Electrolytic bath fault monitoring system

Abstract

According to the electrolytic cell fault monitoring system provided by the invention, an early leakage identification system is constructed by implanting nonmetal marking elements, so that on one hand, advanced early warning before leakage can be realized, and a quantitative relation model of a concentration change rate and lining corrosion is established through characteristic spectrum detection of a boron-carbon compound in an electrolyte; element migration signals of one millionth level can be captured at the initial stage of permeation; on the other hand, the interference of an aluminum-silicon molten salt system can be broken through, a double-calibration strategy of a boron element characteristic spectral line and a carbon element diffraction peak is adopted, spectral line overlapping interference of iron and silicon elements is effectively avoided, and the detection signal-to-noise ratio is greatly increased; and finally, by constructing a dynamic compensation algorithm, the influence of fused salt component fluctuation is automatically corrected, so that the false alarm rate is greatly reduced.

Description

Technical Field

[0001] This invention relates to the field of electrolytic cell fault handling technology, and in particular to an electrolytic cell fault monitoring system. Background Technology

[0002] Because the silicon and iron content of the raw materials used in the aluminum-silicon oxide molten salt co-precipitation technology is relatively high, the traditional and most effective method of judging leakage through primary aluminum quality analysis has become ineffective. Other methods, such as measuring the temperature of the furnace bottom shell and the cathode steel rod, are used to determine whether leakage has occurred. However, these methods are relatively slow and cannot identify safety risks at the first moment when leakage occurs in the electrolytic cell. Therefore, it is necessary to study a technology that can accurately, efficiently, and in advance detect the risk of leakage. Summary of the Invention

[0003] In view of this, the present invention provides an electrolytic cell fault monitoring system. One or more embodiments of this specification also relate to an electrolytic cell fault monitoring method to address the technical deficiencies existing in the prior art.

[0004] According to a first aspect of the present invention, an electrolytic cell fault monitoring system is provided, comprising:

[0005] An electrolytic cell damage and leakage fault monitoring system includes a marker element release unit, a multi-dimensional sampling unit, a spectral analysis unit, and a dynamic decision-making unit embedded in the cathode component;

[0006] The marker element release unit implants non-metallic marker elements into the cathode liner and steel rod according to a preset distribution pattern;

[0007] The multi-dimensional sampling unit periodically extracts electrolyte samples and transmits them to the spectral analysis unit;

[0008] The spectral analysis unit detects the concentration of labeled elements and generates a heat map by using characteristic spectra;

[0009] The dynamic decision-making unit performs graded early warnings based on the current concentration value, historical trends, and electrolyzer operating parameters.

[0010] In some embodiments, the marker element release unit includes a cathode liner with a gradient concentration distribution and a double-coated steel rod.

[0011] The concentration of boron carbide compounds in the cathode liner decreases exponentially along the depth direction, and the double coating of the steel rod includes an inner boron carbide wear-resistant layer and an outer graphene-coated nano-carbon particle slow-release layer.

[0012] In some implementations, the multi-dimensional sampling unit includes a spatial matrix sampler and a timing trigger. The spatial matrix sampler sets a three-dimensional sampling point array in the electrolytic cell, and the timing trigger switches to emergency sampling mode when the cell voltage fluctuation exceeds three percent.

[0013] In some embodiments, the spectral analysis unit is arranged in parallel with an inductively coupled plasma atomic emission spectrometer and an X-ray fluorescence spectrometer. When the concentration detected by the X-ray fluorescence spectrometer exceeds 60% of the threshold, the inductively coupled plasma atomic emission spectrometer is automatically activated for fine measurement.

[0014] In some implementations, the dynamic decision-making unit includes a baseline threshold setting module, an environmental compensation module, and a trend prediction module. The baseline threshold setting module adjusts the threshold in stages according to the service life of the electrolyzer. The environmental compensation module corrects the influence of temperature and electrolyte composition in real time. The trend prediction module establishes a concentration change rate model based on time series.

[0015] In some implementations, the environmental compensation module performs the following calculation:

[0016]

[0017] Among them, T adj The corrected threshold is derived from the coupled calculation of the current baseline threshold T0 and the deviation of environmental parameters; ΔP i This represents the deviation value of the i-th operating condition parameter, derived from the difference between real-time sensor data and the standard value; α i The compensation coefficient for the i-th parameter is derived from historical data fitting; ΔC j This represents the change in concentration of the j-th electrolyte component, derived from the output of the spectral analysis unit; β j The weights for the influence of components are derived from experimental calibration data; n and m represent the total number of operating parameters and component types, respectively.

[0018] In some implementations, the compensation coefficient α_i is calculated using the following formula:

[0019]

[0020] Where, γ k σ is the k-th process characteristic coefficient, derived from the electrolytic cell design parameters; k / μ k θ represents the coefficient of variation of the k-th parameter, derived from three months of historical data statistics; k ω is the shape factor, derived from a material properties database; l The temperature influence factor is derived from the thermodynamic model; ΔT l This indicates the temperature difference between different areas, derived from infrared thermometry data.

[0021] In some embodiments, the spectral analysis unit locks the detection wavelength of boron at 209 nm and the detection peak of carbon at 0.28 nm, and establishes a mapping relationship between the concentration ratio of the two elements and the corrosion rate of the lining.

[0022] In some implementations, the trend prediction module triggers a level-two warning when it detects a concentration increase of more than 20% for three consecutive periods. The increase calculation includes the weighted difference between the current detected value and the average value of the previous three periods.

[0023] In some embodiments, the electrolytic cell damage and leakage fault monitoring system further includes a digital twin visualization unit, which displays in real time a cloud map of the concentration distribution of marked elements, a threshold boundary line, and a predicted corrosion path. The concentration distribution cloud map is derived from the heat map data of the spectral analysis unit, and the predicted corrosion path is derived from the trend analysis results of the dynamic decision-making unit.

[0024] At least one embodiment of this invention constructs an early leakage identification system by implanting non-metallic marker elements. On the one hand, it can achieve early warning before leakage occurs. By detecting the characteristic spectra of boron-carbon compounds in the electrolyte, a quantitative relationship model between the concentration change rate and the lining corrosion is established, allowing the capture of element migration signals at the part-in-a-million level in the early stages of penetration. On the other hand, it can overcome the interference of the aluminum-silicon molten salt system. By adopting a dual calibration strategy of boron element characteristic spectral lines and carbon element diffraction peaks, it can effectively avoid the interference of overlapping spectral lines of iron and silicon elements, and significantly improve the detection signal-to-noise ratio. Finally, by constructing a dynamic compensation algorithm, the influence of molten salt composition fluctuations is automatically corrected, greatly reducing the false alarm rate. Attached Figure Description

[0025] Figure 1 This is a simplified structural diagram of an electrolytic cell fault monitoring system provided by the present invention. Detailed Implementation

[0026] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0027] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the one or more embodiments of this specification. The singular forms “a” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items. The modifications “a” and “a plurality” as used in this disclosure are illustrative and not restrictive, and those skilled in the art will understand that they should be understood as “one or more” unless the context clearly indicates otherwise.

[0028] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0029] See Figure 1 , Figure 1 A simplified structural diagram of an electrolytic cell fault monitoring system according to some embodiments of this specification is shown, specifically including: a marker element release unit, a multi-dimensional sampling unit, a spectral analysis unit, and a dynamic decision-making unit embedded in a cathode component; the marker element release unit implants non-metallic marker elements into the cathode liner and steel rod according to a preset distribution pattern; the multi-dimensional sampling unit periodically extracts electrolyte samples and transmits them to the spectral analysis unit; the spectral analysis unit detects the concentration of the marker elements through characteristic spectra and generates a thermogram; the dynamic decision-making unit performs graded early warning based on the current concentration value, historical trend, and electrolytic cell operating parameters.

[0030] An electrolytic cell can refer to a container used in electrolysis processes to hold electrolytes and realize electrochemical reactions. A cathode component can refer to a conductive part in the electrolytic cell connected to the negative terminal of the power supply, used to conduct current and support the lining material. A labeled element release unit can refer to a slow-release device containing specific chemical elements, used to continuously release detectable tracers into the electrolyte. Non-metallic labeled elements can refer to non-metallic tracers such as boron or carbon, used to identify corrosion states through spectral characteristics. A cathode lining can refer to a refractory material layer covering the cathode surface, used to insulate the steel rod from corrosion by the high-temperature electrolyte. A steel rod can refer to a metallic conductor embedded in the cathode, used to conduct current out of the electrolytic cell. A multi-dimensional sampling unit can refer to a mechanical device with spatial and temporal sampling capabilities, used to obtain representative electrolyte samples. An electrolyte sample can refer to a molten salt mixture extracted from the electrolytic cell, used to analyze the concentration distribution of labeled elements, and can be extracted from the electrolyte surface, bottom sediment, and anode mud. Extraction can be performed by heating to the evaporation temperature. A spectral analysis unit can refer to an analytical system containing optical detection instruments, used to identify the characteristic spectra of specific elements in the sample. A heat map can refer to a two-dimensional spatial distribution map of marked element concentrations, used to visualize corrosion risk areas. A dynamic decision unit can refer to a control module with adaptive algorithms, used to comprehensively assess the risk level of a leaking cell. Historical trend analysis can refer to the changing patterns of marked element concentrations over time, used to predict the rate of corrosion development. Electrolyte operating parameters can refer to real-time operating data including temperature, voltage, and composition, used to adjust detection thresholds. Graded early warning systems can refer to alarm mechanisms categorized according to risk levels, used to implement differentiated response measures.

[0031] As a specific example:

[0032] In a 365kA electrolytic cell, the cathode steel rod surface is coated with a graphene coating containing 5% nano-carbon particles, and the lining material is graded-doped with boron carbide at a depth decreasing by 0.5% per millimeter. A mechanical sampling arm automatically collects nine samples every eight hours. After grinding under argon protection, the samples are first rapidly scanned for 30 seconds using an X-ray fluorescence spectrometer. When the intensity of the carbon element characteristic peak exceeds 60% of the preset value, an inductively coupled plasma atomic emission spectrometer is activated for a 3-minute precise measurement. Based on the current cell temperature of 820℃, the dynamic decision-making system automatically lowers the boron threshold by 8% and, combined with the trend data showing a concentration increase slope exceeding 0.5ppm / h over the past 72 hours, triggers a yellow warning signal. The digital twin interface displays a red thermal patch in the northeast corner of the cathode area in real time, indicating a risk of lining damage in that area.

[0033] This invention constructs an early leakage identification system by implanting non-metallic marker elements. On the one hand, it can achieve early warning before leakage occurs. By detecting the characteristic spectra of boron-carbon compounds in electrolytes, a quantitative relationship model between concentration change rate and lining corrosion is established, allowing the capture of element migration signals at the part-in-a-million level in the early stages of penetration. On the other hand, it can overcome the interference of the aluminum-silicon molten salt system. By adopting a dual calibration strategy of boron element characteristic spectral lines and carbon element diffraction peaks, it effectively avoids the interference of overlapping spectral lines of iron and silicon elements, significantly improving the detection signal-to-noise ratio. Finally, by constructing a dynamic compensation algorithm, it automatically corrects the influence of molten salt composition fluctuations, greatly reducing the false alarm rate.

[0034] In some embodiments, the labeled element release unit includes a cathode liner with a gradient concentration distribution and a double-coated steel rod; the concentration of boron carbide compounds in the cathode liner decreases exponentially along the depth direction, and the double coating of the steel rod includes an inner boron carbide wear-resistant layer and an outer graphene-coated nano-carbon particle slow-release layer. The labeled element release unit can refer to a novel functional component integrated into the cathode structure of the electrolytic cell, used for the directional release of detectable tracers. The gradient concentration distribution of elements can refer to the non-uniform spatial arrangement of chemical components in a material, used to establish a correspondence between corrosion depth and element concentration. The cathode liner can refer to a refractory protective layer in the cathode region of the electrolytic cell, used to resist high-temperature electrolyte corrosion and bear the labeled element. Boron carbide compounds can refer to ceramic phase materials composed of boron and carbon, used as markers with corrosion resistance and spectral recognition characteristics. The exponential decrease can refer to the concentration changing with depth as a negative exponential function with base e, used to achieve a non-linear correlation between corrosion degree and release amount. The double-coated steel rod can refer to a metallic conductor with a composite protective structure, used to simultaneously achieve mechanical protection and slow release of the labeled element. Boron carbide wear-resistant layers can refer to ceramic coatings with a hardness second only to diamond, used to prevent mechanical wear on the surface of steel rods. Graphene nanoparticle slow-release layers can refer to carbon nanoparticle composite materials with graphene as a carrier, used to control the continuous release rate of labeled elements.

[0035] As a specific example:

[0036] In a 400kA electrolytic cell, the cathode liner employs a gradient design with boron carbide mass fraction decreasing from 8% at the surface to 0.5% at the steel rod interface, with a reduction index coefficient set to 0.02 / mm. The steel rod is first deposited with a 20μm boron carbide layer via plasma spraying, followed by a 5-layer graphene film containing 15% nano-carbon particles coated using chemical vapor deposition. When the electrolyte penetrates to a depth of 5mm into the liner, the released boron concentration reaches 3ppm, with a detection limit of 0.5ppm as measured by X-ray fluorescence spectroscopy.

[0037] A gradient concentration distribution achieves a precise correlation between corrosion depth and the release amount of labeled elements, enabling early-stage, minute corrosion to be detected. The synergistic effect of the boron carbide wear-resistant layer and the graphene slow-release layer ensures both the mechanical strength of the steel rod and the continuous and stable release of labeled elements. The exponential concentration distribution significantly improves the monitoring sensitivity for deep corrosion, while the nano-carbon particle carrier optimizes the element release kinetics. The overall solution transforms traditional destructive detection into a non-invasive monitoring method that allows for real-time tracking.

[0038] In some implementations, the multi-dimensional sampling unit includes a spatial matrix sampler and a timing trigger. The spatial matrix sampler sets a three-dimensional sampling point array in the electrolytic cell, and the timing trigger switches to emergency sampling mode when the cell voltage fluctuation exceeds three percent.

[0039] Multi-dimensional sampling units can refer to sampling devices that integrate spatial and temporal dimensions, used for multi-parameter collaborative monitoring of the electrolytic cell's condition. Spatial matrix samplers can refer to mechanical sampling devices arranged according to geometric rules, used to acquire representative samples within the three-dimensional space of the electrolytic cell. Three-dimensional sampling point arrays can refer to sampling points uniformly distributed in the length, width, and depth directions, used for corrosion monitoring covering the entire electrolytic cell area. Timing triggers can refer to control modules based on voltage changes, used to activate enhanced monitoring programs under abnormal operating conditions. Cell voltage fluctuations can refer to the instantaneous changes in the potential difference between the two electrodes of the electrolytic cell, used to determine the stability of the electrolysis process. Emergency sampling modes can refer to emergency mechanisms that increase the sampling frequency, used to capture sudden corrosion events.

[0040] As a specific example:

[0041] In a 300kA electrolytic cell, a spatial matrix sampler is arranged in 7 columns longitudinally, 5 rows laterally, and 3 layers deep along the cell, totaling 105 sampling points. A timing trigger continuously monitors the cell voltage. When a voltage spike from 4.2V to 4.33V (fluctuation exceeding 3%) is detected, the sampling interval is shortened from 4 hours to 15 minutes, and all backup sampling points are activated. A robotic sampling arm prioritizes extracting 21 samples from three concentric rings around the voltage anomaly area, which are then transported to the spectral analysis chamber via pneumatic pipes at a speed of 5 m / s.

[0042] By employing 3D point matrix sampling, the limitations of traditional single-point monitoring are overcome, enabling three-dimensional tracking of corrosion development. A time-triggered mechanism provides the system with rapid response capabilities to sudden faults, and the linkage between voltage fluctuation thresholds and sampling modes effectively balances routine monitoring efficiency with emergency monitoring needs. The synergistic optimization of spatial and temporal dimensions significantly improves the probability of capturing localized corrosion and transient anomalies, providing dual protection for the safe operation of the electrolytic cell.

[0043] In some embodiments, the spectral analysis unit is arranged in parallel with an inductively coupled plasma atomic emission spectrometer and an X-ray fluorescence spectrometer. When the concentration detected by the X-ray fluorescence spectrometer exceeds 60% of the threshold, the inductively coupled plasma atomic emission spectrometer is automatically activated for fine measurement.

[0044] A spectral analysis unit can refer to a detection system integrating multiple spectral technologies, used to achieve multi-level precise analysis of labeled elements in electrolytic cells. Inductively coupled plasma atomic emission spectrometry (ICP-AES) refers to a precision instrument that uses high-temperature plasma to excite atomic emission spectra, used to achieve trace element detection at the part-in-a-million level. X-ray fluorescence spectrometry refers to a rapid detection device that uses X-rays to excite characteristic fluorescence of elements, used for rapid on-site screening within minutes.

[0045] As a specific example:

[0046] In the electrolysis plant, the spectral analysis unit employs a parallel cabinet design, with an X-ray fluorescence spectrometer (detection limit 5 ppm) installed on the left and an inductively coupled plasma atomic emission spectrometer (detection limit 0.1 ppm) on the right. When the X-ray fluorescence spectrometer detects that the boron carbide concentration in the electrolyte sample reaches 60% of the preset threshold of 3 ppm (i.e., 1.8 ppm), the system automatically introduces 3 mL of the sample into the plasma spectrometer through a switching valve, simultaneously initiating a 30-second plasma stabilization program under argon protection. Both systems share the same sample pretreatment module, ensuring the comparability of the detection data.

[0047] The parallel arrangement of dual spectrometers achieves an optimal balance between detection speed and accuracy, while rapid initial screening using X-ray fluorescence effectively reduces the ineffective operating losses of high-cost precision equipment. The threshold linkage mechanism avoids the risk of missed detections and significantly improves the utilization rate of detection resources. The shared sample processing module reduces the possibility of cross-contamination, providing a reliable technical guarantee for the rapid diagnosis of corrosion conditions in electrolytic cells.

[0048] In some implementations, the dynamic decision-making unit includes a baseline threshold setting module, an environmental compensation module, and a trend prediction module. The baseline threshold setting module adjusts the threshold in stages according to the service life of the electrolyzer. The environmental compensation module corrects the influence of temperature and electrolyte composition in real time. The trend prediction module establishes a concentration change rate model based on time series.

[0049] The dynamic decision-making unit can refer to an intelligent control core integrating adaptive algorithms, used to achieve closed-loop management of electrolytic cell corrosion monitoring. The baseline threshold setting module can refer to a threshold adjustment component configured according to the equipment aging pattern, used to match the monitoring needs of different life stages of the electrolytic cell. The environmental compensation module can refer to a multi-physics field coupling correction unit, used to eliminate the interference of temperature fluctuations and electrolyte composition changes on the detection results. The trend prediction module can refer to a time-series analysis engine based on historical data, used to predict corrosion development trends and provide early warnings. The service life phased approach can refer to dividing the electrolytic cell's life cycle into several characteristic intervals for implementing differentiated monitoring strategies. The concentration change rate model can refer to a mathematical formula describing the release rate of labeled elements, used to quantify the dynamic characteristics of the corrosion process.

[0050] As a specific example:

[0051] In the third year of operation (mid-term service phase) of the 300kA electrolyzer, the baseline threshold setting module adjusted the boron alarm threshold from 3 ppm during the new cell period to 4.5 ppm. The environmental compensation module receives 925°C temperature data from the thermocouple and data from the electrolyte LiF-AlF3 proportional sensor every 10 minutes, outputting a 7% threshold compensation coefficient through a multiple regression model. The trend prediction module, based on 72 sets of data collected over the past 30 days, establishes a second-derivative rate-of-change model, triggering a yellow alert when the predicted concentration growth rate exceeds 0.2 ppm per hour over the next 8 hours.

[0052] Precise monitoring of equipment throughout its entire lifecycle is achieved through segmented thresholds based on service duration, avoiding early missed alarms or late false alarms caused by fixed thresholds. Environmental compensation technology effectively eliminates interfering factors, ensuring that detection results accurately reflect the corrosion status. The trend prediction function overcomes the limitations of traditional lagging monitoring, providing a decision-making window for preventative maintenance. The three modules work together to form an intelligent closed loop of "monitoring-correction-prediction," significantly improving system reliability and economy.

[0053] In some implementations, the environmental compensation module performs the following calculation:

[0054]

[0055] Among them, T adj The corrected threshold is derived from the coupled calculation of the current baseline threshold T0 and the deviation of environmental parameters; ΔP i This represents the deviation value of the i-th operating condition parameter, derived from the difference between real-time sensor data and the standard value; α i The compensation coefficient for the i-th parameter is derived from historical data fitting; ΔC j This represents the change in concentration of the j-th electrolyte component, derived from the output of the spectral analysis unit; β jThe weights for the influence of components are derived from experimental calibration data; n and m represent the total number of operating parameters and component types, respectively.

[0056] The environmental compensation module can refer to a multi-parameter coupled threshold adjustment algorithm unit, used to dynamically correct the baseline threshold to adapt to real-time changes in the electrolyzer's operating conditions. The corrected threshold can refer to an alarm limit calibrated for environmental factors, used to improve the accuracy of leak warnings. The baseline threshold can refer to an initial warning value set according to the electrolyzer's design parameters, serving as the baseline input for environmental compensation calculations. Operating parameter deviations can refer to the offset of operating parameters such as pressure and temperature from standard values, used to quantify the degree of environmental anomalies. The compensation coefficient can refer to a parameter sensitivity weighting factor, used to adjust the influence of different operating parameters on the threshold. The electrolyte component concentration change can refer to the fluctuation range of components such as LiF and AlF3, used to reflect changes in the electrolyte's chemical state. The component influence weight can refer to the component corrosiveness contribution parameter, used to characterize the potential risk of different components eroding the tank.

[0057] This compensation algorithm overcomes the limitations of traditional fixed thresholds through multi-dimensional parameter coupling calculations, enabling the early warning mechanism to be environmentally adaptive. Dual correction of operating condition deviations and composition changes significantly reduces the false alarm rate caused by environmental fluctuations while ensuring sensitive detection of real risks. The weighting coefficient design based on historical data fitting achieves accurate quantification of the impact of different parameters, providing a dynamic protective barrier for the safe operation of the electrolyzer.

[0058] In some implementations, the compensation coefficient α_i is calculated using the following formula:

[0059]

[0060] Where, γ k σ is the k-th process characteristic coefficient, derived from the electrolytic cell design parameters; k / μ k θ represents the coefficient of variation of the k-th parameter, derived from three months of historical data statistics; k ω is the shape factor, derived from a material properties database; l The temperature influence factor is derived from the thermodynamic model; ΔT l This indicates the temperature difference between different areas, derived from infrared thermometry data.

[0061] The compensation coefficient can refer to the dynamic adjustment weighting factor of operating parameters, used to quantify the comprehensive influence of environmental variables on alarm thresholds. The process characteristic coefficient can refer to the structural characteristic parameters of the electrolytic cell, used to reflect the inherent influence of cell design on monitoring sensitivity. The coefficient of variation can refer to the ratio of parameter volatility to the average value, used to characterize the discrete characteristics of historical operating data. The shape factor can refer to the material corrosion morphology correction parameter, used to correlate material microscopic properties with macroscopic monitoring response. The temperature influence factor can refer to the thermal gradient conduction effect coefficient, used to assess the nonlinear effect of regional temperature differences on corrosion rates. The temperature difference can refer to the real-time temperature difference between different parts of the electrolytic cell, used to capture local overheating anomaly signals.

[0062] This calculation method achieves accurate modeling of the compensation coefficient through multi-dimensional feature fusion, while process characteristic coefficients ensure parameter adaptability for different cell types. The coefficient of variation incorporates dynamic features from historical data, enabling the compensation amount to adapt to the gradual changes in the electrolytic cell's operating state. The coupled calculation of temperature influence factors and regional temperature differences effectively captures the risk of abnormal corrosion caused by thermal stress, while the shape factor establishes a physical correlation between material properties and monitoring response. The overall algorithm significantly improves the environmental adaptability and reliability of the leak warning system.

[0063] In some embodiments, the spectral analysis unit locks the detection wavelength of boron at 209 nm and the detection peak of carbon at 0.28 nm, and establishes a mapping relationship between the concentration ratio of the two elements and the corrosion rate of the lining.

[0064] The boron detection wavelength (209 nm) refers to a specific optical window of the characteristic spectral lines of boron atoms, used for quantitative analysis of boron concentration changes in the electrolyte. The carbon detection peak position (0.28 nm) refers to the position of the characteristic X-ray diffraction peak of carbon atoms, used to capture the dissolution signal of the carbon lining material in the cathode. The two-element concentration ratio refers to the dynamic ratio of boron / carbon content, used to characterize the degree of electrolyte erosion of the cathode material. The lining corrosion rate mapping relationship refers to a mathematical model of element ratios and tank wear, used to convert spectral data into actual corrosion progress.

[0065] As a specific example:

[0066] During operation of the 280kA electrolyzer, the spectral analysis unit scanned the electrolyte sample every 30 minutes. When the boron spectral line intensity at 209nm reached 3500 counts and the carbon peak intensity at 0.28nm reached 800 counts, the calculated B / C concentration ratio was 4.37. Using a preset quadratic polynomial mapping model, the current cathode lining corrosion rate was determined to be 0.15 mm per hour, triggering a Level 2 warning signal.

[0067] High selectivity for elemental detection is achieved through characteristic wavelength locking, effectively avoiding interference from complex electrolyte components. Dual-element correlation analysis establishes a direct observation indicator of the corrosion process, offering greater reliability than single-element monitoring. The dynamic mapping model transforms spectral data into intuitive corrosion rates, providing a quantitative basis for tank condition assessment. The overall solution significantly improves the accuracy and timeliness of tank leakage early warning.

[0068] In some implementations, the trend prediction module triggers a level-two warning when it detects a concentration increase of more than 20% for three consecutive periods. The increase calculation includes the weighted difference between the current detected value and the average value of the previous three periods.

[0069] The trend prediction module can refer to an early warning triggering unit based on time-series data analysis, used to identify abnormal growth patterns in pollutant concentrations. Concentration increase can refer to the relative growth rate of changes in pollutant levels, used to quantify the accelerating degree of environmental risk. The detection cycle can refer to a fixed interval of data collection, used to establish a continuously comparable analytical benchmark. The average of the previous three periods can refer to the arithmetic mean of a sliding window of historical data, used to eliminate the impact of random fluctuations in a single detection. The weighted difference can refer to the correction deviation between the current value and the historical average, used to enhance the decision-making weight of recent data.

[0070] As a specific example:

[0071] In the electrolysis workshop's exhaust gas monitoring system, the trend prediction module acquires cyanide concentration data every 8 hours. When the measured values ​​for three consecutive periods were 12 ppm, 15 ppm, and 19 ppm, the average value of the previous three periods was 13.3 ppm (weighting coefficient of 0.5). The difference between the current measured value of 19 ppm and the weighted historical average of 16.65 ppm reached 14.1%. Because the increase in all three instances exceeded the 20% threshold, the system automatically triggered a Level 2 warning and initiated the emergency ventilation procedure.

[0072] Continuous verification over multiple cycles effectively avoids false alarms caused by transient interference, while weighted calculation enhances sensitivity to sudden trend changes. The introduction of historical average benchmarks establishes a dynamic reference system, making early warning triggering more environmentally adaptable. The two-tiered early warning system enables precise hierarchical management of risk response, allowing buffer time for handling measures.

[0073] In some embodiments, the electrolytic cell damage and leakage fault monitoring system further includes a digital twin visualization unit, which displays in real time a cloud map of the concentration distribution of marked elements, a threshold boundary line, and a predicted corrosion path. The concentration distribution cloud map is derived from the heat map data of the spectral analysis unit, and the predicted corrosion path is derived from the trend analysis results of the dynamic decision-making unit.

[0074] Digital twin visualization units can refer to graphical interface systems that map virtual and real data, used to dynamically display the evolution of corrosion states in electrolytic cells in three dimensions. Concentration distribution cloud maps can refer to gradient rendering maps of elemental spatial distribution, used to visually present the diffusion pattern of corrosion products in the electrolyte. Threshold boundary lines can refer to graphical markers of safe operating ranges, used to quickly determine whether current operating conditions exceed design tolerances. Predicted corrosion paths can refer to virtual erosion trajectories based on trend analysis, used to predict the development direction of lining damage. Thermal map data can refer to spatial matrices of spectral intensity, used to quantify the enrichment degree of elements in different regions. Dynamic decision-making units can refer to multi-source data fusion processors, used to generate time-series predictive models of corrosion evolution.

[0075] As a specific example:

[0076] In the monitoring of the 320kA electrolytic cell, the digital twin visualization unit updates its interface every 5 minutes. When the spectral analysis unit detects that the boron element thermogram value in the anode region reaches 420 counts / mm², the interface generates a red concentration cloud map and overlays a yellow threshold boundary line (set to 380 counts / mm²). 2 Based on six consecutive data increases, the dynamic decision-making unit generates a blue predicted path extending from the tank wall to the cathode on the three-dimensional model, allowing operators to reinforce the refractory layer in the C12 area in advance.

[0077] The fusion of virtual and real-world displays enables visualized tracking of the corrosion process, while concentration cloud maps make hidden chemical erosion visible. Threshold boundary lines provide intuitive safety benchmarks, and predicted paths empower maintenance personnel with proactive response capabilities. The collaborative work of dynamic decision-making and spectral analysis constructs a complete closed loop from data acquisition to decision support.

[0078] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0079] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this invention. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A fault monitoring system for electrolytic cell damage and leakage, characterized in that, This includes a marker element release unit, a multi-dimensional sampling unit, a spectral analysis unit, and a dynamic decision-making unit embedded in the cathode component; The marker element release unit implants non-metallic marker elements into the cathode liner and steel rod according to a preset distribution pattern; The multi-dimensional sampling unit periodically extracts electrolyte samples and transmits them to the spectral analysis unit; The spectral analysis unit detects the concentration of labeled elements and generates a heat map by using characteristic spectra; The dynamic decision-making unit performs graded early warnings based on the current concentration value, historical trends, and electrolyzer operating parameters.

2. The system according to claim 1, characterized in that, The marked element release unit includes a cathode liner with gradient concentration distribution and a double-coated steel rod. The concentration of boron carbide compounds in the cathode liner decreases exponentially along the depth direction, and the double coating of the steel rod includes an inner boron carbide wear-resistant layer and an outer graphene-coated nano-carbon particle slow-release layer.

3. The system according to claim 1, characterized in that, The multi-dimensional sampling unit includes a spatial matrix sampler and a timing trigger. The spatial matrix sampler sets a three-dimensional sampling point array in the electrolytic cell, and the timing trigger switches to emergency sampling mode when the cell voltage fluctuation exceeds three percent.

4. The system according to claim 1, characterized in that, The spectral analysis unit is configured with an inductively coupled plasma atomic emission spectrometer and an X-ray fluorescence spectrometer in parallel. When the concentration detected by the X-ray fluorescence spectrometer exceeds 60% of the threshold, the inductively coupled plasma atomic emission spectrometer is automatically activated for precise measurement.

5. The system according to claim 1, characterized in that, The dynamic decision-making unit includes a benchmark threshold setting module, an environmental compensation module, and a trend prediction module. The benchmark threshold setting module adjusts the threshold in stages according to the service life of the electrolyzer. The environmental compensation module corrects the influence of temperature and electrolyte composition in real time. The trend prediction module establishes a concentration change rate model based on time series.

6. The system according to claim 5, characterized in that, The environmental compensation module performs the following calculation: Among them, T adj The corrected threshold is derived from the coupled calculation of the current baseline threshold T0 and the deviation of environmental parameters; ΔP i This represents the deviation value of the i-th operating condition parameter, derived from the difference between real-time sensor data and the standard value; α i The compensation coefficient for the i-th parameter is derived from historical data fitting; ΔC j This represents the change in concentration of the j-th electrolyte component, derived from the output of the spectral analysis unit; β j The weights for the influence of components are derived from experimental calibration data; n and m represent the total number of operating parameters and component types, respectively.

7. The system according to claim 6, characterized in that, The compensation coefficient α_i is calculated using the following formula: Where, γ k σ is the k-th process characteristic coefficient, derived from the electrolytic cell design parameters; k / μ k θ represents the coefficient of variation of the k-th parameter, derived from three months of historical data statistics; k ω is the shape factor, derived from a material properties database; l The temperature influence factor is derived from the thermodynamic model; ΔT l This indicates the temperature difference between different areas, derived from infrared thermometry data.

8. The system according to claim 1, characterized in that, The spectral analysis unit locks the detection wavelength of boron at 209 nm and the detection peak of carbon at 0.28 nm, and establishes a mapping relationship between the concentration ratio of the two elements and the corrosion rate of the lining.

9. The system according to claim 5, characterized in that, The trend prediction module triggers a level-two warning when it detects a concentration increase of more than 20% for three consecutive periods. The increase calculation includes the weighted difference between the current detected value and the average value of the previous three periods.

10. The system according to claim 1, characterized in that, It also includes a digital twin visualization unit, which displays in real time a cloud map of the concentration distribution of marked elements, a threshold boundary line, and a predicted corrosion path. The concentration distribution cloud map is derived from the heat map data of the spectral analysis unit, and the predicted corrosion path is derived from the trend analysis results of the dynamic decision-making unit.

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