A passive device state monitoring method of micro-current self-induction energy storage

Abstract

The present application relates to the technical field of industrial equipment and environmental protection monitoring, and proposes a passive equipment state monitoring method of micro-current self-induction energy storage, which senses power from the monitored line through a mutual inductor, stores it in an energy storage capacitor after rectification, and realizes self-starting, overvoltage protection and under-voltage restart of the system by using voltage threshold control to build a passive self-powered system; a super-low power hardware architecture and a sleep wake-up mechanism are used to wake up for data collection and transmission only when necessary to match the micro-energy power supply characteristics; Fourier transform technology is introduced to process the current signal in the frequency domain to filter out interference and improve measurement accuracy; a built-in micro switch monitors the state of the equipment shell in real time, and triggers an early warning and priority upload as soon as the cover opening behavior is detected to prevent data tampering. The method realizes accurate monitoring of the running state of the equipment without external power supply, significantly reduces the deployment and maintenance cost, and improves the authenticity and reliability of the supervision data.

Description

Technical Field

[0001] This invention relates to the field of industrial equipment and environmental monitoring technology, specifically to a passive equipment condition monitoring method for micro-current self-inductive energy storage. Background Technology

[0002] In the fields of industrial manufacturing, environmental supervision, and energy management, real-time monitoring of the operational status of production equipment and pollution control facilities is a crucial means of achieving refined management, fault early warning, and compliance verification. Traditional equipment status monitoring typically relies on wired power supply, requiring the laying of dedicated power lines, or the use of battery-powered wireless sensor nodes. However, industrial production environments are complex, many older devices lack reserved interfaces, and adding new power lines is not only difficult and costly to construct, but also poses safety hazards in many high-risk or enclosed scenarios. While battery-powered solutions offer flexible deployment, they are limited by battery life and require frequent replacements. Maintenance costs are extremely high in long-term unattended outdoor or remote scenarios, and discarded batteries can easily cause environmental pollution.

[0003] While existing technologies have attempted to use solar energy or vibration energy harvesting for auxiliary power supply, their stability is easily affected by the environment, making reliable operation under all weather conditions impossible. Regarding data acquisition, traditional current monitoring often uses direct time-domain sampling, which is susceptible to power frequency interference and harmonics, and the measurement accuracy is insufficient to meet the refined requirements of energy consumption analysis and fault diagnosis. Furthermore, the monitoring equipment itself has security vulnerabilities; unauthorized opening of covers, wiring tampering, or data interference at the physical level are difficult to detect and trace, leading to distorted monitoring data and undermining regulatory credibility. Therefore, there is an urgent need for a device status monitoring solution that can eliminate dependence on external power sources and combines high accuracy with anti-cheating capabilities.

[0004] To address the aforementioned technical challenges, this solution proposes a passive equipment status monitoring method based on micro-current self-inductive energy storage. Under conditions without external power supply, it achieves accurate, reliable, and fraud-proof monitoring of equipment operating status, providing an innovative technical approach for remote intelligent supervision in industrial and environmental fields. Summary of the Invention

[0005] To address the technical problems of existing monitoring equipment relying on external power supply, high deployment and maintenance costs, and easy data tampering, this invention provides a passive equipment status monitoring method based on microcurrent self-sensing energy storage.

[0006] To achieve the above-mentioned objective, the present invention provides the following technical solution: a passive device condition monitoring method for micro-current self-inductive energy storage, comprising the following steps: Monitoring system hardware setup: The system includes current transformers, rectifier circuits, energy storage capacitors, power management chips, ultra-low power MCUs, measurement modules, LoRa communication modules, micro switches, charging cut-off circuits, enable circuits, and ADC analog-to-digital converters. The current transformers are non-contact snap-fit ​​structures, and the micro switches are built into the closed parts of the equipment housing.

[0007] Microcurrent self-induction energy storage and power supply control: It utilizes the current of the power supply line of the monitored equipment to achieve self-induction energy storage, and controls the start and stop of the circuit through voltage threshold control to achieve passive power supply.

[0008] Ultra-low power current data acquisition and accuracy optimization: After the hardware system is powered on, an intermittent acquisition mode combined with Fourier transform technology is used to achieve accurate acquisition of the power current.

[0009] Wireless data transmission and sleep-wake cycle: Combining LORA low-power communication technology to achieve remote transmission of monitoring data, and reducing hardware system power consumption through sleep-wake mechanism to form a periodic monitoring work cycle.

[0010] Anti-cheating monitoring and anomaly warning: The built-in micro switch detects human intervention in the equipment, ensuring the authenticity and integrity of the monitoring data.

[0011] Equipment operation status analysis and remote monitoring: After receiving monitoring data and early warning signals, the remote data center and application platform conduct comprehensive analysis and real-time monitoring of the operation status of the monitored equipment.

[0012] Preferably, the microcurrent self-sensing energy storage and power supply control includes: Inductive power supply: The current transformer is attached to the AC power supply line of the monitored equipment at a turns ratio of 1:1000 to induce a small AC current signal.

[0013] Rectification and energy storage: After the induced current is rectified by the rectifier circuit, it is stored in the energy storage capacitor through the rectifier diode. At this time, except for the energy storage-related components, all other components are in a power-off and shutdown state.

[0014] Low-voltage threshold start-up: The ADC analog-to-digital converter collects the voltage of the energy storage capacitor in real time. When the voltage reaches 2.5V, the ultra-low power MCU triggers the power management chip to turn on and supply power to the subsequent circuits.

[0015] Overvoltage protection cutoff: When the energy storage capacitor voltage exceeds 5.2V, the ultra-low power MCU controls the charging cutoff circuit to disconnect the charging circuit.

[0016] Undervoltage shutdown and restart: When the voltage of the energy storage capacitor drops below 2.5V, the power management chip automatically shuts down, all subsequent circuits are powered off, and the hardware system returns to the energy storage state only.

[0017] Preferably, when the energy storage capacitor voltage is between 2.5V and 5.2V, the ultra-low power MCU controls the on / off state of the charging cutoff circuit to achieve selective suspension of energy storage.

[0018] Preferably, the ultra-low power current data acquisition and accuracy optimization includes: Low-power acquisition settings: The ultra-low-power MCU controls the measurement module to perform intermittent acquisition at a sampling rate of 1Hz. At the same time, the ADC analog-to-digital converter continuously monitors the energy storage capacitor voltage. When the energy storage capacitor voltage is lower than 3V, the hardware system automatically switches to low-power mode.

[0019] Signal processing and accuracy optimization: The ultra-low power MCU performs Fourier transform processing on the acquired analog current signal and eliminates signal interference through frequency domain analysis.

[0020] Data storage: The ultra-low power MCU temporarily stores the processed current and power digital data locally.

[0021] Preferably, the data wireless transmission and sleep / wake cycle includes: Data transmission trigger: After the ultra-low power MCU completes a single data acquisition and processing, it triggers the LORA communication module to start and wirelessly transmits the data to the local power data concentrator via the 470MHz frequency band according to the Modbus RTU protocol.

[0022] Deep sleep control: After data transmission is completed, the ultra-low power MCU sends a power-off command to the measurement module and the LORA communication module, retaining only the voltage acquisition function of the ADC analog-to-digital converter and the basic control function of the ultra-low power MCU, and the hardware system enters deep sleep mode.

[0023] Sleep-wake cycle: When the energy storage capacitor voltage reaches 3.0V, the ultra-low power MCU triggers the measurement module and LORA communication module to power on and wake up, repeatedly executing the acquisition, processing, transmission and sleep operations.

[0024] Preferably, the anti-cheating monitoring and anomaly warning includes: Cheating detection: When the device casing is opened, the microswitch sends an abnormal electrical signal to the ultra-low power MCU.

[0025] Warning signal transmission: After receiving the abnormal signal, the ultra-low power MCU binds the anti-cheating abnormal information with the currently collected current and power data and uploads it through the LORA communication module.

[0026] Continuous monitoring of abnormal conditions: If the device casing is not closed again, the ultra-low power MCU will continuously send anti-cheating warning signals until the device casing is closed again.

[0027] Preferably, the equipment operation status analysis and remote monitoring includes: Data reception and storage: The application platform classifies and stores the received power consumption data, power data, and anti-cheating warning information.

[0028] Status assessment and anomaly warning: The application platform compares the real-time collected data with preset thresholds, and issues an alarm for abnormal device operation when the data is abnormal.

[0029] Remote monitoring: Supervisors can remotely view the real-time data and historical records of the monitored equipment through computer or mobile application platforms.

[0030] Preferably, for pollution control equipment, the application platform binds the power supply line monitoring data of the pollutant generating equipment and the pollution control equipment, and through the current linkage between the two, it determines whether the pollution control equipment is operating illegally by not turning on when it should and issues corresponding warnings.

[0031] Preferably, the monitoring equipment operation and maintenance steps are also included: a professional inspection of the hardware system is carried out every six months, including the induction accuracy of the current transformer, the capacity of the energy storage capacitor, the signal triggering sensitivity of the micro switch, the signal strength of the LORA communication module, and aging or damaged components are replaced.

[0032] Preferably, the current transformer has a non-contact snap-fit ​​structure, and the components of the hardware system are integrated on a circuit board with a size of less than 2.5cm × 2.8cm.

[0033] Compared with the prior art, the present invention provides a passive device condition monitoring method for micro-current self-inductive energy storage, which has the following beneficial effects:

[0034] 1. This solution utilizes micro-current self-induction energy storage technology to directly obtain power from the power supply line of the monitored equipment, eliminating the need for an external power source or battery replacement. This completely solves the problems of power supply difficulties and complex wiring associated with existing monitoring equipment in industrial and environmental scenarios. Combined with ultra-low power hardware design and a sleep-wake mechanism, the system only wakes up when necessary, remaining in deep sleep mode the rest of the time. This significantly improves energy utilization efficiency and achieves long-term, maintenance-free, stable operation. The current transformer adopts a non-contact snap-fit ​​structure, supporting live installation. Its highly integrated circuit board is compact and can be flexibly adapted to various devices, reducing deployment barriers and subsequent maintenance costs. It possesses broad scenario adaptability and large-scale promotion value.

[0035] 2. In this solution, at the measurement and monitoring level, Fourier transform technology is used to perform frequency domain analysis on the collected current signal, effectively filtering out power frequency interference and harmonic noise, improving the measurement accuracy of parameters such as current and power, and providing reliable data support for equipment energy consumption analysis and fault diagnosis. A built-in microswitch monitors the equipment casing status in real time; once human intervention such as opening the casing or tampering is detected, an early warning is immediately triggered and abnormal data is uploaded first, effectively preventing data falsification and illegal equipment interference, and ensuring the authenticity and integrity of the monitoring data. Combined with LORA low-power wide-area communication and a cloud platform, remote automatic transmission, storage, analysis, and visualization of monitoring data are achieved. Multi-level users can view equipment status and historical records in real time, significantly reducing the frequency of manual inspections, improving the level of intelligent supervision, and fundamentally solving the problems of poor data reliability and low supervision efficiency in existing technologies. Attached Figure Description

[0036] Figure 1 This is a block diagram of the hardware system structure of the present invention; Figure 2 This is a flowchart of the microcurrent self-induction energy storage and power supply control of the present invention; Figure 3 This is a flowchart of the ultra-low power current data acquisition and accuracy optimization process of the present invention; Figure 4 This is a flowchart of the data wireless transmission and sleep / wake-up loop of the present invention; Figure 5 This is a schematic diagram illustrating the anti-cheating monitoring and anomaly warning system of the present invention; Figure 6 This is a schematic diagram illustrating the equipment operation status analysis and remote monitoring of the present invention; Figure 7 This is a schematic diagram illustrating the operation and maintenance of the monitoring equipment of the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Please see Figures 1 to 7This paper presents a passive device status monitoring method based on micro-current self-induction energy storage technology. This method achieves passive power supply by combining ultra-low power consumption design, precise Fourier transform measurement, LORA wireless communication, and anti-cheating monitoring. It enables current status monitoring of industrial production equipment, pollution control equipment, and other electrical equipment without an external power source. The method can accurately collect equipment current data, upload it in real time, and issue early warnings for anomalies. It also features low energy consumption, easy deployment, and tamper-proof characteristics, making it suitable for monitoring scenarios where external power supply is difficult. The specific implementation steps are as follows:

[0039] Step 1: Hardware Setup for the Monitoring System The hardware system for implementing this monitoring method is constructed, which includes a current transformer, a rectifier circuit, an energy storage capacitor, a power management chip, an ultra-low power MCU, a measurement module, a LoRa communication module, a micro switch, a charging cut-off circuit, an enable circuit, and an ADC analog-to-digital converter. The current transformer has a non-contact snap-fit ​​structure, which is suitable for live installation of AC power supply lines. The micro switch is built into the closed part of the equipment shell. All components of the hardware system are integrated into a circuit board with a size of less than 2.5cm × 2.8cm. The hardware connection is as follows: the output of the current transformer is connected to the energy storage capacitor through a rectifier diode. The energy storage capacitor is electrically connected to the charging cutoff circuit, the power management chip, and the ADC analog-to-digital converter. The power management chip supplies power to the ultra-low power MCU, the measurement module, and the LoRa communication module through an enable circuit. The ultra-low power MCU is electrically connected to the measurement module, the LoRa communication module, the micro switch, the charging cutoff circuit, and the ADC analog-to-digital converter. The ADC analog-to-digital converter is used to collect the voltage signal of the energy storage capacitor and transmit it to the ultra-low power MCU.

[0040] Step 2: Micro-current self-induction energy storage and power supply control The system utilizes the self-current of the power supply line of the monitored equipment to achieve self-induced energy storage, and controls the start and stop of the circuit through a voltage threshold to achieve passive power supply. The specific steps include: 1. Inductive power supply: The current transformer is snapped onto the AC power supply line of the monitored equipment at a turns ratio of 1:1000. The current transformer induces a small AC current signal of a few milliamps to several hundred milliamps from the large current of the monitored line. The amplitude of the small AC current signal depends on the load current of the monitored line. 2. Rectification and Energy Storage: The induced sinusoidal AC small current signal is rectified by the rectifier circuit to convert the current of both the positive and negative half-axis of the sinusoidal wave into DC power. The DC power is stored in the energy storage capacitor through the unidirectional conduction characteristic of the rectifier diode. At this time, the initial voltage of the energy storage capacitor is 0V. All induced current is used for energy storage. Except for the energy storage-related components, the other components in the hardware system are in a power-off and shutdown state, and the leakage current is <1μA. 3. Low-voltage threshold start-up: The ADC analog-to-digital converter collects the voltage signal of the energy storage capacitor in real time and transmits it to the ultra-low power MCU. When the voltage of the energy storage capacitor reaches the 2.5V operating threshold, the ultra-low power MCU triggers the power management chip to turn on. The power management chip provides a stable operating power to the subsequent circuits through the enable circuit, and the hardware system enters the working state. 4. Overvoltage protection cutoff: When the ADC analog-to-digital converter detects that the energy storage capacitor voltage exceeds the 5.2V safety threshold, the ultra-low power MCU controls the switching MOSFET in the charging cutoff circuit to disconnect the current transformer from the energy storage capacitor, stopping the charging of the energy storage capacitor. At the same time, the induced current automatically leaks through the bypass diode. When the energy storage capacitor voltage is in the range of 2.5V to 5.2V, the ultra-low power MCU dynamically controls the on / off of the charging cutoff circuit through software algorithm to achieve selective suspension of energy storage. 5. Undervoltage shutdown and restart: During the operation of the hardware system, the energy stored in the energy storage capacitor is consumed. When the ADC analog-to-digital converter detects that the voltage of the energy storage capacitor has dropped below 2.5V, the power management chip automatically shuts down, all subsequent circuits are powered off and stop running, and the hardware system returns to the energy storage-only working state until the voltage of the energy storage capacitor reaches the 2.5V working threshold again and restarts.

[0041] In this step, the energy conversion efficiency of the hardware system is 80% to 90%, and the energy storage efficiency is ≥85%. When the load current of the monitored equipment is 10A, the time for the energy storage capacitor voltage to rise to 2.5V is 10 to 15 seconds. The energy storage capacitor can maintain the continuous operation of the hardware system for 1 to 5 minutes when fully loaded.

[0042] Step 3: Ultra-low power current data acquisition and accuracy optimization After the hardware system is powered on, it uses an intermittent acquisition mode combined with Fourier transform technology to achieve accurate acquisition of the power current. The specific steps include: 1. Low power consumption acquisition settings: The ultra-low power MCU controls the measurement module to intermittently acquire the power consumption current of the monitored device at a sampling rate of 1Hz. At the same time, the ADC analog-to-digital converter continuously monitors the voltage of the energy storage capacitor. When the voltage of the energy storage capacitor is lower than 3V, the hardware system automatically switches to low power consumption mode, and the power consumption of the whole machine is <10mW. 2. Signal Processing and Accuracy Optimization: The measurement module transmits the acquired analog current signal to the ultra-low power MCU. The ultra-low power MCU performs Fourier transform processing on the analog current signal and eliminates signal interference through frequency domain analysis, thereby improving the measurement accuracy of power consumption and ensuring the accuracy of current data. 3. Data Temporary Storage: The ultra-low power MCU will temporarily store the current and power digital data after Fourier transform processing locally, waiting for data transmission instructions.

[0043] Step 4: Wireless Data Transmission and Sleep / Wake-up Loop By combining LoRa low-power communication technology to achieve remote transmission of monitoring data, and reducing hardware system power consumption through a sleep-wake mechanism, a periodic monitoring cycle is formed. The specific steps include: 1. Data transmission trigger: After the ultra-low power MCU completes the acquisition and processing of a single current data, it triggers the LORA communication module to start. The LORA communication module wirelessly transmits the temporarily stored current and power data to the local power data concentrator through the 470MHz frequency band according to the Modbus RTU protocol. After the power data concentrator performs preliminary processing on the data, it uploads the data to the remote data center and application platform through 3G / 4G / broadband network. 2. Deep Sleep Control: After data transmission is completed, the ultra-low power MCU immediately sends a power-off command to the measurement module and the LORA communication module, retaining only the voltage acquisition function of the ADC analog-to-digital converter and the basic control function of the ultra-low power MCU, and the hardware system enters deep sleep mode; 3. Sleep-Wake-up Cycle: In deep sleep mode, the ADC analog-to-digital converter continuously collects the energy storage capacitor voltage and transmits it to the ultra-low power MCU. When the energy storage capacitor voltage is maintained above 2.5V and reaches the 3.0V acquisition threshold, the ultra-low power MCU triggers the measurement module and LORA communication module to power on and wake up, repeatedly performing the operations of current acquisition, Fourier transformation, data transmission, and deep sleep, so as to realize continuous intermittent monitoring of the current of the monitored device.

[0044] Step 5: Anti-cheating monitoring and anomaly warning The detection of human intervention in the equipment is achieved through a built-in microswitch, ensuring the authenticity and integrity of the monitoring data. This is achieved through the following steps: 1. Cheating detection: The micro switch maintains real-time electrical communication with the ultra-low power MCU. When the device casing is closed, the micro switch is in a steady state. When the device casing is opened by a person, or hardware tampering or data interference is carried out, the opening and closing action of the device casing triggers the steady state switching of the micro switch, and the micro switch sends an abnormal electrical signal to the ultra-low power MCU. 2. Warning signal transmission: After receiving an abnormal electrical signal from the micro switch, the ultra-low power MCU immediately triggers the warning mechanism, binds the anti-cheating anomaly information with the currently collected current and power data, assigns the transmission priority to the bound data packet, and uploads the bound data packet to the remote data center and application platform through the LORA communication module to realize anti-cheating anomaly reminder; 3. Continuous monitoring of abnormal states: If the device casing does not close, the micro switch continuously sends abnormal electrical signals to the ultra-low power MCU. The ultra-low power MCU continuously sends anti-cheating warning signals at fixed time intervals until the device casing closes and the micro switch returns to a steady state.

[0045] Step Six: Equipment Operation Status Analysis and Remote Monitoring After receiving monitoring data and early warning signals, the remote data center and application platform perform comprehensive analysis and real-time monitoring of the operating status of the monitored equipment, specifically including the following steps: 1. Data reception and storage: The application platform receives real-time data on the power consumption of the monitored equipment, power data, and anti-cheating warning information transmitted by the LORA communication module. It classifies and stores various types of data and establishes an equipment energy consumption operation ledger that includes real-time data, historical change curves, anomaly records, and warning occurrence times. 2. Status Judgment and Anomaly Warning: Based on the rated operating parameters of the monitored equipment, the application platform presets the current and power thresholds for normal operation of the equipment. It compares the real-time collected data with the preset thresholds. When abnormal conditions such as sudden increases, sudden decreases, or no current occur, the application platform issues an equipment operation anomaly warning through pop-ups, SMS messages, etc. For pollution control equipment, the application platform binds the power supply line monitoring data of the pollutant generating equipment and the pollution control equipment. Through the current linkage between the two, it determines whether the pollution control equipment is operating illegally by not turning on when it should and issues corresponding warnings. 3. Remote monitoring and management: Environmental regulatory departments and enterprise managers can remotely view the real-time current and power data, historical energy consumption curves, abnormal warning records, and anti-cheating records of the monitored equipment through computer and mobile application platforms, thereby realizing remote intelligent monitoring of the operating status of the monitored equipment.

[0046] Step 7: Operation and Maintenance of Monitoring Equipment To ensure the continued effectiveness of this monitoring method, regular maintenance and environmental management of the hardware system are required, specifically including the following steps: 1. Regular professional inspection: A professional inspection of the hardware system is carried out every six months. The inspection includes the induction accuracy of the current transformer, the capacity of the energy storage capacitor, the signal triggering sensitivity of the micro switch, and the signal strength of the 470MHz band of the LORA communication module. Aging, damaged or substandard components are replaced in a timely manner. 2. Installation Environment Control: The installation environment of the hardware system must meet the requirements of being dry, free of corrosive gases, and free from strong electromagnetic interference to ensure that the induction accuracy of the current transformer is not affected by electromagnetic interference, that the circuit components are not corroded by corrosive gases, and that the signal transmission of the LORA communication band is unobstructed. 3. Professional Operation and Implementation: The installation, disassembly, and maintenance of the hardware system are all carried out by professional technicians in accordance with the operating procedures. The current transformer is installed on the monitored line according to the current direction marking clips to avoid hardware damage, wiring errors, and abnormal data acquisition caused by unprofessional operation.

[0047] This method, through the above technical steps, enables passive, maintenance-free, permanent real-time monitoring of the current and power of the monitored equipment, with a mean time between failures (MTBF) of more than 5 years for the hardware system. This method's passive self-inductive power supply design solves the power supply problem in remote monitoring scenarios in the industrial and environmental protection fields, eliminating the need for external power supplies or battery replacements, thus reducing equipment deployment and subsequent maintenance costs. The ultra-low power consumption design, combined with a sleep / wake-up mechanism, ensures long-term stable operation of the hardware system. Fourier transform technology effectively eliminates signal interference, improves monitoring data accuracy, and provides data support for equipment energy management and fault diagnosis. The anti-cheating design of the microswitch effectively prevents human data tampering and equipment disassembly, ensuring the authenticity of monitoring data. LORA wireless communication, combined with a remote application platform, enables intelligent monitoring of equipment operating status, reducing the frequency of manual inspections and improving monitoring efficiency. The non-contact snap-fit ​​design of the current transformer supports live installation, and the miniaturized circuit board design is adaptable to various industrial and environmental equipment monitoring scenarios. It possesses low-cost and easily promoted technical characteristics, enabling large-scale deployment and application.

[0048] Finally, it should be noted that the above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution. Any obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A passive device condition monitoring method for micro-current self-inductive energy storage, characterized in that: Includes the following steps: Monitoring system hardware setup: A hardware system including current transformers, rectifier circuits, energy storage capacitors, power management chips, ultra-low power MCUs, measurement modules, LORA communication modules, micro switches, charging cut-off circuits, enable circuits, and ADC analog-to-digital converters is set up. The current transformers are non-contact snap-fit ​​structures, and the micro switches are built into the closed part of the equipment housing. Microcurrent self-induction energy storage and power supply control: It utilizes the self-current of the power supply line of the monitored equipment to achieve self-induction energy storage, and controls the start and stop of the circuit through the voltage threshold to achieve passive power supply; Ultra-low power current data acquisition and accuracy optimization: After the hardware system is powered on, an intermittent acquisition mode combined with Fourier transform technology is used to achieve accurate acquisition of the power current. Wireless data transmission and sleep-wake cycle: The remote transmission of monitoring data is achieved by combining LORA low-power communication technology and the power consumption of the hardware system is reduced by the sleep-wake mechanism, forming a periodic monitoring work cycle; Anti-cheating monitoring and anomaly warning: The built-in micro switch detects human intervention in the equipment, ensuring the authenticity and integrity of the monitoring data; Equipment operation status analysis and remote monitoring: After receiving monitoring data and early warning signals, the remote data center and application platform conduct comprehensive analysis and real-time monitoring of the operation status of the monitored equipment.

2. The method for monitoring the condition of a passive device with microcurrent self-inductive energy storage according to claim 1, characterized in that: The microcurrent self-sensing energy storage and power supply control includes: Inductive power supply: The current transformer is snapped onto the AC power supply line of the monitored equipment at a turns ratio of 1:1000 to induce a small AC current signal; Rectification and energy storage: After the induced current is rectified by the rectifier circuit, it is stored in the energy storage capacitor through the rectifier diode. At this time, except for the energy storage-related components, all other components are in a power-off and shutdown state. Low-voltage threshold start-up: The ADC analog-to-digital converter collects the voltage of the energy storage capacitor in real time. When the voltage reaches 2.5V, the ultra-low power MCU triggers the power management chip to turn on and supply power to the subsequent circuits. Overvoltage protection cutoff: When the energy storage capacitor voltage exceeds 5.2V, the ultra-low power MCU controls the charging cutoff circuit to disconnect the charging circuit; Undervoltage shutdown and restart: When the voltage of the energy storage capacitor drops below 2.5V, the power management chip automatically shuts down, all subsequent circuits are powered off, and the hardware system returns to the energy storage state only.

3. The method for monitoring the condition of a passive device with microcurrent self-inductive energy storage according to claim 2, characterized in that: When the energy storage capacitor voltage is between 2.5V and 5.2V, the ultra-low power MCU controls the on / off state of the charging cutoff circuit to achieve selective suspension of energy storage.

4. The method for monitoring the condition of a passive device with microcurrent self-inductive energy storage according to claim 1, characterized in that: The ultra-low power current data acquisition and accuracy optimization includes: Low-power acquisition settings: The ultra-low-power MCU controls the measurement module to perform intermittent acquisition at a sampling rate of 1Hz. At the same time, the ADC analog-to-digital converter continuously monitors the energy storage capacitor voltage. When the energy storage capacitor voltage is lower than 3V, the hardware system automatically switches to low-power mode. Signal processing and accuracy optimization: The ultra-low power MCU performs Fourier transform processing on the acquired analog current signal and eliminates signal interference through frequency domain analysis; Data storage: The ultra-low power MCU temporarily stores the processed current and power digital data locally.

5. The method for monitoring the condition of a passive device with microcurrent self-inductive energy storage according to claim 1, characterized in that: The data wireless transmission and sleep / wake cycle includes: Data transmission trigger: After the ultra-low power MCU completes a single data acquisition and processing, it triggers the LORA communication module to start and wirelessly transmits the data to the local power data concentrator via the 470MHz frequency band according to the Modbus RTU protocol. Deep sleep control: After data transmission is completed, the ultra-low power MCU sends a power-off command to the measurement module and the LORA communication module, retaining only the voltage acquisition function of the ADC analog-to-digital converter and the basic control function of the ultra-low power MCU, and the hardware system enters deep sleep mode; Sleep-wake cycle: When the energy storage capacitor voltage reaches 3.0V, the ultra-low power MCU triggers the measurement module and LORA communication module to power on and wake up, repeatedly executing the acquisition, processing, transmission and sleep operations.

6. The method for monitoring the condition of a passive device with microcurrent self-inductive energy storage according to claim 1, characterized in that: The anti-cheating monitoring and anomaly warning system includes: Cheating detection: When the device casing is opened, the microswitch sends an abnormal electrical signal to the ultra-low power MCU; Warning signal transmission: After receiving the abnormal signal, the ultra-low power MCU binds the anti-cheating abnormal information with the currently collected current and power data and uploads it through the LORA communication module; Continuous monitoring of abnormal conditions: If the device casing is not closed again, the ultra-low power MCU will continuously send anti-cheating warning signals until the device casing is closed again.

7. The method for monitoring the condition of a passive device with microcurrent self-inductive energy storage according to claim 1, characterized in that: The equipment operation status analysis and remote monitoring include: Data reception and storage: The application platform classifies and stores the received power consumption data, power data, and anti-cheating warning information. Status assessment and anomaly warning: The application platform compares the real-time collected data with preset thresholds, and issues an alarm for abnormal device operation when the data is abnormal; Remote monitoring: Supervisors can remotely view the real-time data and historical records of the monitored equipment through computer or mobile application platforms.

8. The method for monitoring the condition of a passive device with microcurrent self-inductive energy storage according to claim 7, characterized in that: For pollution control equipment, the application platform binds the power supply line monitoring data of the pollutant generating equipment and the pollution control equipment. By analyzing the current linkage between the two, it can determine whether the pollution control equipment is operating illegally by not turning on when it should and issue corresponding warnings.

9. The method for monitoring the condition of a passive device with microcurrent self-inductive energy storage according to claim 1, characterized in that: It also includes the operation and maintenance steps of the monitoring equipment: a professional inspection of the hardware system is carried out every six months, including the induction accuracy of the current transformer, the capacity of the energy storage capacitor, the signal triggering sensitivity of the micro switch, the signal strength of the LORA communication module, and the replacement of aging or damaged components.

10. The method for monitoring the condition of a passive device with microcurrent self-inductive energy storage according to claim 1, characterized in that: The current transformer has a non-contact snap-fit ​​structure, and all components of the hardware system are integrated on a circuit board with a size of less than 2.5cm × 2.8cm.

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