A low-power-consumption sensor cluster monitoring system and method adaptive to electromagnetic environment of a converter station

Abstract

The application discloses a kind of low-power consumption sensing cluster monitoring systems and methods suitable for electromagnetic environment of converter station.The system includes sensor node, wireless communication module, power module and control management module.Sensor node is used to collect at least two different nature sensing parameters.Control management module controls node to switch between deep sleep mode and real-time communication mode based on the comparison of sensing parameters and preset threshold.In deep sleep mode, node is periodically awakened to collect data;In real-time communication mode, wireless communication module evaluates channel quality before sending, and automatically switches to standby channel to send data if the quality is below the threshold.The application solves the technical problems of single sensor function, poor communication reliability and high power consumption in converter station monitoring through multi-parameter integration, threshold triggered dynamic power management and channel adaptive switching, and realizes long endurance, multi-dimensional and high reliable monitoring of the state of converter station.

Description

Technical Field

[0001] This invention relates to the field of converter station monitoring technology, and in particular to a low-power sensor cluster monitoring system and method adapted to the electromagnetic environment of converter stations. Background Technology

[0002] In large power facilities such as high-voltage converter stations, the safe operation of critical infrastructure (such as underground pipelines) directly affects the stability and reliability of the entire system. Therefore, real-time and continuous monitoring of these critical components is of great significance.

[0003] Currently, monitoring in such scenarios generally employs single-function sensor devices, each used to collect specific physical parameters. This approach suffers from several drawbacks: complex wiring, significantly increased installation and maintenance costs, and increased space requirements and system integration difficulties. Furthermore, the intense power frequency and transient electromagnetic interference within converter stations severely threatens conventional wireless communication. General-purpose modules lack anti-interference design, often leading to signal attenuation, data loss, and low communication reliability. In addition, traditional sensors employ extensive power management, resulting in high overall energy consumption and difficulty meeting long-term maintenance-free requirements under battery power. Frequent battery replacements in high-voltage, high-risk areas also pose significant safety hazards.

[0004] Chinese patent CN113676862B discloses a safety monitoring system and method for converter valves. However, this disclosure has significant limitations in the specific scenario of underground pipeline monitoring. First, when monitoring multiple physical quantities such as vibration, temperature, and strain along underground pipelines simultaneously, the disclosed system uses single-function sensors deployed at various points. This results in a large number of devices and densely packed locations, making deployment extremely difficult and incurring high installation and maintenance costs in confined and complex underground spaces. Second, the underground environment exhibits shielding and attenuation effects on wireless signals. Furthermore, the conventional wireless communication technology used in this disclosure suffers from further reduced communication link reliability due to the combined effects of strong electromagnetic interference from converter stations, making it difficult to guarantee stable and real-time transmission of monitoring data between underground and surface areas. Third, underground pipeline monitoring typically requires equipment to operate without maintenance for several years. However, the sensors in this disclosure have high power consumption and insufficient battery life, failing to meet this requirement. Frequent excavation for battery replacement not only damages the site and increases risks but also contradicts the fundamental purpose of long-term automated monitoring.

[0005] Therefore, existing technologies are insufficient to meet the long-term, stable, and low-maintenance monitoring requirements of underground pipelines in high-voltage converter stations, in terms of deployment feasibility, communication reliability, and endurance.

[0006] In summary, existing monitoring technologies for converter stations have significant shortcomings in terms of functional integration, communication reliability, and energy consumption control, making it difficult to meet the long-term, stable, and low-maintenance monitoring requirements in their complex electromagnetic environment. Summary of the Invention

[0007] This invention aims to provide a low-power sensor cluster monitoring system and method adapted to the electromagnetic environment of converter stations. In the harsh environment of underground pipelines in converter stations, which is characterized by strong electromagnetic interference, weak wireless signals, and the requirement for long-term maintenance-free operation, it enables long-term, highly reliable, and ultra-low-power monitoring of the multi-dimensional status of pipelines (such as vibration, temperature, and strain).

[0008] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station, characterized by comprising: Sensor nodes are used to acquire at least two different types of sensing parameters that reflect the status of the converter station; A wireless communication module is used to transmit the sensing parameters and acquire communication quality information; Power module; The control and management module is connected to the sensor node, the wireless communication module, and the power module, respectively. The control management module is configured to perform the following operations: When all sensing parameters do not exceed their corresponding preset thresholds, the system is controlled to enter deep sleep mode; when any sensing parameter exceeds its corresponding preset threshold, the system is controlled to enter real-time communication mode. In deep sleep mode, the sensor node is woken up at a first preset period to collect parameters, and the power module is controlled to cut off the power supply to the wireless communication module. In real-time communication mode, the power module is controlled to supply power to the wireless communication module, and the wireless communication module is controlled to obtain the communication quality information of the current channel before sending sensing parameters; if the communication quality information is lower than a preset quality threshold, the wireless communication module is controlled to switch to the backup channel to send data; otherwise, the wireless communication module is controlled to use the current channel to send data.

[0009] As a preferred embodiment, the wireless communication module is configured as a LoRaWAN wireless communication module; the system further includes: Multiple repeaters are used to receive and forward LoRaWAN wireless signals from the sensor nodes; At least one gateway, communicating with the repeater and / or the sensor node via a LoRaWAN wireless network, is used to aggregate data and upload the data to a backend server via a remote communication link.

[0010] Furthermore, the gateway is configured to periodically broadcast global scheduling parameters, which include a superframe start timestamp, a timeslot length, a total number of timeslots per superframe, a list of available channels, and a random salt value. The control and management module is configured to: receive the global scheduling parameters through the wireless communication module; calculate the target wake-up time slot and target communication channel of the sensor node in the current superframe using a preset hash function based on the unique identifier of the sensor node, the random salt value in the global scheduling parameters, and the current superframe number; wherein, the target wake-up time slot is a time slot within the total number of time slots in each superframe, and the target communication channel is a channel in the available channel list; In deep sleep mode, the sensor node is woken up and controlled to collect sensing parameters in the target wake-up time slot according to the real-time clock and the start timestamp of the superframe; In real-time communication mode, the wireless communication module is controlled to send sensing parameters on the target communication channel.

[0011] As a preferred embodiment, the control management module is used to: switch to the deep sleep mode when all sensing parameters do not exceed their corresponding preset thresholds; and switch to the real-time communication mode when any sensing parameter exceeds its corresponding preset threshold.

[0012] Furthermore, in the deep sleep mode, the control management module is used to cut off the power supply from the power module to the sensor node, and restore the power supply from the power module to the sensor node after a preset period.

[0013] As a preferred embodiment, the communication quality information is the current signal-to-noise ratio evaluated by the wireless communication module, and the preset channel quality threshold is a signal-to-noise threshold value configured in the range of -5dB to -20dB. Before sending sensing parameters, the wireless communication module performs preamble listening to obtain the signal-to-noise ratio (SNR) of the current channel and provides it to the control and management module. The control and management module compares the SNR with the SNR threshold and sends a control command to the wireless communication module to switch to the backup channel when the SNR is lower than the SNR threshold.

[0014] As a preferred embodiment, the sensor node is configured to collect sensing parameters reflecting the status of underground pipelines in the converter station; the sensing parameters include temperature sensing parameters, displacement sensing parameters, and tilt sensing parameters.

[0015] Furthermore, the sensor node includes a temperature sensing unit for acquiring the temperature sensing parameters, and an acceleration sensing unit for acquiring the displacement sensing parameters and tilt angle sensing parameters. The sensor node also includes a housing, within which the temperature sensing unit and the acceleration sensing unit are mounted.

[0016] Furthermore, the temperature sensing unit is configured as a platinum resistance temperature sensor, and the detection range of the platinum resistance temperature sensor is -40℃ to 120℃. The acceleration sensing unit is configured as a triaxial MEMS accelerometer with a range of -16g to +16g and can be configured in tilt measurement mode. The housing is made of polycarbonate material and has an IP68 protection rating. The battery module is configured as a lithium thionyl chloride battery.

[0017] In a second aspect, the present invention provides a low-power sensor cluster monitoring method adapted to the electromagnetic environment of a converter station, applicable to a monitoring system comprising sensor nodes, a wireless communication module, and a power supply module, characterized by comprising the following steps: Multiple sensors are configured in the sensor node to collect at least two different types of sensing parameters that reflect the operating status of the converter station; The sensing parameters are sent and communication quality information is acquired via the wireless communication module; When all sensing parameters do not exceed their corresponding preset thresholds, the system is controlled to enter deep sleep mode; when any sensing parameter exceeds its corresponding preset threshold, the system is controlled to enter real-time communication mode. In deep sleep mode, the sensor node is woken up at a first preset period to collect parameters, and the power module is controlled to cut off the power supply to the wireless communication module. In real-time communication mode, the power module is controlled to supply power to the wireless communication module, and the wireless communication module is controlled to obtain the communication quality information of the current channel before sending sensing parameters; if the communication quality information is lower than a preset quality threshold, the wireless communication module is controlled to switch to the backup channel to send data; otherwise, the wireless communication module is controlled to use the current channel to send data.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) In this invention, by configuring sensor nodes that can collect at least two different types of sensing parameters, multi-dimensional state perception of the monitored object is realized, and multiple sensing functions are integrated into a single node, thereby simplifying the wiring and installation structure, reducing the complexity of hardware deployment and overall cost, and facilitating integrated deployment in environments with limited space in converter stations.

[0019] (2) In this invention, by introducing a threshold-triggered dynamic power management mechanism and combining it with periodic wake-up detection, energy is allocated on demand and extremely economical. Its working principle is to maintain deep sleep to minimize static power consumption when there are no anomalies, and only periodically perform low-power sampling and comparison; only when an anomaly actually occurs is the high-power real-time communication function activated. This event-driven working mode fundamentally avoids ineffective energy consumption in the absence of anomalies, enabling the entire system to achieve ultra-long continuous operation time under battery power conditions, significantly reducing maintenance frequency and lifecycle costs. Through the above-mentioned threshold-based dynamic power management, it is calculated that the node is in deep sleep mode (current <8μA) for more than 99% of the time, performs low-power sampling only about 1% of the time, and starts wireless transmission for <0.1% of the time. This allows a theoretical battery life of more than 5 years using a 19,000mAh lithium thionyl chloride battery, fully meeting the maintenance-free cycle requirements of the converter station.

[0020] (3) In this invention, by endowing the wireless communication module with channel quality assessment and adaptive switching functions, the communication reliability in complex electromagnetic environments is effectively improved. The technical principle is that before each critical data transmission, the quality of the current wireless channel is actively assessed, and when preset interference is detected, the system automatically switches to a clean backup channel. This mechanism enables the system to actively avoid communication quality degradation caused by power frequency and transient electromagnetic interference generated during the operation of the converter station, thereby ensuring the stability and integrity of the transmission link of critical information such as alarm data and enhancing the robustness of the entire monitoring system in harsh industrial environments. Through channel quality assessment and switching before transmission, in the simulated converter station pulse interference test of 80dBμV / m, the success rate of data packet transmission on the first attempt is increased from less than 70% in the conventional scheme to more than 99%, solving the key problem of alarm information loss under strong interference.

[0021] (4) In this invention, furthermore, by periodically broadcasting global scheduling parameters through the gateway, each node deterministically calculates its exclusive target wake-up time slot and target communication channel based on its unique identifier, random salt value, and superframe sequence number using a hash function. This mechanism transforms the traditional competitive random access into an ordered and predictable deterministic scheduling, fundamentally avoiding data packet conflicts generated when a large-scale node cluster wakes up and communicates simultaneously, thereby significantly improving network capacity and communication reliability. At the same time, the deterministic dispersion of communication behavior in the time and frequency dimensions not only greatly reduces self-interference within the network and localizes the impact of external random interference, but also enables nodes to operate only within extremely short exclusive time slots, achieving overall power consumption optimization at the cluster level, and ultimately supporting the long-term, stable, and collaborative operation of massive nodes in complex electromagnetic environments. Attached Figure Description

[0022] Figure 1 This is one of the functional block diagrams of a low-power sensor cluster monitoring system according to an embodiment of the present invention; Figure 2 This is a second functional block diagram of a low-power sensor cluster monitoring system according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating a low-power sensor cluster monitoring method according to an embodiment of the present invention.

[0023] Reference numerals: 10, sensor node; 11, temperature sensing unit; 12, acceleration sensing unit; 13, housing; 20, control and management module; 30, wireless communication module; 40, power supply module; 50, repeater; 60, gateway. Detailed Implementation

[0024] To better illustrate the objectives, technical solutions, and advantages of the present invention, the specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0025] Example 1

[0026] like Figure 1 and Figure 2 The diagram illustrates a low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station, based on an embodiment of the present invention. Its core lies in constructing an integrated, low-power, and highly reliable distributed sensing network. The system includes sensor nodes 10, a wireless communication module 30, a power supply module 40, and a control and management module 20.

[0027] Specifically, sensor node 10 includes a housing 13 and sensing units disposed within the housing 13 for collecting at least two different types of sensing parameters reflecting the state of the converter station. For example, to reflect the state of underground pipelines in the converter station, sensor node 10 includes a temperature sensing unit 11 and an acceleration sensing unit 12. The temperature sensing unit 11 is used to collect the temperature sensing parameters to monitor the overheating state in the underground pipelines. The acceleration sensing unit 12 is used to collect the displacement sensing parameters and the tilt sensing parameters. The displacement sensing parameters can be used to estimate the deformation state of the underground pipelines, and the tilt sensing parameters can reflect the spatial attitude changes of the underground pipelines. Both the temperature sensing unit 11 and the acceleration sensing unit 12 are installed inside a single housing 13, which not only ensures that sensor node 10 can withstand the corrosive environment of the converter station's underground environment for a long time, guaranteeing the long-term reliability of the hardware, but also makes the detection of sensing parameters more centralized, reducing wiring between sensors and lowering interference from the electromagnetic environment of the converter station.

[0028] Specifically, the wireless communication module 30 is used to transmit sensing parameters and acquire communication quality information. The wireless communication module 30 is specifically configured as a LoRaWAN wireless communication module 30, utilizing LoRa technology to achieve long-distance, low-power wireless transmission. Communication quality information includes the signal-to-noise ratio (SNR). The power supply module 40 is connected to the sensor node 10, the wireless communication module 30, and the control and management module 20, respectively, to provide power for system operation. Specifically, the power supply module 40 is configured as a lithium thionyl chloride battery.

[0029] Specifically, the control management module 20 is connected to the sensor node 10 and the wireless communication module 30, and works in conjunction with the sensor node 10 and the wireless communication module 30. The control management module 20 is configured as follows:

[0030] (1) Determining whether to execute deep sleep mode or real-time communication mode. Specifically, compare the temperature sensing parameter with a preset temperature threshold (e.g., 70℃), compare the displacement sensing parameter with a preset displacement threshold (e.g., 5 mm), and compare the tilt angle sensing parameter with a preset tilt angle threshold (e.g., 2°). When all sensing parameters do not exceed their preset thresholds (e.g., temperature sensing parameter < 70℃, displacement sensing parameter < 5 mm, and tilt angle sensing parameter < 2°), control the system to switch to deep sleep mode. When any sensing parameter exceeds its preset threshold (e.g., temperature sensing parameter ≥ 70℃, displacement sensing parameter ≥ 5 mm, or tilt angle sensing parameter ≥ 2°), control the system to switch to real-time communication mode. In deep sleep mode, on the one hand, the control and management module 20 cuts off the power supply from the power module 40 to the wireless communication module 30; on the other hand, the control and management module 20 also cuts off the power supply from the power module 40 to the sensor node 10, maintaining only its own basic timing circuit operation, reducing static power consumption to an extremely low level. After a preset time interval, the control and management module 20 restores the power supply from the power module 40 to the sensor node 10, thereby waking up the sensor node 10 and collecting sensing parameters. Thus, deep sleep mode achieves extremely low power consumption. In real-time communication mode, if an anomaly in the sensing parameters occurs, the control and management module 20 restores the power supply from the power module 40 to the sensor node 10, uploads the sensing parameters, and completes the monitoring task.

[0031] (2) Execute the judgment and selection of the communication channel of the wireless communication module 30. Specifically, obtain the signal-to-noise ratio of the current channel obtained by the wireless communication module 30, and compare the signal-to-noise ratio of the current channel with a preset signal-to-noise threshold (such as -10dB); if the signal-to-noise ratio of the current channel is lower than the signal-to-noise threshold, control the wireless communication module 30 to switch to the backup channel and send the sensor parameter data; if the signal-to-noise ratio of the current channel is not lower than the signal-to-noise threshold, control the wireless communication module 30 to send the sensor parameter data with the current channel.

[0032] Therefore, according to the embodiments of the present invention, by integrating the perception of multiple sensing parameters, judging based on corresponding thresholds, and combining the dynamic sleep mechanism triggered by the adaptive anti-interference communication technology, the system can achieve multi-dimensional monitoring of underground pipeline status, extreme optimization of system energy consumption, and significant improvement of data transmission reliability in the complex electromagnetic environment of the converter station, thereby achieving long-term maintenance-free operation.

[0033] Specifically, in this embodiment, the system includes a gateway 60 and multiple repeaters 50 above the sensor node 10. Both the sensor node 10 and the repeaters 50 are equipped with LoRaWAN wireless communication modules 30, operating in a specific frequency band (e.g., 470-510MHz), utilizing their long-range and strong penetration characteristics to construct a low-level wireless sensor network within the complex space of the converter station. Repeaters 50 are deployed between the sensor node 10 and the gateway 60, or in areas with weak signal coverage, and can receive wireless signals from one or more sensor nodes 10, amplify them, and forward them. By deploying multiple repeaters 50, the wireless coverage range of the network can be effectively extended, bypassing physical obstructions and ensuring that each sensor node 10 is reliably covered by the network, solving the signal attenuation problem caused by underground and indoor environments. The gateway 60 can communicate directly with multiple repeaters 50 and possibly some of the sensor nodes 10 for protocol conversion and data aggregation. The gateway 60 aggregates and parses all received sensor data packets and uploads them to the backend server via a remote communication link (e.g., Ethernet, fiber optic, or 4G / 5G cellular network). Ultimately, the backend server receives and stores data from gateway 60, which reflects the status of the entire underground pipeline of the converter station, enabling the backend server to perform application-layer functions such as data display, analysis, and alarm management.

[0034] To resolve the potential wireless channel contention caused by periodic wake-ups of a large number of nodes, this embodiment specifically includes the following steps: S10 and Gateway 60 broadcast a frame of global scheduling parameters to the entire network at fixed time intervals (e.g., every minute or at the start of each superframe). These global scheduling parameters include at least the superframe start timestamp ( ), time slot length ( ), total number of time slots per superframe ( Available Channel List The system uses a superframe start timestamp, an absolute or relative time reference point for network-wide time synchronization. The timeslot length is the basic time unit for system scheduling, such as 5 seconds. The total number of timeslots per superframe represents the number of timeslots contained within a complete scheduling cycle (i.e., a superframe). For example, a superframe can be 600 seconds long with 5-second timeslots, resulting in 600 seconds divided by 5 seconds, or 120 timeslots. The available channel list represents a list containing multiple frequency points (e.g., 470MHz, 475MHz, ..., 510MHz), identifying currently permitted channels for communication. The random salt is a periodically updated (e.g., hourly or daily) random number generated by gateway 60 to increase the randomness of scheduling results and prevent long-term resource allocation fixation due to fixed sensor node IDs.

[0035] Step S10 establishes a coordinate system for a unified spatiotemporal resource grid within the network. Time is divided into continuous, numbered time slots, and frequency resources are defined as a series of selectable channels. A broadcast mechanism ensures that all sensor nodes 10 receive the same scheduling rules and resource views.

[0036] S20: Each sensor node 10's control and management module 20 listens for and receives global scheduling parameter broadcasts from the gateway 60 via its LoRaWAN wireless communication module 30. Subsequently, the sensor node 10 independently performs a localized deterministic calculation to determine its dedicated communication resources within the current superframe. Step S20 specifically includes the following steps: S21. Sensor node 10 gathers its own unique identifier (NodeID), the random salt value (Salt) obtained from gateway 60, and the current superframe sequence number (FrameCounter) calculated based on the local real-time clock (RTC) and the superframe start timestamp (T_start) obtained from gateway 60.

[0037] S22. Concatenate the unique identifier (NodeID), random salt value (Salt), and current superframe number (FrameCounter), and input them into a pre-defined, lightweight hash function with good discrete properties (such as an enhanced variant of CRC16 or a simplified SHA algorithm). The determinism of the hash function guarantees that the same input will produce the same output. Next, map the hash output to a specific resource index: Calculate the target wake-up slot index : , in, This represents the modulo operation. The formula takes the hash value modulo the total number of time slots, with a result between 0 and... An integer between -1 and 1, representing the wake-up slot number assigned to sensor node 10 within this superframe.

[0038] Calculate the target communication channel index: , in, The length( represents the floor operator) () indicates the list of available channels The number of channels in the hash value. This formula utilizes the high-order bits of the hash value (divided by...). The quotient of () is modulo the number of available channels, and the result is between 0 and length( An integer between 1 and 1, used to select from The corresponding channel is selected as the target communication channel.

[0039] In step S20, a hash function binds the unique identity information of sensor node 10 to dynamic system parameters (salt value, superframe number), deterministically and distributedly mapping them to a specific cell in the vast two-dimensional time-slot-channel resource grid. Due to the uniform distribution characteristic of the hash function, the probability of different sensor nodes 10 being mapped to the same cell (i.e., collision) is extremely low. This essentially transforms the traditional random contention access into a predictable pseudo-static scheduling without communication negotiation.

[0040] S30. In deep sleep mode, the control management module 20 no longer relies on a fixed preset period to wake up, but performs precise wake-up based on the target wake-up time slot calculated in step S2.

[0041] S31, Sensor node 10 utilizes its own RTC and, according to the broadcast from gateway 60, Perform continuous time synchronization calibration to ensure that its local clock is aligned with the entire network's spatiotemporal grid.

[0042] S32. When the local time reaches the target wake-up time slot allocated in the current superframe, the control management module 20 wakes up the sensor node 10 and performs a sensor parameter acquisition.

[0043] S33. After data acquisition is completed, the data is immediately compared with a preset threshold. If all parameters are normal (not exceeding the threshold), sensor node 10 quickly switches back to deep sleep mode after completing the judgment, until the next target wake-up time slot. This avoids the unnecessary energy consumption peak caused by all sensor nodes 10 waking up and acquiring data simultaneously under the traditional fixed cycle.

[0044] S40. When the sensing parameters exceed the threshold, sensor node 10 switches to real-time communication mode, and its communication behavior is also subject to scheduling constraints: S41. The control and management module 20 controls the wireless communication module 30 to directly frame and send sensing parameters on the target communication channel calculated in step S2.

[0045] S42. This target communication channel is one of the available channels selected by gateway 60 based on a global perspective. Before transmitting on this channel, sensor node 10 will still perform the original channel quality assessment (such as preamble sniffing to measure SNR). If the quality of the specified channel is found to be poor (SNR below the threshold), the original mechanism will be followed first, switching to a preset backup channel for this transmission to ensure the reliability of emergency data. Subsequently, gateway 60 can optimize global scheduling by updating Ch_List (temporarily removing the interfered channel).

[0046] Therefore, by assigning a unique time slot-channel pair to each sensor node 10, packet collisions caused by multiple sensor nodes 10 attempting to transmit simultaneously are fundamentally avoided. Simultaneously, sensor nodes 10 are active only within extremely short dedicated time slots, completely staggered in time, which smooths out the peak instantaneous power consumption of the cluster, significantly reducing average power consumption. Since collisions are virtually eliminated, the number of retransmissions due to collisions is drastically reduced, directly saving communication energy. Wake-up actions themselves become predictable and sparse, further reducing control overhead. Furthermore, the gateway 60 can periodically update the list of available channels (… This proactively excludes heavily interfered channels from the scheduling resource pool, achieving cluster-level interference avoidance. The deterministic dispersion of communication behavior in time and frequency means that occasional transient interference usually only affects the communication of a few sensor nodes 10 on a specific time slot-channel, without causing network-wide paralysis, thus improving the system's robustness.

[0047] In summary, according to the embodiments of the invention, by superimposing a lightweight collaborative scheduling layer on top of the existing underlying technologies of dynamic power management and adaptive anti-interference communication, the problem of conflict and interference superposition in cluster deployment is cleverly solved, thereby achieving a synergistic leap in communication reliability, energy efficiency and anti-interference capability at the system level.

[0048] Regarding the structural design of sensor node 10, specifically in this embodiment, the outer shell 13 of sensor node 10 is preferably made of polycarbonate (PC) material and has an IP68 protection rating. This combination of material and protection rating endows the node with excellent mechanical strength, corrosion resistance, and dust and water resistance, enabling it to directly withstand the harsh environment of the converter station's underground shaft, such as humidity and chemical corrosion, thus ensuring the long-term operational reliability of the hardware from a physical perspective.

[0049] Regarding the implementation of multi-dimensional sensing parameter perception, in this embodiment, the acceleration sensing unit 12 is preferably a triaxial MEMS accelerometer. Through firmware configuration, this same hardware unit can operate in acceleration mode to sense vibration displacement, or in tilt mode to measure spatial attitude changes, thus achieving the acquisition of two different parameters—displacement and tilt—with a single device. This achieves hardware integration, significantly reducing the internal space occupied by the node and the number of components. Specifically, the temperature sensing unit 11 uses a platinum resistance sensor with a detection range between -40℃ and 120℃. The range of the triaxial MEMS accelerometer (e.g., ±16g) ensures that the monitoring system has a wide measurement range and sufficient accuracy margin, covering various operating conditions from normal to extreme anomalies.

[0050] It is worth noting that the deep sleep mode has extremely low power consumption characteristics. In this mode, by cutting off the power supply to non-essential modules, the overall node can achieve an average standby current of less than 8 microamps (μA). Combined with a wake-up mechanism with a preset time interval (such as 20 seconds), the system maintains this microamp-level power consumption state for most of the time, thereby minimizing energy consumption at the source. This is the core data foundation that supports years of maintenance-free operation under battery power.

[0051] Understandably, regarding the anti-interference communication mechanism, the signal-to-noise ratio threshold used for judgment can be flexibly configured and optimized within a reasonable engineering range of -5dB to -20dB, based on the interference spectrum characteristics of different converter stations (for example, it can be set to -10dB in areas with strong interference and -15dB in areas with weak interference), rather than a fixed value. This configurability enhances the system's adaptability to different electromagnetic environment conditions. The entire evaluation and switching decision process is coordinated by the control management module 20, which ultimately issues explicit switching control commands to the wireless communication module 30, reflecting the system's intelligent coordination. Specifically, in this embodiment, the channel quality evaluation is preferably completed by the wireless communication module 30 performing preamble detection before transmission.

[0052] Regarding the long-endurance support of the power module 40, in this embodiment, the power module 40 is specifically a lithium thionyl chloride battery, and can specifically adopt a model with a rated voltage of 3.6V and a nominal capacity of not less than 19,000mAh. This type of battery has the characteristics of ultra-high energy density and extremely low annual self-discharge rate, which enables the system to have a continuous working life of more than 5 years, fundamentally solving the safety and cost problems of frequent battery replacement in high-risk areas.

[0053] Example 2

[0054] According to Embodiment 2 of the present invention, a low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station is disclosed. Based on the monitoring system of the aforementioned embodiments, the sensor unit configuration of the sensor node 10 is not limited to a combination of temperature and acceleration. In another preferred embodiment, for health monitoring of critical components such as underground pipeline joints, flanges, or compensators in a converter station, the sensor node 10 may integrate sensor units for monitoring humidity and stress / strain. Specifically, the sensor node 10 may include a humidity sensing unit and a strain sensing unit. The humidity sensing unit employs a capacitive or resistive polymer thin-film humidity sensor, typically with a detection range of 0%RH to 100%RH and an accuracy of ±3%RH. This unit is used to monitor the environmental humidity inside underground manholes or cable ducts, and is particularly suitable for early detection of potential moisture-induced joint problems caused by seal aging or external water seepage. The strain sensing unit employs a metal foil strain gauge or a MEMS piezoresistive strain sensor, which is firmly adhered to the surface to be measured on the pipeline or joint using a special adhesive. This unit is used to directly measure the micro-strain (με) of pipelines caused by internal pressure, external load, or thermal expansion and contraction, thereby assessing their mechanical stress state and providing early warning of overload or fatigue damage.

[0055] In this configuration, the control management module 20 will set corresponding humidity thresholds (e.g., 85%RH) and strain thresholds (e.g., 500με). If the ambient humidity consistently exceeds the threshold, it may indicate a seal failure; if the strain value increases abnormally, it may indicate abnormal pipeline stress. Exceeding either parameter's limit will trigger the sensor node 10 to switch from deep sleep mode to real-time communication mode and report alarm data.

[0056] Thus, under the multi-parameter integration and threshold triggering mechanism of the present invention, it can be flexibly adapted to combinations of temperature-vibration-tilt angle, humidity-strain, and even more physical quantities, to achieve multi-dimensional targeted monitoring of different facilities and different fault modes of the converter station.

[0057] This embodiment demonstrates that the system architecture of the present invention possesses high flexibility and scalability. Although the type of sensor unit can be adapted according to the characteristics of the monitored object (such as pipeline joints, flanges, etc.) (e.g., replaced with humidity and strain sensing units), the core mechanisms of the system, such as multi-functional integration, threshold-triggered sleep, and adaptive channel switching, remain unchanged. The control and management module still determines the working status based on multi-parameter thresholds, only initiating real-time communication in abnormal situations, and ensuring data transmission through channel evaluation and switching under strong electromagnetic interference. This enables the present invention to achieve multi-dimensional, customizable, and highly reliable monitoring for different facilities and fault modes in converter stations, systematically solving the complex problems of single sensor type, difficult deployment, and susceptibility to communication interference in underground pipeline monitoring.

[0058] Example 3

[0059] According to Embodiment 3 of the present invention, a low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station is provided. Based on the monitoring system of the aforementioned embodiments, the wireless communication module 30 is not limited to a LoRaWAN module. In converter station areas with cellular network coverage, the wireless communication module 30 can also be configured as an NB-IoT (Narrowband Internet of Things) module. Before initiating data transmission, the NB-IoT module can also perform channel quality assessment (such as measuring the Reference Signal Received Power (RSRP) or Signal-to-Interference-plus-Noise Ratio (SINR)). The control and management module 20 compares the assessment results with a preset threshold. If the quality does not meet the requirements, it can control the NB-IoT module to attempt cell reselection or delay transmission to the next better network scheduling opportunity, thereby achieving reliable anti-interference transmission based on the cellular network. Similarly, in short-range, high-density monitoring scenarios, the Zigbee protocol can also be used, and the decision to switch to a preset backup channel can be made by evaluating the Link Quality Indicator (LQI) or Received Signal Strength Indicator (RSSI).

[0060] Building upon the aforementioned hybrid network, this invention also supports a Mesh self-organizing network mode. In this mode, some or all of the sensor nodes 10 have relay functionality. When a sensor node 10 needs to report data but the direct link to the gateway is of poor quality, its control and management module 20 can drive the wireless communication module 30 to send the data packet to a neighboring node with a better link quality. This neighboring node then performs multi-hop forwarding until the data reaches the gateway 60. This mode is particularly suitable for environments with winding underground pipelines and severe obstructions, and can enhance the robustness of network coverage through inter-node cooperation. The channel assessment and handover mechanisms in the Mesh network are also applicable, and scheduling information (such as time slot allocation) can be synchronized within the network via multi-hop methods.

[0061] This embodiment further demonstrates the adaptability and systematic nature of the invention at the communication level. Regardless of whether different wireless communication technologies such as LoRaWAN, NB-IoT, or Zigbee are used, the system's threshold-triggered sleep mechanism and channel adaptive switching strategy can be effectively integrated and function. In Mesh networking mode, the combination of inter-node collaborative relay and intelligent channel selection not only expands network coverage but also enhances overall communication robustness in complex underground environments. This indicates that the present invention is a systematic method that enables on-demand wake-up, interference avoidance, and reliable data upload, applicable across communication protocols and network topologies. It can collaboratively solve the fundamental problems of harsh communication environments and data loss in converter station underground pipeline monitoring from three dimensions: power consumption control, anti-interference transmission, and network reliability.

[0062] Example 4

[0063] According to Embodiment 4 of the present invention, a low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station is provided. Based on the monitoring system of the aforementioned embodiments, the preset threshold and wake-up period are configured to be dynamically adjustable according to changes in equipment status and environment.

[0064] Specifically, the control and management module 20 can adaptively adjust the preset thresholds of sensing parameters based on environmental baselines or historical equipment data. For example, in summer, when the ambient temperature baseline is high, the temperature alarm threshold can be appropriately increased (e.g., from 70℃ to 75℃) to reduce false alarms caused by normal seasonal temperature differences. When the vibration data of a certain node shows a slow upward trend but has not yet exceeded the limit, the vibration threshold of that node can be lowered to achieve earlier warning. The threshold adjustment strategy can be preset in the algorithm of the control and management module 20, or it can be remotely issued by the backend server after big data analysis.

[0065] Specifically, the wake-up cycle (or superframe duration and time slot length in collaborative scheduling) in the deep sleep mode can be dynamically adjusted according to the remaining power of the power module 40. For example, when the battery power is sufficient (>80%), a shorter wake-up cycle (e.g., 20 seconds) is maintained to achieve high-frequency monitoring; when the battery power drops to a moderate level (20%~80%), the wake-up cycle is automatically extended (e.g., 60 seconds); when the power is insufficient (<20%), it can be further extended to several minutes, and a low power alarm is reported. This "power-sensing" cycle adjustment strategy can maximize the effective monitoring time of the system at the end of the battery life.

[0066] This embodiment demonstrates a further extension of the invention in terms of intelligent management and adaptive optimization. By making the preset threshold and wake-up cycle dynamically adjustable, the system not only maintains the basic energy-saving mechanism of threshold-triggered sleep, but also endows it with intelligent characteristics of environmental perception and state adaptation. The threshold is dynamically adjusted according to the season and historical data, reducing false alarms and providing early warnings; the wake-up cycle is adaptively extended according to the battery level, greatly extending the system's effective monitoring time at the end of the battery life. This dynamic self-optimization capability, combined with mechanisms such as adaptive channel switching and collaborative scheduling, realizes the evolution from static rule execution to dynamic intelligent collaboration, systematically improving the continuous ability to cope with environmental changes and maintain high-reliability monitoring during long-term operation.

[0067] Example 5

[0068] According to Embodiment 5 of the present invention, a low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station is provided. Based on the monitoring system of the aforementioned embodiments, resource allocation can be further optimized by calculating using a hash function.

[0069] Specifically, for sensor nodes 10 deployed in particularly critical areas (such as the main transformer incoming line area), a priority factor can be introduced into the hash calculation. The scheduling parameters broadcast by gateway 60 can include time slot ranges corresponding to different priorities. After hash calculation, the NodeID and salt value parameters of high-priority nodes will be mapped to the "high-priority time slot group" with lower collision probability and faster wake-up response, ensuring that their data can be uploaded with priority and reliability.

[0070] Specifically, the periodic updating of the random salt value is crucial for avoiding long-term fixed scheduling and handling node additions and subtractions. In extreme cases, if two nodes have hash collisions (calculating the same time slot-channel pair), the control and management module 20 can enable a secondary collision resolution mechanism. For example, after detecting a transmission failure (no response), the node can attempt to retransmit in its next allocated time slot, or after a short random backoff period, on a backup channel. The gateway 60 can also fundamentally eliminate collisions by listening for collisions and adjusting the salt value during the next scheduling parameter update.

[0071] This embodiment deeply optimizes the collaborative scheduling mechanism, further improving communication efficiency and reliability in large-scale clusters by introducing priority scheduling and conflict resolution strategies. The priority mechanism ensures that data from key nodes is uploaded first; random salt value updates and conflict resolution strategies guarantee scheduling fairness and network stability. This optimized scheduling layer, closely integrated with the underlying threshold-triggered sleep and channel adaptive switching, forms a three-layer collaborative architecture of event-driven wake-up, deterministic resource allocation, and dynamic interference avoidance. It systematically resolves the superimposed effects of inter-node conflicts and external interference from multiple dimensions of time, frequency, and priority, enabling this invention to achieve ultra-low power consumption and high-reliability communication not only at the single-node level but also at the cluster level, achieving orderly, efficient, and scalable system operation, comprehensively addressing the severe challenges of dense deployment, complex interference, and long-term collaborative requirements in underground pipeline monitoring.

[0072] In summary, this invention is not a simple aggregation of existing technologies. It addresses deployment challenges through hardware integration, battery life challenges through threshold-triggered dynamic power consumption, communication reliability challenges through channel adaptation, and network coverage and conflict challenges through optional relaying and coordinated scheduling. These interconnected features constitute a complete and self-consistent technical solution specifically designed for the demanding monitoring environment of converter station underground pipelines, producing synergistic effects far exceeding the results of simply adding the individual components together.

[0073] Example 6

[0074] like Figure 3As shown, Embodiment Six of the present invention relates to a low-power sensor cluster monitoring method adapted to the electromagnetic environment of a converter station. This method is applied to a monitoring system comprising sensor nodes 10, a wireless communication module 30, and a power supply module 40. The method specifically includes the following steps: S1. Configure multiple sensors in a sensor node 10 to collect at least two different types of sensing parameters that reflect the operating status of the converter station. S2. When one or more sensing parameters do not exceed their corresponding preset thresholds, control the sensor node 10 to switch to deep sleep mode; when one or more sensing parameters exceed their corresponding preset thresholds, control the sensor node 10 to switch to real-time communication mode. S3. In deep sleep mode, wake up sensor node 10 at preset time intervals and perform sensor parameter acquisition. S4. In real-time communication mode, obtain the communication quality information of wireless communication module 30, and determine whether the channel quality information is lower than the preset channel quality threshold. If not, control wireless communication module 30 to send sensing parameters. If yes, control wireless communication module 30 to switch to a pre-configured backup channel and send sensing parameters.

[0075] Example 7

[0076] The following describes the implementation of the system and method of this invention using the monitoring of underground pipelines at the ±800kV Longmen converter station as an application scenario. This system is used for multi-parameter, long-term, and highly reliable condition monitoring of underground cables and their associated manhole facilities within the station.

[0077] 1. System Overall Architecture and Network Composition This sensor cluster uses, as follows Figure 1 The layered distributed architecture shown mainly includes the following parts: Multifunctional sensor node 10: As the end device for data acquisition, it is directly installed on the monitored object (such as the surface of a cable, the inner wall of a well, or the back of a well cover).

[0078] Repeater 50: Deployed based on the results of on-site radio environment survey, used to receive and forward wireless signals from sensor node 10, extend network coverage, and enhance signal reliability.

[0079] Gateway 60 (also known as acquisition terminal): As a regional data aggregation point, it receives data from sensor node 10 or repeater 50.

[0080] IoT Platform: Deployed on-site or in the cloud, it receives and processes data from all gateways 60, providing status visualization, threshold alarms, and data analysis functions.

[0081] Sensor node 10, repeater 50, and gateway 60 form a wireless ad hoc network using the LoRaWAN protocol. Gateway 60 then uploads the aggregated data to the IoT platform via wired Ethernet or 4G / 5G remote communication links.

[0082] 2. Specific composition of the multi-functional sensor node 10 Taking a sensor node 10 deployed in a key well as an example, its internal structure is as follows: Shell 13: Made of engineering PC (polycarbonate) material by injection molding, with IP67 protection rating to adapt to underground humid environments.

[0083] Power supply unit: The core is a lithium thionyl chloride (Li-SOCl2) battery. This battery has extremely high energy density and an annual self-discharge rate of less than 1%, laying the foundation for ultra-long battery life.

[0084] Sensing module: A highly integrated multi-parameter module.

[0085] Temperature sensing unit 11: Employs a platinum resistance (Pt100) patch sensor with a detection range covering -40℃ to 120℃ and a full-range accuracy better than ±0.5℃. The probe is tightly attached to the cable surface using thermally conductive silicone.

[0086] Displacement and tilt sensing unit: Employs a digital chip (such as ADXL357) integrating a three-axis MEMS accelerometer. This chip can be configured via firmware to achieve two functional modes: Displacement monitoring mode: When sensor node 10 is rigidly fixed to the cable or pipe wall, the chip operates in acceleration mode with a range of ±16g, which is used to sense vibrations or small displacements caused by external forces or deformations.

[0087] Tilt monitoring mode: When sensor node 10 is installed on the back of the manhole cover, the chip works in tilt mode, using the gravitational acceleration component to calculate the tilt angle, with a measurement range of 0° to ±90°.

[0088] Core Control and Power Management Unit: Employs an ultra-low-power microcontroller (management and control module) as its core. Its internal firmware implements integrated dynamic power management and collaborative scheduling execution logic.

[0089] LoRaWAN wireless communication module 30: It adopts a radio frequency chip that operates in the 470-510MHz frequency band and conforms to Chinese standards. The transmit power can be dynamically adjusted between 0-20dBm through the management control module command.

[0090] 3. On-site deployment and integration process The specific deployment and operation process of the ±800kV gantry converter station project is as follows: (1) Network deployment A total of 121 of the aforementioned multi-functional sensor nodes 10 were deployed along the pipeline and in key manholes. All sensor nodes 10 were securely installed on the monitored objects using stainless steel brackets or cable ties.

[0091] Based on the results of on-site radio surveys, 35 repeaters (50) and 2 gateways (60) were deployed to form a hybrid mesh topology, ensuring that there are no communication blind spots within the station.

[0092] All gateways 60 are configured to broadcast global scheduling parameters to their respective networks once per minute.

[0093] (2) Normal low power consumption operation Under normal circumstances, all sensor nodes 10 operate by following these steps: Parameter reception and resource calculation: The management and control module of each sensor node 10 receives the global scheduling parameters broadcast by the gateway 60 through the LoRaWAN module. Subsequently, the management and control module performs local hash calculation based on its own unique identifier, the received random salt value, and the calculated current superframe sequence number.

[0094] Thus, each sensor node 10 deterministically obtains its own wake-up time and communication channel within the current superframe.

[0095] Wake-up and Data Acquisition by Scheduling: Sensor node 10 enters deep sleep mode, and the management and control module only maintains RTC operation. When the RTC timer reaches the time point corresponding to its dedicated $Slot_{index}$, the management and control module is woken up, and then the sensor module is powered on to quickly acquire temperature, acceleration / tilt angle data once (takes about 100ms).

[0096] Threshold judgment and decision: The management and control module compares the collected data with preset thresholds (such as temperature <60℃, tilt angle change <5°).

[0097] If all data is normal: the management control module immediately powers off all units except its own RTC, and sensor node 10 re-enters deep sleep, waiting for the next dedicated wake-up slot. At this time, the average standby current can be as low as 6μA.

[0098] If any data exceeds the threshold, the management and control module determines it as an abnormal event and immediately triggers the following real-time communication process.

[0099] Through the above mechanism, under normal circumstances, the wake-up actions of dozens of sensor nodes 10 are automatically and evenly distributed over a superframe of up to 10 minutes, completely avoiding wireless channel contention and data packet collisions caused by the simultaneous wake-up of all sensor nodes 10, thereby reducing network internal friction and power consumption peaks from the root.

[0100] (3) Handling of abnormal events When an anomaly occurs (taking temperature exceeding the limit as an example), sensor node 10 handles it according to the following procedure: Real-time communication is initiated: After the management and control module determines that the temperature exceeds the limit (for example, 65°C is detected), it immediately switches to real-time communication mode and powers on the LoRaWAN wireless communication module 30.

[0101] Channel assessment and priority scheduling: The wireless communication module 30 prepares to transmit data on its calculated target communication channel (e.g., 510MHz). Before transmission, it still performs a preamble listening to assess the instantaneous signal-to-noise ratio (SNR) of the channel.

[0102] Adaptive anti-interference transmission: If the assessed SNR (e.g., -6dB) is better than a preset threshold (e.g., -10dB), then an alarm data packet is sent directly to the target channel.

[0103] If the SNR deteriorates (e.g., -15dB), indicating that the dedicated channel may also be subject to transient interference, the management control module switches to a preset backup channel (e.g., 505MHz) for transmission. This mechanism ensures reliable transmission of emergency data even when the scheduled channel is disrupted.

[0104] Data reporting: Alarm data packets are sent at a rate of 1.2Kbps, forwarded to gateway 60 via repeater 50, and finally triggered by the IoT platform.

[0105] (4) Operational effect Statistics after one year of trial operation: 1) Communication Reliability: Under the strong electromagnetic interference environment of the converter station, the overall data packet transmission success rate of the system reached 99.2%, which is about 35 percentage points higher than the original system without coordinated scheduling. This is due to the scheduling mechanism avoiding collisions and the two-level (scheduling avoidance + real-time switching) anti-interference strategy.

[0106] 2) Energy consumption and lifespan: Since sensor node 10 only operates within a dedicated, short time slot and collision retransmissions are extremely rare, the average power consumption of the entire device is very low. Combined with lithium-ion batteries, in a typical scenario where alarms are triggered less than twice a day, the battery life of sensor node 10 is expected to reach more than 5.5 years, truly achieving long-term maintenance-free operation.

[0107] 3) Deployment and maintenance advantages: The multi-functional integrated design reduces the number of devices; the collaborative scheduling mechanism ensures stable network performance and strong scalability as the number of sensor nodes increases; and the ultra-long battery life significantly reduces the maintenance frequency and risk in high-risk areas.

[0108] This embodiment demonstrates that by deeply integrating multi-parameter integrated sensing, threshold-triggered dynamic power consumption management, channel adaptive anti-interference, and deterministic hash-based collaborative scheduling, this invention constructs a low-power, high-reliability sensor cluster monitoring solution that is particularly suitable for the complex electromagnetic environment of converter stations, and has significant engineering application value.

[0109] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0110] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station, characterized in that, include: Sensor node (10) is used to acquire at least two different types of sensing parameters that reflect the state of the converter station; The wireless communication module (30) is used to send the sensing parameters and acquire communication quality information; Power module (40); The control and management module (20) is connected to the sensor node (10), the wireless communication module (30), and the power module (40), respectively. The control management module (20) is configured to perform the following operations: When all sensing parameters do not exceed their corresponding preset thresholds, the system is controlled to enter deep sleep mode; when any sensing parameter exceeds its corresponding preset threshold, the system is controlled to enter real-time communication mode. In deep sleep mode, the sensor node (10) is woken up at the first preset cycle to collect parameters, and the power module (40) is controlled to cut off the power supply to the wireless communication module (30); In real-time communication mode, the power module (40) is controlled to supply power to the wireless communication module (30), and the wireless communication module (30) is controlled to obtain the communication quality information of the current channel before sending the sensing parameters; if the communication quality information is lower than the preset quality threshold, the wireless communication module (30) is controlled to switch to the backup channel to send data; otherwise, the wireless communication module (30) is controlled to use the current channel to send data.

2. The low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station as described in claim 1, characterized in that, The wireless communication module (30) is configured as a LoRaWAN wireless communication module (30); the system also includes: Multiple repeaters (50) are used to receive and forward LoRaWAN wireless signals from the sensor node (10). At least one gateway (60) communicates with the repeater (50) and / or the sensor node (10) via a LoRaWAN wireless network for aggregating data and uploading the data to a backend server via a remote communication link.

3. The low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station as described in claim 2, characterized in that, The gateway (60) is configured to periodically broadcast global scheduling parameters, which include a superframe start timestamp, a timeslot length, a total number of timeslots per superframe, a list of available channels, and a random salt value. The control management module (20) is also configured to: The global scheduling parameters are received through the wireless communication module (30); Based on the unique identifier of the sensor node (10), the random salt value in the global scheduling parameters, and the current superframe number, the target wake-up time slot and target communication channel of the sensor node (10) in the current superframe are calculated by a preset hash function; wherein, the target wake-up time slot is a time slot within the total number of time slots in each superframe, and the target communication channel is a channel in the list of available channels; In deep sleep mode, the sensor node (10) is woken up and controlled to collect sensing parameters in the target wake-up time slot according to the real-time clock and the start timestamp of the superframe; In real-time communication mode, the wireless communication module (30) is controlled to send sensing parameters on the target communication channel.

4. The low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station as described in claim 1, characterized in that, In the deep sleep mode, the control management module (20) is used to cut off the power supply of the power module (40) to the sensor node (10), and restore the power supply of the power module (40) to the sensor node (10) after a preset time interval.

5. A low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station as described in claim 1, characterized in that, The communication quality information is the current signal-to-noise ratio evaluated by the wireless communication module (30), and the preset channel quality threshold is a signal-to-noise threshold value configured in the range of -5dB to -20dB. The wireless communication module (30) performs preamble listening before sending sensing parameters to obtain the signal-to-noise ratio of the current channel and provides it to the control management module (20); the control management module (20) compares the signal-to-noise ratio with the signal-to-noise threshold value, and when the signal-to-noise ratio is lower than the signal-to-noise threshold value, sends a control command to the wireless communication module (30) to switch to the backup channel.

6. The low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station as described in claim 1, characterized in that, The sensor node (10) is configured to collect sensing parameters reflecting the status of underground pipelines in the converter station; the sensing parameters include temperature sensing parameters, displacement sensing parameters and tilt sensing parameters.

7. A low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station as described in claim 6, characterized in that, The sensor node (10) includes a temperature sensing unit (11) for acquiring the temperature sensing parameters, and an acceleration sensing unit (12) for acquiring the displacement sensing parameters and tilt angle sensing parameters. The sensor node (10) also includes a housing (13), and the temperature sensing unit (11) and the acceleration sensing unit (12) are installed inside the housing (13).

8. A low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station as described in claim 7, characterized in that, The temperature sensing unit (11) is configured as a platinum resistance temperature sensor, and the detection range of the platinum resistance temperature sensor is -40℃ to 120℃. The acceleration sensing unit (12) is configured as a triaxial MEMS accelerometer with a range of -16g to +16g and can be configured in tilt measurement mode. The housing (13) is made of polycarbonate material and has an IP68 protection rating.

9. A low-power sensor cluster monitoring system adapted to the electromagnetic environment of a converter station as described in claim 7 or 8, characterized in that, The battery module is configured as a lithium thionyl chloride battery.

10. A low-power sensor cluster monitoring method adapted to the electromagnetic environment of a converter station, applied to a monitoring system comprising sensor nodes (10), a wireless communication module (30), and a power supply module (40), characterized in that, Includes the following steps: Multiple sensors are configured in the sensor node (10) to collect at least two different types of sensing parameters that reflect the operating status of the converter station; The sensing parameters are sent and communication quality information is obtained through the wireless communication module (30); When all sensing parameters do not exceed their corresponding preset thresholds, the system is controlled to enter deep sleep mode; when any sensing parameter exceeds its corresponding preset threshold, the system is controlled to enter real-time communication mode. In deep sleep mode, the sensor node (10) is woken up at the first preset cycle to collect parameters, and the power module (40) is controlled to cut off the power supply to the wireless communication module (30); In real-time communication mode, the power module (40) is controlled to supply power to the wireless communication module (30), and the wireless communication module (30) is controlled to obtain the communication quality information of the current channel before sending the sensing parameters; if the communication quality information is lower than the preset quality threshold, the wireless communication module (30) is controlled to switch to the backup channel to send data; otherwise, the wireless communication module (30) is controlled to use the current channel to send data.

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