A wireless hydrogen sensor system based on multi-mode energy harvesting and link adaptation transmission and a control method thereof

Abstract

The application discloses a wireless hydrogen sensor system based on multi-mode energy collection and link adaptive transmission and a control method thereof, relates to the field of hydrogen energy safety monitoring and Internet of Things sensing, and comprises a plurality of intelligent wireless hydrogen sensor nodes, a convergence gateway and an upper computer. The intelligent wireless hydrogen sensor node comprises a multi-mode energy collection module, an energy management and storage module, a hydrogen sensor array, an array mutual interference suppression module, an edge processing module and a multi-mode wireless communication module. The multi-mode energy collection module collects at least two kinds of environmental energy, ensuring long-term autonomous operation of the node. The array mutual interference suppression module suppresses crosstalk and cross-sensitivity through a dedicated algorithm, improving detection accuracy. The edge processing module generates a control instruction, and the multi-mode wireless communication module adaptively adjusts communication parameters, ensuring reliable transmission. The application can adapt to multi-scene large-scale monitoring and provide support for hydrogen safety testing and engineering management.

Description

Technical Field

[0001] This application relates to the fields of hydrogen energy safety monitoring and Internet of Things sensing, and in particular to a wireless hydrogen sensor system and its control method based on multi-mode energy harvesting and link adaptive transmission. Background Technology

[0002] Hydrogen energy is considered a crucial technological pathway for achieving energy structure transformation and enhancing the absorption capacity of renewable energy. With the continuous growth of installed capacity from renewable energy sources such as wind and solar power, hydrogen production through water electrolysis and "green hydrogen" demonstration projects are progressing rapidly. Simultaneously, the hydrogen industry chain is rapidly developing, encompassing industrial by-product hydrogen purification, high-pressure hydrogen compression and storage, liquid hydrogen and cryogenic storage, the application of solid-state hydrogen storage materials, the construction of hydrogen refueling station networks, and fuel cell vehicles, hydrogen-powered heavy-duty trucks, hydrogen-powered ships, and distributed power generation. The trend towards large-scale and diversified hydrogen energy infrastructure is evident. However, with the expansion of equipment scale and the increasing complexity of operating conditions, the risks of hydrogen leakage, accumulation, and ignition / explosion have become key factors restricting the safe development of hydrogen energy, highlighting the growing importance of hydrogen safety monitoring and testing.

[0003] Hydrogen gas has characteristics such as small molecular weight, rapid diffusion, easy diffusion along gaps and accumulation in areas like ceilings after leakage, low ignition energy, and a wide flammability range. In poorly ventilated or semi-enclosed spaces, once a leak occurs, a flammable mixture may form locally and ignite under the influence of electrostatic sparks, mechanical sparks, or high-temperature surfaces. The poor visibility of hydrogen flames and their radiation characteristics differ from conventional fuels, making accident identification and handling more challenging. Therefore, establishing a reliable hydrogen leak monitoring system at key points throughout the entire "production-storage-transportation-refueling-use" chain, and verifying monitoring and alarm capabilities through systematic hydrogen safety testing, is a crucial foundation for the safety management of hydrogen energy projects.

[0004] In hydrogen safety assessment and experimental research, it is often necessary to conduct leakage-diffusion-ventilation coupling tests at different scales and under different flow fields and boundary conditions. Examples include: leakage and diffusion tests in large-scale hydrogen production plants or experimental chambers; ventilation and concentration field coupling tests in underground pipe corridors; wind field coupling tests between the process area and vehicle parking area of ​​hydrogen refueling stations; jet stream and strong convection tests formed by high-pressure discharge; and tracer tests using helium instead of hydrogen. These tests often require the deployment of hydrogen or helium concentration sensors at multiple points in a matrix to achieve high spatiotemporal resolution measurements of the concentration field. The following requirements are typically imposed on hydrogen or helium concentration sensors and acquisition systems: First, as the experimental scale increases, the number of measurement points increases significantly, requiring support for synchronous or quasi-synchronous acquisition and reporting of dozens to hundreds of points; Second, under conditions of strong convection and jet diffusion, concentration changes rapidly, requiring higher sampling frequencies and higher effective reporting rates to capture transient peaks and diffusion fronts; Third, in a matrix-based deployment, the close proximity of nodes and the large number of concurrent reports easily lead to issues such as co-frequency collisions, hidden nodes, intermodulation interference, and electromagnetic coupling interference; Fourth, large-scale wiring in explosion-proof areas or test chambers increases construction workload and maintenance risks, and wiring harnesses and supports can also alter local flow fields, affecting experimental boundary conditions and the accuracy of results; Fifth, some monitoring points are located in high-altitude pipe corridors, valve group interlayers, underground wells, or on moving targets, making power supply and maintenance inconvenient, and long-term reliance on batteries will lead to frequent replacements and safety management costs.

[0005] Existing wireless gas sensing systems mostly rely on disposable or lithium batteries for power, which have limited lifespans, high replacement and maintenance costs, and frequent battery replacements in high-risk areas pose additional safety hazards. Some studies have introduced single environmental energy harvesting technologies such as solar energy, vibration energy, or thermal energy, but under conditions of insufficient light, interrupted vibration, or reduced temperature differences, it is still difficult to ensure long-term continuous operation of nodes. On the other hand, hydrogen energy facilities have dense metal structures and pipelines, complex and time-varying electromagnetic interference, and severe multipath effects and obstruction. Traditional fixed communication modes and fixed transmission power cannot simultaneously balance energy consumption and reliability under low signal-to-noise ratio or strong interference conditions. Under strong convection conditions, insufficient communication rate or excessive latency can lead to the loss of information on rapid concentration changes, affecting the accuracy of experimental evaluation and alarms. In addition, multi-point array deployment can cause mutual interference between sensors and channels: on the one hand, signal coupling caused by gas cross-sensitivity and temperature and humidity disturbances; on the other hand, crosstalk caused by array wiring and electromagnetic coupling, which can lead to false alarms and missed alarms.

[0006] Therefore, existing technologies are insufficient to meet the actual needs of large-scale array experiments and online monitoring of hydrogen safety. The industry urgently needs an intelligent wireless hydrogen sensor system and method that can achieve multi-mode energy harvesting, low-interference array sensing, and high-speed, low-latency, anti-interference wireless transmission. Summary of the Invention

[0007] The purpose of this application is to provide a wireless hydrogen sensor system and its control method based on multi-mode energy harvesting and link adaptive transmission, which can solve the technical problems in existing hydrogen energy safety monitoring, such as difficulty in power supply maintenance, severe crosstalk of sensor arrays under matrix deployment, and large data transmission delay and easy loss of key information under strong convection conditions.

[0008] To achieve the above objectives, this application provides the following solution: In the first aspect, this application provides a wireless hydrogen sensor system based on multi-mode energy harvesting and link adaptive transmission, including: several intelligent wireless hydrogen sensor nodes, a convergence gateway, and a host computer; The intelligent wireless hydrogen sensor node includes: A multimode energy harvesting module for harvesting at least two types of energy from the environment, including vibration energy, thermoelectric energy, light energy, and radio frequency energy. The energy management and storage module is connected to the multimode energy acquisition module and is used to rectify, stabilize, impedance match or track the maximum power point of the acquired energy, and store the processed energy to power other modules in the smart wireless hydrogen sensor node. A hydrogen sensor array is used to collect hydrogen concentration signals. An array crosstalk suppression module, connected to the hydrogen sensor array, is used to suppress crosstalk and perform cross-sensitivity processing on the hydrogen concentration signal through time-division excitation sampling, differential compensation, and multivariate decoupling algorithms to obtain the processed hydrogen concentration signal. The edge processing module is connected to the array mutual interference suppression module and the energy management and storage module respectively. It is used to extract features and determine the risk level of the processed hydrogen concentration signal, and generate control commands based on the average energy harvesting power, remaining energy, risk level and link quality indicators. A multi-mode wireless communication module, connected to the edge processing module, is used to adaptively select the communication channel, transmission power, data rate and access method according to the control command, and send the processed hydrogen concentration signal to the aggregation gateway. The aggregation gateway is used to receive data packets uploaded by each intelligent wireless hydrogen sensor node, perform time alignment and integrity checks, and forward the aligned and verified data to the host computer; the data packet includes the processed hydrogen concentration signal, node ID, timestamp and risk level; The host computer is used to receive data packets forwarded by the aggregation gateway and to display and analyze them.

[0009] Secondly, this application provides a control method for the aforementioned wireless hydrogen sensor system based on multi-mode energy harvesting and link adaptive transmission, comprising: At least two types of energy from the environment, namely vibration energy, thermal energy, light energy and radio frequency energy, are harvested using a multimode energy harvesting module. Hydrogen concentration signals are acquired using a hydrogen sensor array; The hydrogen concentration signal is processed by performing time-division excitation sampling, differential compensation, and multivariate decoupling on the hydrogen concentration signal through the array mutual interference suppression module. The edge processing module extracts features and determines the risk level of the processed hydrogen concentration signal, and generates control commands based on the average energy harvesting power, remaining energy, risk level, and link quality indicators. The multi-mode wireless communication module adaptively selects the communication channel, transmission power, data rate, and access method according to the control command, and sends the data packet containing the corrected hydrogen concentration signal to the aggregation gateway.

[0010] According to the specific embodiments provided in this application, this application has the following technical effects: (1) Solve the problems of unreliable power supply and high operation and maintenance costs: The multi-mode energy acquisition module collects at least two kinds of environmental energy, and with the rectification and voltage regulation of the energy management and storage module, it realizes multi-source energy complementary storage, gets rid of the dependence on single battery and single energy acquisition, realizes the long-term autonomous operation of the smart wireless hydrogen sensor node, reduces battery replacement, reduces operation and maintenance costs and battery swapping safety hazards, and is suitable for special monitoring points. (2) Solve the problem of crosstalk and cross sensitivity of multi-sensor arrays: The array mutual interference suppression module suppresses crosstalk and cross sensitivity of hydrogen concentration signal through time-division excitation sampling, differential compensation and multivariate decoupling algorithm, effectively suppresses electromagnetic crosstalk and signal coupling, reduces the probability of false alarm and false alarm, improves detection accuracy, and adapts to the matrix-based multi-point deployment requirements. (3) Solve the problem of unreliable data transmission under complex working conditions: The multi-mode wireless communication module adaptively selects the communication channel, transmission power, data rate and access method according to the control command, and sends the processed hydrogen concentration signal to the aggregation gateway. It adapts to the complex electromagnetic environment of the hydrogen energy station, takes into account both high-speed transmission and low latency, avoids loss of transient concentration information, and ensures transmission reliability. (4) Adapt to large-scale monitoring in multiple scenarios: The system integrates core functions, adapts to various test scenarios, supports the simultaneous acquisition of dozens to hundreds of measurement points, eliminates the need for large-scale wiring, reduces construction and maintenance risks, avoids disturbing the flow field, and ensures the accuracy of test results. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 A functional module diagram of a wireless hydrogen sensor system based on multimode energy harvesting and link adaptive transmission provided in Embodiment 1 of this application; Figure 2 This is a schematic diagram of the functional modules of the intelligent wireless hydrogen sensor node provided in Embodiment 1 of this application. Detailed Implementation

[0013] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0014] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, this application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0015] Example 1: like Figure 1 As shown, a wireless hydrogen sensor system based on multi-mode energy harvesting and adaptive link transmission is provided, including: several intelligent wireless hydrogen sensor nodes (11-1n), a convergence gateway 2, and a host computer 3. The intelligent wireless hydrogen sensor nodes (hereinafter referred to as "nodes") are the core sensing units of the system, such as... Figure 2 As shown, it integrates the following functional modules: multimode energy harvesting module 101, energy management and storage module 102, hydrogen sensor array 103, array mutual interference suppression module 104, edge processing module 105, and multimode wireless communication module 106.

[0016] (1) Multimode energy harvesting module 101.

[0017] The multimode energy harvesting module 101 is used to harvest at least two types of energy from the environment, including vibration energy, temperature difference energy, light energy, and radio frequency energy.

[0018] The multimode energy harvesting module 101 includes at least two of the following: a piezoelectric energy harvesting unit (harvesting vibration energy), a thermoelectric energy harvesting unit (harvesting temperature difference energy), a photovoltaic energy harvesting unit (harvesting light energy), and a radio frequency energy recovery unit (harvesting radio frequency energy).

[0019] (2) Energy management and storage module 102.

[0020] The energy management and storage module 102 is connected to the multimode energy acquisition module 101 and is used to rectify, stabilize, impedance match or track the acquired energy, and store the processed energy to power other modules in the intelligent wireless hydrogen sensor node.

[0021] The energy management and storage module 102 includes a rectifier circuit, a voltage regulator circuit, an impedance matching circuit or a maximum power point tracking circuit, and an energy storage unit (supercapacitor or rechargeable battery).

[0022] During the cold start process, the energy management and storage module 102 allocates the collected and stored energy according to the preset power supply priority, giving priority to ensuring the operation of basic node control, energy storage status detection, remaining energy estimation and low-power basic measurement functions; when the energy storage unit's energy storage voltage reaches the preset working threshold and the remaining energy meets the minimum energy requirements for the node to enter normal working state, it then provides working power to the node's high-power functional units according to the preset power supply strategy.

[0023] (3) Hydrogen sensor array 103.

[0024] The hydrogen sensor array 103 is used to acquire hydrogen concentration signals.

[0025] The hydrogen sensor array 103 includes at least two hydrogen sensor units with different sensitive materials or different operating temperatures. The hydrogen sensor array 103 is arranged in a matrix or grid pattern.

[0026] (4) Array mutual interference suppression module 104.

[0027] The array crosstalk suppression module 104 is connected to the hydrogen sensor array 103 and is used to suppress crosstalk and perform cross-sensitivity processing on the hydrogen concentration signal through time-division excitation sampling, differential compensation and multivariate decoupling algorithm to obtain the processed hydrogen concentration signal.

[0028] The array mutual interference suppression module 104 includes a timing control unit, a differential compensation unit, a multivariable decoupling unit, and a consistency verification unit.

[0029] 1) Timing control unit.

[0030] The timing control unit is connected to the hydrogen sensor array 103 and is used to divide the multiple hydrogen sensor units in the hydrogen sensor array 103 into several excitation groups, and send excitation signals to each excitation group in sequence according to a preset time-division excitation sequence.

[0031] Specifically, based on the array size N and the sensor thermal response time and target refresh cycle Establish a channel scan table to divide all hydrogen sensor units into several excitation groups. It operates sequentially according to the time-division excitation sequence of "preheating-stabilization-sampling-shutdown-switching" to avoid thermal coupling and power supply fluctuations caused by simultaneous excitation of adjacent channels.

[0032] 2) Differential compensation unit.

[0033] The differential compensation unit, connected to the hydrogen sensor array 103, is used to perform differential processing on the output vectors of the hydrogen sensor unit under test and the reference hydrogen sensor unit according to the reference compensation coefficient matrix, so as to obtain the differentially compensated response vector.

[0034] Specifically, in each round of sampling, the output vector of the hydrogen sensor unit under test is acquired synchronously. Output vector of the reference hydrogen sensor unit Perform differential compensation: in, This is the response vector after differential compensation. This is the reference compensation coefficient matrix.

[0035] 3) Multivariable decoupling unit.

[0036] A multivariate decoupling unit, connected to the differential compensation unit, is used to perform multivariate decoupling operations on the differentially compensated response vector using the cross-interference matrix and the channel confidence weight matrix to obtain the real gas response vector.

[0037] Specifically, an array crosstalk model is established based on factory calibration or field calibration: in, For the real gas response vector to be solved, For cross-interference matrix, This is the noise term.

[0038] Applying linear inverse decoupling or least squares decoupling with regularization to this model yields: in, The solution is the real gas response vector. This is the channel confidence weight matrix. The regularization coefficient is . This is the identity matrix. For nonlinear response scenarios, multivariate regression, principal component analysis, or neural network mapping models can be further used to complete nonlinear compensation.

[0039] 4) Consistency verification unit.

[0040] The consistency verification unit, connected to the multivariate decoupling unit, is used to calculate the consistency index of each hydrogen sensor unit. When the consistency index of any hydrogen sensor unit exceeds a preset threshold, the corresponding weight in the channel confidence weight matrix is ​​adjusted to output the processed hydrogen concentration signal.

[0041] Specifically, after obtaining the decoupling results for each channel, a consistency index is calculated: in, Let be the consistency index for the i-th hydrogen sensor unit. The average output value of similar hydrogen sensor units. Let i be the actual gas response vector output by the i-th hydrogen sensor unit. To prevent tiny constants with a denominator of zero.

[0042] When the consistency index of a certain hydrogen sensor unit exceeds a preset threshold, the weight of that hydrogen sensor unit in the channel confidence matrix is ​​automatically reduced. The weights in the output channel are adjusted, and redundant channels are switched to output when necessary. Through the combined processing of timing isolation, differential compensation, and matrix decoupling described above, measurement errors caused by thermal coupling, electromagnetic crosstalk, and cross-sensitivity can be effectively reduced. At the hardware level, electromagnetic coupling can be reduced through partitioned wiring, ground isolation, shielding, and guard rings.

[0043] (5) Edge processing module 105.

[0044] The edge processing module 105 is connected to the array interference suppression module 104 and the energy management and storage module 102 respectively. It is used to extract features and determine the risk level of the processed hydrogen concentration signal, and generate control commands based on the average energy harvesting power, remaining energy, risk level and link quality indicators.

[0045] The edge processing module 105 includes a signal preprocessing unit, a feature extraction unit, a risk level determination unit, and a strategy generation unit.

[0046] 1) Preprocessing unit.

[0047] The signal preprocessing unit, connected to the array mutual interference suppression module 104, is used to perform zero-point correction, baseline tracking, and filtering and noise reduction on the processed hydrogen concentration signal to obtain a stable signal.

[0048] Specifically, firstly, the processed hydrogen concentration signal... Zero-point correction and baseline tracking are performed to obtain the correction signal. : in, The baseline estimate is preferably updated using a moving average or exponential smoothing method. Then, median filtering and amplitude limiting filtering are used to remove impulse interference, resulting in a stable signal. .

[0049] 2) Feature extraction unit.

[0050] The feature extraction unit, connected to the signal preprocessing unit, is used to extract feature parameters from the stable signal; the feature parameters include instantaneous concentration, concentration change rate, and multi-channel consistency coefficient.

[0051] Specifically, the following feature parameters are extracted from the stable signal: instantaneous concentration. Concentration change rate and multi-channel consistency coefficient .

[0052] in, This is the average concentration value of multiple sensor units. The standard deviation of the concentration values ​​of multiple sensor units. To prevent the use of tiny constants with a denominator of zero. The closer it is to 1, the more consistent the output of each channel is.

[0053] in, The time interval between two adjacent samples. This represents the gas concentration value at the previous sampling time.

[0054] 3) Risk level determination unit.

[0055] A risk level determination unit, connected to the feature extraction unit, is used to determine the risk level based on feature parameters.

[0056] Specifically, risk levels are classified based on preset thresholds and trend discrimination rules. A primary concentration threshold is set. Secondary concentration threshold First-order rate of change threshold Secondary rate of change threshold Multi-channel consistency coefficient And satisfy .

[0057] A risk level of Level 1 is determined when any of the following conditions are met, and a pre-alarm state needs to be entered.

[0058] (a) And duration ≥ ; (b) And it has been rising continuously; (c) .

[0059] A risk level of 2 must be met, and an alarm must be activated if any of the following conditions are met: (a) ; (b) And the incremental amount is accumulated within the predetermined window.

[0060] 4) Strategy generation unit.

[0061] The strategy generation unit is connected to the risk level determination unit and the energy management and storage module 102, respectively. It is used to construct a system state vector based on the average energy harvesting power, remaining energy, risk level and link quality indicators, and output control commands based on a preset rule table or Markov decision model.

[0062] At the start of each running cycle, the node first reads the nearest... Average energy harvesting power per cycle and remaining energy And simultaneously obtain the risk level. Simultaneously, the node obtains the received signal strength indication through statistical analysis of probe frames or normal service frames. Signal-to-noise ratio Data packet reception rate Average number of retransmissions and queuing delay Link quality metrics. Then construct the system state vector: This is then input into a rule table or Markov decision process model. The corresponding set of actions (i.e., control commands) is: in, For communication mode, For the operating frequency band or channel, For transmission power level, For modulation coding and data rate, For data packet length, This is the reporting cycle.

[0063] To achieve coordinated optimization of reliability, latency, and energy consumption, the following cost function can be used: in, To transmit energy consumption, For end-to-end delay, As a cost of channel interference, These are the weighting coefficients. The preferred action combination that minimizes the cost function while satisfying the constraints is selected as the communication parameter for the current cycle.

[0064] The edge processing module adaptively adjusts the node's operating mode based on the risk level. Under normal conditions, it maintains low-frequency sampling and periodic reporting. Under warning or alarm conditions, it increases the sampling frequency, shortens the reporting cycle, and prioritizes sending abnormal event frames, rate of change features, and key raw data fragments, thereby balancing energy consumption and real-time performance. (6) Multimode wireless communication module 106.

[0065] The multi-mode wireless communication module 106 is connected to the edge processing module 105 and is used to adaptively select the communication channel, transmission power, data rate and access method according to the control command, and send the processed hydrogen concentration signal to the aggregation gateway.

[0066] Specifically, the control commands output by the edge processing module 105 correspond to the aforementioned set of actions: in, For communication mode, For the operating frequency band or channel, For transmission power level, For modulation coding and data rate, For data packet length, This is the reporting cycle.

[0067] Therefore, the adaptive communication process executed by the multi-mode wireless communication module 106 has the following correspondence with the action set: the communication channel is formed by the action set... Confirmed, the transmission power is determined by Determined, data rate is determined by Determined, the data packet length is determined by Confirmed, the reporting cycle is from Confirmed, the access method is determined by the communication mode. The specific values ​​are determined. In other words, packet access, time-slotted reporting, dynamic channel switching, or frequency hopping mechanisms are not additional strategies independent of control commands, but rather a set of actions of the multi-mode wireless communication module 106. The specific execution results.

[0068] Under matrix-based high-density deployment conditions, when the communication mode in the control command... When configured for packet access mode, nodes cluster or report packets according to the packet information issued by the aggregation gateway; when the communication mode... When configured for time-slotted access mode, the node sends data within the specified time slot according to the time slot table issued by the aggregation gateway; when the communication mode... When configured for frequency hopping access mode, the node switches channels according to the candidate channel set or frequency hopping sequence; when the working channel in the control command... When updated, the node switches to the new communication channel. This reduces co-channel collisions, the influence of hidden nodes, and channel interference when multiple nodes report concurrently, thus improving data transmission reliability in high-density deployment scenarios.

[0069] When the remaining energy When the power level is low and close to the preset lower limit, the edge processing module 105 generates an energy-saving control command, causing the multi-mode wireless communication module 106 to select a low-power wide-area communication mode and reduce the transmission power level. Reduce data rate and increase the reporting cycle. To reduce communication energy consumption.

[0070] when Increase or When the preset threshold is exceeded, the edge processing module 105 generates an event-enhanced control command, causing the multi-mode wireless communication module 106 to switch to short-range high-speed communication mode or high data rate communication mode to increase the data rate. Shorten the reporting cycle Furthermore, the transmission priority of abnormal data frames is increased to ensure that alarm data and transient concentration change data are delivered in a timely manner.

[0071] decline, Reduce or When the signal is raised, the edge processing module 105 generates an anti-interference control command, causing the multi-mode wireless communication module 106 to reduce the data packet length. It employs a more robust modulation and coding scheme, increases forward error correction redundancy, and adjusts the working channel according to the candidate channel number or frequency hopping sequence. To improve data arrival rate in complex electromagnetic environments.

[0072] In high-density deployment scenarios, the aggregation gateway groups nodes according to spatial proximity, risk areas, or link quality, and assigns transmission time slots and candidate channels to each group. After receiving the grouping information, time slot table, and candidate channel set from the aggregation gateway, the nodes use these as their communication mode and working channels. and working channel Based on the configuration, the aggregation gateway performs packet access, time-slotted transmission, dynamic channel switching, or frequency hopping transmission under the corresponding access method. The aggregation gateway performs time alignment, integrity checks, and retransmission request control on the received data, and returns the latest link feedback results to the nodes as the set of update actions for the next cycle. Based on this, a dynamic, reliable, high-speed transmission closed loop is formed.

[0073] When the risk level is high but the link quality deteriorates, the multi-mode wireless communication module 106 prioritizes ensuring the reliable delivery of critical data. Its control methods include increasing forward error correction redundancy, adopting more robust modulation and coding schemes, switching to low-interference candidate channels, and using time-slotted access or frequency-hopping access. To prevent system oscillations caused by frequent switching of communication parameters, the multi-mode wireless communication module 106 also performs parameter switching based on a dual-threshold hysteresis mechanism and a minimum hold time. After a certain communication mode is enabled, if the reverse switching condition is not met and the hold time is not yet complete, the current communication mode remains unchanged.

[0074] When link quality is restored and energy reserves are sufficient again, the multi-mode wireless communication module 106 does not immediately switch to the highest communication performance state. Instead, it gradually reverts communication parameters in the order of "low-speed recovery - medium-speed recovery - normal recovery," adjusting only one or two communication control variables in the action set each time. For example, it might first shorten the reporting cycle and then increase the data rate, or first reduce the forward error correction redundancy and then switch the communication mode. The system records the latency, energy consumption, and data arrival rate after each round of communication parameter adjustments for use in the next round of threshold revision, rule optimization, and model update, thereby achieving a long-term stable, adaptive, and continuously optimized wireless transmission mechanism.

[0075] The multi-mode wireless communication module 106 performs low-power wide-area communication or short-range high-speed communication under different distance, interference and rate requirements, and supports channel switching, rate adaptation and time-slotted access to complete dynamic, reliable and high-speed wireless transmission of gas data.

[0076] The aforementioned intelligent wireless hydrogen sensor node further includes a signal conditioning module, connected to the hydrogen sensor array, used to amplify, filter, and perform analog-to-digital conversion on the hydrogen concentration signal. The signal conditioning module includes conditioning circuits for amplification, filtering, and analog-to-digital conversion.

[0077] The aforementioned intelligent wireless hydrogen sensor node also includes a local storage and diagnostic module, which is connected to the energy management and storage module, the hydrogen sensor array, and the multimode wireless communication module, respectively.

[0078] The local storage and diagnostic module includes a data acquisition unit, a health index construction unit, and a health index construction unit.

[0079] A data acquisition unit is used to periodically collect and store operational indicators; the operational indicators include energy storage voltage. Energy storage current Energy input power Operating current of hydrogen sensor array Zero-point drift Sensitivity attenuation coefficient Data packet reception rate Average number of retransmissions And link latency D, etc.

[0080] A health index construction unit, connected to the data acquisition unit, is used to calculate a health index based on operational indicators; the health index includes an energy health index, a sensor health index, and a link health index.

[0081] in, , , These represent the energy health index, sensor health index, and link health index, respectively. , where i = 1, 2, 3. This is the reference voltage for the energy storage unit. For reference input power, For reference energy value, Zero-point drift threshold, This is the threshold for the number of retransmissions. This is the link latency threshold.

[0082] The diagnostic unit is connected to both the data acquisition unit and the health index construction unit, and is used to perform anomaly judgment and system diagnosis based on the health index and the generated operating indicators.

[0083] Specifically, the diagnostic unit reads operational indicators according to a preset diagnostic cycle, compares these indicators with corresponding preset thresholds, historical benchmark values, or sliding window averages, and determines whether a node exhibits anomalies based on the comparison results. The specific process is as follows: Specifically, the diagnostic unit reads the energy health index, sensor health index, and link health index according to a preset diagnostic cycle, and simultaneously reads the corresponding operational indicators for each health index. The health indices are then compared with their corresponding preset health thresholds to determine if any node exhibits abnormal energy, sensor, or link status. When any health index falls below its corresponding preset health threshold, the diagnostic unit further compares the operational indicator used to generate that health index with its corresponding preset threshold, historical benchmark value, or sliding window average to determine the source and type of the anomaly.

[0084] When the energy health index is lower than the preset energy health threshold, and the energy storage voltage is lower than the preset voltage threshold, or the estimated remaining energy decreases for several consecutive diagnostic cycles, the node is determined to have an energy deficiency anomaly.

[0085] When the energy health index is lower than the preset energy health threshold, and the energy input power is consistently lower than the reference input power and the energy storage voltage fails to recover to the normal range, the node is judged to have insufficient energy collection or energy storage abnormality.

[0086] When the sensor health index is lower than the preset sensor health threshold, and the operating current of any sensor exceeds the normal current range, the zero-point drift exceeds the preset drift threshold, or the sensitivity attenuation coefficient is lower than the preset lower limit, it is determined that the corresponding sensor has an abnormal operation, drift abnormality, or aging abnormality.

[0087] When the link health index is lower than the preset link health threshold, and the data packet reception rate is lower than the preset reception rate threshold, the average number of retransmissions exceeds the preset retransmission threshold, or the link latency exceeds the preset latency threshold, the node is determined to have a communication link abnormality.

[0088] When multiple health indices fall below their corresponding health thresholds simultaneously within the same diagnostic period, or multiple operational indicators exceed their corresponding thresholds simultaneously within the same diagnostic period, or the same health index or the same operational indicator continues to deteriorate within multiple consecutive diagnostic periods, the diagnostic unit raises the abnormality level and generates a corresponding abnormality type identifier.

[0089] When the energy storage voltage is lower than the preset voltage threshold, or when the estimated remaining energy decreases for several consecutive diagnostic cycles, the node is determined to have an energy shortage anomaly.

[0090] When the energy input power is consistently lower than the reference input power and the energy storage voltage fails to return to the normal range, the node is determined to have insufficient energy harvesting or an energy storage anomaly.

[0091] When the operating current of any sensor exceeds the normal current range, the zero-point drift exceeds the preset drift threshold, or the sensitivity attenuation coefficient is lower than the preset lower limit, it is determined that the corresponding sensor has an abnormal operation, drift abnormality, or aging abnormality.

[0092] When the data packet reception rate is lower than the preset reception rate threshold, the average number of retransmissions exceeds the preset retransmission threshold, or the link delay exceeds the preset delay threshold, the node is determined to have a communication link abnormality.

[0093] When multiple operational indicators exceed their corresponding thresholds simultaneously within the same diagnostic cycle, or when the same operational indicator continues to deteriorate within multiple consecutive diagnostic cycles, the diagnostic unit raises the anomaly level and generates a corresponding anomaly type identifier.

[0094] Furthermore, the diagnostic unit classifies the diagnostic results into minor, moderate, and severe anomalies based on the duration of the anomaly, the number of abnormal indicators, and the degree to which the health index or operational indicator deviates from the threshold. For minor anomalies, anomaly logs are recorded and the self-check frequency is increased; for moderate anomalies, parameter rollback, recalibration, sensor weight adjustment, backup channel switching, or communication channel reselection are performed; for severe anomalies, fault codes are generated and fault information is reported to the aggregation gateway or host computer.

[0095] Therefore, the diagnostic unit directly judges anomalies based on the node's operating indicators and their changing trends, making the system diagnostic process correspond to the actual collected operating status data, and forming a continuous correlation between operating indicators, health indices, and the system diagnostic process.

[0096] At the same time, the diagnostic results are graded. For minor anomalies, only the self-test frequency is recorded and increased. For moderate anomalies, recalibration, parameter rollback, or link reselection is initiated. For severe anomalies, fault codes are generated and reported to the aggregation gateway. The aggregation gateway or host computer combines multiple diagnostic records to determine whether maintenance, device replacement, or relocation is required.

[0097] The aggregation gateway has multi-channel concurrent reception capability and is responsible for receiving data packets uploaded by each node. The aggregation gateway parses the data packets, extracting node IDs, timestamps, concentration data, and risk tags. It performs time alignment to eliminate clock skew between different nodes and performs CRC integrity checks. For high-density deployment scenarios, the aggregation gateway is also responsible for distributing time slot assignment tables (TDMA Slot Assignments) and candidate channel lists to coordinate node access and reduce collisions.

[0098] The aggregation gateway includes: a multi-channel receiving unit, a time synchronization unit, an integrity verification unit, and a data forwarding unit.

[0099] A multi-channel receiving unit is used to receive data packets uploaded by each intelligent wireless hydrogen sensor node.

[0100] A time synchronization unit, connected to the multi-channel receiving unit, is used for timestamp alignment of data packets.

[0101] An integrity verification unit, connected to the multi-channel receiving unit, is used to check the integrity of data packets.

[0102] The data forwarding unit, connected to the time synchronization unit and the integrity verification unit, is used to forward aligned and verified data to the host computer.

[0103] The host computer runs monitoring software, receives data forwarded by the aggregation gateway, and displays real-time hydrogen concentration cloud maps, trend curves, and alarm information. Simultaneously, the host computer can view the health status of nodes (battery life prediction, sensor aging level) and supports remote configuration of node parameters.

[0104] Example 2 This embodiment provides a control method for the aforementioned wireless hydrogen sensor system based on multi-mode energy harvesting and link adaptive transmission, including: S1: Harvest at least two types of energy from the environment, including vibration energy, thermal energy, light energy, and radio frequency energy, through a multimode energy harvesting module.

[0105] S2: Collect hydrogen concentration signals through a hydrogen sensor array.

[0106] S3: The hydrogen concentration signal is processed by performing time-division excitation sampling, differential compensation, and multivariate decoupling on the hydrogen concentration signal through the array mutual interference suppression module.

[0107] S4: The edge processing module extracts features and determines the risk level of the processed hydrogen concentration signal, and generates control commands based on the average energy harvesting power, remaining energy, risk level, and link quality indicators.

[0108] S5: The multi-mode wireless communication module adaptively selects the communication channel, transmission power, data rate and access method according to the control command, and sends the data packet containing the corrected hydrogen concentration signal to the aggregation gateway.

[0109] Example 3 Hydrogen leakage monitoring and large-scale testing at a hydrogen production plant (hydrogen production by water electrolysis).

[0110] (1) Layout: In the hydrogen production plant, several nodes are laid out in key locations such as the electrolysis cell area, hydrogen manifold, compressor room, valve group room, vent, accumulation area on the roof of the plant and exhaust outlet, forming a two-dimensional grid or three-dimensional multi-layer matrix of measurement points; there are fan-induced ventilation, equipment vibration and temperature difference in the plant, and there is also multipath effect caused by metal equipment blocking.

[0111] (2) Energy strategy: Nodes prioritize the recovery of vibration energy and temperature difference energy near compressors and pipeline supports, recover light energy in well-lit areas, and recover radio frequency energy in densely populated areas of wireless devices; the energy management and storage module classifies the node's working mode according to the energy input and energy storage voltage: in normal mode, low-frequency sampling and periodic reporting are performed, and in event mode, the sampling frequency is increased and high-speed reporting is enabled.

[0112] (3) Array mutual interference suppression: The node configuration includes hydrogen sensor units with different sensitive materials and different operating temperatures, and helium sensor units can be optionally configured for tracing; time-division excitation and polling sampling are used to avoid thermal coupling caused by heating multiple channels at the same time; differential compensation and cross-interference correction matrix are used for compensation.

[0113] (4) High-speed transmission: When the hydrogen concentration rise rate is detected to exceed the threshold or reach the warning threshold, the edge processing module increases the risk level and triggers a high-speed reporting strategy: increase the data rate, shorten the reporting cycle, adopt a shorter packet length and appropriate error correction redundancy; when multiple nodes report concurrently, the aggregation gateway issues a time slot table to realize time slot access, and dynamically switches channels when necessary to reduce co-frequency conflicts.

[0114] The above strategy can generate high-density field data without laying large-scale wiring harnesses, reduce the disturbance of the flow field by the wiring harnesses, and maintain low latency and high data arrival rate under strong convection conditions.

[0115] Example 4 Leakage location and ventilation coupling test of underground hydrogen pipeline.

[0116] (1) Layout: The underground pipe gallery environment is long and narrow, with many metal structures, serious wireless obstruction and inconvenient maintenance; the test usually requires the layout of strip or grid measuring points along the direction of the gallery to obtain the distribution of concentration with distance, and the points are denser at bends, valve chambers, wall-penetrating sections and branch pipe interfaces.

[0117] (2) Energy strategy: The node mainly uses the micro-vibration of the pipeline and the temperature difference in the corridor to recover energy, and reduces the average power consumption by extending the sleep time and grading the wake-up. When the ventilator is started or the test discharge is triggered, the node enters the event mode, shortens the sampling cycle and increases the reporting frequency.

[0118] (3) Anti-interference access and high-speed aggregation: To address the issues of hidden nodes and multipath, the system adopts clustered access: Each cluster is equipped with a cluster head node or relay node responsible for aggregation and communicating with the aggregation gateway; time-slotted reporting is used within the cluster, and different channels or frequency hopping sequences are used between clusters to reduce co-frequency collisions; when a rapid increase in local concentration is detected, neighboring clusters increase the reporting rate and synchronously report the timestamp, and the aggregation gateway uses the time difference of arrival of multiple points and the concentration gradient to locate the leakage segment and assess the diffusion process.

[0119] This embodiment enables stable operation of underground long-distance, multi-point arrays without the need for long-distance cabling, reducing maintenance difficulty and improving testing efficiency.

[0120] Example 5: Leakage monitoring and verification tests at hydrogen refueling stations and in hydrogen-powered vehicles.

[0121] (1) Deployment: Nodes are deployed at locations such as compressors, storage tank areas, refueling machines, hose joints, venting ports and unloading interfaces at hydrogen refueling stations; on hydrogen-powered buses, heavy trucks, forklifts and other vehicles, nodes are deployed at cylinder valve compartments, pipeline routes, fuel cell stack compartments and possible accumulation areas to form multi-point redundant monitoring.

[0122] (2) Operating characteristics: During the refueling process, there are jet streams and local strong convection, and the vehicle starts, stops and drives, generating aerodynamic disturbances; at the same time, there are electromagnetic interference sources such as inverters, motors and charging equipment, and the network topology may change with the vehicle's position.

[0123] (3) Strategy: Under normal circumstances, low-power communication and low sampling frequency are used; when the refueling starts or an event is triggered, the system increases the risk level and switches to a high-speed reporting strategy. At the same time, dynamic channel switching and time-slotted access are used to reduce multi-node concurrent conflicts; for transportation scenarios, the aggregation gateway and nodes combine link quality measurement to perform fast reconnection and route update to ensure continuous reporting under mobile conditions.

[0124] This embodiment can achieve reliable real-time monitoring and test data acquisition under conditions of dispersed locations, strong interference, and strong convection, reducing deployment and maintenance costs.

[0125] Example 6: Helium tracing and transient discharge diffusion experiment in experimental chamber.

[0126] (1) Experimental objective: To simulate the hydrogen diffusion process using helium as a tracer gas in an indoor experimental chamber or semi-enclosed space, to verify the ability of the multi-point array to capture the diffusion front, peak concentration and ventilation dilution process, and to evaluate the impact of different reporting rates on the experimental results.

[0127] (2) Layout method: Nodes are arranged in a grid in the cabin, and the nodes are denser near the ceiling and near the doors and windows; the node array contains both helium sensitive channels and hydrogen sensitive channels. By comparing the responses of the two types of channels, the unified calibration of the tracer test and the actual hydrogen leakage monitoring is completed.

[0128] (3) High-speed reporting and data integrity: At the moment of release, the concentration changes rapidly and the duration is short. The system increases the sampling frequency and reporting rate to the preset high level through the event triggering mechanism. At the same time, it adopts the access strategy of short packet length and low queuing delay, and performs time alignment and missing interpolation marking on the aggregation gateway side to ensure that the dataset can be used for subsequent flow field inversion and model verification.

[0129] This embodiment demonstrates that the present application can maintain high data integrity and low latency under high-density matrix and transient strong convection conditions, providing repeatable and quantifiable data acquisition methods for hydrogen safety experiments.

[0130] In summary, this application achieves wireless, high-density array monitoring capabilities for the hydrogen energy field through three key design features: "energy recovery and reduction of energy consumption", "multi-sensor array to reduce signal interference", and "improved signal transmission speed". It is applicable to various scenarios of hydrogen safety testing and engineering operation.

[0131] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0132] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A wireless hydrogen sensor system based on multi-mode energy harvesting and adaptive link transmission, characterized in that, include: Several intelligent wireless hydrogen sensor nodes, a convergence gateway, and a host computer; The intelligent wireless hydrogen sensor node includes: A multimode energy harvesting module for harvesting at least two types of energy from the environment, including vibration energy, thermoelectric energy, light energy, and radio frequency energy. The energy management and storage module is connected to the multimode energy acquisition module and is used to rectify, stabilize, impedance match or track the maximum power point of the acquired energy, and store the processed energy to power other modules in the smart wireless hydrogen sensor node. A hydrogen sensor array is used to collect hydrogen concentration signals; An array crosstalk suppression module, connected to the hydrogen sensor array, is used to suppress crosstalk and perform cross-sensitivity processing on the hydrogen concentration signal through time-division excitation sampling, differential compensation and multivariate decoupling algorithm to obtain the processed hydrogen concentration signal. The edge processing module is connected to the array mutual interference suppression module and the energy management and storage module respectively. It is used to extract features and determine the risk level of the processed hydrogen concentration signal, and generate control commands based on the average energy harvesting power, remaining energy, risk level and link quality indicators. A multi-mode wireless communication module, connected to the edge processing module, is used to adaptively select the communication channel, transmission power, data rate and access method according to the control command, and send the processed hydrogen concentration signal to the aggregation gateway. The aggregation gateway is used to receive data packets uploaded by each intelligent wireless hydrogen sensor node, perform time alignment and integrity checks, and forward the aligned and verified data to the host computer; the data packet includes the processed hydrogen concentration signal, node ID, timestamp and risk level; The host computer is used to receive data packets forwarded by the aggregation gateway and to display and analyze them.

2. The wireless hydrogen sensor system based on multi-mode energy harvesting and adaptive link transmission according to claim 1, characterized in that, The multimode energy harvesting module includes two or more of the following: piezoelectric energy harvesting unit, thermoelectric energy harvesting unit, photovoltaic energy harvesting unit, and radio frequency energy recovery unit.

3. The wireless hydrogen sensor system based on multi-mode energy harvesting and link adaptive transmission according to claim 1, wherein the energy management and storage module includes a rectifier circuit, a voltage regulator circuit, an impedance matching circuit or a maximum power point tracking circuit, and an energy storage unit.

4. The wireless hydrogen sensor system based on multimode energy harvesting and link adaptive transmission according to claim 1, wherein the hydrogen sensor array includes at least two hydrogen sensor units with different sensitive materials or different operating temperatures.

5. The wireless hydrogen sensor system based on multi-mode energy harvesting and adaptive link transmission according to claim 1, characterized in that, The array mutual interference suppression module includes: A timing control unit, connected to the hydrogen sensor array, is used to divide the multiple hydrogen sensor units in the hydrogen sensor array into several excitation groups, and send excitation signals to each excitation group in sequence according to a preset time-division excitation sequence. A differential compensation unit, connected to the hydrogen sensor array, is used to perform differential processing on the output vectors of the hydrogen sensor unit under test and the reference hydrogen sensor unit according to the reference compensation coefficient matrix, so as to obtain the differentially compensated response vector. A multivariable decoupling unit, connected to the differential compensation unit, is used to perform multivariable decoupling operations on the differentially compensated response vector using the cross-interference matrix and the channel confidence weight matrix to obtain the real gas response vector. The consistency verification unit, connected to the multivariate decoupling unit, is used to calculate the consistency index of each hydrogen sensor unit. When the consistency index of any hydrogen sensor unit exceeds a preset threshold, the corresponding weight in the channel confidence weight matrix is ​​adjusted to output the processed hydrogen concentration signal.

6. The wireless hydrogen sensor system based on multi-mode energy harvesting and adaptive link transmission according to claim 1, characterized in that, The edge processing module includes: The signal preprocessing unit, connected to the array mutual interference suppression module, is used to perform zero-point correction, baseline tracking, and filtering and noise reduction on the processed hydrogen concentration signal to obtain a stable signal. A feature extraction unit, connected to the signal preprocessing unit, is used to extract feature parameters from the stable signal; the feature parameters include instantaneous concentration, concentration change rate, and multi-channel consistency coefficient. A risk level determination unit, connected to the feature extraction unit, is used to determine the risk level based on feature parameters; The strategy generation unit is connected to the risk level determination unit and the energy management and storage module, respectively. It is used to construct a system state vector based on the average energy harvesting power, remaining energy, risk level and link quality indicators, and output control commands based on a preset rule table or Markov decision model.

7. The wireless hydrogen sensor system based on multi-mode energy harvesting and adaptive link transmission according to claim 1, characterized in that, The intelligent wireless hydrogen sensor node also includes: The signal conditioning module, connected to the hydrogen sensor array, is used to amplify, filter, and perform analog-to-digital conversion on the hydrogen concentration signal.

8. The wireless hydrogen sensor system based on multi-mode energy harvesting and adaptive link transmission according to claim 1, characterized in that, The intelligent wireless hydrogen sensor node also includes: The local storage and diagnostic module is connected to the energy management and storage module, the hydrogen sensor array, and the multimode wireless communication module, respectively. The local storage and diagnostics module specifically includes: The data acquisition unit is used to periodically collect and store operating indicators; the operating indicators include energy storage voltage, energy storage current, energy input power, hydrogen sensor array operating current, zero-point drift, sensitivity attenuation coefficient, data packet reception rate, average retransmission count, and link delay. A health index construction unit, connected to the data acquisition unit, is used to calculate a health index based on operational indicators; the health index includes an energy health index, a sensor health index, and a link health index. The diagnostic unit is connected to both the data acquisition unit and the health index construction unit, and is used to perform anomaly judgment and system diagnosis based on the health index and the generated operating indicators.

9. The wireless hydrogen sensor system based on multi-mode energy harvesting and adaptive link transmission according to claim 1, characterized in that, The aggregation gateway includes: A multi-channel receiving unit is used to receive data packets uploaded by each intelligent wireless hydrogen sensor node; A time synchronization unit, connected to the multi-channel receiving unit, is used for timestamp alignment of data packets; An integrity verification unit, connected to the multi-channel receiving unit, is used to check the integrity of data packets; The data forwarding unit, connected to the time synchronization unit and the integrity verification unit, is used to forward aligned and verified data to the host computer.

10. A control method for a wireless hydrogen sensor system based on multi-mode energy harvesting and link adaptive transmission as described in any one of claims 1-9, characterized in that, include: At least two types of energy from the environment, namely vibration energy, thermoelectric energy, light energy and radio frequency energy, are harvested using a multimode energy harvesting module. Hydrogen concentration signals are acquired using a hydrogen sensor array; The hydrogen concentration signal is processed by performing time-division excitation sampling, differential compensation, and multivariate decoupling on the hydrogen concentration signal through the array mutual interference suppression module. The edge processing module extracts features and determines the risk level of the processed hydrogen concentration signal, and generates control commands based on the average energy harvesting power, remaining energy, risk level, and link quality indicators. The multi-mode wireless communication module adaptively selects the communication channel, transmission power, data rate, and access method according to the control command, and sends the data packet containing the corrected hydrogen concentration signal to the aggregation gateway.

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