Family office chair management method suitable for body state monitoring

Abstract

The invention discloses a home office chair management method suitable for body state monitoring, and particularly relates to the technical field of home office chairs. The method comprises the following steps: numbering and classifying electronic components in the chair, monitoring current leakage abnormal indexes and electromagnetic interference sensitive indexes of key components in real time, comprehensively evaluating and managing short-circuit risks, comprehensively analyzing the indexes, dividing the short-circuit risks of the components into high, middle and low levels, and taking corresponding management measures, so that the safety of the chair is improved. According to the intelligent office chair, the safety and reliability of the intelligent office chair are remarkably improved, early warning can be performed in time before a fault occurs, damage to a user caused by a potential mechanical fault is avoided, and the use safety of the user and the long-term stability of the equipment are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of home office chairs, and in particular to a home office chair management method suitable for body status monitoring. Background Art

[0002] A home office chair is a chair designed for a home office environment, designed to provide comfort and support to accommodate long hours of work. This type of chair usually has adjustable height, tilt angle, and lumbar support to help maintain a good sitting posture and reduce the discomfort caused by long periods of sitting. A home office chair must not only be ergonomically designed, but also aesthetically pleasing and durable so that it can blend into the overall decoration style of the home while meeting the actual needs of users working from home.

[0003] In the prior art, home office chair management technology for body status monitoring mainly combines smart sensors and data analysis technology. These office chairs usually have built-in sensors that can monitor the user's sitting posture, body pressure distribution, heart rate, breathing and other physiological data in real time, and perform data analysis and feedback through applications connected to mobile devices or computers. Through these feedbacks, users can adjust their sitting posture or rest time, improve their work habits, and reduce the health problems that may be caused by long-term sitting. However, due to the long-term work of the smart office chair, the electronic components of the smart office chair may short-circuit, causing the chair to be unable to adjust normally, or even sudden mechanical failures (such as sudden tilt or lock) during the adjustment process. And this failure may cause the automatic adjustment mechanism of the chair to lose control. For example, when the user is in a state of concentrated work, the chair suddenly begins to tilt quickly and without warning, the backrest quickly falls back or the seat height suddenly drops. This sudden mechanical action will catch the user off guard, causing the body to lose balance, and may fall directly to the ground, or hit the surrounding furniture, causing serious physical injuries, such as sprains, fractures or head impacts. This may not only damage the chair, but also cause injuries to the user. Summary of the invention

[0004] The purpose of the present invention is to provide a home office chair management method suitable for body status monitoring to solve the shortcomings of the background technology.

[0005] In order to achieve the above object, the present invention provides the following technical solution: a home office chair management method suitable for body status monitoring, comprising the following steps:

[0006] S1: number all electronic components of the smart office chair and divide them into commonly used electronic components and uncommon electronic components according to the frequency of use of each electronic component;

[0007] S2: For commonly used electronic components, obtain in real time the current leakage anomaly index of commonly used electronic components of the smart office chair in low-power standby mode, and obtain the sensitivity index of electromagnetic interference of commonly used electronic components in the smart office chair in the working state to external devices;

[0008] S3: Comprehensively analyze the acquired current leakage anomaly index and electromagnetic interference sensitivity index of common electronic components to assess the risk of short circuit of common electronic components;

[0009] S4: Based on the assessment results, the risks of short circuits of commonly used electronic components are divided into different levels, namely high risk level, medium risk level and low risk level, and corresponding management is carried out;

[0010] S5: Further analyze the risk of short circuit of commonly used electronic components at a medium risk level within a fixed time period, and issue timely warnings before the smart office chair fails based on the analysis results.

[0011] Preferably, in S2, for commonly used electronic components, the current leakage abnormality index of the commonly used electronic components of the smart office chair in the low power standby mode is obtained in real time, and the method for obtaining the current leakage abnormality index is:

[0012] In the normal low-power standby mode, the baseline current leakage value Ibase line of the commonly used electronic components of the smart office chair is measured. In each monitoring cycle, the current current leakage value I current is measured and recorded, and compared with the previously measured baseline current leakage value, and the difference between the currently measured current leakage value and the baseline value is calculated. The calculation formula is: ΔI = I current - I base line; ΔI is the current leakage deviation, which indicates the difference between the current current leakage and the baseline value, I current is the currently measured current leakage value, and I base line is the baseline current leakage value; based on the current leakage deviation, the current leakage anomaly index CL is calculated, and the calculation formula is:

[0013] Preferably, in S2, the electromagnetic interference sensitivity index of the common electronic components in the smart office chair under working condition to the external device is obtained, and the electromagnetic interference sensitivity index is obtained by:

[0014] Select electromagnetic interference sources of different strengths and frequencies, and apply interference to the equipment at a predetermined time and distance. When there is no electromagnetic interference, measure the benchmark output signal of the commonly used electronic components of the smart office chair. Under the condition of applying electromagnetic interference, measure and record the output signal changes of the electronic components in real time, and calculate the change in the output signal before and after the interference, that is, the signal deviation. The signal deviation interpretation expression is: In the formula, Sinterfered is the output signal value after electromagnetic interference is applied, S baseline is the reference output signal value when there is no interference, Signal Deviation (ΔS) is the signal deviation; the electromagnetic interference in different frequency bands is tested, the signal deviation is calculated respectively, and the electromagnetic interference sensitivity index is calculated by weighted average of the signal deviation of each frequency band. The calculation expression is: Where n is the number of interference frequency bands tested, w i is the weight of each frequency band, ΔS i is the signal deviation percentage in the i-th frequency band, and EM is the electromagnetic interference sensitivity index.

[0015] Preferably, in S3, a comprehensive analysis is performed on the acquired current leakage anomaly index and electromagnetic interference sensitivity index of the commonly used electronic components to assess the risk of short circuit of the commonly used electronic components, specifically:

[0016] The current leakage anomaly index and the electromagnetic interference sensitivity index are converted into the first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model predicts the risk value label of short circuit of common electronic components for each group of first eigenvectors as the prediction target, and takes minimizing the sum of prediction errors of risk value labels of short circuit of all common electronic components as the training target. The machine learning model is trained until the sum of prediction errors converges and the model training is stopped. The risk value of short circuit of common electronic components is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0017] Preferably, in S4, the risk of short circuit of common electronic components is divided into different levels according to the evaluation results, and corresponding management is performed, specifically:

[0018] The obtained risk threshold of short circuit of commonly used electronic components is compared with the gradient standard threshold, the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the risk value of short circuit of commonly used electronic components is compared with the first standard threshold and the second standard threshold respectively;

[0019] If the risk value of short circuit of commonly used electronic components is greater than the second standard threshold, it means that the risk of short circuit of commonly used electronic components is high and it is classified as a high risk level; inspection and maintenance should be carried out immediately;

[0020] If the risk value of short circuit of commonly used electronic components is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, it means that the risk of short circuit of commonly used electronic components is average, and it is classified as medium risk level; regular inspection and preventive maintenance are carried out on components of medium risk level to ensure that the components are handled in time before failure occurs;

[0021] If the risk value of short circuit of commonly used electronic components is less than the first standard threshold, it means that the risk of short circuit of commonly used electronic components is low, and they are classified as low risk level. Routine maintenance can be performed on the low risk level components to keep them in normal working condition.

[0022] Preferably, in S5, the risk of short circuit of common electronic components at a medium risk level within a fixed time period is further analyzed, and timely warning is given before a failure of the smart office chair occurs according to the analysis result, specifically:

[0023] When the risk of short circuit of commonly used electronic components is classified as a medium risk level, that is, the risk value of short circuit of commonly used electronic components generated within a fixed time period is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the risk values ​​greater than or equal to the first standard threshold and less than or equal to the second standard threshold generated in a subsequent fixed time period are collected, and a corresponding data set is established, the mean and standard deviation of the data set are calculated, and after analysis, timely warning is issued before a failure event occurs in the smart office chair according to the analysis results.

[0024] Preferably, if the mean value of the risk value in the data set is greater than or equal to the reference threshold value of the mean value of the risk value, and the standard deviation of the risk value is less than the reference threshold value of the standard deviation of the risk value, that is, the mean value of the risk value is high and the fluctuation is small, then a first-level warning signal is generated;

[0025] If the mean value of the risk value is greater than or equal to the reference threshold value of the mean value of the risk value, and the standard deviation of the risk value is greater than or equal to the reference threshold value of the standard deviation of the risk value, that is, the mean value of the risk value is high but the fluctuation is large, then a secondary warning signal is generated;

[0026] If the mean value of the risk value is less than the reference threshold value of the mean value of the risk value, and the standard deviation of the risk value is greater than or equal to the reference threshold value of the standard deviation of the risk value, that is, the mean value of the risk value is low but the risk value fluctuates greatly, a third-level warning signal is generated at this time;

[0027] If the mean risk value is less than the reference threshold of the mean risk value, and the standard deviation of the risk value is less than the reference threshold of the standard deviation of the risk value, that is, the mean and volatility of the risk value are both low, no warning signal is generated and routine monitoring continues.

[0028] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0029] 1. The present invention effectively improves the reliability and safety of the equipment by numbering, classifying, real-time monitoring and risk assessment of the electronic components of the smart office chair. The solution uses a comprehensive analysis of the current leakage anomaly index and the electromagnetic interference sensitivity index, combined with a machine learning model to accurately predict short circuit risks, and takes targeted management measures according to different risk levels to ensure timely warning before a fault occurs, reducing the harm caused to users by potential mechanical failures.

[0030] 2. The present invention can flexibly respond to different risk conditions of electronic components through a graded warning mechanism. The first-level warning can remind users to take immediate action, while the second-level and third-level warnings provide a basis for further monitoring and maintenance. Through this method, the stability of the smart office chair is significantly improved, and the user experience is safer and more comfortable. It effectively prevents sudden accidents caused by short circuits, thereby extending the service life of the equipment and reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0032] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] Example 1, please refer to Figure 1 As shown, the home office chair management method suitable for body status monitoring described in this embodiment includes the following steps:

[0035] S1: number all electronic components of the smart office chair and divide them into commonly used electronic components and uncommon electronic components according to the frequency of use of each electronic component;

[0036] S2: For commonly used electronic components, obtain in real time the current leakage anomaly index of commonly used electronic components of the smart office chair in low-power standby mode, and obtain the sensitivity index of electromagnetic interference of commonly used electronic components in the smart office chair in the working state to external devices;

[0037] S3: Comprehensively analyze the acquired current leakage anomaly index and electromagnetic interference sensitivity index of common electronic components to assess the risk of short circuit of common electronic components;

[0038] S4: Based on the assessment results, the risks of short circuits of commonly used electronic components are divided into different levels, namely high risk level, medium risk level and low risk level, and corresponding management is carried out;

[0039] S5: Further analyze the risk of short circuit of commonly used electronic components at a medium risk level within a fixed time period, and issue timely warnings before the smart office chair fails based on the analysis results.

[0040] In S1, all electronic components in the smart office chair are numbered and divided into commonly used electronic components and uncommonly used electronic components according to the usage frequency of each electronic component.

[0041] Identify electronic components: First, comprehensively identify and list all electronic components in the smart office chair, including sensors, control circuit boards, power modules, communication modules, display screens, etc.

[0042] Numbering: Uniquely number each identified electronic component. Numbering can be done by function, location, or other logical order. For example, sensors are numbered A1, A2, power modules are numbered B1, control boards are numbered C1, etc.

[0043] Record usage frequency: Record the usage frequency of each electronic component through actual usage data or design specifications. This can include working hours, number of activations, or other indicators that reflect the frequency of use.

[0044] Data sources: Data can be obtained from equipment log records, technical specifications in user manuals, or through real-time monitoring systems.

[0045] Set standard frequency threshold: Set a frequency threshold to distinguish between commonly used and unused electronic components. For example, components with working time exceeding 50% of the total working time can be defined as commonly used components, and components with working time below this value can be defined as unused components.

[0046] Classification: According to the set standard frequency threshold, electronic components are divided into commonly used electronic components and uncommon electronic components. The use frequency of electronic components is compared with the standard frequency threshold. If the use frequency of electronic components is greater than or equal to the standard frequency threshold, it is marked as a commonly used electronic component; the use frequency of electronic components is compared with the standard frequency threshold. If the use frequency of electronic components is less than the standard frequency threshold, it is marked as an uncommon electronic component. Common components are those that are frequently used and are essential to the daily functions of the smart office chair, while uncommon components are those that are occasionally used or enabled in specific circumstances.

[0047] S2: For commonly used electronic components, obtain in real time the current leakage anomaly index of commonly used electronic components of the smart office chair in low-power standby mode, and obtain the electromagnetic interference sensitivity index of commonly used electronic components in the smart office chair under working conditions to external devices.

[0048] For commonly used electronic components, the current leakage anomaly index of commonly used electronic components of the smart office chair in low-power standby mode is obtained in real time. It is very important to obtain the current leakage anomaly index of commonly used electronic components of the smart office chair in low-power standby mode in real time, because it can detect possible electrical failures or component aging problems in advance. An increase in the current leakage anomaly index is usually an early sign of a decrease in component insulation performance or circuit failure. Timely detection of this anomaly can help prevent potential short circuits or equipment failures. In addition, by monitoring the current leakage anomaly index, energy consumption management can be optimized and the service life of the equipment can be extended, while ensuring user safety and avoiding sudden failures caused by electrical problems.

[0049] The method for obtaining the current leakage abnormality index is:

[0050] In normal low-power standby mode, measure the baseline current leakage value Ibase line of the common electronic components of the smart office chair. The specific value should be measured after the equipment has been running for a period of time without faults or interference. Define regular monitoring time intervals (such as daily or weekly) and repeatedly measure the current leakage value I current at these time points.

[0051] In each monitoring cycle, the current current leakage value I current is measured and recorded, and compared with the previously measured reference current leakage value, and the difference between the currently measured current leakage value and the reference value is calculated to reflect the change of current leakage. The calculation formula is: ΔI = I current - I base line; ΔI is the current leakage deviation, which indicates the difference between the current current leakage and the reference value, I current is the currently measured current leakage value, and I base line is the reference current leakage value; based on the current leakage deviation, the current leakage anomaly index CL is calculated to quantify the abnormal degree of the current leakage change, and the calculation formula is: Based on experience or historical data, a current leakage abnormality index threshold CLthreshold is set; if CL exceeds this threshold, it means that the current leakage is abnormal and further inspection or maintenance is required. Once CL exceeds the set threshold, the system should automatically issue an early warning to remind the user of the possible risk of failure.

[0052] The larger the current leakage anomaly index, the more significant the current leakage of common electronic components is compared to the baseline value, which is usually an early sign of insulation degradation or circuit damage. As the current leakage anomaly index increases, the risk of short circuits in common electronic components also increases significantly. This is because excessive current leakage may cause component overheating, electrical insulation failure, and ultimately cause serious faults such as short circuits. Therefore, the current leakage anomaly index is an important indicator for evaluating the health of electronic components. Timely monitoring of this index can help prevent potential electrical failures and ensure the safety and stability of equipment.

[0053] The benefit of obtaining the EMI sensitivity index is that it can quantify the sensitivity of electronic components in smart office chairs to external EMI and help identify key components that are susceptible to interference. This index helps engineers optimize electromagnetic compatibility during the design and development process, prevent potential functional failures or misoperations, improve the overall reliability of the device and user experience, and ensure stable operation of the device in various environments.

[0054] The method for obtaining the electromagnetic interference sensitivity index is:

[0055] Select electromagnetic interference sources of different strengths and frequencies (such as mobile phone signals, Wi-Fi, microwaves, etc.), and apply interference to the equipment at a predetermined time and distance. In the absence of electromagnetic interference, measure the benchmark output signals (such as voltage, current or data transmission speed) of commonly used electronic components of smart office chairs. Under the condition of applying electromagnetic interference, measure and record the output signal changes of electronic components in real time, and calculate the change in output signal before and after the interference, that is, signal deviation. The signal deviation interpretation expression is: In the formula, S interferedis the output signal value after electromagnetic interference is applied, S baseline The reference output signal value when there is no interference. Signal Deviation (ΔS) reflects the influence of interference on the signal.

[0056] The electromagnetic interference of different frequency bands is tested, the signal deviation is calculated respectively, and the electromagnetic interference sensitivity index is calculated by weighted average of the signal deviation of each frequency band. The calculation expression is: Where n is the number of interference frequency bands tested, w i The weight of each frequency band can be assigned according to its importance or actual usage, ΔS i is the signal deviation percentage in the i-th frequency band, and EM is the electromagnetic interference sensitivity index.

[0057] The larger the EMI sensitivity index, the more sensitive common electronic components are to external EMI, which means that under strong or continuous EMI, the electrical performance of the components is more easily affected. The higher the sensitivity index, the more current fluctuations or abnormal signals in the components, which increases the possibility of circuit failure, insulation damage or overheating, which may eventually lead to short circuits. Therefore, the larger the EMI sensitivity index, the greater the risk of short circuits in common electronic components.

[0058] S3: Comprehensively analyze the acquired current leakage anomaly index and electromagnetic interference sensitivity index of common electronic components to assess the risk of short circuit of common electronic components.

[0059] The current leakage anomaly index and the electromagnetic interference sensitivity index are converted into the first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model predicts the risk value label of short circuit of common electronic components for each group of first eigenvectors as the prediction target, and takes minimizing the sum of prediction errors of risk value labels of short circuit of all common electronic components as the training target. The machine learning model is trained until the sum of prediction errors converges and the model training is stopped. The risk value of short circuit of common electronic components is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0060] The method for obtaining the risk value of short circuit of common electronic components is as follows: from the first feature vector training data of the trained machine learning model, the corresponding function expression is obtained: CR = f 1 (CL, EM); where f 1 is the output function of the model, CL is the current leakage anomaly index, EM is the electromagnetic interference sensitivity index, and CR is the risk value of short circuit of common electronic components.

[0061] S4: Based on the assessment results, the risks of short circuits in commonly used electronic components are divided into different levels, namely high risk level, medium risk level and low risk level, and managed accordingly.

[0062] The obtained risk value of short circuit of commonly used electronic components is compared with a gradient standard threshold, wherein the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the risk value of short circuit of commonly used electronic components is compared with the first standard threshold and the second standard threshold respectively;

[0063] If the risk value of short circuit of common electronic components is greater than the second standard threshold, it means that the risk of short circuit of common electronic components is high and they are classified as high risk level. Emergency inspection, maintenance or replacement should be arranged immediately to prevent short circuit accidents. Increase the frequency of real-time monitoring of these components, closely track the changes of parameters such as current and temperature, and ensure that abnormalities are discovered in the first place.

[0064] If the risk value of short circuit of commonly used electronic components is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, it means that the risk of short circuit of commonly used electronic components is general, and it is classified as a medium risk level; regular inspection and preventive maintenance should be carried out on components of the medium risk level to ensure that the components are handled in time before failure occurs.

[0065] If the risk value of short circuit of commonly used electronic components is less than the first standard threshold, it means that the risk of short circuit of commonly used electronic components is low and they are classified as low risk level. For low risk level components, routine maintenance is sufficient to keep them in normal working condition. Although the risk is low, it is still necessary to regularly review the status of components to prevent the risk from increasing due to environmental changes or long-term use.

[0066] S5: Further analyze the risk of short circuit of commonly used electronic components at a medium risk level within a fixed time period, and issue timely warnings before the smart office chair fails based on the analysis results.

[0067] When the risk of short circuit of commonly used electronic components is classified as a medium risk level, that is, the risk value of short circuit of commonly used electronic components generated within a fixed time period is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the risk values ​​greater than or equal to the first standard threshold and less than or equal to the second standard threshold generated in a subsequent fixed time period are collected, and a corresponding data set is established, the mean and standard deviation of the data set are calculated, and after analysis, timely warning is issued before a failure event occurs in the smart office chair according to the analysis results.

[0068] If the mean of the risk values ​​in the data set is greater than or equal to the reference threshold of the mean of the risk values, and the standard deviation of the risk values ​​is less than the reference threshold of the standard deviation of the risk values, that is, the mean of the risk values ​​is high and the fluctuation is small, indicating that the short-circuit risk is continuously increasing and the trend is relatively stable. At this time, a first-level warning signal is generated, prompting detailed inspection or maintenance, because the short-circuit risk of the component is very high and stable, and failure may occur in a short time;

[0069] If the mean value of the risk value is greater than or equal to the reference threshold value of the mean value of the risk value, and the standard deviation of the risk value is greater than or equal to the reference threshold value of the standard deviation of the risk value, that is, the mean value of the risk value is high but the fluctuation is large, which means that although the overall risk is high, there is a large uncertainty, which may be caused by changes in the external environment or unstable working conditions. At this time, a secondary warning signal is generated, and it is recommended to conduct environmental monitoring and adjust operating conditions. At the same time, further diagnosis of the components is carried out to confirm the cause of the fluctuation and take corresponding preventive measures;

[0070] If the mean value of the risk value is less than the reference threshold value of the mean value of the risk value, and the standard deviation of the risk value is greater than or equal to the reference threshold value of the standard deviation of the risk value, that is, the mean value of the risk value is low but the risk value fluctuates greatly, it indicates that the overall short circuit risk is not high, but there is a possibility of sudden increase, which may be caused by intermittent external factors or component instability. At this time, a third-level warning signal is generated to closely monitor these fluctuations, especially during periods of large fluctuations, and be prepared to take action when necessary;

[0071] If the mean risk value is less than the reference threshold of the mean risk value, and the standard deviation of the risk value is less than the reference threshold of the standard deviation of the risk value, that is, the mean and fluctuation of the risk value are low, it indicates that the overall short circuit risk is low and stable, and the electronic components are currently in a relatively safe state. At this time, no warning signal is generated, but routine monitoring continues to ensure that the risk level remains low, and regular inspections are carried out.

[0072] It should be noted here that the importance of the first-level warning signal is greater than that of the second-level warning signal, and the importance of the second-level warning signal is greater than that of the third-level warning signal. Relevant personnel can take corresponding adjustment measures according to different warning signal levels.

[0073] In this embodiment, by systematically numbering, classifying, monitoring and risk assessment of electronic components in the smart office chair, accurate management and early warning of short-circuit risks of commonly used electronic components are achieved. By obtaining the current leakage anomaly index and electromagnetic interference sensitivity index in real time, and combining comprehensive analysis and assessment of short-circuit risks, the risks are effectively divided into different levels and targeted management is carried out. Especially at the medium risk level, further analysis and early warning mechanisms ensure that necessary measures can be taken before a fault occurs, thereby significantly improving the safety, stability and service life of the smart office chair and avoiding the impact of unexpected faults on users.

[0074] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0075] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0076] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0077] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0078] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for managing a home office chair adapted for body status monitoring, characterized in that: The steps include: S1: number all electronic components in the smart office chair and divide them into commonly used electronic components and uncommon electronic components according to the usage frequency of each electronic component; S2: For commonly used electronic components, obtain in real time the current leakage anomaly index of commonly used electronic components of the smart office chair in low-power standby mode, and obtain the sensitivity index of electromagnetic interference of commonly used electronic components in the smart office chair in the working state to external devices; S3: Comprehensively analyze the acquired current leakage anomaly index and electromagnetic interference sensitivity index of common electronic components to assess the risk of short circuit of common electronic components; S4: Based on the assessment results, the risks of short circuits of commonly used electronic components are divided into different levels, namely high risk level, medium risk level and low risk level, and corresponding management is carried out; S5: Further analyze the risk of short circuit of commonly used electronic components at a medium risk level within a fixed time period, and issue timely warnings before the smart office chair fails based on the analysis results.

2. A method for managing a home office chair adapted for body condition monitoring according to claim 1, characterized in that: In S2, for common electronic components, the current leakage anomaly index of the common electronic components of the smart office chair in the low power standby mode is obtained in real time. The method for obtaining the current leakage anomaly index is: In the normal low-power standby mode, the baseline current leakage value Ibaseline of the commonly used electronic components of the smart office chair is measured. In each monitoring cycle, the current current leakage value Icurrent is measured and recorded, and compared with the previously measured baseline current leakage value, and the difference between the currently measured current leakage value and the baseline value is calculated. The calculation formula is: ΔI = Icurrent-Ibaseline; ΔI is the current leakage deviation, which indicates the difference between the current current leakage and the baseline value, Icurrent is the currently measured current leakage value, and Ibaseline is the baseline current leakage value; based on the current leakage deviation, the current leakage anomaly index CL is calculated, and the calculation formula is:

3. A method for managing a home office chair adapted for body condition monitoring according to claim 2, characterized in that: In S2, the electromagnetic interference sensitivity index of the common electronic components in the smart office chair under working condition to the external device is obtained. The electromagnetic interference sensitivity index is obtained by: Select electromagnetic interference sources of different strengths and frequencies, and apply interference to the equipment at a predetermined time and distance. When there is no electromagnetic interference, measure the benchmark output signal of the commonly used electronic components of the smart office chair. Under the condition of applying electromagnetic interference, measure and record the output signal changes of the electronic components in real time, and calculate the change in the output signal before and after the interference, that is, the signal deviation. The signal deviation interpretation expression is: In the formula, S interfered is the output signal value after electromagnetic interference is applied, S baseline is the reference output signal value when there is no interference, SignalDeviation (ΔS) is the signal deviation; the electromagnetic interference in different frequency bands is tested, the signal deviation is calculated respectively, and the electromagnetic interference sensitivity index is calculated by weighted average of the signal deviation of each frequency band. The calculation expression is: Where n is the number of interference frequency bands tested, w i is the weight of each frequency band, ΔS i is the signal deviation percentage in the i-th frequency band, and EM is the electromagnetic interference sensitivity index.

4. A method for managing a home office chair adapted for body status monitoring according to claim 3, characterized in that: In S3, the current leakage anomaly index and electromagnetic interference sensitivity index of the commonly used electronic components are comprehensively analyzed to evaluate the risk of short circuit of the commonly used electronic components, specifically: The current leakage anomaly index and the electromagnetic interference sensitivity index are converted into the first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model predicts the risk value label of short circuit of common electronic components for each group of first eigenvectors as the prediction target, and takes minimizing the sum of prediction errors of risk value labels of short circuit of all common electronic components as the training target. The machine learning model is trained until the sum of prediction errors converges and the model training is stopped. The risk value of short circuit of common electronic components is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

5. A method for managing a home office chair adapted for body status monitoring according to claim 4, characterized in that: In S4, based on the assessment results, the risk of short circuits in commonly used electronic components is divided into different levels and managed accordingly, specifically: The acquired risk threshold of short circuit of commonly used electronic components is compared with the gradient standard threshold, where the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the risk threshold of short circuit of commonly used electronic components is compared with the first standard threshold and the second standard threshold respectively; If the risk value of short circuit of commonly used electronic components is greater than the second standard threshold, it means that the risk of short circuit of commonly used electronic components is high and it is classified as a high risk level; inspection and maintenance should be carried out immediately; If the risk value of short circuit of commonly used electronic components is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, it means that the risk of short circuit of commonly used electronic components is average, and it is classified as medium risk level; regular inspection and preventive maintenance are carried out on components of medium risk level to ensure that the components are handled in time before failure occurs; If the risk value of short circuit of commonly used electronic components is less than the first standard threshold, it means that the risk of short circuit of commonly used electronic components is low, and they are classified as low risk level. Routine maintenance can be performed on the low risk level components to keep them in normal working condition.

6. A method for managing a home office chair adapted for body condition monitoring according to claim 1, characterized in that: In S5, the risk of short circuit of common electronic components at a medium risk level within a fixed time period is further analyzed, and timely warning is issued before the failure of the smart office chair occurs based on the analysis results, specifically: When the risk of short circuit of commonly used electronic components is classified as a medium risk level, that is, the risk value of short circuit of commonly used electronic components generated within a fixed time period is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the risk values ​​greater than or equal to the first standard threshold and less than or equal to the second standard threshold generated in a subsequent fixed time period are collected, and a corresponding data set is established, the mean and standard deviation of the data set are calculated, and after analysis, timely warning is issued before a failure event occurs in the smart office chair according to the analysis results.

7. A method for managing a home office chair adapted for body condition monitoring according to claim 6, characterized in that: If the mean value of the risk value in the data set is greater than or equal to the reference threshold of the mean value of the risk value, and the standard deviation of the risk value is less than the reference threshold of the standard deviation of the risk value, that is, the mean value of the risk value is high and the fluctuation is small, then a first-level warning signal is generated; If the mean value of the risk value is greater than or equal to the reference threshold value of the mean value of the risk value, and the standard deviation of the risk value is greater than or equal to the reference threshold value of the standard deviation of the risk value, that is, the mean value of the risk value is high but the fluctuation is large, then a secondary warning signal is generated; If the mean value of the risk value is less than the reference threshold value of the mean value of the risk value, and the standard deviation of the risk value is greater than or equal to the reference threshold value of the standard deviation of the risk value, that is, the mean value of the risk value is low but the risk value fluctuates greatly, a third-level warning signal is generated at this time; If the mean risk value is less than the reference threshold of the mean risk value, and the standard deviation of the risk value is less than the reference threshold of the standard deviation of the risk value, that is, the mean and volatility of the risk value are both low, no warning signal is generated and routine monitoring continues.

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