Boiler anti-leakage monitoring and positioning method, system, product and medium

Abstract

The invention discloses a boiler anti-leakage monitoring and positioning method and system, a product and a medium. The method comprises the following steps: when the dissolved hydrogen concentration variation of two or more monitoring units in a unit time period exceeds a preset rising or falling threshold value and one of the monitoring units periodically fluctuates, controlling to apply instantaneous electric pulse disturbance to all the monitoring units; collecting dissolved hydrogen response change values and capacitance change values before and after the pulse of each monitoring unit, and selecting the unit with the maximum dissolved hydrogen response change value as the unit with the maximum amplitude; and if the capacitance change value of the unit with the maximum amplitude has nonlinear offset or is lower than a threshold value, judging whether the change trend of the unit with the maximum amplitude is consistent with that of other units, and if so, pausing the alarm function of the unit with the maximum amplitude and continuing to monitor other units. By implementing the technical scheme provided by the invention, the accuracy of boiler leakage monitoring and positioning is improved.

Description

Technical Field

[0001] The present application relates to the field of analyzing materials by measuring the physical properties of the materials, and in particular to a boiler leakage prevention monitoring and positioning method, system, product and medium. Background Art

[0002] Boilers, as key components of large-scale thermal systems, are widely used in high-temperature, high-pressure, and continuously operating industries such as power generation, chemical engineering, and metallurgy. With increasing demands for operational efficiency and safety, early detection and location of boiler water-wall leaks have become crucial for ensuring stable system operation.

[0003] In related technologies, multiple dissolved hydrogen concentration sensors are typically installed at the boiler water wall outlet or its associated waterways to collect real-time dissolved hydrogen content in water samples and determine whether there are signs of leaks. If the hydrogen concentration at a monitoring point continues to rise and exceeds the alarm threshold, the system triggers an alarm and locates the leak.

[0004] However, the related art approach of leak detection based on single-point concentration changes has certain limitations. When the sensor is obstructed by non-leakage factors such as bubbles or impurities in the water, abnormal hydrogen signal fluctuations may occur, causing the system to misjudge the leak location and reduce the reliability of the monitoring system. Summary of the Invention

[0005] The present application provides a boiler anti-leakage monitoring and positioning method, system, product and medium for improving the accuracy of boiler leakage monitoring and positioning.

[0006] In a first aspect of the present application, a boiler leakage prevention monitoring and positioning method is provided, the method comprising: When it is detected that the changes in the dissolved hydrogen concentration readings of two or more monitoring units within a preset unit time period all exceed the preset rising floating threshold or the preset falling floating threshold and the reading of one of the monitoring units shows periodic fluctuations, an electric pulse disturbance instruction is issued to apply a preset instantaneous electric pulse disturbance to the electrode interfaces of all monitoring units; the dissolved hydrogen signal response change values and the capacitance change values of the electrode interfaces of each monitoring unit before and after the issuance of the electric pulse disturbance instruction are collected respectively; the dissolved hydrogen signal response change values are sorted, and the monitoring unit with the largest dissolved hydrogen signal response change value is taken as the unit with the largest amplitude; it is determined whether the capacitance change value of the unit with the largest amplitude has a nonlinear offset or is less than the preset capacitance change threshold; if so, the change trend of the dissolved hydrogen concentration readings of all detection units within the unit time period is obtained again; when the change trend of the unit with the largest amplitude is consistent with the change direction of the change trend of other detection units, the use of the unit with the largest amplitude as the alarm basis is suspended and the monitoring of the dissolved hydrogen concentration readings of the monitoring unit used as the alarm basis is returned to again.

[0007] In the above embodiment, by taking the dissolved hydrogen concentration readings of multiple monitoring units as the premise of disturbance triggering, the characteristics of simultaneous rise or fall in a unit time period and at least one monitoring unit accompanied by periodic fluctuations, it is possible to screen out suspected abnormal scenes that may be affected by local disturbances, interface abnormalities or system coupling effects, avoid unnecessary disturbance operations on single-point mutations or noise fluctuations, and improve the pertinence of disturbance response analysis. Subsequently, by applying electric pulse disturbances and collecting the dissolved hydrogen response change values and capacitance change values of each monitoring unit before and after the disturbance, the signal response amplitudes are sorted, and the unit with the most significant change is located as the unit with the largest amplitude, which helps to determine the main abnormal contribution unit in the context of simultaneous fluctuations at multiple points. Further judging whether the capacitance change value of the unit has a nonlinear offset or is lower than the threshold value helps to identify whether there may be problems such as contamination, adhesion or failure on its electrode interface; if it is confirmed that there is an abnormality, it is judged in combination with the consistency of the change trend direction of other units, which can effectively identify such synchronous trends caused by electrode abnormal amplification rather than real leakage, and then suspend the use of the unit as an alarm basis to prevent it from misleading positioning judgment. By constructing a multi-dimensional dynamic identification mechanism, this method not only enhances the system's ability to identify the status of the monitoring unit in a disturbed environment, but also ensures that the alarm basis comes from a stable and reliable detection channel. In this way, under complex operating conditions such as multi-point coupling interference, sensor aging, and interface contamination, the false alarm rate and mislocation risk are reduced, ultimately improving the accuracy of boiler leakage monitoring and positioning.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, after determining whether the capacitance change value of the unit with the largest amplitude has a nonlinear offset or is less than a preset capacitance change threshold, the method further includes: If not, the dissolved hydrogen concentration readings and electrode interface electrical parameters of the unit with the largest amplitude are continuously collected at a preset sampling frequency to obtain a dissolved hydrogen concentration reading sequence and an electrode interface electrical parameter sequence; the dissolved hydrogen concentration reading sequence is compared with the benchmark reading sequence before the electric pulse disturbance instruction is issued, and the baseline drift rate and the noise level change rate are calculated; the electrode interface electrical parameter sequence is compared with the benchmark electrical parameter value before the electric pulse disturbance instruction is issued, and the drift integral and the stability variation coefficient are calculated; in the case that the unit with the largest amplitude is a post-effect soft fault, the weight of the unit with the largest amplitude in subsequent alarm decisions is reduced.

[0009] In the above embodiment, after determining that the capacitance change value of the cell with the largest amplitude is normal, its dissolved hydrogen concentration and electrode parameters are further collected, and the baseline drift rate, noise change rate, and electrical parameter stability are analyzed. If the drift increases and the stability decreases, it is determined to be a soft fault with a delayed effect, and its weight in the alarm judgment is dynamically reduced. By introducing time domain and multi-dimensional electrical parameter features to conduct a secondary assessment of the suspicious cell, it avoids misidentifying cells with short-term abnormalities but long-term instability as critical leak sources. This is particularly applicable in scenarios where temperature differential disturbances or local electrode aging are present during boiler operation, thereby improving the accuracy of boiler leak monitoring and location.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, after reducing the weight of the unit with the largest amplitude in subsequent alarm decisions, the method further includes: When the baseline drift rate of the unit with the largest amplitude is greater than the drift rate threshold, the dissolved hydrogen concentration readings of the unit with the smallest amplitude and the unit with the largest amplitude are obtained in real time within unit time, and the minimum drift rate and the maximum drift rate are obtained by calculating the ratio of the change in the dissolved hydrogen concentration reading to the unit time. If the abnormal drift contribution factor is positive and the abnormal drift direction of the unit with the largest amplitude is consistent with the initial drift direction, a false drift prompt signal is issued. If the abnormal drift contribution factor is negative and the abnormal drift direction is inconsistent with the initial drift direction, the unit with the largest amplitude is suspended from being used as an alarm basis, and the unit with the largest amplitude is marked as being in maintenance status.

[0011] In the above embodiment, after reducing the weight of the unit with the largest amplitude, a real-time minimum and maximum drift rate comparison mechanism is further introduced. By calculating the abnormal drift contribution factor, it is determined whether the drift of the unit with the largest amplitude is a systematic trend amplification or an independent abnormal deviation. If the drift direction is consistent with the overall concentration change initially monitored and the contribution is positive, it indicates the presence of a false drift trend for manual review; if the direction is opposite and the contribution is negative, the unit with the largest amplitude is identified as an independent abnormal source and suspended as an alarm basis, and is marked as under maintenance. This can effectively distinguish between real leakage trends and individual sensor drift anomalies during boiler operation, and is suitable for complex operating conditions such as electrode aging and local thermal disturbances, thereby significantly improving the accuracy of boiler leak monitoring and positioning.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, determining whether the capacitance change value of the unit with the largest amplitude has a nonlinear offset or is less than a preset capacitance change threshold specifically includes: Obtain the historical capacitance change curve, real-time operating temperature, and real-time electrolyte conductivity of the electrode interface corresponding to the unit with the largest amplitude, calculate the capacitance curve deviation between the historical capacitance change curve and the real-time capacitance change curve obtained based on the capacitance change value; and determine whether the capacitance change value of the unit with the largest amplitude has a nonlinear offset or is less than a preset capacitance change threshold.

[0013] In the above embodiment, when determining whether the capacitance change value of the unit with the largest amplitude has a nonlinear offset or low-amplitude response, a comparison mechanism is introduced between the historical capacitance change curve and the current real-time capacitance curve. The influence of the real-time operating temperature and electrolyte conductivity on the capacitance characteristics is comprehensively considered to calculate the capacitance curve deviation and identify nonlinear responses caused by environmental factors or structural changes. This not only avoids misjudgments caused by short-term temperature changes or oil conductivity fluctuations, but also allows for timely identification of potential abnormal nodes in the early stages of electrode aging, contamination, or interface degradation. By improving the ability to resolve capacitance anomalies, the accuracy of judging the authenticity of the amplitude response is enhanced, thereby effectively eliminating signal distortion nodes under complex operating conditions, and ultimately improving the accuracy of boiler leak monitoring and positioning.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, after determining whether the capacitance change value of the unit with the largest amplitude has a nonlinear offset or is less than a preset capacitance change threshold, the method further includes: If there is a nonlinear offset in the capacitance change value of the unit with the largest amplitude, the self-cleaning mechanism of the unit with the largest amplitude is triggered; the capacitance response value of the unit with the largest amplitude after cleaning is obtained again, and the deviation of the capacitance curve after cleaning is calculated; if there is a nonlinear offset in the deviation of the capacitance curve after cleaning or it is less than the preset capacitance change threshold, the unit with the largest amplitude is suspended as an alarm basis.

[0015] In the above embodiment, after detecting that the capacitance change value of the unit with the largest amplitude has a nonlinear offset, its self-cleaning mechanism is actively triggered to eliminate interface anomalies that may be caused by electrode contamination, oil adhesion or microbubble interference, and then the capacitance response value after cleaning is re-acquired and the deviation of the capacitance curve after cleaning is calculated. If there is still a nonlinear offset or insufficient response amplitude after cleaning, it is judged that the unit has structural or long-term stability problems, and its use as an alarm basis is suspended. By introducing a self-cleaning and secondary verification mechanism, false abnormal signals caused by interface contamination are eliminated, and it is avoided that the surface problems of the equipment are misjudged as boiler body leaks, thereby significantly improving the accuracy of boiler leak monitoring and positioning.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after determining whether the capacitance change value of the unit with the largest amplitude has a nonlinear offset or is less than a preset capacitance change threshold, the method further includes: If not, extract the previous cycle signal features and the next cycle signal features from the dissolved hydrogen concentration reading sequence of the maximum amplitude unit before and after the electric pulse disturbance instruction is issued; if the spectrum energy change ratio of the next cycle signal feature at the fundamental frequency and harmonic frequency of the previous cycle signal feature exceeds the preset spectrum change tolerance threshold range, or a modulation sideband related to the electric pulse disturbance parameter appears at the harmonic frequency, and the energy of the modulation sideband is greater than the preset modulation sideband energy threshold, then suspend the use of the unit with the maximum amplitude as an alarm basis.

[0017] In the above embodiment, after confirming that the capacitance change value of the unit with the largest amplitude has no obvious nonlinear offset, the periodic signal characteristics in the dissolved hydrogen concentration reading sequence before and after the electric pulse disturbance are further extracted, and by comparing the spectral energy change ratio at the fundamental frequency and the harmonic frequency, it is identified whether there is a significant spectrum anomaly, especially detecting whether a modulation sideband signal related to the disturbance parameter appears. If the spectrum energy change exceeds the tolerance threshold or the modulation sideband energy is abnormally enhanced, it indicates that the unit may be affected by electromagnetic interference or system coupling effect, that is, it is suspended as an alarm basis. By introducing frequency domain features and modulation signal recognition, the pseudo-periodic response caused by local electromagnetic interference is effectively eliminated, which is particularly suitable for boiler operation environment under high-frequency disturbance background, thereby enhancing the ability to identify real leakage signals and ultimately improving the accuracy of boiler leakage monitoring and positioning.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, after the maximum pause amplitude unit is used as an alarm basis, the method further includes: A stable dissolved hydrogen concentration reading sequence is obtained for each of the remaining monitoring units except the unit with the largest amplitude after a preset stress observation period after the issuance of an electric pulse disturbance instruction; based on the stable dissolved hydrogen concentration reading sequence and the interference-free dissolved hydrogen concentration reading sequence before the issuance of the electric pulse disturbance instruction, the standard deviation or fluctuation energy is calculated as the post-pulse noise level and the pre-pulse noise level, respectively; the post-pulse noise level of each remaining detection unit is compared with the pre-pulse noise level before the issuance of the electric pulse disturbance instruction, and the noise gain factor is calculated; if the noise gain factor of a certain degradation monitoring unit is greater than the noise gain factor mean or the post-pulse noise level is greater than the preset post-pulse degradation threshold, the duration window required for alarm confirmation of the degradation monitoring unit is extended and the degradation monitoring unit is included in the priority maintenance list.

[0019] In the above embodiment, after the unit with the largest pause amplitude is used as the basis for alarm, the stable dissolved hydrogen reading sequence of the remaining monitoring units after the electric pulse disturbance is further analyzed, and by comparing with the interference-free reading sequence before the disturbance, the noise gain factor is calculated to quantify the degree of signal degradation caused by the disturbance. If the noise gain of a certain unit is significantly higher than the mean or exceeds the preset threshold, it means that there may be a decrease in interface stability or degradation of the response system. Based on this, the duration window required for its alarm confirmation is extended to prevent short-term fluctuations from falsely triggering the alarm, and the unit is included in the priority maintenance list. By introducing the noise comparison mechanism before and after the disturbance, the ability to identify the degradation of the monitoring unit state is enhanced, which is particularly suitable for scenarios where the sensor performance gradually decays after a long period of boiler operation, thereby improving the robustness of the overall system monitoring and the reliability of alarm judgment, and ultimately improving the accuracy of boiler leak monitoring and positioning.

[0020] In a second aspect, an embodiment of the present application provides a boiler leakage prevention monitoring and positioning system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the boiler leakage prevention monitoring and positioning system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions. When the computer program product is run on a boiler leakage prevention monitoring and positioning system, the boiler leakage prevention monitoring and positioning system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions. When the instructions are executed on a boiler leakage prevention monitoring and positioning system, the boiler leakage prevention monitoring and positioning system executes the method described in the first aspect and any possible implementation method of the first aspect.

[0023] It is understood that the boiler leakage prevention monitoring and positioning system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the boiler leakage prevention monitoring and positioning method provided in the embodiments of this application. Therefore, the beneficial effects achieved by these methods can be referenced to the beneficial effects of the corresponding methods and will not be further elaborated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. This application uses the characteristics of dissolved hydrogen concentration readings of multiple monitoring units rising or falling simultaneously within a unit time period and at least one monitoring unit accompanied by periodic fluctuations as a prerequisite for disturbance triggering. It can screen out suspected abnormal scenarios that may be affected by local disturbances, interface anomalies or system coupling effects, avoid unnecessary disturbance operations on single-point mutations or noise fluctuations, and improve the pertinence of disturbance response analysis. Subsequently, by applying electric pulse disturbances and collecting the dissolved hydrogen response change values and capacitance change values of each monitoring unit before and after the disturbance, the signal response amplitudes are sorted, and the unit with the most significant change is located as the unit with the largest amplitude, which helps to determine the main abnormal contribution unit in the context of simultaneous fluctuations at multiple points. Further judging whether the capacitance change value of the unit has a nonlinear offset or is lower than the threshold value helps to identify whether there may be problems such as contamination, adhesion or failure on its electrode interface; if it is confirmed that there is an abnormality, it is judged in combination with the consistency of the change trend direction of other units. This can effectively identify such synchronous trends caused by abnormal electrode amplification rather than real leakage, and then suspend the unit from being used as an alarm basis to prevent it from misleading positioning judgment. By constructing a multi-dimensional dynamic identification mechanism, this method not only enhances the system's ability to identify the status of the monitoring unit in a disturbed environment, but also ensures that the alarm basis comes from a stable and reliable detection channel. In this way, under complex operating conditions such as multi-point coupling interference, sensor aging, and interface contamination, the false alarm rate and mislocation risk are reduced, ultimately improving the accuracy of boiler leakage monitoring and positioning.

[0025] 2. After determining that the capacitance change value of the unit with the largest amplitude is normal, this application further collects its dissolved hydrogen concentration and electrode parameters, analyzes the baseline drift rate, noise change rate, and electrical parameter stability, and if it shows the characteristics of increased drift and decreased stability, it is determined to be a post-effect soft fault, and its weight in the alarm judgment is dynamically reduced. By introducing the time domain and multi-dimensional characteristics of electrical parameters to conduct a secondary assessment of suspicious units, it avoids misjudging short-term abnormal but long-term unstable units as key leak sources. It is particularly suitable for scenarios where there are temperature difference disturbances or local electrode aging during boiler operation, thereby improving the accuracy of boiler leak monitoring and positioning.

[0026] 3. After reducing the weight of the unit with the largest amplitude, this application further introduces a real-time minimum and maximum drift rate comparison mechanism, and determines whether the drift of the unit with the largest amplitude is a systematic trend amplification or an independent abnormal offset by calculating the abnormal drift contribution factor. If the drift direction is consistent with the overall concentration change and the contribution is positive, it indicates the presence of a false drift trend for manual review; if the direction is opposite and the contribution is negative, the unit with the largest amplitude is identified as an independent abnormal source and suspended as an alarm basis, and marked as a maintenance status. It can effectively distinguish between real leakage trends and individual sensor drift anomalies during boiler operation, and is suitable for complex working conditions such as electrode aging and local thermal disturbances, thereby significantly improving the accuracy of boiler leakage monitoring and positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart of a boiler leakage prevention monitoring and positioning method in an embodiment of the present application; Figure 2 This is another flow chart of the boiler leakage prevention monitoring and positioning method in an embodiment of the present application; Figure 3 This is an exemplary hardware structure diagram of the boiler leakage prevention monitoring and positioning system in the embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following examples of the present application are for the purpose of describing specific embodiments only and are not intended to limit the present application. As used in the specification and appended claims of the present application, the singular expressions "a," "an," "said," "above," "the," and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to and encompasses any or all possible combinations of one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0030] In related technologies, multiple dissolved hydrogen concentration sensors are usually installed at the outlet of the boiler water-cooled wall or its associated water channels to collect the dissolved hydrogen content in the water sample in real time and determine whether there are signs of leakage. When the hydrogen concentration at a certain monitoring point continues to rise and exceeds the preset alarm threshold, it is considered that there may be a leak at that point and an alarm is triggered. However, this type of method mainly relies on the trend of concentration changes at a single point for judgment, lacks in-depth analysis of the source of abnormal signals, and is easily affected by non-leakage factors such as bubble interference, electrode contamination, or local hydraulic fluctuations, resulting in periodic or sudden abnormal fluctuations in individual sensors, which in turn causes false alarms or missed alarms, reducing the system's ability to identify actual leakage events and the accuracy of positioning.

[0031] In the present application, when it is detected that a sudden change in concentration occurs in multiple monitoring units within a unit time, and one of the units is accompanied by periodic fluctuations, an electric pulse disturbance instruction is actively issued to apply instantaneous disturbances to all electrode interfaces to stimulate interface responses, thereby collecting the dissolved hydrogen signal change values and capacitance change values before and after the disturbance, and identifying the unit with the largest amplitude accordingly. Further, by judging whether there is nonlinear offset or abnormal attenuation in its capacitance response, combined with the trend consistency analysis of each monitoring unit, it is identified whether the unit is amplified due to interface abnormality or false response. If it is confirmed to be consistent, it is removed from the alarm basis and the remaining units are refocused. By introducing electric pulse intervention and multi-monitoring point collaborative judgment mechanism, the interference of single-point errors on the overall judgment is avoided, and the system's ability to identify real leakage signals under complex interference backgrounds is improved, ultimately improving the accuracy of boiler leakage monitoring and positioning.

[0032] Figure 1 This is a flow chart of a boiler leakage prevention monitoring and positioning method according to an embodiment of the present application, comprising the following steps: S101. When it is detected that the changes in the dissolved hydrogen concentration readings of two or more monitoring units within a preset unit time period exceed a preset rising floating threshold or a preset falling floating threshold and the reading of one of the monitoring units fluctuates periodically, an electric pulse disturbance instruction is issued to apply a preset instantaneous electric pulse disturbance to the electrode interfaces of all monitoring units.

[0033] Specifically, the system first continuously samples the multiple dissolved hydrogen monitoring units installed in the boiler, obtains the dissolved hydrogen concentration readings of each monitoring unit within a preset unit time period, and calculates the difference between the readings of each monitoring unit at the beginning and end of the unit time period to form the variation data. An ascending floating threshold and a descending floating threshold are preset to identify a significant increase or decrease in dissolved hydrogen concentration, respectively. When the dissolved hydrogen concentration change of two or more monitoring units is detected to exceed the floating threshold in a certain direction, that is, when all the monitored monitoring points change in the same direction (all rising or all falling), and the amplitude of the change exceeds the corresponding threshold, it is preliminarily determined that a large-scale concentration disturbance or abnormal change may exist within the current boiler.

[0034] Furthermore, based on the above trend determination, the real-time concentration reading sequences of all monitoring units are analyzed in the time domain or frequency domain to identify whether there are periodic fluctuation characteristics. The identification of periodic fluctuations can be achieved through various methods, such as extracting spectral components based on fast Fourier transform (FFT), or using autocorrelation functions to identify the repetitive periodic structure of the signal. If it is determined that the readings of at least one monitoring unit have significant periodic components within the unit time period, indicating that its signal may be affected by unstable factors such as periodic bubble interference, electrochemical interface oscillation, or fluid disturbance, an electric pulse disturbance instruction will be issued based on the result of the composite trigger condition being met.

[0035] This electrical pulse perturbation command is generated by the control module and sent down to the electrode control modules of multiple monitoring units via a signal control path. The perturbation signal takes the form of an electrical pulse with preset parameters, applied directly to the electrode interface of the monitoring unit. The goal is to induce a transient electrochemical perturbation at the electrode-liquid interface, thereby stimulating the sensor's dissolved hydrogen response mechanism. In this way, the sensor can be actively induced to produce a clear response change, which can then be compared with the signal change values before and after the perturbation, providing data support for subsequent determination of sensor status and identification of the source of the anomaly.

[0036] The above technical steps are based on a logical triggering mechanism for trend consistency judgment and periodic fluctuation identification, combined with active electric pulse intervention methods, which enhances the monitoring system's ability to identify and eliminate errors caused by non-leakage disturbances (such as bubble adhesion, temperature fluctuations, fluid disturbances, etc.), thereby improving the accuracy of fault location.

[0037] S102 , respectively collecting the dissolved hydrogen signal response change value and the capacitance change value of the electrode interface of each monitoring unit before and after the electric pulse disturbance instruction is issued.

[0038] Specifically, before the electric pulse is applied, a pre-disturbance signal acquisition window is set to record the initial dissolved hydrogen concentration reading and capacitance value of each monitoring unit. Subsequently, immediately after the electric pulse is applied, a post-disturbance signal acquisition window is opened to record the two post-disturbance data again. By comparing the difference between the readings before and after the disturbance, the dissolved hydrogen response change value and capacitance change value of the unit are respectively obtained. These values reflect the instantaneous response capability of the monitoring unit under the electric pulse excitation.

[0039] S103 , sorting the dissolved hydrogen signal response change values, and taking the monitoring unit with the largest dissolved hydrogen signal response change value as the unit with the largest amplitude.

[0040] Specifically, after collecting dissolved hydrogen concentration readings from each monitoring unit before and after the electric pulse perturbation, the dissolved hydrogen signal response change value for each monitoring unit is calculated. This is the difference in dissolved hydrogen concentration between the monitoring unit before and after the electric pulse application. This difference reflects the instantaneous response of the monitoring unit to the perturbation. A larger value indicates a more sensitive point to the perturbation, potentially closer to the leak source or the presence of some local anomaly.

[0041] In order to further analyze the response characteristics of each monitoring unit and identify the most likely abnormal point, the dissolved hydrogen concentration differences of all monitoring units are arranged from large to small, and the monitoring unit with the largest dissolved hydrogen concentration difference is selected as the unit with the largest amplitude.

[0042] The above sorting process can be implemented by a standard data processing algorithm, such as quick sort, bubble sort or key-based dictionary sorting method, or a one-time sorting can be performed directly.

[0043] S104 . When the capacitance change value of the unit with the largest amplitude has a nonlinear offset or is less than a preset capacitance change threshold, obtaining again the change trend of the dissolved hydrogen concentration readings of all detection units within a unit time period.

[0044] Specifically, the capacitance change value of the unit with the largest amplitude is first determined to be abnormal. If this value is lower than the preset capacitance change threshold, that is, the difference between the capacitance before and after the disturbance is insufficient to reflect the normal electrode interface reaction amplitude, it is considered to be insufficient response. On the other hand, if the capacitance change curve shows nonlinear offset before and after the disturbance, such as sudden change, rebound, oscillation, multi-peak and other non-monotonic change characteristics, it is believed that the electrode may be affected by non-real leakage factors such as bubble adhesion, electrode degradation, electrochemical polarization hysteresis, etc. These anomalies will cause the dissolved hydrogen response value of the monitoring unit to be distorted or amplified.

[0045] Determining whether the capacitance change curve exhibits nonlinear shifts before and after a perturbation is primarily accomplished by analyzing the trends and morphological characteristics of the capacitance time series data during the perturbation process. A high-frequency sampling window is set before and after the perturbation begins, and the continuous capacitance change curve is recorded in real time. This data is then divided into several time periods for trend analysis. If the capacitance change curve, under the influence of the perturbation, does not exhibit a stable, monotonic upward or downward trend, but instead exhibits significant fluctuations, such as instantaneous jumps (a sharp increase or decrease in capacitance within a very short period of time), rebounds (a rapid decrease after an increase in capacitance, or vice versa), oscillations (frequent fluctuations in capacitance within a short period of time), or a multimodal structure (the presence of two or more local maxima or minima in the curve), then it is considered a nonlinear shift. Furthermore, first-order derivative rate of change analysis or curve fitting residuals can be used as auxiliary criteria for nonlinear shifts. If the rate of change of the curve reverses multiple times within the perturbation period, or if it cannot be well fitted by a linear function or a smooth trend function, and the fitting residual exceeds a set threshold, these can also be used as auxiliary criteria for nonlinear shifts. This type of nonlinear response usually reflects that the monitoring electrode is affected by bubble disturbance, electrochemical interface instability or contamination layer adhesion, causing its capacitance response to deviate from normal disturbance behavior.

[0046] If there is a nonlinear offset or the capacitance change is less than a preset threshold, then within the set unit time period, continuous dissolved hydrogen concentration readings are taken for all monitoring units again within a future unit time period, and the concentration change trend of each monitoring unit is calculated based on this. This trend can be determined in a variety of ways, such as calculating the difference in dissolved hydrogen concentration at each monitoring point at the start and end of the time period to determine whether its concentration is increasing, decreasing, or generally stable; the direction and strength of the trend can also be determined by fitting a linear change curve, calculating the rate of change, analyzing the slope of the concentration change, etc.

[0047] This trend analysis can be used to determine whether the current phenomenon is a global phenomenon, such as a systemic concentration change caused by boiler operation adjustments, water flow disturbances, or temperature fluctuations, or a local anomaly caused by a true leak at a specific location. If the trend analysis finds that the concentration change direction of most monitoring units is consistent with the unit with the largest amplitude, it indicates that the unit may simply be an amplified response point under the systemic disturbance and does not have an independent leak indicator. Conversely, if the trend of the unit with the largest amplitude deviates significantly from the other units, and the other units do not change much, it supports the possibility that it is a true anomaly point.

[0048] In some embodiments, when the capacitance change value of the unit with the largest amplitude does not have a nonlinear offset and is greater than or equal to a preset capacitance change threshold, the dissolved hydrogen concentration reading and the electrode interface electrical parameters of the monitoring unit can be further subjected to a multi-dimensional dynamic analysis to identify whether there is a post-effect soft fault, thereby improving the robustness of fault identification on the basis of ensuring the effectiveness of the initial response, and avoiding misjudgment due to potential electrode aging or interface instability. Among them, a post-effect soft fault refers to a monitoring unit that responds normally on the surface and the signal amplitude meets the set threshold, but its internal electrode interface or sensor performance has gradually degraded, such as increased baseline drift, increased noise fluctuations, or deterioration of electrical parameter stability. This type of fault will not immediately lead to functional failure, but may cause misjudgment or signal distortion in subsequent monitoring. Because of its hysteresis and concealment, it is called a post-effect soft fault.

[0049] After confirming that the capacitance change value of the unit with the largest amplitude has no nonlinear offset and is greater than or equal to the preset capacitance change threshold, the dissolved hydrogen concentration readings and electrode interface electrical parameters of the unit with the largest amplitude are continuously collected at a preset sampling frequency to obtain a dissolved hydrogen concentration reading sequence and an electrode interface electrical parameter sequence. The sampling process lasts for a complete disturbance response cycle to ensure that the dynamic characteristics of the entire response process are captured. By establishing two synchronized time series, the hydrogen response behavior and electrode state changes of the monitoring unit can be tracked throughout the entire process, providing a data basis for subsequent stability analysis and drift judgment.

[0050] The sequence of dissolved hydrogen concentration readings collected above is compared point by point with the baseline sequence before the electrical pulse perturbation. The baseline trend of the response curve is determined using methods such as linear fitting, sliding average, or polynomial regression, and the rate of baseline change per unit time, i.e., baseline drift, is calculated. The rate of change of the noise level is also calculated by calculating the standard deviation of the readings at the sampling point in each time period before and after the perturbation. A significant increase in the drift rate indicates a decrease in the sensor's background stability; an increase in the noise level may indicate interface contamination or electronic interference.

[0051] Based on the analysis of concentration readings, the electrode electrical parameter sequence is further processed. First, each electrical parameter value after disturbance is differentiated from the baseline value, and the electrical parameter drift integral is accumulated to characterize the overall deviation of the electrode interface performance during the disturbance process. Secondly, the coefficient of variation of the parameter sequence, that is, the ratio of the standard deviation to the mean, is calculated to evaluate the stability. A high drift integral indicates a continuous change in electrode performance, while a high coefficient of variation reflects a sharp fluctuation in electrical parameters and an unstable response. Through the comprehensive evaluation of this dual indicator, soft damage such as electrochemical interface degradation or poor contact can be identified.

[0052] If any of the above indicators (baseline drift rate, noise change rate, drift integral, coefficient of variation) exceeds the corresponding set threshold, the unit with the largest amplitude is determined to have a post-effect soft fault. Although this type of fault does not manifest as an immediate signal failure, it will cause cumulative errors or response anomalies in subsequent sampling. To prevent it from causing dominant interference in the overall judgment, the weight of this unit in the alarm judgment algorithm will be dynamically reduced, for example through weighting coefficient adjustment, response score reduction, or weakening of the trust in the fusion model. This will retain its reference value while controlling its scope of influence, achieving robust fault-tolerant handling of potential fault sources.

[0053] To further enhance the identification of drift anomaly independence, when significant drift is detected in the maximum amplitude unit, the monitoring unit with the smallest dissolved hydrogen response change within the same time period is selected as the minimum amplitude unit. The concentration change rates per unit time for the maximum amplitude unit and the minimum amplitude unit are calculated, respectively, to obtain the maximum and minimum drift rates. Subtracting these rates from each other yields the abnormal drift contribution factor, which is used to quantify the degree of drift anomaly for the maximum amplitude unit relative to other units.

[0054] After calculating the difference between the maximum and minimum drift rates, the abnormal drift contribution factor is derived. This factor is then combined with the post-disturbance dissolved hydrogen concentration trend detected by the system to determine the direction of the change. This trend is determined by analyzing the concentration readings of each monitoring unit within a unit time period during the initial phase of the disturbance response. If the overall change exceeds the rising or falling floating threshold, an "upward trend" or "downward trend" is determined, respectively. Furthermore, if the abnormal drift direction of the unit with the largest amplitude aligns with the aforementioned trend and the abnormal drift contribution factor is positive, meaning the drift rate of that unit is significantly greater than the background reference value, the system deems the response to be an amplified effect of a systemic disturbance. To prevent such amplified responses from being misinterpreted as independent leaks, the system will not trigger an alarm but instead issue a "false drift warning signal," indicating that the monitoring point has background-consistent drift but no independent anomaly. This mechanism, by introducing dual criteria based on directional consistency and abnormal amplitude, effectively improves the system's ability to suppress false alarms from coordinated disturbances.

[0055] If in the above judgment, the abnormal drift contribution factor is negative, it means that the drift rate of the unit with the largest amplitude is less than the response rate of the unit with the smallest amplitude, and the abnormal drift direction of the unit with the largest amplitude is inconsistent with the overall trend direction. For example, the system as a whole is in an upward direction and the unit is in a downward trend, or the system as a whole is declining and the point has a reverse fluctuation, then it means that the response behavior of the unit with the largest amplitude is directional inconsistent with the main trend. This feature usually indicates that there is an isolated drift or local fault at this point, which may be caused by factors such as poor electrode contact, interface contamination, and abnormal internal noise. In order to avoid misleading the overall judgment, the usage weight of the unit with the largest amplitude in the alarm logic will be immediately suspended, and its status will be marked as maintenance status. This marking information will be used in subsequent data fusion and diagnosis processes to automatically block the data participation of this point and generate maintenance prompts.

[0056] Through the above-mentioned multi-dimensional sequence analysis and dynamic judgment mechanism, not only can potential soft faults be identified under the premise of effective disturbance response, but also false drift items can be eliminated through spatial comparison and directional consistency judgment, thereby improving the accuracy and anti-interference ability of alarm decisions, avoiding misjudgments and missed judgments, and improving the accuracy of boiler leakage monitoring and positioning.

[0057] S105. When the change trend of the unit with the largest amplitude is consistent with the change direction of the change trend of other detection units, suspend the use of the unit with the largest amplitude as the basis for alarm and return to monitoring the dissolved hydrogen concentration reading of the monitoring unit used as the basis for alarm.

[0058] Specifically, a directional consistency judgment algorithm is used to determine whether the cell exhibits independent anomalies. If the trend direction is consistent (i.e., all monitoring points exhibit an upward or downward trend), the alarm basis for the cell with the largest amplitude will be suspended and marked as a pending unit. At this point, an alarm will not be issued based on this point. Instead, the system will switch to returning dissolved hydrogen concentration readings from other monitoring cells and reassess whether other cells exhibit independent trend deviations or sudden changes, which will serve as new alarm targets.

[0059] This step can be implemented using various algorithms, such as trend matrix analysis, correlation comparison, and principal component analysis, to comprehensively determine trend consistency and anomaly independence. Trend matrix analysis is accomplished by constructing a two-dimensional matrix with the rate of change of dissolved hydrogen concentration at each monitoring unit per unit time period before and after the disturbance as the core indicator. Each row of the matrix corresponds to a monitoring unit, and each column corresponds to a time sampling point or a characteristic change indicator (such as concentration increment, rate of change, or direction of change). By analyzing the trend similarity between rows, the consistency of the response of each monitoring unit within the same time period can be identified. The specific method involves calculating the cosine similarity or Pearson correlation coefficient between the row vectors of the matrix to assess the correlation between the change trends between any two monitoring points. If the trend vectors of the unit with the largest amplitude are highly correlated with the trend vectors of most other units (for example, the correlation coefficient is above a set threshold), its change trend is considered consistent with the overall system, and its response is likely to be a systemic disturbance rather than a localized, independent anomaly. Trend matrix analysis can extract change patterns in the coordinated response of multiple points, enabling quantitative identification of anomaly independence and trend consistency.

[0060] In the above embodiment, by taking the dissolved hydrogen concentration readings of multiple monitoring units as the premise of disturbance triggering, the characteristics of simultaneous rise or fall in a unit time period and at least one monitoring unit accompanied by periodic fluctuations, it is possible to screen out suspected abnormal scenes that may be affected by local disturbances, interface abnormalities or system coupling effects, avoid unnecessary disturbance operations on single-point mutations or noise fluctuations, and improve the pertinence of disturbance response analysis. Subsequently, by applying electric pulse disturbances and collecting the dissolved hydrogen response change values and capacitance change values of each monitoring unit before and after the disturbance, the signal response amplitudes are sorted, and the unit with the most significant change is located as the unit with the largest amplitude, which helps to determine the main abnormal contribution unit in the context of simultaneous fluctuations at multiple points. Further judging whether the capacitance change value of the unit has a nonlinear offset or is lower than the threshold value helps to identify whether there may be problems such as contamination, adhesion or failure on its electrode interface; if it is confirmed that there is an abnormality, it is judged in combination with the consistency of the change trend direction of other units, which can effectively identify such synchronous trends caused by electrode abnormal amplification rather than real leakage, and then suspend the use of the unit as an alarm basis to prevent it from misleading positioning judgment. By constructing a multi-dimensional dynamic identification mechanism, this method not only enhances the system's ability to identify the status of the monitoring unit in a disturbed environment, but also ensures that the alarm basis comes from a stable and reliable detection channel. In this way, under complex operating conditions such as multi-point coupling interference, sensor aging, and interface contamination, the false alarm rate and mislocation risk are reduced, ultimately improving the accuracy of boiler leakage monitoring and positioning.

[0061] In other embodiments of the present application, when an abnormal capacitance response occurs in the unit with the largest amplitude, it may be due to electrode contamination or bubble adhesion, causing signal distortion and affecting leak detection. The boiler anti-leakage monitoring and location method provided in this application triggers the self-cleaning mechanism and analyzes the deviation of the capacitance curve after cleaning to determine whether the abnormality is reversible, thereby effectively eliminating false signals caused by interface contamination and improving the accuracy of leak location.

[0062] like Figure 2 FIG. 1 is another flow chart of the boiler leakage prevention monitoring and positioning method provided in an embodiment of the present application, comprising the following steps: S201. When it is detected that the changes in the dissolved hydrogen concentration readings of two or more monitoring units within a preset unit time period exceed the preset rising floating threshold or the preset falling floating threshold and the reading of one of the monitoring units fluctuates periodically, an electric pulse disturbance instruction is issued to apply a preset instantaneous electric pulse disturbance to the electrode interfaces of all monitoring units.

[0063] S202 , respectively collecting the dissolved hydrogen signal response change value and the capacitance change value of the electrode interface of each monitoring unit before and after the electric pulse disturbance instruction is issued.

[0064] S203 , sorting the dissolved hydrogen signal response change values, and taking the monitoring unit with the largest dissolved hydrogen signal response change value as the unit with the largest amplitude.

[0065] S204 , obtaining a historical capacitance change curve, a real-time operating temperature, and a real-time electrolyte conductivity corresponding to the electrode interface of the unit with the largest amplitude, and calculating a capacitance curve deviation between the historical capacitance change curve and the real-time capacitance change curve obtained according to the capacitance change value.

[0066] Specifically, after determining the unit with the largest amplitude, in order to further verify the credibility of the response of the unit with the largest amplitude and the consistency of the electrode state, the historical capacitance change curve of the electrode interface corresponding to the unit with the largest amplitude, the current real-time operating temperature and the real-time electrolyte conductivity are obtained, and the real-time capacitance change curve is constructed based on the capacitance change value collected during the current disturbance response process.

[0067] The historical curve is then compared with the real-time curve, and the deviation between the two curves is calculated using point-to-point or segment fitting. This deviation can be achieved using a variety of algorithms, such as Euclidean distance, dynamic time warping, or cosine angle, to measure the similarity of the two curve shapes. The historical curve is also normalized and corrected using real-time temperature and conductivity data. This normalization process primarily involves two steps: First, the current real-time operating temperature and electrolyte conductivity are compared with the environmental parameters corresponding to the historical capacitance curve at the time of acquisition to calculate the temperature deviation and conductivity deviation. Then, based on a pre-established model of the capacitance response's sensitivity to temperature and conductivity (e.g., a linear or nonlinear function model obtained through experimental fitting), the capacitance value at each point in the historical curve is corrected to its equivalent value under the current temperature and conductivity conditions. For example, if the model indicates that the capacitance value increases by 0.5% for every 1°C increase in temperature, then if the current temperature is 2°C higher than the historical curve, the system will adjust the historical curve upward by 1%. Similarly, conductivity deviation is corrected using a similar coefficient model. The final corrected historical curve is comparable to the real-time curve under the same environmental conditions, so that the deviation of the capacitance curve calculated subsequently truly reflects the performance difference of the electrode itself, rather than the external environmental disturbance, so as to eliminate the objective deviation of the capacitance response caused by the change of environmental conditions, thereby ensuring that the deviation reflects the change of the performance of the electrode itself rather than the interference of the medium or background factors.

[0068] If the deviation increases significantly, it means that the current capacitance response behavior is different from the performance of the electrode under the historical normal state, suggesting that the electrode may have performance degradation or change in response characteristics.

[0069] S205 . When the capacitance change value of the unit with the largest amplitude has a nonlinear offset or is less than a preset capacitance change threshold, obtain again the change trend of the dissolved hydrogen concentration readings of all detection units within a unit time period.

[0070] In some embodiments, when the capacitance change value of the unit with the largest amplitude does not have a nonlinear offset and is greater than or equal to a preset capacitance change threshold, an in-depth comparative analysis can be performed based on the frequency domain characteristics of the dissolved hydrogen concentration reading sequence before and after the disturbance to identify whether there is a hidden modulation response or structural degradation feature caused by the electric pulse, thereby further improving the accuracy of anomaly detection and leak location.

[0071] First, confirm that the capacitance change in the disturbance response of the unit with the largest amplitude satisfies the linear characteristic and is not lower than the set effective threshold. This indicates that the response strength of this unit with the largest amplitude meets the analytical basis and is free of typical nonlinear distortion. Subsequently, the dissolved hydrogen concentration reading series of this unit with the largest amplitude before and after the electric pulse disturbance are extracted, and the spectrum of these two time series is analyzed separately. Extraction methods typically include signal processing methods such as fast Fourier transform (FFT) or wavelet packet decomposition, aiming to obtain the spectral map and energy distribution structure of the periodic signal before and after.

[0072] Next, the fundamental frequency and its main harmonic frequency components are identified from the previous cycle spectrum, and a previous cycle spectrum feature template is constructed as a reference baseline. The energy changes of the corresponding frequency points in the subsequent cycle spectrum are then compared, and the spectrum energy change ratio is calculated. If this ratio exceeds the spectrum change tolerance threshold set by the system, it means that the disturbance has caused abnormal amplification or weakening of the system's frequency domain response, reflecting potential changes in the electrode or local oil characteristics. In addition, the subsequent cycle spectrum is also checked to see whether modulation sidebands associated with disturbance parameters (such as pulse frequency and duration) appear near the main harmonic frequencies. If the energy of the sideband frequency component exceeds the modulation sideband energy threshold, it means that the unit may have enhanced spectrum modulation due to disturbance coupling effects or structural nonlinearity, and is potentially unstable.

[0073] If any of these conditions are met, the unit with the largest amplitude is temporarily suspended from use as an alarm basis, preventing frequency domain anomalies from interfering with the overall judgment logic. Compared to traditional methods that rely solely on amplitude changes, this approach can more sensitively identify hidden frequency domain anomalies. It is particularly suitable for situations such as early electrode degradation, micro-bubble disturbances in the oil, or local nonlinear responses, improving the system's forward-looking recognition capabilities.

[0074] Through the above technical steps, it is possible to further identify spectral anomalies or modulation effects under the premise of normal amplitude response, thereby effectively avoiding false alarms caused by frequency domain disturbances, improving the ability to distinguish complex disturbance responses and the accuracy of leak location.

[0075] S206. When the change trend of the unit with the largest amplitude is consistent with the change direction of the change trends of other detection units, suspend the use of the unit with the largest amplitude as an alarm basis.

[0076] S207 : If the capacitance change value of the unit with the largest amplitude has a nonlinear offset, trigger a self-cleaning mechanism of the unit with the largest amplitude.

[0077] Specifically, the self-cleaning mechanism is a physical or electrochemical cleaning process that automatically initiates upon detecting an abnormality in the sensor electrode surface or interface performance. This process aims to remove any sludge, impurities, bubbles, or reaction byproducts that may be attached to the electrode surface, restoring it to normal operating condition. This mechanism is typically implemented through controlled electrode polarity reversal, high-frequency pulse excitation, micro-heating modules, or electrochemical regeneration pulses. This allows for online maintenance without disassembling the sensor, improving the long-term stability and reliability of the system.

[0078] When a nonlinear offset is detected in the capacitance change of the cell with the largest amplitude, the self-cleaning mechanism for that cell is automatically triggered. Nonlinear offsets typically indicate a loss of linearity in the electrode response behavior, which can be caused by factors such as electrode surface contamination, microbubble adhesion, electrochemical passivation, abnormal conductive media, or localized oil degradation. To prevent these abnormal signals from interfering with the overall system logic, a self-cleaning operation attempts to restore the electrode's original response state.

[0079] The implementation methods of the self-cleaning mechanism are mainly divided into three categories based on the electrode structure and system hardware configuration: the first is pulse reverse polarity cleaning, which is to apply a short, high-amplitude polarity reversal voltage pulse to the electrode through the control system, changing the direction of the electric field to dissipate the ions or oil film adsorbed on the electrode surface; the second is micro-thermal cleaning. When the electrode is equipped with a micro-heating module, the system heats the electrode area to a specific temperature in a short time to promote the desorption of attachments and the escape of bubbles; the third is electrochemical regeneration cleaning, which is suitable for sensors with a three-electrode system. The system reactivates the redox species on the electrode surface by applying a cyclic voltammetry scan in a specific potential window, thereby restoring the electrode response characteristics. Based on the electrode type, the degree of response abnormality and the current environmental parameters, the most appropriate cleaning method and parameter configuration are automatically selected, and the cleaning duration and frequency are controlled to ensure self-cleaning without damaging the electrode material.

[0080] S208 , obtaining the capacitance response value of the unit with the largest amplitude after cleaning again, and calculating the deviation of the capacitance curve after cleaning.

[0081] Specifically, after completing the self-cleaning operation on the unit with the largest amplitude, the capacitance response data of the unit is re-collected to obtain its capacitance change value after cleaning, and a capacitance change curve after cleaning is constructed. This process is usually completed within a stable waiting period (such as 10 to 30 seconds) after the cleaning is completed to ensure that the electrode surface state tends to be stable and is not disturbed by the residual effect of cleaning. Using the same curve processing algorithm as before cleaning, the capacitance change curve after cleaning is compared with the historical normal response curve of the unit, and its deviation is calculated. The deviation can be calculated using Euclidean distance, dynamic time warping or correlation coefficient matching, and a comparison model consistent with the previous one is selected to ensure that the results are consistent and comparable. The deviation reflects the degree of difference between the electrode response characteristics after cleaning and its historical normal state, and is an indicator for judging whether the cleaning operation is effective.

[0082] S209: If the capacitance curve deviation after cleaning has a nonlinear offset or is less than a preset capacitance change threshold, the unit with the largest pause amplitude is used as an alarm basis.

[0083] Specifically, after completing the self-cleaning operation for the electrode with the largest amplitude, a re-perturbation test is performed to obtain the post-cleaning capacitance change data for that cell. This data is then subjected to two key assessments: first, to determine whether the capacitance response curve still exhibits nonlinear deviations. This is done by analyzing the curve morphology to determine whether the variation trend deviates from the linear response characteristics represented by the historical reference curve. Second, the absolute amplitude of the capacitance change is calculated and compared with a minimum valid change threshold set by the system to confirm whether it possesses sufficient signal strength for anomaly detection. First, a deviation determination algorithm (such as one based on Euclidean distance, dynamic time warping (DTW), or a morphological matching model) is used to analyze the difference between the post-cleaning capacitance curve and the normal reference curve. If the deviation is still greater than the nonlinear offset threshold, it indicates that the electrode response behavior has not yet returned to linear characteristics. Second, the maximum capacitance change resulting from the perturbation response is read and determined to determine whether it meets the detection system's minimum signal resolution requirement. If either condition is not met, indicating that the cell's state is still unstable or the detection sensitivity is insufficient, the cell is suspended from use as an alarm basis. The pause operation automatically removes its data input from the alarm logic by modifying the internal alarm weight matrix or marking the unit status as abnormal, preventing the node signal from participating in subsequent fault identification calculations.

[0084] S210 , respectively obtaining a sequence of stable dissolved hydrogen concentration readings of the remaining monitoring units except the unit with the largest amplitude after a preset stress observation period after the electric pulse disturbance instruction is issued.

[0085] Specifically, after the previous electric pulse disturbance instruction is issued, the disturbance response process is entered. In order to ensure the stability and representativeness of the collected data, a fixed stress observation period is set after the disturbance is executed to filter out transient signal fluctuations caused by short-term overreaction of the electrode. After the end of the stress observation period, the stable dissolved hydrogen concentration reading sequence of all remaining monitoring units except the unit with the largest amplitude is obtained. Under the premise of excluding the interference of abnormal points, a centralized response state evaluation of the remaining normal units is established, thereby providing a reliable data basis for subsequent horizontal comparison, concentration trend analysis or spatial interpolation calculation.

[0086] When a unified electrical pulse disturbance command is initially issued, all monitoring nodes simultaneously receive the disturbance signal, triggering the electrochemical response mechanism within their sensing electrodes. After the disturbance is complete, a stress observation timer is started, and a preset buffer period begins. This phase is used to wait for the electrode response to stabilize and avoid errors caused by the disturbance tail. After the stress observation period, data from each non-maximum amplitude unit is read sequentially or in parallel, extracting its stable capacitance response value at that moment and converting it to the corresponding dissolved hydrogen concentration value using an embedded feature conversion model (such as a capacitance-concentration response mapping function, a nonlinear fitting model, or a lookup table). All concentration readings are indexed by timestamps and form a stable concentration reading sequence, which is used for subsequent anomaly identification, concentration distribution assessment, and multi-point fusion analysis.

[0087] S211. Based on the stable dissolved hydrogen concentration reading sequence and the undisturbed dissolved hydrogen concentration reading sequence before the electric pulse disturbance instruction is issued, the standard deviation or fluctuation energy is calculated as the post-pulse noise level and the pre-pulse noise level, respectively.

[0088] Specifically, on the one hand, the dissolved hydrogen concentration reading sequence before the disturbance is extracted, and a continuous and stable period of data before the pulse trigger is usually selected as the interference-free baseline; on the other hand, the stable concentration reading sequence obtained after the disturbance and at the end of the stress observation period is used to represent the state that tends to be stable after the disturbance response. The concentration reading sequences of these two time periods are statistically analyzed respectively, and the standard deviation or fluctuation energy is used as the noise quantification index. The standard deviation calculation is used to measure the degree of dispersion of the data near the mean, while the fluctuation energy method analyzes the residual sum of squares after smoothing to reflect the intensity of high-frequency fluctuations in the signal. Finally, the system obtains the baseline noise level before the disturbance and the response noise level after the disturbance as the post-pulse noise level and the pre-pulse noise level.

[0089] S212 , respectively comparing the post-pulse noise level of each remaining detection unit with the pre-pulse noise level before the electrical pulse disturbance instruction is issued, and calculating a noise gain factor.

[0090] Specifically, the noise level before and after the disturbance is obtained for each remaining monitoring unit. The ratio of the two is then calculated: noise gain factor = post-pulse noise level / pre-pulse noise level. This factor reflects whether the disturbance has increased the signal fluctuation of that unit. This indicator can not only be used to identify potential abnormal units but also provide a basis for subsequent signal correction, weight adjustment, or fault warning.

[0091] First, the noise level of each unit before and after the perturbation is normalized to ensure comparability among nodes with different amplitudes and response characteristics. In the standard deviation method, the variance of the original concentration reading sequence is calculated and then squared to obtain the pre-perturbation standard deviation and post-perturbation standard deviation. The noise gain factor is then calculated as: post-perturbation standard deviation / pre-perturbation standard deviation.

[0092] In some embodiments, units with a noise gain factor greater than a set gain threshold are marked as having abnormal noise gain and are then either removed as an alarm or downgraded. This operation can be performed in batches using matrix processing, ensuring efficient operation in multi-node systems.

[0093] S213: If the noise gain factor of a degradation monitoring unit is greater than the noise gain factor mean or the post-pulse noise level is greater than the preset post-pulse degradation threshold, extend the duration window required for the degradation monitoring unit alarm confirmation and include the degradation monitoring unit in the priority maintenance list.

[0094] Specifically, the mean value of the noise gain factors of all remaining monitoring units is calculated as a horizontal comparison benchmark to identify abnormal units whose relative noise amplification degree is significantly higher than the average level.

[0095] If the noise gain factor of a monitoring unit is greater than the mean noise gain factor, or its post-pulse noise level exceeds the set post-pulse degradation threshold, the unit will be determined to have a potential degradation trend or structural response anomaly. In this case, two response strategies will be implemented for the unit: first, the duration window required for its alarm confirmation will be extended. That is, when determining the alarm status, the abnormality of the unit will be required to last longer and the signal will be more stable. This will raise the threshold for entering the alarm state and prevent misjudgment due to noise interference. Second, the unit will be added to the priority maintenance list so that it will be given priority during regular maintenance, inspections, or remote diagnosis. This will prevent potential degradation trends in advance and enhance the system's preventive maintenance capabilities.

[0096] Steps S201-S203, S205-S206 and Figure 1 Steps S101 to S105 in the illustrated embodiment are similar, and reference may be made to the description of steps S101 to S105 , which will not be repeated here.

[0097] In the above embodiment, when multiple monitoring units simultaneously experience dramatic fluctuations in dissolved hydrogen concentration and periodic anomalies, an electric pulse disturbance command is actively issued and hydrogen signals and capacitance responses before and after the disturbance are collected, thereby identifying the unit with the largest amplitude. The deviation is determined by combining its historical capacitance curve, temperature, conductivity and other parameters to identify false enhanced responses caused by electrode anomalies, contamination adhesion or local thermal disturbances. On this basis, if the capacitance offset of the unit with the largest amplitude is abnormal and its trend is consistent with that of other units, it is suspended as an alarm basis to avoid misattributing common trends to individual anomalies. If its capacitance offset persists, self-cleaning is triggered and re-verification is performed to further eliminate errors caused by surface contamination factors. In addition, by comparing the changes in the noise levels of the remaining units before and after the disturbance, the monitoring units with degraded responses are identified, their confirmation cycles are extended, and they are included in the priority maintenance list, thereby enhancing the system's fault tolerance and adaptability to performance boundary units, improving the system's ability to distinguish between disturbance sources, abnormal signals and true leakage trends, and ultimately significantly improving the accuracy of boiler leak monitoring and positioning.

[0098] The following introduces an exemplary boiler leakage prevention monitoring and positioning system 300 provided in an embodiment of the present application. Figure 3 Schematic diagram of an exemplary hardware structure of a boiler leakage prevention monitoring and positioning system 300 provided in an embodiment of the present application.

[0099] In some embodiments, the boiler leakage prevention monitoring and positioning system 300 is a computer device or the boiler leakage prevention monitoring and positioning system 300 includes a computer device. The computer device includes a processor, a memory and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with other external terminals or servers via a network connection. In some embodiments, the network interface can be a wired network interface, and in some embodiments, the network interface can also be a wireless network interface. When the computer program is executed by the processor, the method in the embodiment of the present application is implemented.

[0100] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0101] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0102] As used in the above embodiments, the term “when…” may be interpreted as “if…” or “after…” or “in response to determining…” or “in response to detecting…”, depending on the context. Similarly, the phrases “upon determining…” or “if (stated condition or event) is detected” may be interpreted as “if determining…” or “in response to determining…” or “upon detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

[0103] In the above embodiments, all or part of the embodiments may be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product comprises one or more computer instructions. When loaded and executed on a computer, the computer program instructions fully or partially perform the processes or functions described in the embodiments of this application. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium accessible by a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium may be magnetic media (e.g., floppy disk, hard disk, magnetic tape), optical media (e.g., DVD), or semiconductor media (e.g., solid-state drive).

[0104] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A boiler leakage prevention monitoring and positioning method, characterized in that: include: When it is detected that the changes in the dissolved hydrogen concentration readings of two or more monitoring units within a preset unit time period all exceed a preset rising floating threshold or a preset falling floating threshold and the reading of one of the monitoring units fluctuates periodically, an electric pulse disturbance instruction is issued to apply a preset instantaneous electric pulse disturbance to the electrode interfaces of all monitoring units; respectively collecting the dissolved hydrogen signal response change value and the capacitance change value of the electrode interface of each monitoring unit before and after the electric pulse disturbance instruction is issued; sorting the dissolved hydrogen signal response change values, and taking the monitoring unit with the largest dissolved hydrogen signal response change value as the unit with the largest amplitude; Determining whether the capacitance change value of the maximum amplitude unit has a nonlinear offset or is less than a preset capacitance change threshold; If so, obtaining again the change trend of the dissolved hydrogen concentration readings of all detection units within the unit time period; When the change trend of the unit with the largest amplitude is consistent with the change direction of the change trends of other detection units, the use of the unit with the largest amplitude as an alarm basis is suspended and the monitoring of the dissolved hydrogen concentration reading of the monitoring unit serving as the alarm basis is returned to again.

2. The method according to claim 1, characterized in that After determining whether the capacitance change value of the maximum amplitude unit has a nonlinear offset or is less than a preset capacitance change threshold, the method further includes: If not, continuously sampling the dissolved hydrogen concentration readings and electrode interface electrical parameters of the unit with the largest amplitude at a preset sampling frequency to obtain a dissolved hydrogen concentration reading sequence and an electrode interface electrical parameter sequence; comparing the dissolved hydrogen concentration reading sequence with a baseline reading sequence before issuing the electric pulse disturbance instruction and calculating a baseline drift rate and a noise level change rate; Comparing the electrode interface electrical parameter sequence with the reference electrical parameter value before issuing the electrical pulse disturbance instruction, and calculating the drift integral and the stability variation coefficient; In the case where the unit with the largest amplitude is a post-effect soft fault, the weight of the unit with the largest amplitude in subsequent alarm decisions is reduced; the post-effect soft fault is that the baseline drift rate is greater than the preset drift rate threshold, the noise level change rate is greater than the preset noise change rate threshold, the drift integral is greater than the preset integral threshold, or the noise level change rate is greater than the preset noise change rate threshold.

3. The method according to claim 2, characterized in that After reducing the weight of the unit with the largest amplitude in subsequent alarm decisions, the method further includes: When the baseline drift rate of the unit with the largest amplitude is greater than the drift rate threshold, the dissolved hydrogen concentration readings of the unit with the smallest amplitude and the unit with the largest amplitude are respectively obtained in real time within the unit time, and the minimum drift rate and the maximum drift rate are respectively obtained by calculating the ratio of the dissolved hydrogen concentration reading change to the unit time; the unit with the smallest amplitude is the monitoring unit with the smallest ranking after sorting the dissolved hydrogen signal response change values; If the abnormal drift contribution factor is positive and the abnormal drift direction of the unit with the largest amplitude is consistent with the initial drift direction, a false drift prompt signal is issued; the abnormal drift contribution factor is the difference between the maximum drift rate and the minimum drift rate; the initial drift direction is the direction of change of the dissolved hydrogen concentration readings of two or more monitoring units detected within the unit time period; If the abnormal drift contribution factor is negative, and the abnormal drift direction is inconsistent with the initial drift direction, the unit with the largest amplitude is suspended from being used as an alarm basis, and the unit with the largest amplitude is marked as being in maintenance status.

4. The method according to claim 1, wherein The determining whether the capacitance change value of the maximum amplitude unit has a nonlinear offset or is less than a preset capacitance change threshold specifically includes: Obtaining a historical capacitance change curve, a real-time operating temperature, and a real-time electrolyte conductivity of the electrode interface corresponding to the unit with the largest amplitude, and calculating a capacitance curve deviation between the historical capacitance change curve and a real-time capacitance change curve obtained according to the capacitance change value; Determine whether the capacitance change value of the maximum amplitude unit has a nonlinear offset or is less than a preset capacitance change threshold; the nonlinear offset is the deviation of the capacitance curve from the preset reference deviation threshold range, and the real-time operating temperature exceeds the preset operating temperature threshold range or the real-time electrolyte conductivity exceeds the preset conductivity threshold range.

5. The method according to claim 4, characterized in that After determining whether the capacitance change value of the unit with the largest amplitude has a nonlinear offset or is less than a preset capacitance change threshold, the method further includes: If the capacitance change value of the unit with the largest amplitude has the nonlinear offset, triggering a self-cleaning mechanism of the unit with the largest amplitude; obtaining again the capacitance response value of the unit with the largest amplitude after cleaning, and calculating the deviation of the capacitance curve after cleaning; If the deviation of the capacitance curve after cleaning has the nonlinear offset or is less than the preset capacitance change threshold, the maximum amplitude unit is suspended for use as an alarm basis.

6. The method according to claim 1, characterized in that After determining whether the capacitance change value of the maximum amplitude unit has a nonlinear offset or is less than a preset capacitance change threshold, the method further includes: If not, extracting the pre-cycle signal feature and the post-cycle signal feature from the dissolved hydrogen concentration reading sequence of the maximum amplitude unit before and after the electric pulse disturbance instruction is issued; If the spectral energy change ratio of the post-cycle signal feature at the fundamental frequency and harmonic frequency of the pre-cycle signal feature exceeds the preset spectral change tolerance threshold range, or a modulation sideband related to the electric pulse disturbance parameter appears at the harmonic frequency, and the energy of the modulation sideband is greater than the preset modulation sideband energy threshold, then the maximum amplitude unit is suspended for use as an alarm basis.

7. The method according to claim 1, characterized in that After suspending the use of the maximum amplitude unit as an alarm basis, the method further includes: respectively obtaining a sequence of stable dissolved hydrogen concentration readings of the remaining monitoring units except the unit with the largest amplitude after a preset stress observation period after the electric pulse disturbance instruction is issued; Based on the stable dissolved hydrogen concentration reading sequence and the interference-free dissolved hydrogen concentration reading sequence before issuing the electric pulse disturbance instruction, respectively calculating the standard deviation or the fluctuation energy as the post-pulse noise level and the pre-pulse noise level; Comparing the post-pulse noise level of each of the remaining detection units with the pre-pulse noise level before the electrical pulse disturbance instruction is issued, and calculating a noise gain factor; If the noise gain factor of a degradation monitoring unit is greater than the noise gain factor mean or the post-pulse noise level is greater than the preset post-pulse degradation threshold, the duration window required for the degradation monitoring unit alarm confirmation is extended and the degradation monitoring unit is included in the priority maintenance list; the noise gain factor is the ratio of the post-pulse noise level to the pre-pulse noise level; the noise gain factor mean is the average value of the noise gain factors of all the remaining detection units.

8. A boiler anti-leakage monitoring and positioning system, characterized in that: The boiler leakage prevention monitoring and positioning system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the boiler leakage prevention monitoring and positioning system to execute the method according to any one of claims 1 to 7.

9. A computer program product comprising instructions, characterized in that When the computer program product is run on a boiler leakage prevention monitoring and positioning system, the boiler leakage prevention monitoring and positioning system is enabled to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the boiler leakage prevention monitoring and positioning system, the boiler leakage prevention monitoring and positioning system is caused to execute the method according to any one of claims 1 to 7.

Images