A method, system, device and medium for monitoring the operating state of a shared massage chair

Abstract

The present invention relates to a method, system, device and medium for monitoring the operating state of a shared massage chair. The method includes the following steps: collecting the operating data of the shared massage chair and preprocessing the operating data of the shared massage chair; constructing a feature extraction model for operating data, and extracting the features of the operating data of the shared massage chair based on the preprocessed operating data of the shared massage chair; constructing a feature deviation correction model to correct the features of the operating data of the shared massage chair; constructing a life evaluation model for the shared massage chair, and evaluating the life of the shared massage chair based on the preprocessed operating data of the shared massage chair; weighted summing the corrected features of the operating data of the shared massage chair and the life evaluation result of the shared massage chair to obtain a comprehensive health state evaluation result of the shared massage chair, and giving an early warning when the comprehensive health state of the shared massage chair reaches a preset threshold.

Description

Technical Field

[0001] The present invention relates to a method, system, device and medium for monitoring the operating state of a shared massage chair, and belongs to the technical field of massage chair state monitoring. Background Art

[0002] Currently, for the operating state monitoring and fault prediction of massage chairs and similar shared devices, the following technical means are generally adopted:

[0003] Most existing systems rely on single or a few sensors (such as temperature sensors, pressure sensors or vibration sensors), and judge the device state by collecting single-item data; this method lacks the fusion of multi-dimensional data and is prone to ignoring the comprehensive effects brought by different working environments and multi-component interactions.

[0004] Existing monitoring systems usually set fixed thresholds and trigger alarms when the sensor data exceeds or is lower than the preset value; this method is difficult to adapt to the situations of equipment aging, environmental changes or diverse usage patterns, and is prone to false alarms or missed alarms.

[0005] Some systems only rely on traditional signal analysis methods, such as Fourier transform, filtering technology, etc. for anomaly detection, ignoring the coupling effects between multiple subsystems inside the device (such as the main motor, transmission system, cushion, heating system, etc.), and it is difficult to identify complex fault patterns in a timely manner.

[0006] Most current monitoring schemes adopt preset parameters and static models, and lack the adaptive ability to judge the operating conditions of the device, and it is difficult to cope with parameter drift and sudden failures after the device has been running for a long time. Summary of the Invention

[0007] In order to solve the problems existing in the above-mentioned prior art, the present invention proposes a method, system, device and medium for monitoring the operating state of a shared massage chair.

[0008] The technical solution of the present invention is as follows:

[0009] On the one hand, the present invention provides a method for monitoring the operating state of a shared massage chair, including the following steps:

[0010] Collect the operating data of the shared massage chair and preprocess the operating data of the shared massage chair;

[0011] Construct an operating data feature extraction model, and extract the features of the operating data of the shared massage chair based on the preprocessed operating data of the shared massage chair;

[0012] Construct a feature deviation correction model to correct the features of the operating data of the shared massage chair;

[0013] Build a life evaluation model for shared massage chairs, and evaluate the life of shared massage chairs based on the preprocessed operation data of shared massage chairs;

[0014] Weighted sum the characteristics of the corrected operation data of the shared massage chair and the life evaluation result of the shared massage chair to obtain the comprehensive health status evaluation result of the shared massage chair, and give an alarm when the comprehensive health status of the shared massage chair reaches the preset threshold.

[0015] Furthermore, the operation data feature extraction model is specifically shown as the following formula:

[0016] ;

[0017] Where: represents the result of extracting the operation data features of the shared massage chair; represents the total number of monitoring sensors; represents the initial weight of the th monitoring sensor; represents the adjustment value of the th monitoring sensor; represents the operation data of the shared massage chair at the represents the total number of modulation periods of the th monitoring sensor; represents the amplitude of the th modulation period of the th monitoring sensor; represents the angular frequency of the th modulation period of the th monitoring sensor; represents the

[0018] Furthermore, the feature deviation correction model is specifically shown as the following formula:

[0019] ;

[0020] Where: represents the result of correcting the features of the operation data of the shared massage chair; represents the total number of key parameters in the operation data features of the shared massage chair; represents the correction coefficient of the th key parameter; represents the adaptive factor of the th key parameter at the The value of a key parameter; Denote the ideal calibration value of the key parameter value; Denote the sensitivity coefficient of the key parameter value; Denote the normalization coefficient of the key parameter value.

[0021] Furthermore, the shared massage chair life evaluation model is specifically shown as the following formula:

[0022] ;

[0023] Where: Denote the shared massage chair life evaluation result; Denote the number of shared massage chair subsystem; Denote the th subsystem of the shared massage chair at the time state index; Denote the th ideal state index of the shared massage chair subsystem; Denote the th weight of the shared massage chair subsystem; Denote the th historical failure times of the shared massage chair subsystem.

[0024] Furthermore, collect the environmental data and historical abnormal data of the shared massage chair, and construct the environment and abnormal correction factor based on the environmental data and historical abnormal data of the shared massage chair, specifically shown as the following formula:

[0025] ;

[0026] Where: Denote the environment and abnormal correction factor; Denote the scaling coefficient; Denote the amplitude influence factor; Denote the difference between the environmental temperature and the optimal working temperature of the shared massage chair; Denote up to the time failure frequency of the shared massage chair; Denote the adjustment coefficient; Denote the predicted failure probability of the shared massage chair;

[0027] Add the environment and abnormal correction factor to the comprehensive health state evaluation result of the shared massage chair to obtain the corrected comprehensive health state evaluation result of the shared massage chair.

[0028] Further, a fault classification model is constructed based on a support vector machine, and the faults of the shared massage chair are classified based on the comprehensive health status evaluation result of the modified shared massage chair.

[0029] On the other hand, the present invention also provides a shared massage chair operating state monitoring system, including a data acquisition module, a feature extraction module, a feature correction module, a life evaluation module, and a health status evaluation module;

[0030] The data acquisition module is used to collect the operating data of the shared massage chair and preprocess the operating data of the shared massage chair;

[0031] The feature extraction module is used to construct a feature extraction model for operating data, and extract the features of the operating data of the shared massage chair based on the preprocessed operating data of the shared massage chair;

[0032] The feature correction module is used to construct a feature deviation correction model to correct the features of the operating data of the shared massage chair;

[0033] The life evaluation module is used to construct a life evaluation model for the shared massage chair, and evaluate the life of the shared massage chair based on the preprocessed operating data of the shared massage chair;

[0034] The health status evaluation module is used to perform a weighted sum of the features of the corrected operating data of the shared massage chair and the life evaluation result of the shared massage chair to obtain the comprehensive health status evaluation result of the shared massage chair, and give an early warning when the comprehensive health status of the shared massage chair reaches a preset threshold.

[0035] On yet another aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements a shared massage chair operating state monitoring method as described in the present invention.

[0036] On yet another aspect, the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements a shared massage chair operating state monitoring method as described in the present invention.

[0037] The present invention has the following beneficial effects:

[0038] The present invention performs multi-level fusion of various sensor data and the states of various subsystems, not only considering individual deviations, but also taking into account the overall coordination effect of the device, realizing a refined quantitative evaluation of the device's health status. At the same time, machine learning technology is introduced to update weights and correction parameters in real time, overcoming the limitations of traditional static models. By integrating multiple sensors such as pressure, temperature, and vibration, comprehensive monitoring of each key component of the device is achieved, forming multi-dimensional data input, and significantly improving the comprehensiveness and accuracy of device state evaluation. Description of the Drawings

[0039] Figure 1 This is a flowchart of the method of the present invention. Detailed Embodiments

[0040] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0041] It should be understood that the step numbers used in the text are only for convenient description and do not limit the execution order of the steps.

[0042] It should be understood that the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0043] The terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0044] The term " / and / " refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0045] Embodiment 1:

[0046] Refer to Figure 1 , a method for monitoring the operating state of a shared massage chair, comprising the following steps:

[0047] Collect the operating data of the shared massage chair and preprocess the operating data of the shared massage chair;

[0048] Construct a feature extraction model for the operating data, and extract the features of the operating data of the shared massage chair based on the preprocessed operating data of the shared massage chair;

[0049] Construct a feature deviation correction model to correct the features of the operating data of the shared massage chair;

[0050] Construct a life evaluation model for the shared massage chair, and evaluate the life of the shared massage chair based on the preprocessed operating data of the shared massage chair;

[0051] The characteristic of the corrected operation data of the shared massage chair and the result of the shared massage chair life evaluation are weighted and summed to obtain the comprehensive health status evaluation result of the shared massage chair. When the comprehensive health status of the shared massage chair reaches a preset threshold, a warning is issued.

[0052] As a preferred embodiment of this embodiment, the operation data feature extraction model is specifically shown as follows:

[0053] ;

[0054] Where: Represents the result of the operation data feature extraction of the shared massage chair; Represents the total number of monitoring sensors; Represents the Initial weight of the th monitoring sensor, reflecting the importance of various sensor data in the overall health status evaluation, and the initial value can be set by experiments; Represents the adjustment value of the th monitoring sensor, which is adjusted according to different models of shared massage chairs through a machine learning model; Represents The operation data of the shared massage chair at the th moment (the operation data of the shared massage chair is collected by monitoring sensors, including seat cushion pressure, backrest force, vibration amplitude, historical faults, motor status, transmission status, heating system status, control unit status, communication module status); Represents the total number of modulation periods of the th monitoring sensor; Represents the th amplitude of the th monitoring sensor in the th modulation period; Represents the angular frequency of the th monitoring sensor in the th modulation period, which is used to capture periodic features within a specific frequency band; Represents the phase shift of the th monitoring sensor in the th modulation period, which is used to correct the starting position of the signal;

[0055] As a preferred embodiment of this embodiment, the feature deviation correction model is specifically shown as follows:

[0056] ;

[0057] Where: Indicates the characteristic correction result of the shared massage chair operation data; Indicates the total number of key parameters in the shared massage chair operation data characteristics. The key parameters are specifically those that can significantly affect the normal operation of the massage chair, including main motor current, component temperature, vibration peak value, etc.; Indicates the correction coefficient of the th key parameter, which is mainly estimated preliminarily based on experimental data; Indicates the adaptive factor of the th key parameter; Indicates the value of the th key parameter at the time; Indicates the ideal calibration value of the th key parameter value; Indicates the sensitivity coefficient of the

[0058] th key parameter value; And

[0059] th key parameter and its reference value are collected for a long time under normal and abnormal operating conditions of the massage chair, as well as the corresponding health status indicators or fault records; Determine the calibration value of the device in the ideal state based on experimental measurements to provide a basis for subsequent calculations;

[0060] Construct an error model:

[0061] Define the error term ;

[0062] Establish the model for predicting the failure probability of the massage chair, as shown in the following formula:

[0063] ;

[0064] Define the loss function :

[0065] ;

[0066] Where: Indicates the actual failure probability corresponding to the value of the th key parameter at the

[0067] Use the gradient descent method, genetic algorithm or other optimization algorithms to find And The optimal value of

[0068] As a preferred implementation manner of this embodiment, the shared massage chair life evaluation model is specifically shown as follows:

[0069] ;

[0070] Where: represents the evaluation result of the shared massage chair life; represents the number of the shared massage chair subsystem; represents the th subsystem of the shared massage chair at the moment state index; represents the th ideal state index of the shared massage chair subsystem; represents the th weight of the shared massage chair subsystem; represents the th historical failure times of the shared massage chair subsystem;

[0071] In this embodiment, the shared massage chair subsystem specifically includes: a main power system, a transmission system, a cushion system, a heating system, a control unit system, and a communication system;

[0072] The calculation formula for the state index of the main power system is:

[0073] ;

[0074] Where: represents the state index of the main power system at the represents the rotational speed of the main motor at the moment; represents the ideal rotational speed of the main motor; represents the working current of the main motor at the moment; represents the ideal working current of the main motor; represents the working temperature of the main motor at the moment; represents the ideal working temperature of the main motor; represents the working vibration amplitude of the main motor at the moment; represents the ideal working vibration amplitude of the main motor; represents the cumulative running time of the main motor up to the moment;

[0075] The calculation formula for the state index of the transmission system is:

[0076] ;

[0077] Wherein: represents the state index of the transmission system at a moment; represents the transmission system the actual value of the key torque or rotational speed index at a moment, specifically including the motor output rotational speed (the initial rotational speed directly provided by the motor, reflecting the driving ability of the motor), the gear set output rotational speed (the actual output rotational speed after gear transmission, closely related to the transmission ratio, used to evaluate the efficiency of the transmission system), the input and output torques (input torque: the driving force transmitted by the motor to the transmission system, output torque: the actual working torque transmitted to the massage mechanism (such as massage heads, massage pads, etc.), directly affecting the massage effect and the equipment load); represents the ideal value of the key torque or rotational speed index of the transmission system; represents the amplitude of the transmission vibration at a moment; represents the ideal amplitude of the transmission vibration; represents the degree of wear of the gear set at a moment; represents the lubrication treatment of the gear set at a moment;

[0078] The calculation formula for the state index of the gasket system is:

[0079] ;

[0080] Wherein: represents the state index of the gasket system at a moment; represents the cumulative degree of wear of the gasket at a moment; represents the maximum allowable wear of the gasket; represents the pressure distribution of the gasket at a moment; represents the elastic modulus of the gasket;

[0081] The calculation formula for the state index of the heating system is:

[0082] ;

[0083] Wherein: represents the state index of the heating system at a moment; represents the heating temperature of the heating system at a moment; represents the target temperature of the heating system at a moment; represents Resistance deviation of the heating element of the moment heating system; Indicates the response time of the heating system;

[0084] The state index calculation formula of the control unit system is:

[0085] ;

[0086] Where: Indicates The state index of the control unit system at the moment; Indicates The CPU load at the moment; Indicates The deviation between the control response delay and the ideal value at the moment; Indicates up to The cumulative number of abnormal instruction executions at the moment;

[0087] The state index calculation formula of the communication system is:

[0088] ;

[0089] Where: Indicates The state index of the communication system at the moment; Indicates The signal strength of the communication system at the moment; Indicates the communication strength threshold of the communication system; Indicates The packet loss rate of the communication system at the moment; Indicates The communication interference level at the moment (such as noise index or interference signal amplitude); Indicates The communication delay of the communication system at the moment.

[0090] As a preferred implementation mode of this embodiment, the environmental data and historical abnormal data of the shared massage chair are collected, and an environment and anomaly correction factor is constructed based on the environmental data and historical abnormal data of the shared massage chair, as shown in the following formula:

[0091] ;

[0092] Where: Indicates the environment and anomaly correction factor; Indicates the scaling coefficient; Indicates the amplitude influence factor; Indicates the difference between the environmental temperature and the optimal working temperature of the shared massage chair; Indicates up to The failure frequency of the shared massage chair is shared in real time and calculated based on the historical failure data of the shared massage chair; represents an adjustment coefficient; represents the predicted failure probability of the shared massage chair;

[0093] Add the environmental and anomaly correction factors to the comprehensive health status assessment result of the shared massage chair to obtain the corrected comprehensive health status assessment result of the shared massage chair.

[0094] As a preferred implementation manner of this embodiment, a failure classification model is constructed based on a support vector machine, and the failures of the shared massage chair are classified based on the corrected comprehensive health status assessment result of the shared massage chair;

[0095] According to the classification results, early warning prompts can be given for minor failures, maintenance scheduling can be automatically triggered for medium and serious failures, and historical data is recorded for subsequent model optimization and maintenance decision-making reference.

[0096] Embodiment 2:

[0097] A shared massage chair operating state monitoring system includes a data acquisition module, a feature extraction module, a feature correction module, a life assessment module, and a health status assessment module;

[0098] The data acquisition module is used to collect the operating data of the shared massage chair and preprocess the operating data of the shared massage chair;

[0099] The feature extraction module is used to construct a feature extraction model for operating data and extract the features of the operating data of the shared massage chair based on the preprocessed operating data of the shared massage chair;

[0100] The feature correction module is used to construct a feature deviation correction model to correct the features of the operating data of the shared massage chair;

[0101] The life assessment module is used to construct a life assessment model for the shared massage chair and assess the life of the shared massage chair based on the preprocessed operating data of the shared massage chair;

[0102] The health status assessment module is used to perform a weighted sum of the corrected features of the operating data of the shared massage chair and the life assessment result of the shared massage chair to obtain the comprehensive health status assessment result of the shared massage chair, and give an early warning when the comprehensive health status of the shared massage chair reaches a preset threshold.

[0103] This system is used to implement the method in Embodiment 1 and will not be elaborated here.

[0104] Embodiment 3:

[0105] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the method described in any embodiment of the present invention is implemented.

[0106] Embodiment 4:

[0107] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the method described in any embodiment of the present invention is implemented.

[0108] In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent the case where A exists alone, A and B exist simultaneously, or B exists alone. Where A and B may be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following" and its similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, and c may represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c may be single or multiple.

[0109] Those of ordinary skill in the art can realize that the units and algorithm steps described in the embodiments disclosed herein can be implemented by a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0110] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be described herein again.

[0111] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0112] The above are only the embodiments of the present invention, and thus do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall equally be included in the patent protection scope of the present invention.

Claims

1. A method for monitoring the operating status of a shared massage chair, characterized in that: The following steps are involved: Collecting and preprocessing the shared massage chair operation data; An operation data feature extraction model is constructed to extract the features of the shared massage chair operation data based on the preprocessed shared massage chair operation data. The operation data feature extraction model is specifically shown in the following formula: ； in: Indicates the feature extraction results of the shared massage chair operation data; Indicates the total number of monitoring sensors; Indicates The initial weights of the monitoring sensors; Indicates A monitoring sensor adjustment value; Indicates the starting time; express Share massage chair operation data at all times; Indicates The total number of modulation cycles of the monitoring sensors; Indicates Monitoring sensor No. The amplitude of each modulation cycle; Indicates Monitoring sensor No. The angular frequency of the modulation cycle; Indicates Monitoring sensor No. The phase shift of each modulation cycle; Indicates the end time; A feature deviation correction model is constructed to correct the features of the shared massage chair operation data. The feature deviation correction model is specifically shown in the following formula: ； in: Indicates the feature correction result of the shared massage chair operation data; Represents the total number of key parameters in the shared massage chair operation data characteristics; Indicates Correction factors for key parameters; Indicates Adaptive factors of key parameters; express The moment Key parameter values; Indicates The ideal calibration value of each key parameter; Indicates Sensitivity coefficients of key parameter values; Indicates Normalization coefficients of key parameter values; A shared massage chair life assessment model is constructed to assess the life of the shared massage chair based on the preprocessed shared massage chair operation data. The shared massage chair life assessment model is specifically shown in the following formula: ； in: Indicates the results of the life assessment of shared massage chairs; Indicates the number of shared massage chair systems; Shared massage chair Subsystems in Status indicators at all times; Shared massage chair The ideal state indicator of each subsystem; Shared massage chair The weight of each subsystem; Shared massage chair The number of historical failures of each subsystem; The weighted sum of the features of the corrected shared massage chair operation data and the shared massage chair life assessment results is used to obtain the comprehensive health status assessment result of the shared massage chair. When the comprehensive health status of the shared massage chair reaches a preset threshold, an early warning is issued.

2. A method for monitoring the operation status of a shared massage chair according to claim 1, characterized in that: Collect the environmental data and historical abnormal data of the shared massage chair, and build the environmental and abnormal correction factors based on the environmental data and historical abnormal data of the shared massage chair, as shown in the following formula: ； in: Indicates environmental and abnormal correction factors; represents the scaling factor; represents the amplitude influence factor; Indicates the difference between the ambient temperature and the optimal operating temperature of the shared massage chair; Indicates to The frequency of massage chair failures is shared moment by moment; represents the adjustment coefficient; represents the predicted failure probability of the shared massage chair; The environmental and abnormal correction factors are added to the comprehensive health status assessment result of the shared massage chair to obtain the corrected comprehensive health status assessment result of the shared massage chair.

3. A method for monitoring the operation status of a shared massage chair according to claim 2, characterized in that: A fault classification model was constructed based on support vector machine, and the faults of shared massage chairs were classified based on the revised comprehensive health status assessment results of shared massage chairs.

4. A shared massage chair operation status monitoring system, characterized in that: It includes data acquisition module, feature extraction module, feature correction module, life span assessment module and health status assessment module; The data acquisition module is used to collect the shared massage chair operation data and pre-process the shared massage chair operation data; The feature extraction module is used to construct an operation data feature extraction model, and extract the features of the shared massage chair operation data based on the preprocessed shared massage chair operation data. The operation data feature extraction model is specifically shown in the following formula: ； in: Indicates the feature extraction results of the shared massage chair operation data; Indicates the total number of monitoring sensors; Indicates The initial weights of the monitoring sensors; Indicates A monitoring sensor adjustment value; Indicates the starting time; express Share massage chair operation data at all times; Indicates The total number of modulation cycles of the monitoring sensors; Indicates Monitoring sensor No. The amplitude of each modulation cycle; Indicates Monitoring sensor No. The angular frequency of the modulation cycle; Indicates Monitoring sensor No. The phase shift of each modulation cycle; Indicates the end time; The feature correction module is used to construct a feature deviation correction model to correct the features of the shared massage chair operation data. The feature deviation correction model is specifically shown in the following formula: ； in: Indicates the feature correction result of the shared massage chair operation data; Represents the total number of key parameters in the shared massage chair operation data characteristics; Indicates Correction factors for key parameters; Indicates Adaptive factors of key parameters; express The moment Key parameter values; Indicates The ideal calibration value of each key parameter; Indicates Sensitivity coefficients of key parameter values; Indicates Normalization coefficients of key parameter values; The life evaluation module is used to construct a shared massage chair life evaluation model, and evaluate the life of the shared massage chair based on the preprocessed shared massage chair operation data. The shared massage chair life evaluation model is specifically shown in the following formula: ； in: Indicates the results of the life assessment of shared massage chairs; Indicates the number of shared massage chair systems; Shared massage chair Subsystems in Status indicators at all times; Shared massage chair The ideal state indicator of each subsystem; Shared massage chair The weight of each subsystem; Shared massage chair The number of historical failures of each subsystem; The health status assessment module is used to obtain a comprehensive health status assessment result of the shared massage chair by weighted summing the features of the corrected shared massage chair operation data and the shared massage chair life assessment results, and to issue an early warning when the comprehensive health status of the shared massage chair reaches a preset threshold.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 3 is implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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