WO2023045154A1 - 冰箱的故障检测方法和装置 - Google Patents

冰箱的故障检测方法和装置 Download PDF

Info

Publication number
WO2023045154A1
WO2023045154A1 PCT/CN2021/141386 CN2021141386W WO2023045154A1 WO 2023045154 A1 WO2023045154 A1 WO 2023045154A1 CN 2021141386 W CN2021141386 W CN 2021141386W WO 2023045154 A1 WO2023045154 A1 WO 2023045154A1
Authority
WO
WIPO (PCT)
Prior art keywords
refrigerator
target
temperature
curve
electronic control
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2021/141386
Other languages
English (en)
French (fr)
Inventor
毕略
陈泽伟
武继荣
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hefei Hualing Co Ltd
Midea Group Co Ltd
Hefei Midea Refrigerator Co Ltd
Original Assignee
Hefei Hualing Co Ltd
Midea Group Co Ltd
Hefei Midea Refrigerator Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hefei Hualing Co Ltd, Midea Group Co Ltd, Hefei Midea Refrigerator Co Ltd filed Critical Hefei Hualing Co Ltd
Publication of WO2023045154A1 publication Critical patent/WO2023045154A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
    • F25D21/00—Defrosting; Preventing frosting; Removing condensed or defrost water
    • F25D21/06—Removing frost
    • F25D21/08—Removing frost by electric heating
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
    • F25D29/00—Arrangement or mounting of control or safety devices
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B40/00—Technologies aiming at improving the efficiency of home appliances, e.g. induction cooking or efficient technologies for refrigerators, freezers or dish washers

Definitions

  • the present application relates to the technical field of electrical appliances, and in particular to a refrigerator fault detection method and device.
  • the present application aims to solve at least one of the technical problems existing in the related art. For this reason, the present application proposes a refrigerator fault detection method to improve the timeliness of fault detection and the accuracy of detection results, thereby improving user experience.
  • the application also proposes a refrigerator fault detection device.
  • the application also proposes an electronic device.
  • the present application also proposes a non-transitory computer-readable storage medium.
  • the present application also proposes a computer program product.
  • the refrigerator is generated based on at least one item of electronic control data in the refrigerating room temperature, refrigerating defrosting temperature, freezing room temperature, freezing defrosting temperature, compressor gear, heating wire status and fan gear at each time in the electronic control log.
  • the actual operation curve within the target time period, each item of electronic control data corresponds to at least one of the actual operation curve;
  • the refrigerator fault detection method of the embodiment of the present application by comparing the actual operating curve of the refrigerator with the reference operating curves in one or more usage scenarios, when the similarity exceeds the target threshold, it is determined that the refrigerator is faulty or is about to When a fault occurs, the fault of the refrigerator can be detected in real time, and the fault prediction can be performed in a timely manner, and the accuracy and precision of the judgment result are high, which significantly improves the user experience.
  • the determining the similarity between the actual operating curve and at least one of a plurality of reference operating curves includes:
  • a degree of similarity between the actual operating curve and the target reference operating curve is determined.
  • the target usage scenario is determined through the following steps:
  • a target usage scenario corresponding to the refrigerator in the target time period is determined based on the door opening and closing information.
  • the determining the similarity between the actual operation curve and at least one of a plurality of reference operation curves includes: determining the similarity between the actual operation curve and each of the reference operation curves;
  • the determining the failure of the refrigerator in the case that the similarity exceeds the corresponding target threshold includes:
  • the reference operating curve is determined through the following steps:
  • At least one of the refrigerating room temperature, refrigerating defrosting temperature, freezing room temperature, freezing defrosting temperature, compressor gear, heating wire status and fan gear at each moment in the electronically controlled log is A piece of electronic control data to generate the actual operating curve of the refrigerator within the target period, including:
  • an actual operating curve of the refrigerator within a target period is generated.
  • the usage scenarios include:
  • the first processing module is configured to use at least one of the temperature in the refrigerating room, the defrosting temperature in the refrigerating room, the temperature in the freezing room, the defrosting temperature in the freezing room, the position of the compressor, the state of the heating wire and the position of the fan at each moment in the electronic control log.
  • Control data generate the actual operation curve of the refrigerator in the target period based on the electric control log to generate the actual operation curve in the target period, and each item of the electronic control data corresponds to at least one of the actual operation curve;
  • the second processing module is used to determine the similarity between the actual operation curve and at least one of a plurality of reference operation curves, each of which corresponds to a use scenario;
  • the reference operation curve is based on a simulated use scenario Generated by at least one working parameter and its corresponding time value in refrigerator temperature, refrigerator defrost temperature, freezer temperature, freezer defrost temperature, compressor gear, heating wire state and fan gear and its corresponding time value.
  • the parameters correspond to at least one of the reference operating curves to determine the similarity between the actual operating curve and at least one of the plurality of reference operating curves, and each of the reference operating curves corresponds to a usage scenario;
  • a third processing module configured to determine the failure of the refrigerator when the similarity exceeds a target threshold corresponding to the usage scenario, and determine the failure when the similarity exceeds a corresponding target threshold .
  • the refrigerator fault detection device of the embodiment of the present application by comparing the actual operating curve of the refrigerator with the reference operating curve in one or more usage scenarios, when the similarity exceeds the target threshold, it is determined that the refrigerator is faulty or is about to When a fault occurs, the fault of the refrigerator can be detected in real time, and the fault prediction can be performed in a timely manner, and the accuracy and precision of the judgment result are high, which significantly improves the user experience.
  • the electronic device includes a memory, a processor, and a computer program stored on the memory and operable on the processor.
  • the processor executes the computer program, the above-mentioned The steps of any one of the refrigerator fault detection methods.
  • a computer program is stored thereon, and when the computer program is executed by a processor, the steps of any one of the refrigerator fault detection methods described above are implemented.
  • the computer program product includes a computer program, and when the computer program is executed by a processor, the steps of any method for detecting a refrigerator fault described above are implemented.
  • Fig. 1 is one of the schematic flow charts of the refrigerator fault detection method provided by the embodiment of the present application.
  • Fig. 2 is the second schematic flow diagram of the refrigerator fault detection method provided by the embodiment of the present application.
  • Fig. 3 is one of the principle schematic diagrams of the refrigerator fault detection method provided by the embodiment of the present application.
  • Fig. 4 is the second schematic diagram of the fault detection method of the refrigerator provided by the embodiment of the present application.
  • Fig. 5 is the third schematic diagram of the principle of the refrigerator fault detection method provided by the embodiment of the present application.
  • Fig. 6 is the fourth schematic diagram of the principle of the refrigerator fault detection method provided by the embodiment of the present application.
  • Fig. 7 is a schematic structural diagram of a refrigerator fault detection device provided by an embodiment of the present application.
  • FIG. 8 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.
  • the refrigerator fault detection method may be executed by the refrigerator or a server communicatively connected with the refrigerator.
  • the refrigerator fault detection method includes: step 110 , step 120 and step 130 .
  • Step 110 based on at least one item of electronic control data in the electronic control log at each time of the refrigerating room temperature, refrigerating defrosting temperature, freezing room temperature, freezing defrosting temperature, compressor gear, heating wire status, and fan gear, generate The actual operating curve of the refrigerator within the target time period, each electronic control data corresponds to at least one actual operating curve;
  • the electronic control log includes working parameters used to characterize the working state of the refrigerator and the time values corresponding to each working parameter.
  • the target period is a user-defined period, for example, it can be set to 24 hours or 48 hours.
  • the abscissa of the actual operation curve is the time value within the target time period, and the ordinate is the working parameters of the refrigerator at each time within the target time period.
  • the actual operation curve is used to characterize the actual operation of the refrigerator within the target period.
  • the electronic control Data based on at least one of the refrigerating room temperature, refrigerating defrosting temperature, freezing room temperature, freezing defrosting temperature, compressor gear, heating wire status and fan gear at each moment in the electronic control log, the electronic control Data, respectively generate the actual operation curve corresponding to the electronic control data.
  • the electronic control data includes working parameters and time values corresponding to the working parameters, and the electronic control data are used to represent the working status of the refrigerator in various usage scenarios.
  • the temperature of the refrigerator, the defrost temperature of the refrigerator, the temperature of the freezer and the defrost temperature of the freezer can be collected through sensors, and each type of sensor is used to collect a kind of electronic control data;
  • Electronic control data such as the position of the compressor, the state of the heating wire and the position of the fan can be obtained through the main control command. It should be noted that each electronic control data corresponds to a curve.
  • the collected electronic control data can be cleaned to eliminate erroneous data, so as to improve the accuracy of the calculation results.
  • step 110 also includes:
  • the actual operating curve of the refrigerator within the target period is generated.
  • the target electronic control data is the data after eliminating the error electronic control data.
  • the working parameters of the refrigerator may be in error due to the interference of external factors.
  • the first period and the second period may be user-defined.
  • the first period may be set to 1 hour, and the second period may be set to 1.5 hours.
  • the electrical control logs uploaded by the refrigerator within 24 hours can be collected, and the electrical control data within 1 hour after opening and closing the refrigerator door and within 1.5 hours after defrosting are eliminated to obtain the target electrical control data.
  • the actual operation curve can be generated.
  • the actual operation curve includes at least one curve, and each actual operation curve corresponds to a type of electronic control data respectively.
  • the actual operating curves can include the curves corresponding to the temperature of the refrigerator, the curve corresponding to the defrosting temperature of the refrigerator, the curve corresponding to the temperature of the freezer, the curve corresponding to the defrosting temperature of the freezer, the curve corresponding to the compressor gear, and the curve corresponding to the state of the heating wire
  • the curves corresponding to fan gears One or more curves corresponding to fan gears.
  • the abscissa of the actual operation curve is the time value within 24 hours, and the ordinate is the temperature value of the refrigerating room, refrigerating defrosting temperature, freezing room temperature, freezing and defrosting temperature, compressor gear, heating wire One or more of status value and fan gear value.
  • the actual operation curve is generated by obtaining the electronic control log of the refrigerator in the target period, which is convenient for subsequent comparison with the reference operation curve, so as to realize the prediction and judgment of the refrigerator failure.
  • Step 120 determine the similarity between a plurality of reference operation curves and at least one of the actual operation curves, each reference operation curve corresponds to a use scenario; the reference operation curve is based on the refrigerating room temperature, refrigerating defrosting temperature, freezing At least one working parameter and its corresponding time value in room temperature, freezing and defrosting temperature, compressor gear, heating wire status and fan gear, and each working parameter corresponds to at least one reference operation curve;
  • the reference operating curve is the operating curve of the refrigerator under normal working conditions.
  • the abscissa of the benchmark operation curve is the time value, and the ordinate is the working parameters of the refrigerator under normal working conditions.
  • the working parameter can be obtained through the electric control log of the refrigerator.
  • the usage scenario is the usage scenario corresponding to the refrigerator.
  • the usage scenarios include: initial power-on operation, no-load operation of the compartment, half-load operation of the compartment, full-load operation of the compartment, first cooling of the warm gear, frequent opening and closing of the door in a short period of time, long-term opening and closing of the door, and normal operation at least one of the
  • each reference operation curve corresponds to a class of operating parameters respectively.
  • refrigerators of the same model are taken as examples for description.
  • the DTW (Dynamic Time Warping) algorithm can be used to determine the similarity between the benchmark operating curve and the actual operating curve, that is, to adjust the benchmark operating curve and the actual operating curve to a curve with the same time series, and calculate the two curves similarity between.
  • the baseline operating curve is determined by the following steps:
  • At least one benchmark running curve corresponding to the simulated usage scenario is respectively generated.
  • the execution subject of this embodiment is a server or an operator's terminal that is communicatively connected to the refrigerator, such as the operator's mobile phone or computer.
  • the simulated use scenarios include but are not limited to the first power-on operation, no-load operation of the compartment, half-load operation of the compartment, full-load operation of the compartment, the first cooling of the warm gear, frequent opening and closing of the door in a short period of time, long-term opening and closing of the door, and normal operation, etc. .
  • the working parameters in the simulated usage scenario are the working condition data of the refrigerator in normal operation in the simulated usage scenario.
  • the baseline operating curve is determined by the following steps:
  • the working parameters include at least one of the temperature of the refrigerator compartment, the defrost temperature of the refrigerator, the temperature of the freezer compartment, the defrost temperature of the freezer, the position of the compressor, the state of the heating wire and the position of the fan;
  • At least one reference operation curve corresponding to the work parameter is respectively generated; wherein, each work parameter corresponds to a reference operation curve, and one or more work under the same usage scenario
  • the reference operating curves corresponding to the parameters jointly represent the normal working state of the refrigerator in this usage scenario.
  • the time value corresponding to the working parameter can be determined by the time when the sensor uploads data or the time when the electronic control log is reported.
  • the working parameters of the refrigerators of different models in the third period of time under different usage scenarios may be collected respectively.
  • the reference operation curves corresponding to the same type of refrigerators in each simulated usage scenario can be generated.
  • the background database stores the 24-hour benchmark operating curves of refrigerators of model A-model N in different usage scenarios.
  • the reference operating curve within hours, which includes multiple reference operating curves corresponding to the refrigerating room temperature sensor, refrigerating defrosting sensor, freezing temperature sensor and freezing defrosting sensor, as well as the axis position of the press obtained through the main control command Multiple reference operating curves corresponding to working parameters such as heating wire status and fan gear.
  • the abscissa of the above multiple reference operation curves is the time value within 24 hours, and the ordinate is the temperature or gear position data.
  • the working parameters after the working parameters are collected, the working parameters can also be eliminated, and the working parameters of the refrigerator within 1 hour after opening and closing the door and within 1.5 hours after defrosting are eliminated, and the remaining data are stored as standard data , to improve the accuracy of the calculation results.
  • the actual operating curves of the refrigerator can be compared with the benchmark operating curves in different usage scenarios, which significantly improves the accuracy and accuracy of the calculation results.
  • Step 130 If each similarity exceeds the corresponding target threshold, determine that the refrigerator is faulty.
  • the target threshold is the maximum value of the absolute value of the difference between the actual operating curve and the reference operating curve of the refrigerator in each usage scenario under normal operating conditions.
  • target thresholds corresponding to different usage scenarios may be the same, or may also be different.
  • Target thresholds can be user-defined.
  • the similarity is the similarity between the actual operating curve obtained through step 120 and one or more reference operating curves.
  • the temperature of the compartment of the refrigerator will fluctuate abnormally when a refrigeration failure occurs or before the refrigeration failure, that is, the actual operating curves corresponding to the sensors will change significantly.
  • the traditional method of fault diagnosis by collecting sensor abnormal values is sensitive to abnormal values and user operations (frequent door opening and closing, door opening and closing timeout, etc.), and is prone to false positives and false negatives.
  • the similarity is one, if the one similarity exceeds the target threshold, it is determined that the refrigerator is faulty or has a potential fault.
  • the target threshold By comparing the target threshold with the size of the similarity, if the similarity exceeds the target threshold, it indicates that the actual operating state of the refrigerator in each usage scenario is not in a normal operating state, and it is determined that the refrigerator is faulty or has a potential fault .
  • the refrigerator fault detection method by comparing the actual operating curve of the refrigerator with the reference operating curves in one or more usage scenarios, when the similarity exceeds the target threshold, it is determined that the refrigerator is faulty or When a failure is about to occur, it can detect the failure of the refrigerator in real time and predict the failure in time, and the accuracy and precision of the judgment result are high, which significantly improves the user experience.
  • Step 120 includes:
  • the target usage scenario is the usage scenario corresponding to the actual operating curve of the refrigerator.
  • the target benchmark operating curve is the benchmark operating curve corresponding to the refrigerator of the same model in the target usage scenario.
  • the use scenario corresponding to the actual operation curve can be determined first, so as to determine the target use scenario.
  • Figures 4-6 respectively provide the actual operating curves corresponding to the refrigerators in three different usage scenarios.
  • Figure 4 shows the actual operating curves in the half-load cooling usage scenario.
  • the actual operating curves include the curves corresponding to multiple sensors.
  • Fig. 5 is the actual operation curve under the scene of full load cooling for the first time, and the actual operation curve includes curves corresponding to multiple sensors; The curve corresponding to each sensor;
  • the target usage scenario is matched with multiple usage scenarios corresponding to the multiple benchmark operating curves, and the benchmark operating curve corresponding to the target usage scenario is obtained through screening, so as to determine the target benchmark operating curve.
  • the similarity exceeds the range of the target threshold, it indicates that the actual operating state of the refrigerator in the current usage scenario is an abnormal operating state, and it can be determined that the refrigerator is faulty or is about to fail.
  • the step of generating the target usage scenario includes:
  • the door opening and closing information of the refrigerator within the target period can be obtained through the electronic control log.
  • the actual usage scenario corresponding to the target time period of the refrigerator can be determined.
  • the usage scene of the refrigerator in the target time period is frequent door opening and closing;
  • the usage scenario within the target period is to open the door for a long time.
  • the refrigerator fault detection method by comparing the actual operating curve of the refrigerator with the target reference operating curve corresponding to the refrigerator in the current usage scenario, it is determined that the refrigerator has a fault when the similarity exceeds the target threshold. Faults or imminent faults can help reduce data redundancy and increase computing speed, thereby improving the timeliness of fault diagnosis.
  • Step 120 also includes: determining multiple similarities between multiple benchmark operating curves and actual operating curves;
  • Step 130 also includes: determining that the refrigerator is faulty if the multiple similarities exceed the corresponding target thresholds.
  • the DTW calculation is directly performed on the actual operation curve and the reference operation curves in all usage scenarios corresponding to refrigerators of the same model, to generate corresponding The multiple similarities of , and compare the multiple similarities with the target threshold.
  • the refrigerator fault detection method by comparing the actual operating curve of the refrigerator with the reference operating curves in all usage scenarios, it is determined that the refrigerator has a fault or is about to fail when all similarities exceed the target threshold.
  • a fault occurs, it avoids the wrong judgment result caused by missing a certain usage scenario, which significantly improves the accuracy of the fault prediction result and improves the user experience.
  • the refrigerator fault detection device provided by the embodiment of the present application is described below, and the refrigerator fault detection device described below and the refrigerator fault detection method described above can be referred to in correspondence.
  • the refrigerator fault detection device includes: a first processing module 710 , a second processing module 720 and a third processing module 730 .
  • the first processing module 710 is configured to be based on at least one of the temperature of the refrigerator compartment, the defrost temperature of the refrigerator, the temperature of the freezer compartment, the defrost temperature of the freezer, the position of the compressor, the state of the heating wire and the position of the fan at each time in the electronic control log
  • the electronic control data generates the actual operating curve of the refrigerator within the target time period, and each electronic control data corresponds to at least one actual operating curve;
  • the second processing module 720 is used to determine the similarity between the actual operation curve and at least one of a plurality of reference operation curves, and each reference operation curve corresponds to a usage scenario; It is generated by at least one working parameter and its corresponding time value in defrosting temperature, freezing room temperature, freezing defrosting temperature, compressor gear, heating wire status and fan gear, and each working parameter corresponds to at least one reference operation curve;
  • the third processing module 730 is configured to determine that the refrigerator is faulty when each similarity exceeds a corresponding target threshold.
  • the refrigerator fault detection device by comparing the actual operating curve of the refrigerator with the reference operating curve in one or more usage scenarios, when the similarity exceeds the target threshold, it is determined that the refrigerator is faulty or When a failure is about to occur, it can detect the failure of the refrigerator in real time and predict the failure in time, and the accuracy and precision of the judgment result are high, which significantly improves the user experience.
  • the second processing module 720 is also used for:
  • Determining at least one similarity of the actual operating profile to a plurality of baseline operating profiles including:
  • the refrigerator fault detection device by comparing the actual operating curve of the refrigerator with the target benchmark operating curve corresponding to the refrigerator in the current usage scenario, it is determined that the refrigerator has a fault when the similarity exceeds the target threshold. Faults or imminent faults can help reduce data redundancy and increase computing speed, thereby improving the timeliness of fault diagnosis.
  • the target usage scenario is determined through the following steps:
  • the second processing module 720 is also used to: respectively determine the similarity between each reference operating curve and the actual operating curve;
  • the third processing module 730 is further configured to: determine that the refrigerator is faulty when all the similarities exceed the target threshold.
  • the refrigerator fault detection device by comparing the actual operating curve of the refrigerator with the reference operating curves in all usage scenarios, it is determined that the refrigerator has a fault or is about to fail when all similarities exceed the target threshold.
  • a fault occurs, it avoids the wrong judgment result caused by missing a certain usage scenario, which significantly improves the accuracy of the fault prediction result and improves the user experience.
  • the baseline operating curve is determined by the following steps:
  • At least one benchmark operating curve corresponding to the simulated usage scenario is respectively generated.
  • the first processing module 710 is also used for:
  • the actual operating curve of the refrigerator within the target period is generated.
  • the usage scenarios include: initial power-on operation, no-load operation of the compartment, half-load operation of the compartment, full-load operation of the compartment, first cooling of the warm gear, frequent opening and closing of the door in a short period of time, long-term opening and closing of the door, and normal operation at least one of the
  • the present application also provides a refrigerator.
  • the refrigerator includes the above-mentioned refrigerator fault detection device, and the refrigerator fault detection device can execute the steps of any one of the refrigerator fault detection methods described above.
  • FIG. 8 illustrates a schematic diagram of the physical structure of an electronic device.
  • the electronic device may include: a processor (processor) 810, a communication interface (Communications Interface) 820, a memory (memory) 830, and a communication bus 840, Wherein, the processor 810 , the communication interface 820 , and the memory 830 communicate with each other through the communication bus 840 .
  • the processor 810 can call the logic instructions in the memory 830 to execute the fault detection method of the refrigerator.
  • the method includes: based on the temperature of the refrigerator compartment at each time in the electronic control log, the temperature of the refrigerator defrost, the temperature of the freezer compartment, the temperature of the freezer defrost, At least one item of electronic control data in the position of the compressor, the state of the heating wire, and the position of the fan is used to generate the actual operating curve of the refrigerator within the target period, and each item of electronic control data corresponds to at least one actual operating curve; determine the relationship between the actual operating curve and multiple The similarity of at least one of the reference operation curves, each reference operation curve corresponds to a use scenario; the reference operation curve is based on the refrigerating room temperature, refrigerating defrosting temperature, freezing room temperature, freezing defrosting temperature, compressor It is generated by at least one working parameter and its corresponding time value in gear position, heating wire state and fan gear position, and each working parameter corresponds to at least one benchmark operating curve; when the similarity exceeds the target threshold corresponding to the usage scenario Next, determine the fault of the refrigerator.
  • the above logic instructions in the memory 830 may be implemented in the form of software functional units and when sold or used as an independent product, may be stored in a computer-readable storage medium.
  • the computer software product is stored in a storage medium, including several
  • the instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc, etc., which can store program codes. .
  • the present application also provides a computer program product, the computer program product includes a computer program, the computer program can be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can execute
  • the refrigerator fault detection method provided by the above method embodiments, the method includes: based on the temperature of the refrigerator compartment, the defrost temperature of the refrigerator, the temperature of the freezer compartment, the defrost temperature of the freezer, the gear position of the compressor, the heating At least one item of electronic control data in the wire status and fan gear position to generate the actual operating curve of the refrigerator within the target period, and each electronic control data corresponds to at least one actual operating curve; determine the actual operating curve and at least one of the multiple reference operating curves
  • Each benchmark operating curve corresponds to a usage scenario; the benchmark operating curve is based on the temperature of the refrigerator compartment, defrost temperature of refrigerator, freezer compartment temperature, defrost temperature of freezer, compressor gear, and heating wire status in the simulated usage scenario. Generated with at least one working parameter
  • the embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it is implemented to implement the refrigerator fault detection method provided by the above-mentioned embodiments , the method includes: at least one electronic control data based on the temperature of the refrigerator compartment, the defrost temperature of the refrigerator, the temperature of the freezer compartment, the defrost temperature of the freezer, the position of the compressor, the state of the heating wire and the position of the fan at each time in the electronic control log , to generate the actual operating curve of the refrigerator within the target time period, each electronic control data corresponds to at least one actual operating curve; determine the similarity between the actual operating curve and at least one of multiple benchmark operating curves, and each benchmark operating curve corresponds to a usage scenario ;
  • the reference operating curve is based on at least one working parameter in the refrigerating room temperature, refrigerating defrosting temperature, freezing room temperature, freezing defrosting temperature, compressor gear, heating wire status
  • the device embodiments described above are only illustrative, and the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without any creative effort.
  • each implementation can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware.
  • the essence of the above technical solutions or the part that contributes to related technologies can be embodied in the form of software products, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, disk , CD, etc., including several instructions to make a computer device (which may be a personal computer, server, or network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

Landscapes

  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • Thermal Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • Devices That Are Associated With Refrigeration Equipment (AREA)
  • Defrosting Systems (AREA)

Abstract

一种冰箱的故障检测方法和装置，冰箱的故障检测方法包括：基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成冰箱在目标时段内的实际运行曲线，各项电控数据对应至少一条实际运行曲线；确定实际运行曲线与多个基准运行曲线的至少一个的相似度，各基准运行曲线分别对应一个使用场景；各项工作参数对应至少一条基准运行曲线；在相似度均超过使用场景对应的目标阈值的情况下，确定冰箱故障。

Description

冰箱的故障检测方法和装置
相关申请的交叉引用
本申请要求于2021年9月23日提交的申请号为202111117370.X，发明名称为“冰箱的故障检测方法和装置”的中国专利申请的优先权，其通过引用方式全部并入本申请。
技术领域
本申请涉及电器技术领域，尤其涉及冰箱的故障检测方法和装置。
背景技术
冰箱在使用过程中不可避免会出现故障，因此故障检测作为一种重要的维护手段，被广泛应用于冰箱的制造与维护中。相关技术中，通常是在冰箱出现故障后，才会对冰箱进行故障检测，导致故障发现不及时，用户体验较差。
发明内容
本申请旨在至少解决相关技术中存在的技术问题之一。为此，本申请提出一种冰箱的故障检测方法，以提高故障检测的及时性以及检测结果的准确性，从而提高用户的使用体验。
本申请还提出一种冰箱的故障检测装置。
本申请还提出一种电子设备。
本申请还提出一种非暂态计算机可读存储介质。
本申请还提出一种计算机程序产品。
根据本申请第一方面实施例的冰箱的故障检测方法，包括：
基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成所述冰箱在目标时段内的实际运行曲线，各项所述电控数据对应至少一条所述实际运行曲线；
确定所述实际运行曲线与多个基准运行曲线的至少一个的相似度，各 所述基准运行曲线分别对应一个使用场景；所述基准运行曲线为基于模拟使用场景下的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项工作参数及其对应的时刻值生成的，各项所述工作参数对应至少一条所述基准运行曲线；
在所述相似度均超过所述使用场景对应的目标阈值的情况下，确定所述冰箱故障。
根据本申请实施例的冰箱的故障检测方法，通过将冰箱的实际运行曲线与一个或多个使用场景下的基准运行曲线进行比较，在相似度均超过目标阈值的情况下，确定冰箱故障或即将发生故障，能够对冰箱的故障进行实时检测，并进行及时地故障预测，且判断结果的准确性和精确度较高，显著提高了用户的使用体验。
根据本申请的一个实施例，
所述确定所述实际运行曲线与多个基准运行曲线的至少一个的相似度，包括：
基于目标使用场景和所述冰箱的型号，从所述多个基准运行曲线中确定目标基准运行曲线；
确定所述实际运行曲线与所述目标基准运行曲线之间的相似度。
根据本申请的一个实施例，所述目标使用场景通过如下步骤确定：
获取所述冰箱在所述目标时段内的开关门信息；
基于所述开关门信息确定所述冰箱在所述目标时段对应的目标使用场景。
根据本申请的一个实施例，
所述确定所述实际运行曲线与多个基准运行曲线的至少一个的相似度，包括：确定所述实际运行曲线与每个所述基准运行曲线的相似度；
所述在所述相似度均超过对应的目标阈值的情况下，确定所述冰箱故障，包括：
在每个所述相似度均超过对应的目标阈值的情况下，确定所述冰箱故障。
根据本申请的一个实施例，所述基准运行曲线通过如下步骤确定：
获取所述冰箱在至少一个模拟使用场景下的工作参数；
基于所述工作参数以及所述工作参数对应的时刻值，分别生成所述至少一个模拟使用场景对应的基准运行曲线。
根据本申请的一个实施例，所述基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成所述冰箱在目标时段内的实际运行曲线，包括：
剔除所述电控日志中所述冰箱在开关门后第一时段内与化霜后第二时段内的电控数据，确定目标电控数据；
基于所述目标电控数据，生成所述冰箱在目标时段内的实际运行曲线。
根据本申请的一个实施例，所述使用场景，包括：
初次上电运行，间室空载运行，间室半载运行，间室满载运行，暖档首次降温，短时间频繁开关门，长时间开关门和正常运行中的至少一种。
根据本申请第二方面实施例的冰箱的故障检测装置，包括：
第一处理模块，用于基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成所述冰箱在目标时段内的实际运行曲线基于电控日志生成所述在目标时段内的实际运行曲线，各项所述电控数据对应至少一条所述实际运行曲线；
第二处理模块，用于确定所述实际运行曲线与多个基准运行曲线的至少一个的相似度，各所述基准运行曲线分别对应一个使用场景；所述基准运行曲线为基于模拟使用场景下的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项工作参数及其对应的时刻值生成的，各所述工作参数对应至少一条所述基准运行曲线确定所述实际运行曲线与多个基准运行曲线的至少一个的相似度，各项所述基准运行曲线分别对应一个使用场景；
第三处理模块，用于在所述相似度均超过所述使用场景对应的目标阈值的情况下，确定所述冰箱故障在所述相似度均超过对应的目标阈值的情况下，确定所述故障。
根据本申请实施例的冰箱的故障检测装置，通过将冰箱的实际运行曲线与一个或多个使用场景下的基准运行曲线进行比较，在相似度均超过目 标阈值的情况下，确定冰箱故障或即将发生故障，能够对冰箱的故障进行实时检测，并进行及时地故障预测，且判断结果的准确性和精确度较高，显著提高了用户的使用体验。
根据本申请第三方面实施例的电子设备，包括存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现如上述任一种所述冰箱的故障检测方法的步骤。
根据本申请第四方面实施例的非暂态计算机可读存储介质，其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如上述任一种所述冰箱的故障检测方法的步骤。
根据本申请第五方面实施例的计算机程序产品，包括计算机程序，所述计算机程序被处理器执行时实现如上述任一种所述冰箱的故障检测方法的步骤。
本申请实施例中的上述一个或多个技术方案，至少具有如下技术效果之一：
通过将冰箱的实际运行曲线与一个或多个使用场景下的基准运行曲线进行比较，在相似度均超过目标阈值的情况下，确定冰箱故障或即将发生故障，能够对冰箱的故障进行实时检测，并进行及时地故障预测，且判断结果的准确性和精确度较高，显著提高了用户的使用体验。
进一步的，通过将冰箱的是实际运行曲线与该冰箱在当前使用场景下对应的目标基准运行曲线进行比较，在相似度超过目标阈值的情况下确定冰箱发生故障或即将发生故障，有助于减少数据冗余，提高计算速率，从而提高故障诊断的及时性。
更进一步的，通过将冰箱的是实际运行曲线与所有使用场景下的基准运行曲线进行比较，在所有相似度均超过目标阈值的情况下确定冰箱发生故障或即将发生故障，避免因漏掉某一使用场景而导致的判断结果错误，显著提高了故障预测结果的准确性，提高用户的使用体验。
本申请的附加方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本申请的实践了解到。
附图说明
为了更清楚地说明本申请实施例或相关技术中的技术方案，下面将对实施例或相关技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请实施例提供的冰箱的故障检测方法的流程示意图之一；
图2是本申请实施例提供的冰箱的故障检测方法的流程示意图之二；
图3是本申请实施例提供的冰箱的故障检测方法的原理示意图之一；
图4是本申请实施例提供的冰箱的故障检测方法的原理示意图之二；
图5是本申请实施例提供的冰箱的故障检测方法的原理示意图之三；
图6是本申请实施例提供的冰箱的故障检测方法的原理示意图之四；
图7是本申请实施例提供的冰箱的故障检测装置的结构示意图；
图8是本申请实施例提供的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的实施方式作进一步详细描述。以下实施例用于说明本申请，但不能用来限制本申请的范围。
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实施例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必须针对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一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
下面结合图1-图6描述本申请实施例的冰箱的故障检测方法。
需要说明的是，该冰箱的故障检测方法的执行主体可以为冰箱或者与冰箱通信连接的服务器。
如图1所示，该冰箱的故障检测方法包括：步骤110、步骤120和步骤130。
步骤110、基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成冰箱在目标时段内的实际运行曲线，各项电控数据对应至少一条实际运行曲线；
其中，电控日志中包括用于表征冰箱工作状态的工作参数以及各工作参数对应的时刻值。
目标时段为用户自定义时段，例如可以设置为24小时或48小时等。
实际运行曲线的横坐标为目标时段内的时刻值，纵坐标为冰箱在目标时段内各时刻的工作参数。
实际运行曲线用于表征冰箱在目标时段内的实际运行情况。
在该步骤中，基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项电控数据，分别生成电控数据对应的实际运行曲线。
其中，电控数据包括工作参数和工作参数对应的时刻值，电控数据用于表征冰箱在各使用场景下的工作状态。
冷藏室温度、冷藏化霜温度、冷冻室温度以及冷冻化霜温度可以通过传感器进行采集，各类传感器分别用于采集一种电控数据；
压机档位、加热丝状态和风机档位等电控数据可以通过主控命令获取。需要说明的是，各电控数据分别对应一条曲线。
在实际执行过程中，在采集到电控数据后，可以将采集到的电控数据进行清洗，剔除错误数据，以提高计算结果的准确性。
在一些实施例中，步骤110还包括：
剔除电控日志中冰箱在化霜后第二时段内与开关门后第一时段内的电控数据，确定目标电控数据；
基于目标电控数据，生成冰箱在目标时段内的实际运行曲线。
在该实施例中，目标电控数据为剔除误差电控数据后的数据。
可以理解的是，在一些使用场景下，冰箱的工作参数会因外界因素的干扰而出现误差。
第一时段与第二时段可以基于用户自定义。
其中，第一时段可以设置为1小时，第二时段可以设置为1.5小时。
在实际执行过程中，可以采集冰箱上传的24小时内的电控日志，剔除冰箱在开关门后1小时以及在化霜后1.5小时内的电控数据，得到目标电控数据。
基于目标电控数据以及各目标电控数据对应的时刻值，即可生成实际运行曲线。
其中，实际运行曲线包括至少一条曲线，每一条实际运行曲线分别对应一类电控数据。
即实际运行曲线可以包括冷藏室温度对应的曲线、冷藏化霜温度对应的曲线、冷冻室温度对应的曲线、冷冻化霜温度对应的曲线、压机档位对应的曲线、加热丝状态对应的曲线和风机档位对应的曲线中的一条或多条。
其中，实际运行曲线的横坐标为24小时内的时刻值，纵坐标分别为冷藏室温度值、冷藏化霜温度值、冷冻室温度值、冷冻化霜温度值、压机档位值、加热丝状态值和风机档位值中的一种或多种。
在该步骤中，通过获取冰箱在目标时段内的电控日志以生成实际运行曲线，便于后续与基准运行曲线进行比较，以实现对冰箱故障的预测及判断。
步骤120、确定多个基准运行曲线与实际运行曲线的至少一个的相似度，各基准运行曲线分别对应一个使用场景；基准运行曲线为基于模拟使用场景下的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项工作参数及其对应的时刻值生成的，各项工作参数对应至少一条基准运行曲线；
在该步骤中，基准运行曲线为冰箱在正常工作状态下的运行曲线。
基准运行曲线的横坐标为时刻值，纵坐标为冰箱在正常工作状态下的工作参数。
其中，该工作参数可以通过冰箱的电控日志获取。
使用场景为冰箱对应的使用场景。
在一些实施例中，使用场景包括：初次上电运行，间室空载运行，间室半载运行，间室满载运行，暖档首次降温，短时间频繁开关门，长时间开关门和正常运行中的至少一种。
需要说明的是，一个使用场景下，可以包括多条基准运行曲线，其中， 各基准运行曲线分别对应一类工作参数。
可以理解的是，不同型号的冰箱对应有不同的基准运行曲线，在实际执行过程中，应将冰箱的实际运行曲线同与该冰箱型号相同的冰箱所对应的基准运行曲线进行比较。
以下实施例中，均以同一型号的冰箱为例，进行说明。
在实际执行过程中，可以采用DTW(动态时间规整)算法确定基准运行曲线与实际运行曲线之间的相似度，即将基准运行曲线与实际运行曲线调整为时间序列相同的曲线，并计算两条曲线之间的相似度。
下面对基准运行曲线的确定步骤进行说明。
在一些实施例中，基准运行曲线通过如下步骤确定：
获取冰箱在至少一个模拟使用场景下的工作参数；
基于工作参数对应的时刻值以及工作参数，分别生成至少一个模拟使用场景对应的基准运行曲线。
需要说明的是，基准运行曲线可以在冰箱出厂前进行确定。该实施例的执行主体为与冰箱通信连接的服务器或操作员的终端，如操作员的手机或电脑等。
其中，模拟使用场景包括但不限于次上电运行，间室空载运行，间室半载运行，间室满载运行，暖档首次降温，短时间频繁开关门，长时间开关门和正常运行等。
模拟使用场景下的工作参数为冰箱在该模拟使用场景下正常运行时的工况数据。
下面，对该实施例的实现方式进行具体说明。
在一些实施例中，基准运行曲线通过如下步骤确定：
获取冰箱在模拟使用场景下的工作参数，工作参数包括冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项；
基于至少一项工作参数以及工作参数对应的时刻值，分别生成工作参数对应的至少一条基准运行曲线；其中，每一项工作参数对应一条基准运行曲线，同一使用场景下的一项或多项工作参数对应的基准运行曲线共同表征该使用场景下的冰箱的正常工作状态。
可以理解的是，不同型号的冰箱对应有不同的基准运行曲线，在模拟使用场景时，应分别模拟各型号的冰箱所对应的使用场景，并采集各型号的冰箱在各模拟使用场景下的工作参数，基于工作参数生成各型号的冰箱在各使用场景下的基准运行曲线。
工作参数对应的时刻值可以通过传感器上传数据的时间或者电控日志的上报时间所确定。
在实际执行过程中，可以对不同型号的冰箱分别采集在不同使用场景下的第三时段内的工作参数。
例如采集每种使用场景对应的冰箱在24h内的48条数据，将采集频率设置30分钟/次，并将采集到的数据保存至后台数据库中作为标准数据。
通过标准数据以及各标准数据对应的时刻值，即可生成同一型号的冰箱所对应的各模拟使用场景下的基准运行曲线。
如图3所示，后台数据库中存储有型号A-型号N的冰箱所对应不同使用场景下的24小时基准运行曲线，如图3所示的曲线为A型号的冰箱在使用场景1下的24小时内的基准运行曲线，该基准运行曲线包括冷藏室温度传感器、冷藏化霜传感器、冷冻温度传感器和冷冻化霜传感器所对应的多条基准运行曲线，以及通过主控命令获取的压机轴位、加热丝状态和风机档位等工作参数所对应的多条基准运行曲线。
其中，以上多条基准运行曲线的横坐标为24h内的时刻值，纵坐标为温度或档位数据。
在一些实施例中，在采集到工作参数后，还可以对工作参数进行剔除，剔除冰箱在开关门后1小时以及在化霜后1.5小时内的工作参数，并将余下数据作为标准数据进行存储，以提高计算结果的准确性。
发明人在研发过程中发现，相关技术中，在对冰箱故障进行检测时，往往只能笼统地将冰箱的实际运行情况与标准运行情况进行比较，比较结果较为粗糙，且准确性不高。
在本步骤中，通过设置多种使用场景下的基准运行曲线，使冰箱的实际运行曲线能够分别与不同使用场景下的基准运行曲线进行对比，显著提高了计算结果的精确度以及准确性。
步骤130、在各相似度均超过对应的目标阈值的情况下，确定冰箱故 障。
在该步骤中，目标阈值为冰箱在正常运行状态下，各使用场景下其实际运行曲线与基准运行曲线之间的差值绝对值的最大值。
可以理解的是，不同使用场景所对应的目标阈值可能相同，或者也可能不同。
目标阈值可以基于用户自定义。
相似度为通过步骤120所得到的实际运行曲线与一个或多个基准运行曲线的相似度。
可以理解的是，冰箱在产生制冷故障时或制冷故障前间室的温度会产生异常的波动，即各传感器对应的实际运行曲线会有明显的变化。
传统的通过采集传感器异常值进行故障诊断的方式，对异常值以及用户操作(频繁开关门、开关门超时等)比较敏感，容易出现误报与漏报的情况。
而在本申请中，通过运行曲线相似度匹配的方式可以更好地对设备的运行状态进行实时的诊断与监控。
在相似度为一个的情况下，在该一个相似度超过目标阈值的情况下，即确定冰箱发生故障或存在潜在故障。
或者，在相似度为多个的情况下，在所有相似度均超过目标阈值的情况下，即确定冰箱故障。
通过比较目标阈值与相似度的大小，在相似度均超过目标阈值的情况下，则表明该冰箱在各使用场景下的实际运行状态均不处于正常运行状态，则确定冰箱发生故障或存在潜在故障。
根据本申请实施例提供的冰箱的故障检测方法，通过将冰箱的实际运行曲线与一个或多个使用场景下的基准运行曲线进行比较，在相似度均超过目标阈值的情况下，确定冰箱故障或即将发生故障，能够对冰箱的故障进行实时检测，并进行及时地故障预测，且判断结果的准确性和精确度较高，显著提高了用户的使用体验。
下面分别从两种实现角度，对本申请的实现方式进行具体说明。
一、将实际运行曲线与相同使用场景下的目标基准运行曲线进行比较。
如图2所示，在一些实施例中，
步骤120包括：
基于冰箱的型号和目标使用场景，从至少一个基准运行曲线中确定目标基准运行曲线；
确定目标基准运行曲线与实际运行曲线之间的相似度。
其中，目标使用场景为冰箱实际运行曲线所对应的使用场景。
目标基准运行曲线为目标使用场景下的同一型号的冰箱所对应的基准运行曲线。
可以理解的是，基准运行曲线有多条，分别对应于多个不同的使用场景。而冰箱在目标时段内实际运行时所对应的使用场景往往不可能涵盖所有的使用场景。
在实际执行过程中，在确定冰箱在目标时段内的实际运行曲线后，可以优先确定该实际运行曲线所对应的使用场景，以确定目标使用场景。
图4-图6分别提供了三种不同使用场景下的冰箱所对应的实际运行曲线，其中图4为半载降温使用场景下的实际运行曲线，该实际运行曲线包括多个传感器所对应的曲线；图5为满载首次降温使用场景下的实际运行曲线，该实际运行曲线包括多个传感器所对应的曲线；图6为暖档满载首次降温使用场景下的实际运行曲线，该实际运行曲线包括多个传感器所对应的曲线；
然后将目标使用场景与多个基准运行曲线所对应的多个使用场景进行匹配，筛选得到目标使用场景所对应的基准运行曲线，从而确定目标基准运行曲线。
利用目标基准运行曲线与实际运行曲线，计算DTW，以得到目标基准运行曲线与实际运行曲线之间的相似度，并直接将该相似度与目标阈值进行比较。
在该相似度超过目标阈值的范围时，则表明该冰箱在当前使用场景下的实际运行状态为非正常运行状态，即可确定冰箱故障，或即将发生故障。
在一些实施例中，目标使用场景的生成步骤，包括：
获取冰箱在目标时段内的开关门信息；
基于开关门信息确定冰箱在目标时段对应的目标使用场景。
在该实施例中，冰箱在目标时段内的开关门信息可以通过电控日志获 取。
基于开关门信息以及传感器采集的工作参数，可以确定冰箱在目标时段所对应的实际使用场景。
例如，当冰箱在第四时段内开关门次数超过第一阈值时，则确定冰箱在该目标时段内的使用场景为频繁开关门；或者，当冰箱一次开门时长超过第五时段时，则确定冰箱在该目标时段内的使用场景为长时间开门。
根据本申请实施例提供的冰箱的故障检测方法，通过将冰箱的是实际运行曲线与该冰箱在当前使用场景下对应的目标基准运行曲线进行比较，在相似度超过目标阈值的情况下确定冰箱发生故障或即将发生故障，有助于减少数据冗余，提高计算速率，从而提高故障诊断的及时性。
二、将实际运行曲线与全部使用场景下的基准曲线进行比较。
在一些实施例中，
步骤120还包括：确定多个基准运行曲线与实际运行曲线的多个相似度；
步骤130还包括：在多个相似度均超过对应的目标阈值的情况下，确定冰箱故障。
在该实施例中，在生成冰箱的实际运行曲线后，直接将该实际运行曲线与同一型号下的冰箱所对应的全部使用场景下的基准运行曲线进行DTW计算，分别生成多个使用场景所对应的多个相似度，并将多个相似度分别与目标阈值进行比较。
在所有相似度均超过对应的目标阈值的情况下，表明冰箱当前实际运行状态不符合任何用户使用场景下的正常运行状态，则确定冰箱发生故障或即将发生故障。
根据本申请实施例提供的冰箱的故障检测方法，通过将冰箱的是实际运行曲线与所有使用场景下的基准运行曲线进行比较，在所有相似度均超过目标阈值的情况下确定冰箱发生故障或即将发生故障，避免因漏掉某一使用场景而导致的判断结果错误，显著提高了故障预测结果的准确性，提高用户的使用体验。
下面对本申请实施例提供的冰箱的故障检测装置进行描述，下文描述的冰箱的故障检测装置与上文描述的冰箱的故障检测方法可相互对应参 照。
如图7所示，该冰箱的故障检测装置包括：第一处理模块710、第二处理模块720和第三处理模块730。
第一处理模块710，用于基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成冰箱在目标时段内的实际运行曲线，各项电控数据对应至少一条实际运行曲线；
第二处理模块720，用于确定实际运行曲线与多个基准运行曲线的至少一个的相似度，各基准运行曲线分别对应一个使用场景；基准运行曲线为基于模拟使用场景下的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项工作参数及其对应的时刻值生成的，各项工作参数对应至少一条基准运行曲线；
第三处理模块730，用于在各相似度均超过对应的目标阈值的情况下，确定冰箱故障。
根据本申请实施例提供的冰箱的故障检测装置，通过将冰箱的实际运行曲线与一个或多个使用场景下的基准运行曲线进行比较，在相似度均超过目标阈值的情况下，确定冰箱故障或即将发生故障，能够对冰箱的故障进行实时检测，并进行及时地故障预测，且判断结果的准确性和精确度较高，显著提高了用户的使用体验。
在一些实施例中，第二处理模块720还用于：
确定实际运行曲线与多个基准运行曲线的至少一个相似度，包括：
基于冰箱的型号和目标使用场景，从至少一个基准运行曲线中确定目标基准运行曲线；
确定目标基准运行曲线与实际运行曲线之间的相似度。
根据本申请实施例提供的冰箱的故障检测装置，通过将冰箱的是实际运行曲线与该冰箱在当前使用场景下对应的目标基准运行曲线进行比较，在相似度超过目标阈值的情况下确定冰箱发生故障或即将发生故障，有助于减少数据冗余，提高计算速率，从而提高故障诊断的及时性。
在一些实施例中，目标使用场景通过如下步骤确定：
获取冰箱在目标时段内的开关门信息；
基于开关门信息确定冰箱在目标时段对应的目标使用场景。
在一些实施例中，第二处理模块720还用于：分别确定各基准运行曲线与实际运行曲线的相似度；
第三处理模块730还用于：在各相似度均超过目标阈值的情况下，确定冰箱故障。
根据本申请实施例提供的冰箱的故障检测装置，通过将冰箱的是实际运行曲线与所有使用场景下的基准运行曲线进行比较，在所有相似度均超过目标阈值的情况下确定冰箱发生故障或即将发生故障，避免因漏掉某一使用场景而导致的判断结果错误，显著提高了故障预测结果的准确性，提高用户的使用体验。
在一些实施例中，基准运行曲线通过如下步骤确定：
获取冰箱在至少一个模拟使用场景下的工作参数；
基于工作参数，分别生成至少一个模拟使用场景对应的基准运行曲线。
在一些实施例中，第一处理模块710还用于：
剔除电控日志中冰箱在化霜后第二时段内与开关门后第一时段内的电控数据，确定目标电控数据；
基于目标电控数据，生成冰箱在目标时段内的实际运行曲线。
在一些实施例中，使用场景包括：初次上电运行，间室空载运行，间室半载运行，间室满载运行，暖档首次降温，短时间频繁开关门，长时间开关门和正常运行中的至少一种。
本申请还提供一种冰箱。
在一些实施例中，该冰箱包括如上所述的冰箱的故障检测装置，该冰箱的故障检测装置可以执行如上任一所述的冰箱的故障检测方法的步骤。
图8示例了一种电子设备的实体结构示意图，如图8所示，该电子设备可以包括：处理器(processor)810、通信接口(Communications Interface)820、存储器(memory)830和通信总线840，其中，处理器810，通信接口820，存储器830通过通信总线840完成相互间的通信。处理器810可以调用存储器830中的逻辑指令，以执行冰箱的故障检测方法，该方法包括：基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控 数据，生成冰箱在目标时段内的实际运行曲线，各项电控数据对应至少一条实际运行曲线；确定实际运行曲线与多个基准运行曲线的至少一个的相似度，各基准运行曲线分别对应一个使用场景；基准运行曲线为基于模拟使用场景下的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项工作参数及其对应的时刻值生成的，各项工作参数对应至少一条基准运行曲线；在相似度均超过使用场景对应的目标阈值的情况下，确定冰箱故障。
此外，上述的存储器830中的逻辑指令可以通过软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对相关技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
进一步地，本申请还提供一种计算机程序产品，所述计算机程序产品包括计算机程序，计算机程序可存储在非暂态计算机可读存储介质上，所述计算机程序被处理器执行时，计算机能够执行上述各方法实施例所提供的冰箱的故障检测方法，该方法包括：基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成冰箱在目标时段内的实际运行曲线，各项电控数据对应至少一条实际运行曲线；确定实际运行曲线与多个基准运行曲线的至少一个的相似度，各基准运行曲线分别对应一个使用场景；基准运行曲线为基于模拟使用场景下的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项工作参数及其对应的时刻值生成的，各项工作参数对应至少一条基准运行曲线；在相似度均超过使用场景对应的目标阈值的情况下，确定冰箱故障。
另一方面，本申请实施例还提供一种非暂态计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现以执行上述各实 施例提供的冰箱的故障检测方法，该方法包括：基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成冰箱在目标时段内的实际运行曲线，各项电控数据对应至少一条实际运行曲线；确定实际运行曲线与多个基准运行曲线的至少一个的相似度，各基准运行曲线分别对应一个使用场景；基准运行曲线为基于模拟使用场景下的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项工作参数及其对应的时刻值生成的，各项工作参数对应至少一条基准运行曲线；在相似度均超过使用场景对应的目标阈值的情况下，确定冰箱故障。
以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性的劳动的情况下，即可以理解并实施。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到各实施方式可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件。基于这样的理解，上述技术方案本质上或者说对相关技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品可以存储在计算机可读存储介质中，如ROM/RAM、磁碟、光盘等，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行各个实施例或者实施例的某些部分所述的方法。
最后应说明的是：以上实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围。
以上实施方式仅用于说明本申请，而非对本申请的限制。尽管参照实施例对本申请进行了详细说明，本领域的普通技术人员应当理解，对本申请的技术方案进行各种组合、修改或者等同替换，都不脱离本申请技术方案的精神和范围，均应涵盖在本申请的权利要求范围中。

Claims (11)

  1. 一种冰箱的故障检测方法，其特征在于，包括：
    基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成所述冰箱在目标时段内的实际运行曲线，各项所述电控数据对应至少一条所述实际运行曲线；
    确定所述实际运行曲线与多个基准运行曲线的至少一个的相似度，各所述基准运行曲线分别对应一个使用场景；所述基准运行曲线为基于模拟使用场景下的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项工作参数及其对应的时刻值生成的，各项所述工作参数对应至少一条所述基准运行曲线；
    在所述相似度均超过所述使用场景对应的目标阈值的情况下，确定所述冰箱故障。
  2. 根据权利要求1所述的冰箱的故障检测方法，其特征在于，所述确定所述实际运行曲线与多个基准运行曲线的至少一个的相似度，包括：
    基于目标使用场景和所述冰箱的型号，从所述多个基准运行曲线中确定目标基准运行曲线；
    确定所述实际运行曲线与所述目标基准运行曲线之间的相似度。
  3. 根据权利要求2所述的冰箱的故障检测方法，其特征在于，所述目标使用场景通过如下步骤确定：
    获取所述冰箱在所述目标时段内的开关门信息；
    基于所述开关门信息确定所述冰箱在所述目标时段对应的目标使用场景。
  4. 根据权利要求1所述的冰箱的故障检测方法，其特征在于，
    所述确定所述实际运行曲线与多个基准运行曲线的至少一个的相似度，包括：确定所述实际运行曲线与每个所述基准运行曲线的相似度；
    所述在所述相似度均超过所述使用场景对应的目标阈值的情况下，确定所述冰箱故障，包括：
    在每个所述相似度均超过所述使用场景对应的目标阈值的情况下，确 定所述冰箱故障。
  5. 根据权利要求1-4任一项所述的冰箱的故障检测方法，其特征在于，所述基准运行曲线通过如下步骤确定：
    获取所述冰箱在多个模拟使用场景下的工作参数；
    基于所述工作参数以及所述工作参数对应的时刻值，分别生成所述多个模拟使用场景对应的多个基准运行曲线。
  6. 根据权利要求1-4任一项所述的冰箱的故障检测方法，其特征在于，所述基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成所述冰箱在目标时段内的实际运行曲线，包括：
    剔除所述电控日志中所述冰箱在开关门后第一时段内与化霜后第二时段内的电控数据，确定目标电控数据；
    基于所述目标电控数据，生成所述冰箱在目标时段内的实际运行曲线。
  7. 根据权利要求1-4任一项所述的冰箱的故障检测方法，其特征在于，所述使用场景，包括：
    初次上电运行、间室空载运行、间室半载运行、间室满载运行、暖档首次降温、短时间频繁开关门、长时间开关门和正常运行中的至少一种。
  8. 一种冰箱的故障检测装置，其特征在于，包括：
    第一处理模块，用于基于电控日志中各时刻的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中至少一项电控数据，生成所述冰箱在目标时段内的实际运行曲线，各项所述电控数据对应至少一条所述实际运行曲线；
    第二处理模块，用于确定所述实际运行曲线与多个基准运行曲线的至少一个的相似度，各所述基准运行曲线分别对应一个使用场景；所述基准运行曲线为基于模拟使用场景下的冷藏室温度、冷藏化霜温度、冷冻室温度、冷冻化霜温度、压机档位、加热丝状态和风机档位中的至少一项工作参数及其对应的时刻值生成的，各项所述工作参数对应至少一条所述基准运行曲线；
    第三处理模块，用于在所述相似度均超过所述使用场景对应的目标阈值的情况下，确定所述冰箱故障。
  9. 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，其特征在于，所述处理器执行所述程序时实现如权利要求1至7任一项所述冰箱的故障检测方法的步骤。
  10. 一种非暂态计算机可读存储介质，其上存储有计算机程序，其特征在于，该计算机程序被处理器执行时实现如权利要求1至7任一项所述冰箱的故障检测方法的步骤。
  11. 一种计算机程序产品，包括计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1至7任一项所述冰箱的故障检测方法的步骤。
PCT/CN2021/141386 2021-09-23 2021-12-24 冰箱的故障检测方法和装置 Ceased WO2023045154A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202111117370.XA CN115900215B (zh) 2021-09-23 2021-09-23 冰箱的故障检测方法和装置
CN202111117370.X 2021-09-23

Publications (1)

Publication Number Publication Date
WO2023045154A1 true WO2023045154A1 (zh) 2023-03-30

Family

ID=85719952

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/141386 Ceased WO2023045154A1 (zh) 2021-09-23 2021-12-24 冰箱的故障检测方法和装置

Country Status (2)

Country Link
CN (1) CN115900215B (zh)
WO (1) WO2023045154A1 (zh)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116595348A (zh) * 2023-05-10 2023-08-15 四川虹美智能科技有限公司 基于冰箱特征曲线的冰箱故障诊断方法及系统
CN117365928A (zh) * 2023-10-16 2024-01-09 合肥美菱物联科技有限公司 一种冰箱压缩机反转检测方法
CN120724169A (zh) * 2025-06-20 2025-09-30 湖北三江博力智能装备有限公司 一种废气净化设备异常运行状态检测方法及系统
CN120992056A (zh) * 2025-10-22 2025-11-21 杭州康钡电机有限公司 单温度探头的偏移故障检测方法、装置及介质

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102590662A (zh) * 2012-02-02 2012-07-18 合肥美的荣事达电冰箱有限公司 冰箱的故障检测方法
CN104764288A (zh) * 2015-03-17 2015-07-08 广东奥马电器股份有限公司 一种动态制冷线的冰箱检测方法
CN110345704A (zh) * 2018-04-02 2019-10-18 合肥美的电冰箱有限公司 检测家用电器的方法和系统、服务器及机器可读存储介质
CN112503828A (zh) * 2019-09-16 2021-03-16 青岛海尔电冰箱有限公司 冰箱及其制冷故障的检测和处理方法

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE10011110B4 (de) * 2000-03-09 2004-08-26 Danfoss A/S Verfahren zum Entdecken von Fehlern in einer Kühlanlage
JP5316674B2 (ja) * 2011-05-09 2013-10-16 パナソニック株式会社 冷蔵庫
CN103398541A (zh) * 2013-08-07 2013-11-20 合肥美菱股份有限公司 一种冰箱的故障检测系统及检测方法
KR20170091423A (ko) * 2016-02-01 2017-08-09 엘지전자 주식회사 냉장고 제어 장치, 냉장고 및 냉장고의 고장 진단 방법
US11668521B2 (en) * 2018-03-20 2023-06-06 Lg Electronics Inc. Refrigerator and cloud server of diagnosing cause of abnormal state

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102590662A (zh) * 2012-02-02 2012-07-18 合肥美的荣事达电冰箱有限公司 冰箱的故障检测方法
CN104764288A (zh) * 2015-03-17 2015-07-08 广东奥马电器股份有限公司 一种动态制冷线的冰箱检测方法
CN110345704A (zh) * 2018-04-02 2019-10-18 合肥美的电冰箱有限公司 检测家用电器的方法和系统、服务器及机器可读存储介质
CN112503828A (zh) * 2019-09-16 2021-03-16 青岛海尔电冰箱有限公司 冰箱及其制冷故障的检测和处理方法

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116595348A (zh) * 2023-05-10 2023-08-15 四川虹美智能科技有限公司 基于冰箱特征曲线的冰箱故障诊断方法及系统
CN117365928A (zh) * 2023-10-16 2024-01-09 合肥美菱物联科技有限公司 一种冰箱压缩机反转检测方法
CN120724169A (zh) * 2025-06-20 2025-09-30 湖北三江博力智能装备有限公司 一种废气净化设备异常运行状态检测方法及系统
CN120992056A (zh) * 2025-10-22 2025-11-21 杭州康钡电机有限公司 单温度探头的偏移故障检测方法、装置及介质

Also Published As

Publication number Publication date
CN115900215A (zh) 2023-04-04
CN115900215B (zh) 2025-09-30

Similar Documents

Publication Publication Date Title
WO2023045154A1 (zh) 冰箱的故障检测方法和装置
CN112665306B (zh) 一种冰箱远程故障诊断系统及其诊断方法
CN110506186B (zh) 用于诊断异常状态的原因的冰箱及云服务器
US12405019B2 (en) Air conditioning system, abnormality estimation method for air conditioning system, air conditioner, and abnormality estimation method for air conditioner
EP3553426A1 (en) Data processing method for refrigerant leakage detection
CN104950685A (zh) 信息处理方法与装置、信息处理方法与家用电器及系统
CN111578445A (zh) 用于空调器的控制方法、装置及空调器
CN105042807B (zh) 检测变频空调运行状态的方法和装置
CN109974845A (zh) 故障警示方法、计算机可读存储介质和制冷设备
CN111720975A (zh) 空调器的控制方法、系统及装置
CN110986282A (zh) 一种热泵空调结霜判断方法、计算机可读存储介质及空调
CN107655173A (zh) 运行控制方法、装置、空调系统和计算机可读存储介质
TWI753417B (zh) 冷卻系統的監控方法及其監控裝置
CN120671038A (zh) 一种基于人工智能的交叉分析数字孪生智能运维方法及系统
CN107328156A (zh) 冰箱故障的判断方法、服务器和计算机可读存储介质
CN108592325B (zh) 控制方法、控制装置、制冷设备和计算机可读存储介质
CN115388610A (zh) 冰箱故障预测方法、装置、系统及电子设备
CN107341520B (zh) 冰箱故障的判断方法、服务器和计算机可读存储介质
Hirata et al. Model Creation Method for Anomaly Detection in Refrigeration and Air Conditioning Systems
CN117068215B (zh) 一种城轨车辆空调机组的性能分析方法及装置
CN110740621A (zh) 一种机架式空调控制方法、控制系统和机架式空调
CN110736239B (zh) 空调中润滑油余量的确定方法及装置
TW202424677A (zh) 冷櫃監控系統與監控主機
CN118776239A (zh) 双循环系统冰箱的制冷系统的故障诊断方法和系统
CN120846023A (zh) 冰箱的控制方法及冰箱、存储介质

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21958265

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 21958265

Country of ref document: EP

Kind code of ref document: A1

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 30/10/2024)

122 Ep: pct application non-entry in european phase

Ref document number: 21958265

Country of ref document: EP

Kind code of ref document: A1