Abnormal sound detection method for dish washing machine

Abstract

The abnormal sound detection method comprises the steps that the dish-washing machine starts to operate, sound wave signals in the operation process of the dish-washing machine are collected, whether the sound wave signals are matched with standard sound wave signals or not is judged, and if yes, the sound wave signals are abnormal sound wave signals; determining the position of abnormal sound at least according to the time delay of the sound wave signal; the sound wave signals at least comprise one standard sound wave signal, performing absolute value operation on the difference value between the characteristic value of the detected sound wave signal and the characteristic value of the standard sound wave signal, and judging whether the characteristic value is matched or not; feeding back the abnormal sound solving strategy corresponding to the abnormal sound generation position of the dishwasher and the standard sound wave signal to the mobile terminal; or the dishwasher display screen displays the abnormal sound solving strategy; the abnormal state of the dish-washing machine can be found and solved in time by detecting the sound wave signal in the operation process of the dish-washing machine, normal operation of equipment is guaranteed, and maintenance efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of household appliances, and more particularly, to a method for detecting abnormal noise of a dishwasher. Background Art

[0002] During the operation of existing dishwashers, different types of abnormalities occur at each stage. Taking a dishwasher as an example, during the operation of the dishwasher, E4 will be automatically displayed on the display screen, accompanied by a beeping alarm sound. In this case, generally, the water pipe is not opened. After opening the water pipe and restarting the dishwasher operation program, the problem of water inlet alarm can be perfectly and quickly solved. However, there is no corresponding fast and efficient solution for abnormal noise during the operation of the dishwasher.

[0003] However, in the above solution, the dishwasher is fully enclosed during operation, making it difficult to locate the source of the abnormal noise; the dishwasher shelf has multiple layers, different operating modes of the spray arms, and complex tableware placement, making it difficult to accurately find the location of the abnormal noise; there is no collection of the components that generate abnormal noise during the operation of the dishwasher, and the characteristic frequencies of the abnormal noise components are not statistically analyzed, making it impossible to quickly identify. When abnormal noise occurs during the operation of the dishwasher, the traditional solution is to repeatedly run the dishwasher during the time period when the abnormal noise occurs to confirm the general location where the abnormal noise is generated; frequently replace the individual components initially determined to generate abnormal noise to further narrow down the range of components that generate abnormal noise; some engineers can finally find the components that generate abnormal noise using the traditional solution and solve the problem of abnormal noise in the dishwasher, but this method of solving the abnormal noise in the dishwasher is inefficient, cumbersome, and lacks intelligence.

[0004] To address the above problems, a method for detecting abnormal noise of a dishwasher is designed. By detecting the sound wave signal to locate the source of the abnormal noise in the dishwasher, it can efficiently and conveniently solve the problem of abnormal noise generated during the operation of the dishwasher, thereby enhancing the engineer's problem-solving ability, improving the competitiveness of the product, and bringing the best living experience to users. Providing a solution strategy based on the characteristic values of the sound wave signal can promptly detect the abnormal noise generated by the dishwasher, enabling quick action to solve the problem and avoiding further damage to the equipment or affecting production. Summary of the Invention

[0005] The object of the present invention is to overcome the deficiencies of the prior art and provide a method for detecting abnormal noise of a dishwasher, which can promptly detect the abnormal state of the dishwasher by detecting the sound wave signal during the operation of the dishwasher and solve it in a timely manner, ensuring the normal operation of the equipment and improving the maintenance efficiency.

[0006] To solve the above technical problems, the basic concept of the technical solution adopted by the present invention is:

[0007] A method for detecting abnormal noises in a dishwasher. When the dishwasher starts to run, sound wave signals during the operation of the dishwasher are collected, and it is determined whether they match the standard sound wave signals. If they match, they are abnormal sound wave signals; the position of the abnormal noise is determined at least according to the time delay of the sound wave signals.

[0008] Further, it at least includes one standard sound wave signal. An absolute value operation is performed on the difference between the characteristic values of the detected sound wave signals and the characteristic values of the standard sound wave signals to determine whether they match.

[0009] Further, the position of the abnormal noise generated by the dishwasher and the corresponding abnormal noise solution strategy of the standard sound wave signal are fed back to the mobile terminal; alternatively, the abnormal noise solution strategy is displayed on the display screen of the dishwasher.

[0010] Further, when the sound wave signals collected during the operation of the dishwasher do not match the standard sound wave signals, it is determined whether they are abnormal sound wave signals according to the operating state of the dishwasher.

[0011] Further, determining according to the operating state of the dishwasher at least includes that when the collected sound wave signals are the sound wave signals during the interruption of the dishwasher operation, they are determined as abnormal sound wave signals.

[0012] And the abnormal sound wave signals are added as new standard sound wave signals.

[0013] Further, a preset time period is set, and the sound wave signals within each time period are collected and matched with the standard sound wave signals.

[0014] If the door of the dishwasher is opened during operation, after closing the door, the sound wave signals during a certain period of the dishwasher operation are monitored again.

[0015] Further, the solution strategy at least includes rearranging the tableware in the dishwasher and checking whether there are foreign objects in the dishwasher cavity.

[0016] Further, the steps of the method for detecting abnormal noises in the dishwasher include:

[0017] S1: The dishwasher starts to run and collects the sound wave signals during the operation of the dishwasher;

[0018] S2: Determine whether it matches the standard sound wave signals;

[0019] S3: If it matches, they are abnormal sound wave signals;

[0020] If it does not match, it is determined whether it is an abnormal sound wave signal according to the operating state of the dishwasher;

[0021] S4: Locate the position of the abnormal noise in the dishwasher according to the characteristics of the abnormal sound wave signals of the dishwasher;

[0022] S5: Feedback on the position corresponding to the abnormal sound generated by the dishwasher and the solution strategy corresponding to the standard sound wave signal.

[0023] An abnormal sound detection method for a dishwasher, the dishwasher includes a control system for abnormal sound detection,

[0024] Abnormal sound detection module: Detect the sound wave signal during the operation of the dishwasher;

[0025] Abnormal sound feedback module: Feedback at least the position information of the abnormal sound wave signal and the solution to the abnormal sound to the mobile terminal;

[0026] Database module: The database module includes a standard sound wave signal database formed by at least one standard sound wave signal and its corresponding solution strategy. When the collected sound wave signal does not match the standard sound wave signal, add the sound wave signal to the standard sound wave signal database.

[0027] Furthermore, according to the abnormal sound detection module, locate the position of the abnormal sound at least through the time delay, intensity and frequency change of the sound wave signal; the abnormal sound detection module is associated with the cloud platform or the mobile terminal, and the detected information is fed back to the cloud platform or the mobile terminal in real time.

[0028] After adopting the above technical solutions, the present invention has the following beneficial effects compared with the prior art:

[0029] 1. It can efficiently and conveniently solve the abnormal sound problem generated during the operation of the dishwasher, thereby improving the engineer's problem-solving ability, enhancing the competitiveness of the product, and bringing the best life experience to users. By monitoring the change of the sound wave signal, the abnormal sound generated by the dishwasher can be detected in time, so as to quickly take action to solve the problem and avoid further damage to the equipment or affecting production.

[0030] 2. Store the abnormal sound wave signal data in the database and perform digital signal processing, which can accumulate a large amount of abnormal sound data, and use data analysis technology to analyze the cause of the abnormal sound, providing a strong basis for formulating solutions.

[0031] 3. By analyzing the abnormal sound wave signal data in the database, an intelligent maintenance system can be established to realize automatic equipment fault diagnosis and solution formulation, improving the efficiency and accuracy of equipment maintenance.

[0032] The following further describes the specific implementation manners of the present invention in detail with reference to the accompanying drawings. Description of the Drawings

[0033] The accompanying drawings, as a part of the present invention, are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention, but do not constitute an improper limitation to the present invention. Obviously, the accompanying drawings in the following description are only some embodiments. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the accompanying drawings:

[0034] Figure 1 is a flowchart of the abnormal sound detection method of the present invention.

[0035] It should be noted that these accompanying drawings and text descriptions are not intended to limit the scope of the concept of the present invention in any way, but to illustrate the concept of the present invention to those skilled in the art by referring to specific embodiments. Detailed implementation manners

[0036] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention.

[0037] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0038] In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0039] An abnormal sound detection method for a dishwasher. When the dishwasher starts to run, acoustic signals during the operation of the dishwasher are collected, and it is determined whether they match the standard acoustic signals. If they match, they are abnormal sound acoustic signals; the position of the abnormal sound is determined at least according to the time delay of the acoustic signals.

[0040] Based on the acoustic signals when the dishwasher previously had a fault or during abnormal operation, the abnormal sound acoustic signals are stored, and at least according to the analysis of the waveform characteristics of the acoustic waves, a solution strategy is formulated. The solution strategy and the abnormal sound acoustic signals are stored in the database as the standard acoustic signals.

[0041] The abnormal sound wave signal is at least a sound wave signal generated due to incorrect placement of tableware during the operation of the dishwasher, which may cause the dishwasher to malfunction.

[0042] When a sound wave signal matching the standard sound wave signal is collected during the operation of the dishwasher, it is determined that the dishwasher has generated an abnormal sound wave signal, and a solution strategy for the abnormal sound wave signal can be timely feedback.

[0043] It is also possible to determine at least the location where the dishwasher makes abnormal noises based on the intensity, frequency, and wavelength information of the sound wave signal.

[0044] Extract the characteristic values of the sound wave signal. The characteristic values of the sound wave signal at least include the wavelength, frequency, and amplitude of the sound wave signal. The characteristic values can be extracted by digital signal processing technology.

[0045] It includes at least one standard sound wave signal, and an absolute value operation is performed on the difference between the characteristic values of the detected sound wave signal and the characteristic values of the standard sound wave signal to determine whether they match.

[0046] Provide another method. For example, use machine learning or pattern recognition methods to input the characteristic values of the sound wave signal into a trained model, and judge whether the sound wave signal matches the standard sound wave signal through the classification or matching results of the model. This is convenient for more accurately judging the matching situation of the sound wave signal, especially in complex environments or when identifying multiple sound wave signals.

[0047] In addition, other sensor data can be combined with the sound wave signal for analysis, such as acceleration sensors, temperature sensors, etc. Multiple sensor data are integrated to judge the operating state and abnormal conditions of the dishwasher, so as to improve the accuracy and reliability of diagnosis.

[0048] Feedback the location where the dishwasher makes abnormal noises and the corresponding solution strategy for the abnormal sound wave signal corresponding to the standard sound wave signal to the mobile terminal; or, the solution strategy for the abnormal sound is displayed on the dishwasher display screen.

[0049] The abnormal sound feedback module in the abnormal sound detection system is used to realize real-time feedback of the sound wave signal during the operation of the dishwasher and the corresponding solution strategy when abnormal noises occur.

[0050] For example, data analysis and feature extraction: Use the digital signal processing technology of the dishwasher control system to analyze and extract the features of the collected sound wave signal data, and extract the characteristic values of the sound wave signal, such as wavelength, frequency, amplitude, etc. Data processing and matching: Match the extracted characteristic values of the sound wave signal with the characteristic values of the pre-set standard sound wave signal. Determine whether abnormal noises occur and the location of the abnormal noises by comparing the absolute value of the difference.

[0051] Feedback to the mobile terminal: Once the abnormal noise generated by the dishwasher is detected, the location information of the abnormal noise and the corresponding solution strategy are uploaded to the cloud platform or sent to the user's mobile terminal. Data transmission can be achieved through Wi-Fi, Bluetooth, or other communication methods.

[0052] Display feedback: At the same time, the location and solution strategy of the abnormal noise can also be directly displayed on the display screen of the dishwasher for the user to view and reference.

[0053] The dishwasher is communicatively connected to the cloud platform or the mobile terminal.

[0054] In this embodiment, the eigenvalue of the acoustic signal further includes at least the frequency eigenvalue: The frequency eigenvalue of the acoustic signal describes the pitch of the sound, including the fundamental frequency and the resonance peak frequency in the sound, etc.

[0055] Amplitude eigenvalue: The amplitude eigenvalue of the acoustic signal describes the loudness of the sound, that is, the intensity of the sound.

[0056] Time-domain eigenvalue: The time-domain eigenvalue describes the characteristics of the acoustic signal on the time axis, such as the duration and fluctuation of the sound.

[0057] Spectral eigenvalue: The spectral eigenvalue of the acoustic signal describes the spectral characteristics of the sound, which can include the spectral shape of the sound, the peak value in the spectrum, the spectral flatness, etc.

[0058] These eigenvalues can be used for the analysis, recognition, and processing of sound signals.

[0059] When the acoustic signal collected during the operation of the dishwasher does not match the standard acoustic signal, it is judged whether it is an abnormal sound acoustic signal according to the operating state of the dishwasher.

[0060] When they do not match, it may be due to the generation of a new abnormal noise, which is different from the existing abnormal sound acoustic signals in the database. It is necessary to analyze the acoustic signal and add the corresponding solution strategy, and add it to the standard acoustic signal database.

[0061] Judging according to the operating state of the dishwasher includes at least that when the collected acoustic signal is the acoustic signal during the interruption of the dishwasher operation, it is judged as an abnormal sound acoustic signal.

[0062] Add it to the existing standard acoustic signal at least according to the time delay of the abnormal sound acoustic signal.

[0063] Compare the collected acoustic signal with the standard acoustic signal. If a time delay or other characteristics are found, it is judged as an abnormal sound acoustic signal.

[0064] Analyze the time delay of the abnormal sound acoustic signal to determine the specific value of the time delay.

[0065] Once the abnormal sound wave signal is identified, upload the location information of the abnormal sound and the corresponding solution strategy to the cloud platform or send it to the mobile terminal.

[0066] Preset a time period, collect the sound wave signals within each time period, and match them with the standard sound wave signals;

[0067] The preset time period can be at least within 2 seconds;

[0068] If the door of the dishwasher is opened during operation, after closing the door, monitor the sound wave signals of the dishwasher during operation for a period of time again. This method can achieve real-time monitoring of the operation status of the dishwasher. If the door of the dishwasher is opened during operation and the sound wave signals of the dishwasher during operation are monitored again, it can help ensure the continuity and accuracy of monitoring, and can promptly detect abnormal situations that occur during the operation of the dishwasher, such as door opening, water pressure change, etc., which is beneficial to improving the operation efficiency and cleaning effect of the dishwasher. At the same time, it can also help users promptly discover problems during the operation of the dishwasher and take timely measures to solve them, improving the user experience.

[0069] For example, after the tableware is placed, monitor the sound wave signals of the dishwasher during operation for a period of time, preset a sound wave range, when the sound wave range exceeds the preset value, the dishwasher makes an abnormal sound, and at the same time the dishwasher makes an abnormal sound; detecting the sound wave signals during the operation of the dishwasher can promptly discover the abnormal state of the dishwasher and solve it in time, ensuring the normal operation of the equipment and improving the maintenance efficiency.

[0070] By analyzing the characteristic values of the sound wave signals emitted by the dishwasher, the operation status of the dishwasher can be monitored in real time, and abnormal situations can be promptly discovered.

[0071] As Figure 1 shown, the steps to implement this abnormal sound detection method at least include, S1: The dishwasher starts to operate, and collect the sound wave signals during the operation of the dishwasher;

[0072] S2: Determine whether it matches the standard sound wave signal;

[0073] S3: If it matches, it is an abnormal sound wave signal;

[0074] If it does not match, determine whether it is an abnormal sound wave signal according to the operation status of the dishwasher;

[0075] S4: Locate the position of the abnormal sound of the dishwasher according to the characteristics of the abnormal sound wave signal of the dishwasher;

[0076] S5: Feedback the position where the dishwasher makes an abnormal sound and the corresponding solution strategy of the standard sound wave signal.

[0077] The operation status of the dishwasher includes that the dishwasher is paused during the washing process, usually paused manually by the user or automatically paused due to a fault.

[0078] The dishwasher has completed all washing, rinsing, and drying operations, and you can open the dishwasher to take out the washed tableware.

[0079] The dishwasher has a malfunction and cannot perform the washing operation properly.

[0080] These states can be monitored and judged through the control panel or sensors of the dishwasher, or the operating status can be received through the cloud platform. In different stages and states, the dishwasher may generate different sound wave signals.

[0081] The dishwasher includes a control system for abnormal sound detection, including an abnormal sound detection module: detecting the sound wave signals during the operation of the dishwasher;

[0082] An abnormal sound feedback module: at least feedback the position information of the abnormal sound wave signal and the solution to the abnormal sound to the mobile terminal;

[0083] A database module: The database module includes a standard sound wave signal database formed by at least one standard sound wave signal and its corresponding solution strategy. When the collected sound wave signal does not match the standard sound wave signal, the sound wave signal is added to the standard sound wave signal database.

[0084] The database stores standard sound wave signals, their characteristic values, and corresponding solution strategies; the standard sound wave signal is defined as the sound wave signal generated during the operation of the dishwasher due to some malfunctions or other reasons that cause the dishwasher to malfunction.

[0085] The system can judge the cause of the abnormality of the dishwasher and prompt the user about the problems and solution strategies found through the mobile terminal, reducing the uncertainty and confusion of the user about the malfunction. The user can quickly find the cause of the malfunction and perform repairs according to the solution strategies provided by the mobile terminal, reducing the inconvenience caused by the malfunction. Through real-time monitoring and automatic diagnosis, the repair efficiency of the dishwasher can be improved, and the downtime caused by the malfunction can be reduced. The user can conveniently obtain the operating status and malfunction information of the dishwasher through the mobile terminal, improving the user experience of using the dishwasher.

[0086] In this embodiment, another method is provided. If the sound wave signal does not match the standard sound wave signal, after the operation of the dishwasher ends, the complete sound wave signal is extracted, and it is judged whether there is any abnormal operation information during the operation of the dishwasher; if there is, digital signal processing is performed on the sound wave signal, and at least characteristic values are formed according to the wavelength, frequency, and amplitude of the sound wave signal,

[0087] Analyze the similarity or correlation with the standard sound wave signal to form at least one solution strategy.

[0088] Upload the eigenvalue of the newly added acoustic signal and the corresponding solution strategy to the cloud platform; select the required solution through the mobile terminal or the dishwasher display screen and add it to the existing solution.

[0089] The solution strategy at least includes rearranging the tableware in the dishwasher, checking whether there are foreign objects in the dishwasher cavity, and checking the components of the dishwasher. The solution strategy also at least includes rearranging the tableware in the dishwasher, checking whether there are foreign objects in the dishwasher cavity, and checking the components of the dishwasher. If the operation result of the dishwasher is normal, it is determined that there is no abnormal sound and the tableware is placed correctly.

[0090] This method can realize the intelligent monitoring and fault diagnosis of the operation state of the dishwasher, improve the automation and intelligence level of the dishwasher, and improve the user experience. Through the real-time monitoring of the acoustic signal and the matching with the standard acoustic signal, the real-time monitoring and abnormal diagnosis of the operation state of the dishwasher can be realized, and the timeliness and accuracy of fault diagnosis are improved.

[0091] By performing digital signal processing on the eigenvalue of the abnormal acoustic signal to form the corresponding solution strategy and uploading it to the cloud platform, users can select the required solution through the mobile terminal or the dishwasher display screen, improving the intelligence and convenience of fault handling.

[0092] Improve the user experience: Users can obtain solutions for different faults in an intelligent way, simplify the fault handling process, and improve the user experience.

[0093] Improve the operation efficiency and reliability of the dishwasher: Through real-time monitoring and intelligent diagnosis, timely discover and solve the abnormal conditions of the dishwasher, which can improve the operation efficiency and reliability of the dishwasher, and ensure the cleaning effect and service life of the dishwasher.

[0094] The database stores the eigenvalue of the abnormal sound acoustic signal, the corresponding position where the dishwasher fails, and the corresponding solution strategy. The database stores a large number of pre-stored acoustic signals that may fail, the abnormal sound positions of the dishwasher, and the corresponding solution strategies.

[0095] For example, when an abnormal sound occurs, check whether there is the same eigenvalue among the existing acoustic signal eigenvalues according to the eigenvalue.

[0096] If the door of the dishwasher is opened halfway during operation, after closing the door, re-monitor the acoustic signal of the dishwasher for a period of time.

[0097] For example, opening the door of the dishwasher midway may be because additional tableware needs to be added, or tableware needs to be taken out, or the door was closed after adjusting the placement of the tableware inside the dishwasher after the previous abnormal noise occurred; after adding or removing tableware and closing the door midway, the acoustic signal needs to be monitored again. If the acoustic signal changes, corresponding adjustments need to be made according to the solution.

[0098] If the tub door is closed after adjusting the placement of the tableware inside the dishwasher after the previous abnormal noise occurred, then monitoring the acoustic signal is to detect whether it has been resolved and ensure the normal operation of the dishwasher.

[0099] Or, when the dishwasher is resolved through the provided solution, the stop of the abnormal noise indicates that the problem has been solved, or when it is resolved, the dishwasher is prompted to resume normal operation through a beep.

[0100] In this embodiment, it is possible to set the mobile terminal to prompt the abnormal noise information of the dishwasher, including adjusting the placement of the tableware inside the dishwasher, detecting whether there are foreign objects in the dishwasher cavity, or optimizing the dishwasher components.

[0101] For example, the possible problems of the dishwasher and the reasons for modification include,

[0102] Adjusting the placement of tableware: According to the analysis of the acoustic signal of the dishwasher, there may be a situation where the placement of the tableware is incorrect. At this time, the user is prompted to readjust the placement of the tableware to ensure that the water flow can fully cover all the surfaces of the tableware, thereby improving the washing effect.

[0103] Detecting whether there are foreign objects in the dishwasher cavity: There may be a situation where there are foreign objects in the dishwasher cavity. At this time, the user is prompted to check whether there are foreign objects in the dishwasher cavity, such as remaining food debris, tableware falling, etc., to avoid affecting the normal operation of the dishwasher or damaging the dishwasher components.

[0104] Optimizing the dishwasher components: Based on the data from the dishwasher's self-diagnosis or user feedback, the system may prompt the user to optimize the dishwasher components, such as replacing the detergent, cleaning the nozzle, or checking whether the water pipe is blocked, etc., to improve the operating efficiency and cleaning effect of the dishwasher.

[0105] The abnormal acoustic signal information detected by the abnormal noise detection module can be used to locate the position where the dishwasher makes an abnormal noise. It can be achieved by using acoustic imaging or acoustic positioning technology, and by analyzing the characteristics such as the propagation path of the sound wave and the intensity of the signal to determine the position of the abnormal noise. Once the position is determined, this information can be received by the abnormal noise feedback module and a solution strategy can be provided.

[0106] In this embodiment, abnormal noises in the dishwasher may come from multiple components or other reasons, including the pump component: the water pump of the dishwasher may generate abnormal noises due to blockage, wear or damage. When the dishwasher is running, it will generate specific acoustic signals, including the sound of the water pump running, the sound of the washer running, the sound of the dish basket rotating, etc. By analyzing these acoustic signals, it can be determined whether the dishwasher is working properly.

[0107] For example, if the dishwasher produces abnormal noises during operation, it may mean that there is a problem with the water pump or the washer; or if the dish basket does not rotate, it may also mean that there is a problem with the dishwasher. Therefore, by analyzing the acoustic signals, the operating state of the dishwasher can be judged, problems can be discovered and solved in time, and the normal operation of the dishwasher can be ensured.

[0108] Motor: The motor of the dishwasher may generate abnormal noises due to wear or other problems.

[0109] Water valve: The water valve may generate abnormal noises when opening or closing.

[0110] Fan or air duct: Some dishwashers may be equipped with a fan, and the fan or its related air duct may generate abnormal noises.

[0111] Other components: For example, components such as filters and nozzles may also generate abnormal noises due to blockage or damage.

[0112] Feature extraction: First, extract representative feature values from the system or data, which may involve technologies such as signal processing, image processing, and data mining.

[0113] Feature matching: Match the extracted feature values with known patterns or features in the database to determine the similarity or relevance between them.

[0114] Decision making: According to the results of the feature value matching, make corresponding decisions or actions, which may involve tasks such as classification, recognition, diagnosis, and prediction.

[0115] Feedback and optimization: Provide feedback and optimization to the matching and decision-making processes according to the actual results to continuously improve the matching algorithm and decision-making model.

[0116] In this embodiment, an abnormal noise enterprise cloud can be set up to collect all the abnormal noises generated during the operation of the dishwasher platform, classify and summarize them according to the module abnormal noises for engineers to query, and at the same time formulate corresponding solutions for the module abnormal noises to improve the speed of problem-solving; the abnormal noise enterprise cloud is associated with the user APP, and the abnormal noise dynamics of the two are updated simultaneously.

[0117] For example, for the abnormal noise user APP, after the user or engineer downloads and registers the APP, it is associated with the abnormal noise detection module. Once abnormal noise occurs during the operation of the prototype, the abnormal noise detection module will feed back the abnormal noise information to the APP, and the user and engineer will receive the relevant abnormal noise information in a timely manner. At the same time, big data will be fed back to the enterprise abnormal noise cloud in the background. The engineer will conduct targeted on-site solutions based on the feedback information, reducing troubleshooting and saving a lot of time, demonstrating the professionalism of the engineer and winning the trust of the user.

[0118] The abnormal noise detection module is very sensitive and can receive weak changes in the abnormal noise wave signal. It determines the location of the abnormal noise by analyzing information such as the time delay, intensity, and frequency change of the abnormal noise wave signal. First, all abnormal noise waves are collected and edited into the detection module, and then the abnormal noise waves are used for positioning. When the abnormal noise wave signal radiates around, the detection module receives these abnormal noise wave signals to determine the location, shape, and distance of the abnormal noise.

[0119] The abnormal noise feedback module feeds back the information of the detection module to the enterprise abnormal noise cloud and the user APP. The enterprise cloud and the user APP give corresponding specific solutions to the abnormal noise in the form of information. On the one hand, it is convenient to sort out and summarize the abnormal noise problems, and on the other hand, it is convenient to solve the abnormal noise problems.

[0120] In this embodiment, for example, the abnormal noise waves can be classified and summarized. The abnormal noise generated by the spray arm at least includes the A sound wave generated when the spray arm hits the front of the tableware, the B sound wave generated when the spray arm hits the back of the tableware, the C sound wave generated when the spray arm hits the left side of the tableware, and the D sound wave generated when the spray arm hits the right side of the tableware. At the position where the spray arm hits the tableware, the detection module detects the types of abnormal noise waves, and the solution method is automatically sent to the user APP or other mobile terminals. The solution methods include: for the A-type sound wave, the solution is to reposition the tableware in front of the middle shelf; for the B-type sound wave, the solution is to reposition the tableware behind the middle shelf; for the C-type sound wave, the solution is to reposition the tableware on the left side of the middle shelf; for the D-type sound wave, the solution is to reposition the tableware on the right side of the middle shelf.

[0121] For example, the abnormal noise generated by the washing pump at least includes the AA sound wave generated by large axial runout, and the solution is to optimize the axial dimension; the BB sound wave generated by large radial runout, and the solution is to optimize the radial dimension; the CC sound wave generated by loose installation, and the solution is to reassemble; the DD sound wave generated by small water inflow, and the solution is to increase the water inflow. The abnormal noise detection module can receive the change of the abnormal noise wave signal and determine the location of the abnormal noise by analyzing information such as the time delay, intensity, and frequency change of the abnormal noise wave signal.

[0122] The above are only the preferred embodiments of the present invention, and there is no limitation to the present invention in any form. Although the present invention has been disclosed as above with the preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art of the present invention can make some changes or modifications to equivalent embodiments with equivalent changes by using the technical content prompted above within the scope of the technical solution of the present invention. The implementation schemes in the above embodiments can be further combined or replaced. However, as long as it does not depart from the technical content of the present invention, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention still fall within the scope of the present invention's solution.

Claims

1. A method for detecting abnormal noise of a dishwasher, characterized in that The dishwasher starts to run, collects the acoustic signals during the operation of the dishwasher, and determines whether they match the standard acoustic signals. If they match, they are abnormal acoustic signals; the position of the abnormal sound is determined at least according to the time delay of the acoustic signals.

2. The abnormal noise detection method of a dishwasher according to claim 1, wherein It includes at least one standard acoustic signal, performs an absolute value operation on the difference between the characteristic values of the detected acoustic signals and the characteristic values of the standard acoustic signals, and determines whether they match.

3. The abnormal noise detection method of a dishwasher according to claim 2, wherein Feed back the position of the abnormal sound generated by the dishwasher and the corresponding abnormal sound solution strategy of the standard acoustic signal to the mobile terminal; or, the dishwasher display screen shows the abnormal sound solution strategy.

4. A method for detecting abnormal noise of a dishwasher according to claim 3, characterized in that, When the acoustic signals collected during the operation of the dishwasher do not match the standard acoustic signals, determine whether they are abnormal acoustic signals according to the operating state of the dishwasher.

5. The abnormal sound detection method of a dishwasher according to claim 4, wherein, Determining according to the operating state of the dishwasher at least includes that when the collected acoustic signal is the acoustic signal during the interruption of the dishwasher operation, it is determined as an abnormal acoustic signal. And add the abnormal acoustic signal as a new standard acoustic signal.

6. The abnormal sound detection method of a dishwasher according to claim 5, characterized in that, Preset a time period, collect the acoustic signals within each time period, and match them with the standard acoustic signals. If the door of the dishwasher is opened halfway during operation, after closing the door, monitor the acoustic signals of the dishwasher for a period of time again.

7. A method for detecting abnormal noise of a dishwasher according to claim 6, characterized in that, The solution strategy at least includes rearranging the tableware in the dishwasher and checking whether there are foreign objects in the dishwasher cavity.

8. A method for detecting abnormal noise of a dishwasher according to claim 7, characterized in that, The steps of the method for detecting abnormal sounds in a dishwasher include: S1: The dishwasher starts to run and collects the acoustic signals during the operation of the dishwasher; S2: Determine whether it matches the standard acoustic signals; S3: If it matches, it is an abnormal acoustic signal; If it does not match, determine whether it is an abnormal acoustic signal according to the operating state of the dishwasher; S4: Locate the position of the abnormal sound in the dishwasher according to the characteristics of the abnormal acoustic signals of the dishwasher; S5: Feed back the position of the abnormal sound generated by the dishwasher and the corresponding solution strategy of the standard acoustic signal.

9. A method for detecting abnormal sounds in a dishwasher according to any one of claims 1-8, the dishwasher includes a control system for abnormal sound detection, characterized in that Abnormal sound detection module: Detect the acoustic signals during the operation of the dishwasher; Abnormal sound feedback module: Feed back at least the position information of the abnormal acoustic signal and the abnormal sound solution to the mobile terminal; Database module: The database module includes a standard acoustic signal database formed by at least one standard acoustic signal and its corresponding solution strategy. When the collected acoustic signal does not match the standard acoustic signal, add the acoustic signal to the standard acoustic signal database.

10. The abnormal noise detection control system according to claim 9, wherein According to the abnormal sound detection module, locate the position of the abnormal sound at least through the time delay, intensity and frequency change of the acoustic signal; the abnormal sound detection module is associated with the cloud platform or the mobile terminal, and feeds back the detected information to the cloud platform or the mobile terminal in real time.

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