一种洗衣机异音检测方法的流程图。本申请 实施例在上述实施例的基础上对前述实施例进行优化，本申请实施例可以与上述一个或者多个实施例中各个可选方案结合。如图2所示，本申请实施例中提供的洗衣机异音检测方法，可包括以下步骤：
S210、获取待检测洗衣机的设备标识信息，并根据所述设备标识信息配置所述待检测洗衣机的数据采集环境。
本实施例中，通过机器视觉***获取待检测洗衣机的设备标识信息，根据获取的设备标识信息配置待检测洗衣机的数据采集环境。判断当前配置的数据采集环境是否满足采集条件，判断标准包括采样频率、采样位数、位数以及环境噪声等参数，响应于当前配置的数据采集环境满足采集条件，采集待检测洗衣机数据；响应于当前配置的数据采集环境不满足采集条件，重新配置采集环境，直到满足采集条件。
可选的，采用图像采集设备获取洗衣机的条形码图像，将所述条形码图像传输至机器视觉***，并获取待检测洗衣机的设备标识信息；
根据获取的待检测洗衣机的设备标识信息，配置所述待检测洗衣机的数据采集环境，判断当前配置的数据采集环境是否满足采集条件；
响应于当前配置的数据采集环境满足采集条件，采集待检测洗衣机的目标声音数据以及目标振动数据；响应于当前配置的数据采集环境不满足采集条件，重新配置采集环境，直至满足所述采集条件；
其中，所述判断当前配置的数据采集环境是否满足采集条件，包括：判断待测洗衣机的采样频率、采样位数以及环境噪声是否满足预设的采集条件。
采用图像采集设备获取待检测洗衣机的设备标识信息，根据设备标识信息配置所述待检测洗衣机的数据采集环境，判断当前配置的数据采集环境是否满足采集条件。配置数据采集环境是由于待检测洗衣机的参数不同，根据待检测洗衣机不同的设备标识信息确定不同的采集环境。
S220、在所述数据采集环境下对待检测洗衣机的声音数据以及振动数据进行采集，得到待检测洗衣机的目标声音数据以及目标振动数据。
可选的，对待检测洗衣机中使用液压装置固定的洗衣机底座进行振动检测，获取待检测洗衣机的底座振动数据，并通过射频识别技术获取待检测洗衣机的底座型号信息；
将采集的底座振动数据与数据库里的历史底座振动数据进行比对，判断采集的底座振动数据是否与历史底座振动数据匹配；
响应于采集的底座振动数据与历史底座振动数据匹配，对所述底座振动数 据进行分析；
响应于采集的底座振动数据与历史底座振动数据不匹配，将所述底座振动数据消除，将历史底座振动数据作为新的底座振动数据以得到待检测洗衣机的目标振动数据。
本实施例中，在数据采集过程中，使用液压装置固定洗衣机底座，通过射频识别技术采集待检测洗衣机底座的型号。将采集的底座振动数据与数据库里的历史振动数据进行比对，判断采集的底座振动数据是否与历史底座振动数据匹配，响应于采集的底座振动数据与历史底座振动数据匹配，将底座振动数据作为目标振动数据进行分析；响应于采集的底座振动数据与历史底座振动数据匹配不匹配，将采集的底座振动数据作为噪声数据进行消除，并判断该噪声数据是否已消除，在该噪声数据已消除时对底座振动数据进行分析，在该噪声数据未消除时继续进行噪声数据的消除。
S230、依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析。
S240、依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因。
本申请实施例提供了一种洗衣机异音检测方法，通过机器视觉***获取待检测洗衣机的设备标识信息，根据获取的设备标识信息配置待检测洗衣机的数据采集环境；通过使用液压装置固定待检测洗衣机的底座，采用射频识别技术获取待检测洗衣机的设备标识信息，根据采集的底座振动数据信息跟历史底座振动数据的匹配度，剔除产生的振动噪声，消除振动噪声对异音检测的影响，提高了异音检测的准确率；依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析；依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因，及时指导维修人员对不合格的待检测洗衣机进行维修。
实施例三
图3为本申请实施例三提供的一种洗衣机异音检测方法的流程图。本申请实施例在上述实施例的基础上对前述实施例进行优化，本申请实施例可以与上述一个或者多个实施例中各个可选方案结合。如图3所示，本申请实施例中提供的洗衣机异音检测方法，可包括以下步骤：
S310、获取待检测洗衣机的目标声音数据以及目标振动数据。
S320、依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析。
本实施例中，根据待检测洗衣机的设备标识信息，异音检测算法平台自动匹配对应型号的声音分析算法与振动分析算法；声音分析算法与振动分析算法对采集到的声音数据和振动数据进行时频分析；声音分析算法对采集的声音数据进行色谱图的分析，生成异音检测结果，振动分析算法对采集的振动数据进行包络线分析，生成异音检测结果。
可选的，选取匹配的声音分析算法对所述目标声音数据进行色谱图分析，生成声音数据分析结果；
选取匹配的振动分析算法对所述目标振动数据进行包络线分析，生成振动数据分析结果。
本实施例中，异音通常具备一定的特征，利用数据驱动深度学习训练模型将采集的多种声音数据进行训练和特征提取，建立声纹数据库，所述声音数据包括摩擦音以及共振音等，所述声纹数据库包括色谱图。将采集到的声音数据色谱图与声纹数据库中的色谱图进行比对，得出是否存在异音，并且基于不同异音色谱图的特点，将异音频率划定在一定的范围，进而得出异音的种类。例如，待检测洗衣机轴承自身的噪声频率范围是2000Hz至5000Hz，若采集的轴承自身的目标声音数据的噪声频率不在2000Hz至5000Hz范围内，则待检测洗衣机的轴承存在异音。
目标振动数据包络线分析同样是比较正常包络线与异常包络线的信号特征，通过判断包络线的声压大小判断是否存在异音。例如，正常情况下包络线的声压大小为-0.3～0.3Pa，若目标振动数据的包络线的声压不在所述-0.3～0.3Pa的范围内，则确定所述目标振动数据存在异常，且所述异音为刮擦音。
S330、响应于声音数据分析结果与振动数据分析结果存在至少一项不合格，确定所述待检测洗衣机不合格。
本实施例中，对声音数据分析结果以及振动数据分析结果进行判断，将以下情况均视为待检测洗衣机不合格：声音数据分析结果不合格但振动数据分析结果合格，声音数据分析结果合格但振动数据分析结果不合格，声音数据分析结果和振动数据分析结果都不合格。
可选的，依据所述声音数据分析结果、振动数据分析结果以及待检测洗衣机的机理模型，确定待检测洗衣机产生异音的位置以及产生异音的原因；
其中，所述待检测洗衣机的机理模型包括洗衣机多个结构的精确分布；
将不合格的待检测洗衣机信息上传到制造执行***与数据库，进行不合格 的待检测洗衣机信息的存储；所述不合格的待检测洗衣机的信息至少包括：设备标识信息、数据采集环境信息、目标声音数据、目标振动数据、声音数据分析结果以及振动数据分析结果。
依据待检测洗衣机产生异音的位置和产生异音的原因对检测不合格的待检测洗衣机进行维修。
对于声音数据分析结果与振动数据分析结果中存在至少一项不合格的情况，则判断所述待检测洗衣机不合格，并将所述不合格的待检测洗衣机的设备标识信息、采集的目标振动数据、目标声音数据、声音数据分析结果以及振动数据分析结果等信息上传到制造执行***与数据库，进行数据信息的存储，并根据待检测洗衣机的机理模型确定异音存在的位置。
S340、响应于声音数据分析结果与振动数据分析结果都合格，确定所述待检测洗衣机合格。
对于声音数据分析结果与振动数据分析结果都合格的情况，则确定所述待检测洗衣机合格。并将合格的所述待检测洗衣机的信息上传至制造执行***与数据库，进行合格的所述待检测洗衣机的信息的存储；合格的所述待检测洗衣机的信息至少包括：设备标识信息、数据采集环境信息、目标声音数据、目标振动数据、声音数据分析结果以及振动数据分析结果。
本申请实施例提供了一种洗衣机异音检测方法，通过获取待检测洗衣机的目标声音数据以及目标振动数据；根据待检测洗衣机的设备标识信息，异音检测算法平台自动匹配对应型号的声音分析算法与振动分析算法；声音分析算法与振动分析算法对采集到的声音数据和振动数据进行时频分析；声音分析算法对采集的声音数据进行色谱图的分析，振动分析算法对采集的振动数据进行包络线分析，生成异音检测结果；响应于声音数据分析结果与振动数据分析结果都合格，确定所述待检测洗衣机合格；响应于声音数据分析结果与振动数据分析结果存在至少一项不合格，确定所述待检测洗衣机不合格，并依据所述声音数据分析结果、振动数据分析结果以及待检测洗衣机的机理模型，确定待检测洗衣机产生异音的位置以及产生异音的原因，及时提醒维修人员对检测不合格的待检测洗衣机进行维修。并将待检测洗衣机的设备标识信息、数据采集环境信息、目标声音数据、目标振动数据、声音数据分析结果以及振动数据分析结果等信息上传到制造执行***与数据库，进行数据信息的存储。
实施例四
图4是本申请实施例四提供的一种洗衣机异音检测装置的结构示意图，该装置包括：数据获取模块410、数据分析模块420和异音位置及原因确定模块 430。其中：
数据获取模块410，设置为获取待检测洗衣机的目标声音数据以及目标振动数据；
数据分析模块420，设置为依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析；
异音位置及原因确定模块430，设置为依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因。
在上述实施例的基础上，可选的，所述数据获取模块410设置为通过如下方式获取待检测洗衣机的目标声音数据以及目标振动数据：
获取待检测洗衣机的设备标识信息，并根据所述设备标识信息配置所述待检测洗衣机的数据采集环境；
在所述数据采集环境下对待检测洗衣机的声音数据以及振动数据进行采集，得到待检测洗衣机的目标声音数据以及目标振动数据。
在上述实施例的基础上，可选的，所述获取待检测洗衣机的设备标识信息，并根据所述设备标识信息配置所述待检测洗衣机的数据采集环境，包括：
采用图像采集设备获取洗衣机的条形码图像，将所述条形码图像传输至机器视觉***，并获取待检测洗衣机的设备标识信息；
根据获取的待检测洗衣机的设备标识信息，配置所述待检测洗衣机的数据采集环境，判断当前配置的数据采集环境是否满足采集条件；
响应于当前配置的数据采集环境满足采集条件，采集待检测洗衣机的目标声音数据以及目标振动数据；响应于当前配置的数据采集环境不满足采集条件，重新配置采集环境，直至满足所述采集条件；
其中，所述判断当前配置的数据采集环境是否满足采集条件，包括：判断待测洗衣机的采样频率、采样位数以及环境噪声是否满足预设的采集条件。
在上述实施例的基础上，可选的，所述数据获取模块420设置为通过如下方式依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析：
对待检测洗衣机中使用液压装置固定的洗衣机底座进行振动检测，获取洗衣机的底座振动数据，并通过射频识别技术获取待检测洗衣机的底座型号信息；
将采集的底座振动数据与数据库里的历史底座振动数据进行比对，判断采集的底座振动数据是否与历史底座振动数据匹配；
响应于采集的底座振动数据与历史底座振动数据匹配，对所述底座振动数据进行分析；
响应于采集的底座振动数据与历史底座振动数据不匹配，将所述底座振动数据消除，将历史底座振动数据作为新的底座振动数据以得到待检测洗衣机的目标振动数据。
在上述实施例的基础上，可选的，所述对所述目标声音数据以及目标振动数据进行分析，包括：
选取匹配的声音分析算法对所述目标声音数据进行色谱图分析，生成声音数据分析结果；
选取匹配的振动分析算法对所述目标振动数据进行包络线分析，生成振动数据分析结果。
在上述实施例的基础上，可选的，所述异音位置及原因确定模块430设置为通过如下方式依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因：
响应于声音数据分析结果与振动数据分析结果存在至少一项不合格，确定所述待检测洗衣机不合格；
依据所述声音数据分析结果、振动数据分析结果以及待检测洗衣机的机理模型，确定待检测洗衣机产生异音的位置以及产生异音的原因；
其中，所述待检测洗衣机的机理模型包括洗衣机多个结构的精确分布。
在上述实施例的基础上，可选的，所述响应于声音数据分析结果与振动数据分析结果存在至少一项不合格，确定所述待检测洗衣机不合格，包括：
将不合格的待检测洗衣机的信息上传到制造执行***与数据库，进行不合格的所述待检测洗衣机的信息的存储；所述不合格的待检测洗衣机的信息至少包括：设备标识信息、数据采集环境信息、目标声音数据、目标振动数据、声音数据分析结果以及振动数据分析结果；
依据待检测洗衣机产生异音的位置和产生异音的原因对检测不合格的待检测洗衣机进行维修。
在上述实施例的基础上，可选的，异音位置及原因确定模块430还设置为通过如下方式依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因：
响应于声音数据分析结果与振动数据分析结果都合格，确定所述待检测洗衣机合格；
将合格的所述待检测洗衣机的信息上传至制造执行***与数据库，进行合格的所述待检测洗衣机的信息的存储；合格的所述洗衣机的信息至少包括：设备标识信息、数据采集环境信息、目标声音数据、目标振动数据、声音数据分析结果以及振动数据分析结果；。
上述装置可执行本申请任意实施例所提供的洗衣机异音检测方法，具备执行该洗衣机异音检测方法相应的功能模块和有益效果。
实施例五
图5是本申请实施例五提供的一种电子设备的结构示意图。本申请实施例提供了一种电子设备，该电子设备中可集成本申请实施例提供的洗衣机异音检测的互动装置。如图5所示，本实施例提供了一种电子设备500，其包括：一个或多个处理器520；存储装置510，用于存储一个或多个程序，当所述一个或多个程序被所述一个或多个处理器520执行，使得所述一个或多个处理520实现本申请实施例所提供的洗衣机异音检测方法，该方法包括：
获取待检测洗衣机的目标声音数据以及目标振动数据；
依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析；
依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因。
本领域技术人员可以理解，处理器520还实现本申请任意实施例所提供的洗衣机异音检测方法的实施方案。
图5显示的电子设备500仅仅是一个示例
如图5所示，该电子设备500包括处理器520、存储装置510、输入装置540和输出装置540；电子设备中处理器520的数量可以是一个或多个，图5中以一个处理器520为例；电子设备中的处理器520、存储装置510、输入装置540和输出装置540可以通过总线或其他方式连接，图5中以通过总线550连接为例。
存储装置510作为一种计算机可读存储介质，可用于存储软件程序、计算机可执行程序以及模块单元，如本申请实施例中的洗衣机异音检测方法对应的程序指令。
存储装置510可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作***、至少一个功能所需的应用程序；存储数据区可存储根据终端的使用所创建的数据等。此外，存储装置510可以包括高速随机存取存储器，还 可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他非易失性固态存储器件。在一些实例中，存储装置510可包括相对于处理器520远程设置的存储器，这些远程存储器可以通过网络连接。上述网络的实例包括互联网、企业内部网、局域网、移动通信网及其组合。
输入装置540可用于接收输入的数字、字符信息或语音信息，以及产生与电子设备的用户设置以及功能控制有关的键信号输入。输出装置540可包括显示屏、扬声器等电子设备。
本申请实施例提供的电子设备，可以确定异音位置及异音原因，提高异音检测准确率。
实施例六
本申请实施例六还提供一种包含计算机可执行指令的存储介质，所述计算机可执行指令在由计算机处理器执行时用于执行一种洗衣机异音检测方法，该方法包括：
获取待检测洗衣机的目标声音数据以及目标振动数据；
依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析；
依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因。
可选的，该程序被处理器执行时还可以用于执行本申请任意实施例中所提供的洗衣机异音检测方法。
本申请实施例的计算机存储介质，可以采用一个或多个计算机可读的介质的任意组合。计算机可读介质可以是计算机可读信号介质或者计算机可读存储介质。计算机可读存储介质例如可以是电、磁、光、电磁、红外线、或半导体的***、装置或器件，或者任意以上的组合。计算机可读存储介质可以包括：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机存取存储器(Random Access Memory，RAM)、只读存储器(Read Only Memory，ROM)、可擦式可编程只读存储器(Erasable Programmable Read Only Memory，EPROM)、闪存、光纤、便携式紧凑磁盘只读存储器(Compact Disc Read-Only Memory，CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行***、装置或者器件使用或者与其结合使用。
计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式，包括：电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质，该计算机可读介质可以发送、传播或者传输用于由指令执行***、装置或者器件使用或者与其结合使用的程序。
计算机可读介质上包含的程序代码可以用任何适当的介质传输，包括但不限于：无线、电线、光缆、无线电频率(RadioFrequency，RF)等等，或者上述的任意合适的组合。
可以以一种或多种程序设计语言或其组合来编写用于执行本申请操作的计算机程序代码，所述程序设计语言包括面向对象的程序设计语言—诸如Java、Smalltalk、C++，还包括常规的过程式程序设计语言—诸如“C”语言或类似的程序设计语言。程序代码可以完全地在用户计算机上执行、部分地在用户计算机上执行、作为一个独立的软件包执行、部分在用户计算机上部分在远程计算机上执行、或者完全在远程计算机或服务器上执行。在涉及远程计算机的情形中，远程计算机可以通过任意种类的网络——包括局域网(Local Area Network，LAN)或广域网(Wide Area Network，WAN)——连接到用户计算机，或者，可以连接到外部计算机(例如利用因特网服务提供商来通过因特网连接)。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本申请的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不一定指的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任何的一个或多个实施例或示例中以合适的方式结合。

Claims (11)

  1. 一种洗衣机异音检测方法，所述方法包括：
    获取待检测洗衣机的目标声音数据以及目标振动数据；
    依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析；
    依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因。
  2. 根据权利要求1所述的方法，其中，所述获取待检测洗衣机的目标声音数据以及目标振动数据，包括：
    获取待检测洗衣机的设备标识信息，并根据所述设备标识信息配置所述待检测洗衣机的数据采集环境；
    在所述数据采集环境下对待检测洗衣机的声音数据以及振动数据进行采集，得到待检测洗衣机的目标声音数据以及目标振动数据。
  3. 根据权利要求2所述的方法，其中，所述获取待检测洗衣机的设备标识信息，并根据所述设备标识信息配置所述待检测洗衣机的数据采集环境，包括：
    采用图像采集设备获取洗衣机的条形码图像，将所述条形码图像传输至机器视觉***，并获取待检测洗衣机的设备标识信息；
    根据获取的待检测洗衣机的设备标识信息，配置所述待检测洗衣机的数据采集环境，判断当前配置的数据采集环境是否满足采集条件；
    响应于当前配置的数据采集环境满足采集条件，采集待检测洗衣机的目标声音数据以及目标振动数据；响应于当前配置的数据采集环境不满足采集条件，重新配置采集环境，直至满足所述采集条件；
    其中，所述判断当前配置的数据采集环境是否满足采集条件，包括：判断待测洗衣机的采样频率、采样位数以及环境噪声是否满足预设的采集条件。
  4. 根据权利要求1所述的方法，其中，所述获取待检测洗衣机的目标振动数据，包括：
    对待检测洗衣机中使用液压装置固定的洗衣机底座进行振动检测，获取待检测洗衣机的底座振动数据，并通过射频识别技术获取待检测洗衣机的底座型号信息；
    将采集的底座振动数据与数据库里的历史底座振动数据进行比对，判断采集的底座振动数据是否与历史底座振动数据匹配；
    响应于采集的底座振动数据与历史底座振动数据匹配，对所述底座振动数 据进行分析；
    响应于采集的底座振动数据与历史底座振动数据不匹配，将所述底座振动数据消除，将历史底座振动数据作为新的底座振动数据以得到待检测洗衣机的目标振动数据。
  5. 根据权利要求1所述的方法，其中，所述对所述目标声音数据以及目标振动数据进行分析，包括：
    选取匹配的声音分析算法对所述目标声音数据进行色谱图分析，生成声音数据分析结果；
    选取匹配的振动分析算法对所述目标振动数据进行包络线分析，生成振动数据分析结果。
  6. 根据权利要求1所述的方法，其中，所述依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因，包括：
    响应于声音数据分析结果与振动数据分析结果存在至少一项不合格，确定所述待检测洗衣机不合格；
    依据所述声音数据分析结果、振动数据分析结果以及待检测洗衣机的机理模型，确定待检测洗衣机产生异音的位置以及产生异音的原因；
    其中，所述待检测洗衣机的机理模型包括洗衣机多个结构的精确分布。
  7. 根据权利要求6所述的方法，所述响应于声音数据分析结果与振动数据分析结果存在至少一项不合格，确定所述待检测洗衣机不合格之后，所述方法还包括：
    将不合格的所述待检测洗衣机的信息上传到制造执行***与数据库，进行不合格的所述待检测洗衣机的信息的存储；不合格的所述待检测洗衣机的信息至少包括：设备标识信息、数据采集环境信息、目标声音数据、目标振动数据、声音数据分析结果以及振动数据分析结果；
    依据待检测洗衣机产生异音的位置和产生异音的原因，对不合格的所述待检测洗衣机进行维修。
  8. 根据权利要求1所述的方法，其中，所述依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因，包括：
    响应于声音数据分析结果与振动数据分析结果都合格，确定所述待检测洗衣机合格；
    将合格的所述待检测洗衣机的信息上传至制造执行***与数据库，进行合格的所述待检测洗衣机的信息的存储；合格的所述待检测洗衣机的信息至少包 括：设备标识信息、数据采集环境信息、目标声音数据、目标振动数据、声音数据分析结果以及振动数据分析结果等。
  9. 一种洗衣机异音检测装置，包括：
    数据获取模块，设置为获取待检测洗衣机的目标声音数据以及目标振动数据；
    数据分析模块，设置为依据待检测洗衣机的设备标识信息，选取匹配的声音分析算法以及振动分析算法，以对所述目标声音数据以及目标振动数据进行分析；
    异音位置及原因确定模块，设置为依据声音数据分析结果以及振动数据分析结果，确定待检测洗衣机产生异音的位置及产生异音的原因。
  10. 一种电子设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现如权利要求1-8中任一所述的洗衣机异音检测方法。
  11. 一种包含计算机可执行指令的存储介质，所述计算机可执行指令在由计算机处理器执行时用于执行如权利要求1-8中任一所述的洗衣机异音检测方法。
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