Fault diagnosis method and system for intelligent door lock, terminal and storage medium

Abstract

The invention discloses a fault diagnosis method and system for an intelligent door lock, a terminal and a storage medium. The method comprises the following steps: acquiring module operation data of the intelligent door lock, preprocessing the module operation data to obtain target data, and performing data processing on the target data to obtain a target processing result; obtaining door lock log data according to the target processing result, performing data analysis on the door lock log data to obtain an analysis result, and performing identification processing on the analysis result to obtain an identification result; if it is determined that the intelligent door lock has potential faults according to the recognition result, early warning information and a corresponding solution strategy are generated according to the recognition result, and the early warning information and the solution strategy are pushed to the target user. According to the method, the collected data can be fully utilized, potential faults can be found in advance, the reliability and safety of the system are improved, early warning notifications and corresponding problem solving strategies can be sent when the potential faults are found, and therefore the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fault diagnosis, and in particular to a fault diagnosis method, system, terminal and computer-readable storage medium for an intelligent door lock. Background Art

[0002] With the development of science and technology and the improvement of people's living standards, smart homes have become an indispensable part of modern life; as an important part of smart homes, the security, reliability and user experience of smart door locks have become the focus of people's attention. Smart door lock systems integrate various sensors and control modules to achieve real-time monitoring and management of locks. However, traditional smart door lock systems have some shortcomings in fault warning and self-diagnosis, which cannot meet the needs of modern users.

[0003] During the use of current smart door locks, users often only notice them when they fail, which leads to a decline in user experience and may even affect safety. At the same time, for operation and maintenance personnel, it is impossible to know the potential failures of smart door locks in advance, which increases the cost and difficulty of maintenance. Existing smart door lock systems usually adopt real-time monitoring and alarm methods, that is, when the lock fails, the system will immediately issue an alarm to remind the user to deal with it. In addition, some smart door lock systems also have self-diagnosis functions, which can detect abnormal states of locks and send warnings to users. However, these smart door lock systems have some limitations in fault warning and self-diagnosis. First, they can only detect the current state of the lock, but cannot predict possible future failures; second, they can usually only send warnings, but cannot provide specific fault analysis and solution suggestions; finally, there are also deficiencies in data processing and analysis, and the collected data cannot be fully utilized, resulting in low reliability of fault analysis.

[0004] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0005] The main purpose of the present invention is to provide a fault diagnosis method, system, terminal and storage medium for a smart door lock, aiming to solve the problem that the prior art cannot predict possible faults of smart door locks, cannot provide specific fault analysis and solution suggestions during early warning, and cannot make full use of the collected data, resulting in low reliability of fault analysis.

[0006] To achieve the above object, the present invention provides a fault diagnosis method for a smart door lock, the fault diagnosis method for a smart door lock comprising the following steps:

[0007] Acquire module operation data of the smart door lock, pre-process the module operation data to obtain target data, and perform data processing on the target data to obtain a target processing result;

[0008] Obtaining door lock log data according to the target processing result, performing data analysis on the door lock log data to obtain an analysis result, and performing recognition processing on the analysis result to obtain a recognition result;

[0009] If it is determined that the smart door lock has a potential fault according to the recognition result, a warning message and a corresponding solution strategy are generated according to the recognition result, and the warning message and the solution strategy are pushed to the target user.

[0010] Optionally, the fault diagnosis method of the smart door lock, wherein the obtaining of module operation data of the smart door lock, preprocessing the module operation data to obtain target data, and performing data processing on the target data to obtain a target processing result, specifically includes:

[0011] When it is detected that the diagnosis time of the smart door lock reaches the preset time, the module operation data of the smart door lock is obtained, and the module operation data is filtered to obtain the target data, wherein the module operation data includes sensor data, current data and working status data;

[0012] The smart door lock is judged to be abnormal according to the target sensor data, target current data and target working status data of the target data, and the corresponding first result, second result and third result are obtained, and the first result, the second result and the third result are combined to obtain the target processing result.

[0013] Optionally, the fault diagnosis method of the smart door lock, wherein the abnormality judgment of the smart door lock is performed according to the target sensor data, the target current data and the target working state data of the target data respectively to obtain the corresponding first result, the second result and the third result, specifically includes:

[0014] Performing abnormality judgment on the mechanical component of the smart door lock according to the target sensor data to obtain a first result;

[0015] Comparing the target current data with a preset current threshold value to obtain a first comparison result, and judging an abnormality of the sensor module of the smart door lock according to the first comparison result to obtain a second result;

[0016] The target working state is compared with the preset module working state to obtain a second comparison result, and the module working state of the smart door lock is judged to be abnormal based on the second comparison result to obtain a third result.

[0017] Optionally, the fault diagnosis method of the smart door lock, wherein the obtaining of door lock log data according to the target processing result, performing data analysis on the door lock log data to obtain an analysis result, and performing identification processing on the analysis result to obtain an identification result, specifically includes:

[0018] Obtaining door lock log data according to the target processing result, performing format conversion on the door lock log data to obtain target door lock log data, and performing feature extraction on the target door lock log data to obtain fault feature information;

[0019] The fault characteristic information is compared with a preset fault chart to obtain an analysis result, information statistics are performed within a target time according to the analysis result to obtain a statistical result, and repeated abnormality identification is performed on the statistical result to obtain an identification result.

[0020] Optionally, the fault diagnosis method for the smart door lock, wherein the statistical results are repeatedly identified as abnormal to obtain an identification result, and then further comprises:

[0021] Determine whether the smart door lock has a potential fault according to the recognition result;

[0022] If the identification result is that the fault corresponding to the fault characteristic information is repeated, it is determined that the smart door lock has a potential fault;

[0023] If the identification result is that the fault corresponding to the fault characteristic information does not repeat, it is determined that the smart door lock does not have a fault.

[0024] Optionally, the fault diagnosis method of the smart door lock, wherein if it is determined according to the recognition result that the smart door lock has a potential fault, generating warning information and a corresponding solution strategy according to the recognition result, and pushing the warning information and the solution strategy to a target user, specifically includes:

[0025] If it is determined that the smart door lock has a potential fault according to the recognition result, corresponding warning information is generated according to the recognition result, and the statistical result is classified into fault categories to obtain the fault category;

[0026] Building a corresponding problem solving strategy library according to the fault category, searching the problem solving strategy library for the fault corresponding to the fault feature information, and obtaining a search result;

[0027] If the search result includes a solution strategy corresponding to the fault, the warning information and the solution strategy are pushed to the target user.

[0028] Optionally, the fault diagnosis method for the smart door lock, wherein the corresponding problem solving strategy library is constructed according to the fault category, and the fault corresponding to the fault feature information is searched for a strategy in the problem solving strategy library to obtain a search result, and then further comprises:

[0029] If the search result does not include a solution strategy corresponding to the fault, a corresponding no-strategy prompt is generated according to the search result, and the maintenance personnel are reminded to supplement the corresponding target solution strategy according to the no-strategy prompt.

[0030] Optionally, in the fault diagnosis method of the smart door lock, the fault diagnosis system of the smart door lock comprises:

[0031] A data processing module, used to obtain module operation data of the smart door lock, pre-process the module operation data to obtain target data, and perform data processing on the target data to obtain a target processing result;

[0032] A fault identification module, used to obtain door lock log data according to the target processing result, perform data analysis on the door lock log data to obtain an analysis result, and perform identification processing on the analysis result to obtain an identification result;

[0033] The information push module is used to generate warning information and corresponding solution strategies according to the recognition result if it is determined that the smart door lock has a potential fault according to the recognition result, and push the warning information and the solution strategy to the target user.

[0034] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and a fault diagnosis program for a smart door lock stored in the memory and executable on the processor, and when the fault diagnosis program for the smart door lock is executed by the processor, the steps of the fault diagnosis method for the smart door lock as described above are implemented.

[0035] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a fault diagnosis program for a smart door lock, and when the fault diagnosis program for a smart door lock is executed by a processor, the steps of the fault diagnosis method for a smart door lock as described above are implemented.

[0036] In the present invention, the module operation data of the smart door lock is obtained, the module operation data is preprocessed to obtain the target data, and the target data is processed to obtain the target processing result; the door lock log data is obtained according to the target processing result, the door lock log data is analyzed to obtain the analysis result, and the analysis result is identified to obtain the identification result; if it is determined that the smart door lock has a potential fault according to the identification result, then the warning information and the corresponding solution strategy are generated according to the identification result, and the warning information and the solution strategy are pushed to the target user. The present invention can make full use of the collected data to more accurately identify the abnormal faults and potential faults of the smart door lock, so that the potential faults can be discovered in advance, and the reliability and safety of the system are improved; when a potential fault is discovered, not only can the warning notification and problem solving strategy be sent to the operation and maintenance personnel and the target user, but also specific fault analysis and solution suggestions can be provided, thereby reducing the inconvenience and loss caused by sudden faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flow chart of a preferred embodiment of the fault diagnosis method of the intelligent door lock of the present invention;

[0038] Figure 2 It is a structural diagram of a preferred embodiment of the fault diagnosis system of the intelligent door lock of the present invention;

[0039] Figure 3 It is a structural diagram of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0041] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0042] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0043] The fault diagnosis method of the smart door lock described in the preferred embodiment of the present invention is as follows: Figure 1 As shown, the fault diagnosis method of the intelligent door lock includes the following steps:

[0044] Step S10: Acquire the module operation data of the smart door lock, pre-process the module operation data to obtain target data, and perform data processing on the target data to obtain a target processing result.

[0045] The step S10 comprises:

[0046] Step S11, when it is detected that the diagnosis time of the smart door lock reaches the preset time, the module operation data of the smart door lock is obtained, and the module operation data is filtered to obtain the target data, wherein the module operation data includes sensor data, current data and working status data;

[0047] Step S12: perform abnormality judgment on the smart door lock according to the target sensor data, target current data and target working status data of the target data, obtain corresponding first result, second result and third result, and combine the first result, the second result and the third result to obtain the target processing result.

[0048] Specifically, in an embodiment of the present invention, the modules used to implement the fault diagnosis method of the above-mentioned smart door lock include a smart door lock, a data collection and processing module, a log generation and storage module, a communication module, a cloud analysis module, an early warning notification module, a user terminal and an operation and maintenance terminal, and the smart door lock has built-in multiple sensors (for example, current sensors, mechanical state sensors, etc.) and controllers for real-time monitoring of the operating parameters of various modules of the smart door lock, wherein each module mainly includes a biometric module, a numeric keyboard module, a human body sensor module, a main control module and an audio and video module, and the corresponding operating parameters include the operating status and power consumption of the biometric module, the numeric keyboard module, the human body sensor module, the main control module and the audio and video module. The status includes whether the module exists (for example, whether the biometric module exists), whether the module works normally (for example, whether the biometric module is in working state) and whether the module generates an early warning (for example, calling the early warning code corresponding to the biometric module, where 01 is a communication abnormality, 02 is abnormal startup, 03 is a sleep failure, and 04 is a work timeout); when it is detected that the diagnosis time of the smart door lock reaches a preset time (for example, three days), the data collection and processing module obtains the module operation data of the smart door lock, wherein the module operation data includes sensor data, current data (i.e., the working current of each module detected) and working status data (i.e., the status returned by the sensor, for example, the status of the lock body working switch).

[0049] Afterwards, the data collection and processing module needs to perform preliminary data processing and analysis on the module operation data, specifically, filter the collected module operation data to obtain target data, the purpose of which is to filter out illegal and invalid data in the module operation data, such as out-of-range data, obviously fluctuating abnormal data, etc.; perform abnormality judgment on the smart door lock according to the target sensor data, target current data and target working status data of the target data, respectively, to obtain the corresponding first result, second result and third result, specifically, perform abnormality judgment on the mechanical components of the smart door lock according to the target sensor data, for example, whether the status of each sensor is normal when unlocking, and perform status detection on the sliding cover, handle, knob, etc. of the smart lock that needs to detect the status, to determine whether an abnormality occurs, and obtain the first result. Result; compare the target current data with the preset current threshold to obtain a first comparison result, and judge the sensor module of the smart door lock for abnormality according to the first comparison result to obtain a second result. For example, the current of the biometric module is not more than 15mA when working and not more than 10uA when sleeping. If the current data of the biometric module collected exceeds the threshold, it means that the biometric module is abnormal; compare the target working state with the preset module working state to obtain a second comparison result, and judge the module working state of the smart door lock for abnormality according to the second comparison result to obtain a third result, for example, whether there is any module startup failure, sleep failure, work failure, communication failure, etc.; and combine the first result, the second result and the third result to obtain the target processing result. The present invention does not require the user to manually initiate fault diagnosis of the smart door lock. The smart door lock will be automatically diagnosed within a predetermined time period. The various operating parameters of the lock are monitored in real time through the built-in sensor and controller, and the data is input into the data collection and processing module for screening, analysis and processing to identify valid data, thereby improving the recognition rate of whether the smart door lock is in an abnormal state.

[0050] Step S20: obtaining door lock log data according to the target processing result, performing data analysis on the door lock log data to obtain analysis results, and performing recognition processing on the analysis results to obtain recognition results.

[0051] The step S20 comprises:

[0052] Step S21, obtaining door lock log data according to the target processing result, performing format conversion on the door lock log data to obtain target door lock log data, and performing feature extraction on the target door lock log data to obtain fault feature information;

[0053] Step S22: compare the fault feature information with a preset fault chart to obtain an analysis result, perform information statistics within a target time according to the analysis result to obtain a statistical result, and perform repeated abnormality identification on the statistical result to obtain an identification result.

[0054] Specifically, after the data collection and processing module obtains the target processing result, the data collection and processing module inputs the target processing result into the log generation and storage module, and the log generation and storage module generates corresponding door lock log data from the target processing result, wherein the door lock log data includes but is not limited to timestamp, sensor reading, module working status, parameter change record and status change record and other logs, and stores the door lock log data; thereafter, the door lock log data needs to be further analyzed and processed, specifically, the communication module uploads the door lock log data to the cloud analysis module, wherein the communication used during uploading includes but is not limited to WiFi, Bluetooth, zigbee, and the communication module not only supports real-time data transmission, but also has power-off transmission resumption, data encryption, etc. to ensure the security and reliability of the data.

[0055] After the cloud analysis module receives the door lock log data, it uses big data analysis and machine learning algorithms to perform in-depth analysis on the door lock log data to identify anomalies and potential faults. Specifically, the cloud analysis module filters the door lock log data to remove repeated, invalid and obviously abnormal content to ensure the accuracy and consistency of the door lock log data. Subsequently, the filtered door lock log data is formatted into a format suitable for analysis by the cloud analysis module to obtain target door lock log data, for example, converting the hexadecimal data format into JSON format; and extracting features related to smart door lock operation failures from the target door lock log data to obtain fault feature information, such as error codes, power consumption distribution, and working status of each module. Afterwards, the fault feature information is compared with a preset fault chart (during the development process, fault data indicators will be modeled for different products and corresponding modules to construct corresponding fault reference charts, i.e., preset fault charts) to obtain analysis results; information statistics are performed within a target time (e.g., 3 days) based on the analysis results to obtain statistical results in order to determine whether the statistical information is repeatable; and repeated anomalies are identified on the statistical results to obtain identification results; the present invention uses big data analysis and machine learning algorithms through a cloud analysis module to perform in-depth analysis of the uploaded door lock log data and identify abnormal situations, so as to discover potential faults in advance, thereby making full use of the collected data and improving the reliability of fault analysis.

[0056] Furthermore, it is determined whether the smart door lock has a potential fault based on the recognition result; if the recognition result is that the fault corresponding to the fault characteristic information is repeated, it is determined that the smart door lock has a potential fault; if the recognition result is that the fault corresponding to the fault characteristic information is not repeated, it is determined that the smart door lock does not have a fault.

[0057] Step S30: If it is determined that the smart door lock has a potential fault according to the recognition result, a warning message and a corresponding solution strategy are generated according to the recognition result, and the warning message and the solution strategy are pushed to the target user.

[0058] The step S30 comprises:

[0059] Step S31: if it is determined that the smart door lock has a potential fault according to the recognition result, corresponding warning information is generated according to the recognition result, and the statistical result is classified into fault categories to obtain the fault category;

[0060] Step S32: construct a corresponding problem solving strategy library according to the fault category, and perform a strategy search on the problem solving strategy library for the fault corresponding to the fault feature information to obtain a search result;

[0061] Step S33: If the search result includes a solution strategy corresponding to the fault, the warning information and the solution strategy are pushed to the target user.

[0062] Specifically, if it is determined that the smart door lock has a potential fault according to the identification result, the cloud analysis module generates corresponding warning information according to the identification result, and classifies the statistical results to obtain a fault category, wherein the fault category includes mechanical fault, electronic component fault and software system fault, and the purpose of fault classification is to facilitate finding the corresponding solution strategy; thereafter, a corresponding problem-solving strategy library is constructed according to the fault category, and the fault corresponding to the fault feature information is subjected to a strategy search in the problem-solving strategy library to obtain a search result; if the search result contains a solution strategy corresponding to the fault, for example, the corresponding fault is that the WIFI communication module of the smart door lock has repeatedly experienced high power consumption and has not returned to normal for many consecutive days, and the solution strategy found is to check the distance between the router and the smart door lock, check the WIFI signal strength and re-configure the network, etc., then the early warning notification module will The warning information and the solution strategy are sent to the user terminal of the target user, and the user terminal receives and displays the warning information and the solution strategy, and provides remote monitoring, fault diagnosis and repair service entrances, so that the target user can solve the corresponding fault according to the solution strategy; if the target user fails to solve the fault, an after-sales warning is generated to remind the user to contact after-sales to handle the problem, and the operation and maintenance terminal pushes the warning information and the solution strategy to after-sales maintenance personnel to remind the maintenance personnel to solve the fault; the present invention provides a remote monitoring, fault diagnosis and repair service entrance on the user terminal of the target user. When a potential fault is found, not only a warning notification and a problem-solving strategy are sent to the target user and maintenance personnel, but also specific fault analysis and solution suggestions are provided, which can reduce the inconvenience and loss caused by sudden faults, thereby improving the user experience and making the user feel more at ease and convenient during use.

[0063] Furthermore, if the search result does not include a solution strategy corresponding to the fault, the cloud analysis module generates a corresponding no-strategy prompt based on the search result, and the early warning notification module sends the no-strategy prompt to the operation and maintenance terminal to remind maintenance personnel to supplement the corresponding target solution strategy, thereby achieving the purpose of optimizing the problem-solving strategy library.

[0064] Furthermore, if Figure 2 As shown, based on the above-mentioned fault diagnosis method of the smart door lock, the present invention also provides a fault diagnosis system of the smart door lock, wherein the fault diagnosis system of the smart door lock comprises:

[0065] The data processing module 51 is used to obtain the module operation data of the smart door lock, pre-process the module operation data to obtain target data, and perform data processing on the target data to obtain a target processing result;

[0066] A fault identification module 52 is used to obtain door lock log data according to the target processing result, perform data analysis on the door lock log data to obtain an analysis result, and perform identification processing on the analysis result to obtain an identification result;

[0067] The information push module 53 is used to generate warning information and corresponding solution strategies according to the recognition result if it is determined that the smart door lock has a potential fault according to the recognition result, and push the warning information and the solution strategy to the target user.

[0068] The present invention provides a fault diagnosis system for a smart door lock. The present invention can make full use of the collected data to more accurately identify abnormal faults and potential faults of the smart door lock, so that potential faults can be discovered in advance, thereby improving the reliability and safety of the system; when potential faults are discovered, not only can early warning notifications and problem-solving strategies be sent to operation and maintenance personnel and target users, but specific fault analysis and solution suggestions can also be provided, thereby reducing the inconvenience and losses caused by sudden faults.

[0069] Furthermore, if Figure 3 As shown, based on the above-mentioned fault diagnosis method of the smart door lock, the present invention also provides a terminal accordingly, and the terminal includes a processor 10, a memory 20 and a display 30. Figure 3 Only some components of the terminal are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0070] The memory 20 may be an internal storage unit of the terminal in some embodiments, such as a hard disk or memory of the terminal. The memory 20 may also be an external storage device of the terminal in other embodiments, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed in the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a fault diagnosis program 40 of a smart door lock is stored on the memory 20, and the fault diagnosis program 40 of the smart door lock can be executed by the processor 10, thereby realizing the fault diagnosis method of the smart door lock in the present application.

[0071] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 20, such as executing the fault diagnosis method of the smart door lock.

[0072] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 30 is used to display information on the terminal and to display a visual user interface. The components 10-30 of the terminal communicate with each other via a system bus.

[0073] In one embodiment, when the processor 10 executes the fault diagnosis program 40 of the smart door lock in the memory 20, the following steps are implemented:

[0074] Acquire module operation data of the smart door lock, pre-process the module operation data to obtain target data, and perform data processing on the target data to obtain a target processing result;

[0075] Obtaining door lock log data according to the target processing result, performing data analysis on the door lock log data to obtain an analysis result, and performing recognition processing on the analysis result to obtain a recognition result;

[0076] If it is determined that the smart door lock has a potential fault according to the recognition result, a warning message and a corresponding solution strategy are generated according to the recognition result, and the warning message and the solution strategy are pushed to the target user.

[0077] The obtaining of the module operation data of the smart door lock, preprocessing the module operation data to obtain target data, and performing data processing on the target data to obtain a target processing result specifically includes:

[0078] When it is detected that the diagnosis time of the smart door lock reaches the preset time, the module operation data of the smart door lock is obtained, and the module operation data is filtered to obtain the target data, wherein the module operation data includes sensor data, current data and working status data;

[0079] The smart door lock is judged to be abnormal according to the target sensor data, target current data and target working status data of the target data, and the corresponding first result, second result and third result are obtained, and the first result, the second result and the third result are combined to obtain the target processing result.

[0080] Among them, the abnormality judgment of the smart door lock is performed according to the target sensor data, the target current data and the target working state data of the target data, and the corresponding first result, second result and third result are obtained, which specifically include:

[0081] Performing abnormality judgment on the mechanical component of the smart door lock according to the target sensor data to obtain a first result;

[0082] Comparing the target current data with a preset current threshold value to obtain a first comparison result, and judging an abnormality of the sensor module of the smart door lock according to the first comparison result to obtain a second result;

[0083] The target working state is compared with the preset module working state to obtain a second comparison result, and the module working state of the smart door lock is judged to be abnormal based on the second comparison result to obtain a third result.

[0084] Wherein, obtaining door lock log data according to the target processing result, performing data analysis on the door lock log data to obtain analysis results, and performing identification processing on the analysis results to obtain identification results, specifically includes:

[0085] Obtaining door lock log data according to the target processing result, performing format conversion on the door lock log data to obtain target door lock log data, and performing feature extraction on the target door lock log data to obtain fault feature information;

[0086] The fault characteristic information is compared with a preset fault chart to obtain an analysis result, information statistics are performed within a target time according to the analysis result to obtain a statistical result, and repeated abnormality identification is performed on the statistical result to obtain an identification result.

[0087] The step of repeatedly identifying anomalies on the statistical results to obtain an identification result further includes:

[0088] Determine whether the smart door lock has a potential fault according to the recognition result;

[0089] If the identification result is that the fault corresponding to the fault characteristic information is repeated, it is determined that the smart door lock has a potential fault;

[0090] If the identification result is that the fault corresponding to the fault characteristic information does not repeat, it is determined that the smart door lock does not have a fault.

[0091] If it is determined that the smart door lock has a potential fault according to the recognition result, then generating warning information and a corresponding solution strategy according to the recognition result, and pushing the warning information and the solution strategy to the target user, specifically includes:

[0092] If it is determined that the smart door lock has a potential fault according to the recognition result, corresponding warning information is generated according to the recognition result, and the statistical result is classified into fault categories to obtain the fault category;

[0093] Building a corresponding problem solving strategy library according to the fault category, searching the problem solving strategy library for the fault corresponding to the fault feature information, and obtaining a search result;

[0094] If the search result includes a solution strategy corresponding to the fault, the warning information and the solution strategy are pushed to the target user.

[0095] The method further comprises: building a corresponding problem solving strategy library according to the fault category, searching the problem solving strategy library for the fault corresponding to the fault feature information, and obtaining a search result; and then:

[0096] If the search result does not include a solution strategy corresponding to the fault, a corresponding no-strategy prompt is generated according to the search result, and the maintenance personnel are reminded to supplement the corresponding target solution strategy according to the no-strategy prompt.

[0097] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a fault diagnosis program for a smart door lock, and when the fault diagnosis program for the smart door lock is executed by a processor, the steps of the fault diagnosis method for the smart door lock as described above are implemented.

[0098] In summary, the present invention provides a fault diagnosis method, system, terminal and storage medium for a smart door lock, the method comprising: obtaining module operation data of the smart door lock, preprocessing the module operation data to obtain target data, and performing data processing on the target data to obtain a target processing result; obtaining door lock log data according to the target processing result, performing data analysis on the door lock log data to obtain an analysis result, and performing identification processing on the analysis result to obtain an identification result; if it is determined that the smart door lock has a potential fault according to the identification result, then generating early warning information and corresponding solution strategies according to the identification result, and pushing the early warning information and the solution strategies to the target user. The present invention can make full use of the collected data to more accurately identify abnormal faults and potential faults of smart door locks, so that potential faults can be discovered in advance, improving the reliability and safety of the system; it can also send early warning notifications and problem solving strategies to operation and maintenance personnel and target users when potential faults are discovered, and also provide specific fault analysis and solution suggestions, thereby reducing the inconvenience and losses caused by sudden faults.

[0099] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or terminal including the element.

[0100] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium that can be read by a computer, and the program can include the processes of the above-mentioned method embodiments when executed. The computer-readable storage medium can be a memory, a disk, an optical disk, etc.

[0101] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A fault diagnosis method for an intelligent door lock, characterized in that: The fault diagnosis method of the intelligent door lock comprises: Acquire module operation data of the smart door lock, pre-process the module operation data to obtain target data, and perform data processing on the target data to obtain a target processing result; Obtaining door lock log data according to the target processing result, performing data analysis on the door lock log data to obtain an analysis result, and performing recognition processing on the analysis result to obtain a recognition result; If it is determined that the smart door lock has a potential fault according to the recognition result, a warning message and a corresponding solution strategy are generated according to the recognition result, and the warning message and the solution strategy are pushed to the target user.

2. The fault diagnosis method of the intelligent door lock according to claim 1, characterized in that: The obtaining of the module operation data of the smart door lock, preprocessing the module operation data to obtain target data, and performing data processing on the target data to obtain a target processing result specifically includes: When it is detected that the diagnosis time of the smart door lock reaches the preset time, the module operation data of the smart door lock is obtained, and the module operation data is filtered to obtain the target data, wherein the module operation data includes sensor data, current data and working status data; The smart door lock is judged to be abnormal according to the target sensor data, target current data and target working status data of the target data, and the corresponding first result, second result and third result are obtained, and the first result, the second result and the third result are combined to obtain the target processing result.

3. The fault diagnosis method of the intelligent door lock according to claim 2, characterized in that: The method of performing abnormality judgment on the smart door lock according to the target sensor data, the target current data and the target working state data of the target data to obtain the corresponding first result, the second result and the third result specifically includes: Performing abnormality judgment on the mechanical component of the smart door lock according to the target sensor data to obtain a first result; Comparing the target current data with a preset current threshold value to obtain a first comparison result, and judging an abnormality of the sensor module of the smart door lock according to the first comparison result to obtain a second result; The target working state is compared with the preset module working state to obtain a second comparison result, and the module working state of the smart door lock is judged to be abnormal based on the second comparison result to obtain a third result.

4. The fault diagnosis method of the intelligent door lock according to claim 1, characterized in that: The obtaining of door lock log data according to the target processing result, performing data analysis on the door lock log data to obtain an analysis result, and performing identification processing on the analysis result to obtain an identification result specifically includes: Obtaining door lock log data according to the target processing result, performing format conversion on the door lock log data to obtain target door lock log data, and performing feature extraction on the target door lock log data to obtain fault feature information; The fault characteristic information is compared with a preset fault chart to obtain an analysis result, information statistics are performed within a target time according to the analysis result to obtain a statistical result, and repeated abnormality identification is performed on the statistical result to obtain an identification result.

5. The fault diagnosis method of the intelligent door lock according to claim 4, characterized in that: Repeating the abnormality identification on the statistical results to obtain the identification results further includes: Determine whether the smart door lock has a potential fault according to the recognition result; If the identification result is that the fault corresponding to the fault characteristic information is repeated, it is determined that the smart door lock has a potential fault; If the identification result is that the fault corresponding to the fault characteristic information does not repeat, it is determined that the smart door lock does not have a fault.

6. The fault diagnosis method of the intelligent door lock according to claim 5, characterized in that: If it is determined according to the recognition result that the smart door lock has a potential fault, then generating warning information and a corresponding solution strategy according to the recognition result, and pushing the warning information and the solution strategy to the target user, specifically includes: If it is determined that the smart door lock has a potential fault according to the recognition result, corresponding warning information is generated according to the recognition result, and the statistical result is classified into fault categories to obtain the fault category; Building a corresponding problem solving strategy library according to the fault category, searching the problem solving strategy library for the fault corresponding to the fault feature information, and obtaining a search result; If the search result includes a solution strategy corresponding to the fault, the warning information and the solution strategy are pushed to the target user.

7. The fault diagnosis method of the intelligent door lock according to claim 6, characterized in that: The method further comprises: constructing a corresponding problem solving strategy library according to the fault category, searching the problem solving strategy library for the fault corresponding to the fault feature information, and obtaining a search result; and then: If the search result does not include a solution strategy corresponding to the fault, a corresponding no-strategy prompt is generated according to the search result, and the maintenance personnel are reminded to supplement the corresponding target solution strategy according to the no-strategy prompt.

8. A fault diagnosis system for an intelligent door lock, characterized in that: The fault diagnosis system of the intelligent door lock comprises: A data processing module, used to obtain module operation data of the smart door lock, pre-process the module operation data to obtain target data, and perform data processing on the target data to obtain a target processing result; A fault identification module, used to obtain door lock log data according to the target processing result, perform data analysis on the door lock log data to obtain an analysis result, and perform identification processing on the analysis result to obtain an identification result; The information push module is used to generate warning information and corresponding solution strategies according to the recognition result if it is determined that the smart door lock has a potential fault according to the recognition result, and push the warning information and the solution strategy to the target user.

9. A terminal, characterized in that: The terminal includes: a memory, a processor, and a fault diagnosis program for a smart door lock stored in the memory and executable on the processor. When the fault diagnosis program for a smart door lock is executed by the processor, the steps of the fault diagnosis method for a smart door lock as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a fault diagnosis program for a smart door lock, and when the fault diagnosis program for a smart door lock is executed by a processor, the steps of the fault diagnosis method for a smart door lock as described in any one of claims 1 to 7 are implemented.

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