Low-power-consumption human body intelligent monitoring equipment convenient to wear

Abstract

The invention discloses low-power-consumption human body intelligent monitoring equipment convenient to wear, and relates to the technical field of intelligent wearing. Comprising a current detection module for collecting human body leakage current and converting the human body leakage current into a first digital signal; the data processing module carries out signal analysis on the first digital signal, if the signal analysis result is suspected to be abnormal, a first control instruction is sent to the electromagnetic noise detection module to obtain a noise detection parameter, and a second control instruction is sent to the magnetic field detection module to obtain a field intensity parameter; and the data processing module is used for analyzing the noise detection parameter and the field intensity parameter to obtain a fault instruction set and sending the fault instruction set to the alarm module to generate a corresponding alarm signal. When suspected abnormity is detected, the electromagnetic noise detection module and the magnetic field detection module are activated, data analysis is carried out to finally determine the fault type, a corresponding alarm is given out, and the working efficiency is improved under the condition that the safety of operators is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of smart wearables, and particularly relates to a low-power human body intelligent monitoring device that is convenient to wear. Background Art

[0002] The construction, renovation and maintenance work of the power grid has a heavy burden, and there are many and wide-ranging on-site points that need to be operated. At the same time, the comprehensive qualities of specific construction workers vary. Especially in the renovation and expansion projects, there are many high-altitude operations, operations near energized bodies, and cross-overs. Workers may experience symptoms such as headache, dizziness, and weakness in the limbs after staying in high-altitude and strong electromagnetic working environments for a long time, which may further induce safety accidents and pose potential safety hazards to personal safety. The issue of safety guarantee for workers during live working has always been a hot topic at home and abroad, but specific feasible solutions are relatively lacking. Therefore, it is urgent to develop a miniature wearable device for safe live working.

[0003] Some progress has been made in the analysis and monitoring technology research on the health impact of special working environments in power grid projects on the human body, but there are still some key technical challenges, such as the complexity of electromagnetic radiation, the accuracy and effectiveness of monitoring, etc.; this has led to a lack of effective intelligent monitoring devices in traditional working methods to ensure the safety of live working personnel, increasing the safety hazards of workers and reducing work efficiency. Summary of the Invention

[0004] The purpose of the present invention is to solve the problems that in traditional working methods, there is a lack of effective intelligent monitoring devices to ensure the safety of live working personnel, increasing the safety hazards of workers and reducing work efficiency, and to propose a low-power human body intelligent monitoring device that is convenient to wear.

[0005] The present invention proposes a low-power human body intelligent monitoring device that is convenient to wear. The device includes a current detection module, a magnetic field detection module, an electromagnetic noise detection module, a data processing module, and an alarm module:

[0006] The current detection module is used to collect the human body leakage current in real time and convert the human body leakage current into a first digital signal and send it to the data processing module;

[0007] The data processing module is used to perform signal analysis on the first digital signal. If the signal analysis result is suspiciously abnormal, it sends a first control instruction to the electromagnetic noise detection module and a second control instruction to the magnetic field detection module respectively;

[0008] The electromagnetic noise detection module is used to perform electromagnetic noise detection according to the first control instruction to obtain noise detection parameters and send the noise detection parameters to the data processing module;

[0009] The magnetic field detection module is configured to perform magnetic field detection according to the second control instruction to obtain field strength parameters, and send the field strength parameters to the data processing module;

[0010] The data processing module is configured to analyze the noise detection parameters and the field strength parameters respectively to obtain a fault instruction set, and send the fault instruction set to the alarm module to generate corresponding alarm signals.

[0011] Optionally, the current detection module includes:

[0012] A leakage current acquisition module, configured to collect human body leakage current in real time through a capacitance sensor to obtain an electrical signal;

[0013] An amplification module, configured to amplify the electrical signal through an operational amplifier to obtain an amplified electrical signal;

[0014] A signal conversion module, configured to convert the amplified electrical signal into a first digital signal through an analog-to-digital converter.

[0015] Optionally, the data processing module includes:

[0016] A filtering module, configured to perform filtering processing on the first digital signal through a band-pass filter to obtain a second digital signal;

[0017] A harmonic analysis module, configured to perform a fast Fourier transform on the second digital signal to obtain the amplitudes and phases of the fundamental wave and harmonics, and calculate the amplitude ratio of the third harmonic to the fundamental wave to obtain a target ratio;

[0018] A target current signal generation module, configured to construct a capacitive current model according to the target ratio, generate a capacitive current digital waveform through harmonic back-projection, and calculate the difference between the second digital signal and the capacitive current digital waveform to obtain a target current signal;

[0019] A signal analysis module, configured to record the signal analysis result as a suspected anomaly if the amplitude of the target current signal is greater than a preset current threshold.

[0020] Optionally, the electromagnetic noise detection module includes:

[0021] An electromagnetic noise sensor device startup module, configured to activate the power supply of the ultrasonic sensor through a first control instruction, and perform electromagnetic noise sampling at a preset sampling frequency to obtain initial electromagnetic noise data;

[0022] An electromagnetic noise filtering module, configured to filter the initial electromagnetic noise data through a band-pass filter to obtain target noise data, and perform digital signal conversion on the target noise data to obtain noise detection parameters.

[0023] Optionally, the magnetic field detection module includes:

[0024] A magnetic field detection device startup module, configured to activate the power supply of the triaxial magnetic field sensor through a second control instruction, and perform magnetic field sampling at the preset sampling frequency to obtain initial magnetic field distribution data;

[0025] A magnetic field distribution filtering module, configured to substitute the initial magnetic field distribution data into an instrumentation amplifier, and then perform active demagnetization through an orthogonal coil to obtain target magnetic field distribution data, and perform digital signal conversion on the target magnetic field distribution data to obtain field strength parameters.

[0026] Optionally, the data processing module further includes:

[0027] A noise detection parameter filtering module, configured to filter the noise detection parameters through an FIR digital filter to obtain target noise parameters;

[0028] A target energy ratio determination module, configured to calculate the energy ratio of the target noise parameters in the target frequency band to obtain a target energy ratio. If the target energy ratio is greater than a preset energy ratio value, an arc discharge alarm instruction is generated and recorded as a fault instruction.

[0029] Optionally, the data processing module further includes:

[0030] A sliding filtering processing module, configured to perform sliding average filtering processing on the field strength parameters to obtain first field strength parameters;

[0031] A band-stop filtering processing module, configured to perform frequency-domain band-stop filtering on the first field strength parameters to obtain second field strength parameters;

[0032] A wavelet denoising processing module, configured to perform wavelet denoising on the second field strength parameters to obtain third field strength parameters;

[0033] Determine the root mean square value and the gradient change value corresponding to the third field strength parameters, and determine a fault instruction according to the root mean square value and the gradient change value.

[0034] Optionally, the device further includes a physiological characteristic detection module, and the physiological characteristic detection module includes:

[0035] A temperature monitoring module, configured to collect temperature through a temperature sensor at a first preset temperature monitoring frequency. When the temperature is not within the preset temperature range, a temperature anomaly instruction is sent to the alarm module;

[0036] A heart rate monitoring module, configured to collect the heart rate through a heart rate sensor at a first preset heart rate monitoring frequency. When the heart rate is not within the preset heart rate range, a heart rate anomaly instruction is sent to the alarm module;

[0037] A blood pressure monitoring module is used to collect blood pressure at a first preset blood pressure monitoring frequency through a blood pressure sensor. When the blood pressure is not within the preset blood pressure range, a blood pressure abnormality instruction is sent to the alarm module.

[0038] Optionally, the data processing module further includes:

[0039] If there is a fault instruction in the fault instruction set, a second preset temperature monitoring frequency instruction, a second preset heart rate monitoring frequency instruction, and a second preset blood pressure monitoring frequency instruction are generated and sent to the physiological feature detection module, so that the physiological feature detection module performs data collection according to the second preset temperature monitoring frequency instruction, the second preset heart rate monitoring frequency instruction, and the second preset blood pressure monitoring frequency instruction.

[0040] Advantages of the present invention:

[0041] The present invention provides a low-power human body intelligent monitoring device that is convenient to wear. The device includes a current detection module, a magnetic field detection module, an electromagnetic noise detection module, a data processing module, and an alarm module: The current detection module is used to collect the human body leakage current in real time and convert the human body leakage current into a first digital signal and send it to the data processing module; The data processing module is used to perform signal analysis on the first digital signal. If the signal analysis result is suspiciously abnormal, a first control instruction is sent to the electromagnetic noise detection module respectively, and a second control instruction is sent to the magnetic field detection module; The electromagnetic noise detection module is used to perform electromagnetic noise detection according to the first control instruction to obtain noise detection parameters and send the noise detection parameters to the data processing module; The magnetic field detection module is used to perform magnetic field detection according to the second control instruction to obtain field strength parameters and send the field strength parameters to the data processing module; The data processing module is used to analyze the noise detection parameters and the field strength parameters respectively to obtain a fault instruction set, and send the fault instruction set to the alarm module to generate corresponding alarm signals. By the current detection module, the human body leakage current is monitored in real time, potential electric shock or leakage risks can be captured in time. When a suspected abnormality is detected, the electromagnetic noise detection module and the magnetic field detection module are activated. By analyzing the data collected by the electromagnetic noise detection module and the magnetic field detection module, the fault type is finally determined and corresponding alarms are issued. Only when a suspected abnormality occurs, the other modules are activated, greatly reducing energy consumption and improving work efficiency while ensuring the safety of operators. Description of the Drawings

[0042] The present invention will be further described below with reference to the drawings.

[0043] Figure 1 It is a framework diagram of a low-power human body intelligent monitoring device that is convenient to wear provided by an embodiment of the present invention;

[0044] Figure 2Schematic diagram of module installation of a low-power human body intelligent monitoring device convenient for wearing provided by an embodiment of the present invention;

[0045] Figure 3 Frame diagram of another low-power human body intelligent monitoring device convenient for wearing provided by an embodiment of the present invention;

[0046] In the figure: 101, left cuff capacitance sensor; 102, right cuff capacitance sensor; 103, left leg cuff capacitance sensor; 104, right leg cuff capacitance sensor; 201, left chest three-axis magnetic field sensor; 202, right chest three-axis magnetic field sensor; 203, left cuff three-axis magnetic field sensor; 204, right cuff three-axis magnetic field sensor; 205, left thigh three-axis magnetic field sensor; 206, right thigh three-axis magnetic field sensor; 207, left leg cuff three-axis magnetic field sensor; 208, right leg cuff three-axis magnetic field sensor; 3, electromagnetic noise detection module; 4, data processing module; 5, alarm module; 6, physiological feature detection module. Specific embodiments

[0047] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with 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.

[0048] Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0049] An embodiment of the present invention provides a low-power human body intelligent monitoring device convenient for wearing. Refer to Figure 1 , Figure 1 Frame diagram of a low-power human body intelligent monitoring device convenient for wearing provided by an embodiment of the present invention. The device includes a current detection module, a magnetic field detection module, an electromagnetic noise detection module, a data processing module, and an alarm module:

[0050] The current detection module is used to collect the human body leakage current in real time and convert the human body leakage current into a first digital signal and send it to the data processing module;

[0051] The data processing module is used to perform signal analysis on the first digital signal. If the signal analysis result is suspiciously abnormal, a first control instruction is sent to the electromagnetic noise detection module and a second control instruction is sent to the magnetic field detection module respectively;

[0052] The electromagnetic noise detection module is used to perform electromagnetic noise detection according to the first control instruction to obtain noise detection parameters and send the noise detection parameters to the data processing module;

[0053] A magnetic field detection module, configured to perform magnetic field detection according to a second control instruction to obtain field strength parameters, and send the field strength parameters to a data processing module;

[0054] A data processing module, configured to analyze the noise detection parameters and the field strength parameters respectively to obtain a fault instruction set, and send the fault instruction set to an alarm module to generate corresponding alarm signals.

[0055] Based on an easy-to-wear low-power human body intelligent monitoring device provided by an embodiment of the present invention, the human body leakage current is monitored in real time through a current detection module, potential electric shock or leakage risks can be captured in time. When a suspected abnormality is detected, the electromagnetic noise detection module and the magnetic field detection module are activated. By analyzing the data collected by the electromagnetic noise detection module and the magnetic field detection module, the fault type is finally determined, and corresponding alarms are issued. Only when a suspected abnormality is detected, the remaining modules are activated, greatly reducing energy consumption and improving work efficiency while ensuring the safety of operators.

[0056] In one implementation, by simultaneously detecting multiple factors such as current, electromagnetic noise, and magnetic field, multiple means for troubleshooting are provided. Traditional single detection methods may miss some potential problems, while this multi-angle inspection can more accurately determine whether there is an abnormality, improving overall safety.

[0057] In one implementation, if the signal analysis result is normal, no subsequent operations are performed.

[0058] In one implementation, when a fault instruction is detected corresponding to the noise detection parameter and a fault instruction is detected corresponding to the field strength parameter, a fault instruction set is finally obtained. When both the fault instruction detected corresponding to the noise detection parameter and the fault instruction detected corresponding to the field strength parameter are normal instructions, a shutdown instruction is generated to shut down the magnetic field detection module and the electromagnetic noise detection module.

[0059] In one implementation, the leakage current is collected in real time and signal analysis is performed, which can quickly identify whether there is current abnormality. Once a suspicious signal is found, the system immediately starts a further detection process (electromagnetic noise and magnetic field detection), avoiding potential hazards.

[0060] In one implementation, see Figure 2 , Figure 2Schematic diagram of module installation of a low-power human body intelligent monitoring device convenient for wearing provided by an embodiment of the present invention. The current detection module includes a plurality of capacitance sensors, namely the left cuff capacitance sensor 101, the right cuff capacitance sensor 102, the left leg cuff capacitance sensor 103, and the right leg cuff capacitance sensor 104; the magnetic field detection module includes a plurality of three-axis magnetic field sensors, namely the left chest three-axis magnetic field sensor 201, the right chest three-axis magnetic field sensor 202, the left cuff three-axis magnetic field sensor 203, the right cuff three-axis magnetic field sensor 204, the left thigh three-axis magnetic field sensor 205, the right thigh three-axis magnetic field sensor 206, the left leg cuff three-axis magnetic field sensor 207, and the right leg cuff three-axis magnetic field sensor 208; the electromagnetic noise detection module 3 is installed at the left chest; the data processing module 4 is installed at the abdomen; the alarm module 5 is installed at the right chest.

[0061] In one implementation, through fully automatic detection, when operating, the operator does not need to focus on safety protection, improving the operation efficiency.

[0062] In one implementation, when an abnormality or fault is detected, the system can quickly generate an alarm signal to remind relevant personnel to take measures. Timely alarm can effectively avoid greater losses.

[0063] In one embodiment, the current detection module includes:

[0064] A leakage current acquisition module for collecting the human body leakage current in real time through a capacitance sensor to obtain an electrical signal;

[0065] An amplification module for amplifying the electrical signal through an operational amplifier to obtain an amplified electrical signal;

[0066] A signal conversion module for converting the amplified electrical signal into a first digital signal through an analog-to-digital converter.

[0067] In one implementation, the capacitance sensor does not need to be in direct contact with the human body, thus avoiding possible safety risks. The capacitance sensor can accurately capture tiny leakage currents, ensuring early detection of current leakage problems, and even extremely small leakage currents can be detected.

[0068] In one implementation, the model of the capacitance sensor can be AD7150, AD7151, FDC1004, CY8C4014LQI, etc.; the model of the operational amplifier can be OPA2188, LT1028, LPV521, etc.; the analog-to-digital converter can be ADS1220, MAX11108, etc.

[0069] In one implementation, an operational amplifier is used to amplify the collected electrical signal to enhance the detectability of the signal. The leakage current is often very weak, and direct measurement may not be sufficient to provide a reliable signal. The operational amplifier can amplify the weak electrical signal to a sufficient intensity to make subsequent processing more accurate.

[0070] In one implementation, an analog-to-digital converter is used to convert the amplified electrical signal into a digital signal for subsequent digital signal processing. Throughout the entire process from current collection to signal conversion, high-precision monitoring of the human body's leakage current is ensured, avoiding missed detections of faults caused by signal loss or errors.

[0071] In one embodiment, the data processing module includes:

[0072] A filtering module for filtering the first digital signal through a band-pass filter to obtain a second digital signal;

[0073] A harmonic analysis module for performing a fast Fourier transform on the second digital signal to obtain the amplitudes and phases of the fundamental wave and harmonics, and calculating the amplitude ratio of the third harmonic to the fundamental wave to obtain a target ratio;

[0074] A target current signal generation module for constructing a capacitive current model based on the target ratio, generating a digital waveform of the capacitive current through harmonic back-projection, and calculating the difference between the second digital signal and the digital waveform of the capacitive current to obtain a target current signal;

[0075] A signal analysis module for, if the amplitude of the target current signal is greater than a preset current threshold, recording the signal analysis result as a suspected anomaly.

[0076] In one implementation, the band-pass filter can remove high-frequency and low-frequency noise, only retaining the signals in the frequency band of interest, reducing external electromagnetic interference and measurement errors, ensuring that the subsequent processed signals are more accurate, and the leakage current signal within a specific frequency range can be extracted through the band-pass filter system.

[0077] In one implementation, the purpose of the filtering process is to retain the fundamental power frequency (50 Hz) and key harmonics (150 Hz, 250 Hz, etc.). The first digital signal is processed through FIR band-pass filtering to obtain a second digital signal; the fast Fourier transform is to extract the amplitudes and phases of the fundamental wave (50 Hz) and the third harmonic (150 Hz) from the filtered signal; the capacitive current model is constructed based on the target ratio by calculating the theoretical value of the capacitive current through the coupling capacitance formula.

[0078] In one implementation, if the amplitude is less than or equal to the preset current threshold, the signal analysis result is recorded as normal and no subsequent operations are performed; the preset current threshold is determined by the technical personnel.

[0079] In one implementation, the Fourier transform can be used to convert a time-domain signal into a frequency-domain signal, enabling the clear display of the signal's frequency components and the identification of different harmonic components, especially the harmonic information in the leakage current. By analyzing the amplitude ratio of the fundamental wave to the harmonics, abnormal current can be effectively identified.

[0080] In one implementation, by constructing a capacitive current model and inversely deriving a digital waveform, the current waveform under normal conditions can be simulated and compared with the actual signal, which helps to identify the abnormal patterns of the leakage current and distinguish normal current from potential leakage current. When the amplitude of the target current signal exceeds the threshold, it is automatically identified as a potential anomaly and an alarm is triggered. This mechanism can quickly detect possible electrical hazards and reduce the need for manual intervention.

[0081] In one embodiment, the electromagnetic noise detection module includes:

[0082] An electromagnetic noise sensor device startup module, used to activate the power supply of the ultrasonic sensor through a first control instruction and perform electromagnetic noise sampling at a preset sampling frequency to obtain initial electromagnetic noise data;

[0083] An electromagnetic noise filtering module, used to filter the initial electromagnetic noise data through a band-pass filter to obtain target noise data, and perform digital signal conversion on the target noise data to obtain noise detection parameters.

[0084] In one implementation, activating the power supply through the ultrasonic sensor and performing electromagnetic noise sampling at a preset sampling frequency ensures the high accuracy and timeliness of the collected data. Using a band-pass filter to filter the initial electromagnetic noise data can effectively remove low-frequency and high-frequency interference noises, only retaining the frequency band useful for the target noise data, which not only improves the quality of the noise data but also avoids misjudgment caused by unnecessary frequency interference.

[0085] In one implementation, the preset sampling frequency is determined by the technician; the ultrasonic sensor can be SPU0410LR5H-QB, ADMP401, ICS-43434, etc.; the band-pass filter

[0086] In one implementation, processing the target noise data through digital signal conversion can convert the analog signal into a digital signal, facilitating subsequent noise detection and analysis. Digital signal processing can achieve more accurate calculation of noise parameters, improving the reliability and accuracy of the detection.

[0087] In one implementation, automatically activating the power supply and starting processes such as data acquisition and filtering through control instructions reduces the need for manual intervention, improves work efficiency and the continuity of data acquisition.

[0088] In one embodiment, the magnetic field detection module includes:

[0089] A magnetic field detection device startup module, configured to activate the power supply of the triaxial magnetic field sensor through a second control instruction, and perform magnetic field sampling at a preset sampling frequency to obtain initial magnetic field distribution data;

[0090] A magnetic field distribution filtering module, configured to substitute the initial magnetic field distribution data into an instrumentation amplifier, and then perform active demagnetization through an orthogonal coil to obtain target magnetic field distribution data, and perform digital signal conversion on the target magnetic field distribution data to obtain field strength parameters.

[0091] In one implementation, by activating the triaxial magnetic field sensor and performing magnetic field sampling at a preset sampling frequency, the magnetic field intensity in each direction in space can be accurately captured to ensure high-quality initial magnetic field distribution data; inputting the initial magnetic field distribution data into an instrumentation amplifier and using an orthogonal coil for active demagnetization can effectively remove the influence of external interference magnetic fields and improve the purity of the measured data; the orthogonal coil can effectively eliminate stray magnetic fields by precisely controlling the phase and amplitude of the magnetic field, and obtain more accurate target magnetic field data.

[0092] In one implementation, after performing digital signal conversion on the target magnetic field distribution data, the field strength parameters can be conveniently calculated, so that the intensity data of the magnetic field can be converted into digital signals, which is convenient for subsequent analysis, storage, and further processing. This not only increases the operability of the data but also facilitates linkage with other devices or systems.

[0093] In one implementation, the power supply and sampling process of the magnetic field sensor are automatically started through a second control instruction, reducing the complexity and possible errors of manual operations, improving work efficiency and accuracy. In addition, the automated operation process allows the device to operate stably for a long time and reduces manual intervention.

[0094] In one embodiment, the data processing module further includes:

[0095] A noise detection parameter filtering module, configured to filter the noise detection parameters through an FIR digital filter to obtain target noise parameters;

[0096] A target energy ratio determination module, configured to calculate the energy ratio of the target noise parameters in the target frequency band to obtain a target energy ratio. If the target energy ratio is greater than a preset energy ratio value, an arc discharge alarm instruction is generated and recorded as a fault instruction.

[0097] In one implementation, the noise detection parameters are filtered by an FIR digital filter, which can efficiently remove high-frequency and low-frequency noise signals and only retain the effective noise data in the target frequency band. The FIR filter has a linear phase characteristic and can retain the waveform of the signal without introducing distortion, which is crucial for the extraction of accurate noise parameters; the preset energy ratio is determined by technicians.

[0098] In one implementation, through the filtered target noise parameters, their spectral characteristics can be further analyzed, which can help the system identify whether there are abnormal noise signals, especially when the energy ratio in the high-frequency band or a specific frequency band is abnormal.

[0099] In one implementation, if the target energy ratio is less than or equal to the preset energy ratio, a normal instruction is generated.

[0100] In one implementation, by calculating the energy ratio (target energy ratio) of the target noise parameters in the target frequency band and comparing it with the preset energy ratio, it is possible to accurately determine whether there are abnormal phenomena such as arc discharge. If the target energy ratio exceeds the set threshold, the system will automatically generate a fault instruction and issue an alarm, timely warning of potential electrical equipment failures or safety hazards. This automated fault warning can greatly improve the safety of the system.

[0101] In one implementation, by setting the preset energy ratio, the sensitivity of the system can be adjusted according to different application scenarios, enabling the system to detect and alarm in a sensitive manner and avoiding damage to the equipment caused by potential failures.

[0102] In one implementation, the entire noise detection and energy ratio calculation process is automated. When the operator is working, the system can monitor the changes in noise parameters in real time without manual intervention. The real-time nature enables the equipment to respond quickly and react promptly to faults such as arc discharge, thus avoiding more serious faults or accidents and improving the work efficiency of the operator.

[0103] In one embodiment, the data processing module further includes:

[0104] A sliding filter processing module for performing sliding average filtering on the field strength parameters to obtain the first field strength parameters;

[0105] A band-stop filter processing module for performing frequency-domain band-stop filtering on the first field strength parameters to obtain the second field strength parameters;

[0106] A wavelet denoising processing module for performing wavelet denoising on the second field strength parameters to obtain the third field strength parameters;

[0107] Determine the root mean square value and gradient change value corresponding to the third field strength parameters, and determine the fault instruction according to the root mean square value and gradient change value.

[0108] In one implementation, by using moving average filtering, short-term fluctuations and mutations in the signal can be effectively eliminated, enabling the subsequent processing module to more accurately capture the long-term trend of the signal, reducing the random fluctuations in the data, and providing a more stable basis for subsequent analysis.

[0109] In one implementation, by using a band-stop filter, interference signals within a specific frequency band can be precisely suppressed, making the signal cleaner, helping to eliminate external noise and interference, ensuring that subsequent signal processing focuses more on meaningful field strength changes, and thus improving the accuracy of fault detection.

[0110] In one implementation, by using wavelet denoising, the signal can be analyzed at multiple scales, the key information of the signal can be retained, and unnecessary noise can be effectively eliminated, improving the quality of the data.

[0111] In one implementation, both the root mean square (RMS) value and the gradient change value correspond to preset thresholds. If both the RMS value and the gradient change value are greater than their corresponding preset thresholds, it is marked as a real leakage and an alarm is immediately issued; if the RMS value is greater than the corresponding preset threshold and the gradient change value is less than or equal to the corresponding preset threshold, it is noise; if the RMS value is less than the corresponding preset threshold and the gradient change value is greater than the corresponding preset threshold, an alarm instruction is generated for the alarm module to prompt the operator to stay away, and normal instructions are generated in other cases.

[0112] In one implementation, the root mean square (RMS) value can reflect the overall strength or power change of the signal, while the gradient change value can reveal the instantaneous change rate of the signal. The combination of the two can help determine whether there are mutations, abnormal fluctuations or signs of electrical equipment failures in the field strength signal; for example, a sudden increase in the RMS value may indicate equipment failure, while a sharp change in the gradient change value can indicate the occurrence of instantaneous arc discharge or other abnormal phenomena.

[0113] In one embodiment, refer to Figure 3 , Figure 3 which is a framework diagram of another low-power human body intelligent monitoring device that is easy to wear provided by the embodiment of the present invention, and further includes a physiological characteristic detection module, and the physiological characteristic detection module includes:

[0114] A temperature monitoring module, configured to collect temperature through a temperature sensor at a first preset temperature monitoring frequency, and when the temperature is not within the preset temperature range, send a temperature anomaly instruction to the alarm module;

[0115] A heart rate monitoring module, configured to collect the heart rate through a heart rate sensor at a first preset heart rate monitoring frequency, and when the heart rate is not within the preset heart rate range, send a heart rate anomaly instruction to the alarm module;

[0116] The blood pressure monitoring module is used to collect blood pressure at the first preset blood pressure monitoring frequency through a blood pressure sensor. When the blood pressure is not within the preset blood pressure range, it sends a blood pressure abnormality instruction to the alarm module.

[0117] In one implementation, each module monitors temperature, heart rate, and blood pressure data in real time through sensors and continuously collects data according to the preset monitoring frequencies, which can provide continuous physiological data to help detect changes in the physical condition in a timely manner, especially when the health condition changes rapidly.

[0118] In one implementation, the first preset temperature monitoring frequency, the first preset heart rate monitoring frequency, and the first preset blood pressure monitoring frequency are determined by technicians; the preset temperature range, the preset heart rate range, and the preset blood pressure range are determined by technicians.

[0119] In one implementation, see Figure 2 , Figure 2 As shown in [FIGURE REFERENCE], it is a schematic diagram of module installation of a low-power human body intelligent monitoring device that is easy to wear provided by an embodiment of the present invention. The physiological characteristic detection module 6 is installed at the left cuff.

[0120] In one implementation, when the collected temperature, heart rate, or blood pressure data exceeds the preset normal range, the corresponding module will send an abnormality instruction to notify the alarm module, which can help the system quickly respond to potential health problems.

[0121] In one embodiment, the data processing module further includes:

[0122] If there is a fault instruction in the fault instruction set, it generates a second preset temperature monitoring frequency instruction, a second preset heart rate monitoring frequency instruction, and a second preset blood pressure monitoring frequency instruction and sends them to the physiological characteristic detection module, so that the physiological characteristic detection module collects data according to the second preset temperature monitoring frequency instruction, the second preset heart rate monitoring frequency instruction, and the second preset blood pressure monitoring frequency instruction.

[0123] In one implementation, when the system detects a fault instruction (such as abnormal temperature, heart rate, or blood pressure), it will automatically adjust the monitoring frequency. Only at this time will the data collection frequency be increased, reducing the power requirement.

[0124] In one implementation, the second preset temperature monitoring frequency instruction, the second preset heart rate monitoring frequency instruction, and the second preset blood pressure monitoring frequency are all greater than the first preset temperature monitoring frequency, the first preset heart rate monitoring frequency, and the first preset blood pressure monitoring frequency. By increasing the monitoring frequencies of temperature, heart rate, and blood pressure, the system can more accurately monitor the body state and make timely responses according to the rapid changes in the data.

[0125] In one implementation, by dynamically adjusting the sampling frequency according to the fault instruction, the system can flexibly adapt to different health states and adjust the monitoring frequency according to actual needs.

[0126] The above has described a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered as defining the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application shall still fall within the scope covered by the patent of the present invention.

Claims

1. A low-power human body intelligent monitoring device that is convenient to wear, characterized in that, The device includes a current detection module, a magnetic field detection module, an electromagnetic noise detection module, a data processing module, and an alarm module: The current detection module is used to collect the human leakage current in real time and convert the human leakage current into a first digital signal and send it to the data processing module; The data processing module is used to perform signal analysis on the first digital signal. If the signal analysis result is suspiciously abnormal, it sends a first control instruction to the electromagnetic noise detection module and a second control instruction to the magnetic field detection module respectively; The electromagnetic noise detection module is used to perform electromagnetic noise detection according to the first control instruction to obtain noise detection parameters and send the noise detection parameters to the data processing module; The magnetic field detection module is used to perform magnetic field detection according to the second control instruction to obtain field strength parameters and send the field strength parameters to the data processing module; The data processing module is used to analyze the noise detection parameters and the field strength parameters respectively to obtain a fault instruction set and send the fault instruction set to the alarm module to generate a corresponding alarm signal.

2. The low-power human body intelligent monitoring device convenient to wear according to claim 1, characterized in that, The current detection module includes: A leakage current acquisition module, which is used to collect the human leakage current in real time through a capacitance sensor to obtain an electrical signal; An amplification module, which is used to amplify the electrical signal through an operational amplifier to obtain an amplified electrical signal; A signal conversion module, which is used to convert the amplified electrical signal into a first digital signal through an analog-to-digital converter.

3. The low-power human body intelligent monitoring device convenient to wear according to claim 2, characterized in that, The data processing module includes: A filtering module, which is used to filter the first digital signal through a band-pass filter to obtain a second digital signal; A harmonic analysis module, which is used to perform a fast Fourier transform on the second digital signal to obtain the amplitudes and phases of the fundamental wave and harmonics, and calculate the amplitude ratio of the third harmonic to the fundamental wave to obtain a target ratio; A target current signal generation module, which is used to construct a capacitive current model according to the target ratio, generate a capacitive current digital waveform through harmonic back-projection, and calculate the difference between the second digital signal and the capacitive current digital waveform to obtain a target current signal; A signal analysis module, which is used to record the signal analysis result as suspiciously abnormal if the amplitude of the target current signal is greater than a preset current threshold.

4. A low-power human body intelligent monitoring device that is convenient to wear according to claim 1, characterized in that, The electromagnetic noise detection module includes: An electromagnetic noise sensor device startup module, which is used to activate the power supply of the ultrasonic sensor through a first control instruction and perform electromagnetic noise sampling at a preset sampling frequency to obtain initial electromagnetic noise data; An electromagnetic noise filtering module, which is used to filter the initial electromagnetic noise data through a band-pass filter to obtain target noise data, and perform digital signal conversion on the target noise data to obtain noise detection parameters.

5. An easily wearable low-power human body intelligent monitoring device according to claim 4, characterized in that, The magnetic field detection module includes: A magnetic field detection device startup module, which is used to activate the power supply of the three-axis magnetic field sensor through a second control instruction and perform magnetic field sampling at the preset sampling frequency to obtain initial magnetic field distribution data; A magnetic field distribution filtering module, which is used to substitute the initial magnetic field distribution data into an instrumentation amplifier, and then obtain target magnetic field distribution data through active demagnetization by an orthogonal coil, and perform digital signal conversion on the target magnetic field distribution data to obtain field strength parameters.

6. An easily wearable low-power human body intelligent monitoring device according to claim 4, characterized in that, The data processing module further includes: A noise detection parameter filtering module, which is used to filter the noise detection parameters through an FIR digital filter to obtain target noise parameters; A target energy ratio determination module, which is used to calculate the energy ratio of the target noise parameters in the target frequency band to obtain a target energy ratio. If the target energy ratio is greater than a preset energy ratio value, an arc discharge alarm instruction is generated and recorded as a fault instruction.

7. An easy-to-wear low-power human body intelligent monitoring device according to claim 5, characterized in that, The data processing module further includes: A sliding filtering processing module, which is used to perform sliding average filtering on the field strength parameters to obtain first field strength parameters; A band-stop filtering processing module, which is used to perform frequency-domain band-stop filtering on the first field strength parameters to obtain second field strength parameters; A wavelet denoising processing module, which is used to perform wavelet denoising on the second field strength parameters to obtain third field strength parameters; Determine the root mean square value and gradient change value corresponding to the third field strength parameters, and determine a fault instruction according to the root mean square value and the gradient change value.

8. An easy-to-wear low-power human body intelligent monitoring device according to claim 1, characterized in that, The device further includes a physiological feature detection module, and the physiological feature detection module includes: A temperature monitoring module, which is used to collect temperature through a temperature sensor at a first preset temperature monitoring frequency. When the temperature is not within the preset temperature range, a temperature anomaly instruction is sent to the alarm module; A heart rate monitoring module, which is used to collect the heart rate through a heart rate sensor at a first preset heart rate monitoring frequency. When the heart rate is not within the preset heart rate range, a heart rate anomaly instruction is sent to the alarm module; A blood pressure monitoring module, which is used to collect blood pressure through a blood pressure sensor at a first preset blood pressure monitoring frequency. When the blood pressure is not within the preset blood pressure range, a blood pressure anomaly instruction is sent to the alarm module.

9. An easy-to-wear low-power human body intelligent monitoring device according to claim 8, characterized in that, The data processing module further includes: If there is a fault instruction in the fault instruction set, a second preset temperature monitoring frequency instruction, a second preset heart rate monitoring frequency instruction, and a second preset blood pressure monitoring frequency instruction are generated and sent to the physiological feature detection module, so that the physiological feature detection module performs data collection according to the second preset temperature monitoring frequency instruction, the second preset heart rate monitoring frequency instruction, and the second preset blood pressure monitoring frequency instruction.

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