Electrolysis equipment monitoring method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to an electrolysis equipment monitoring method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: transmitting a detection optical signal to an optical fiber arranged in the electrolysis equipment in a spatial staggered winding manner, and acquiring a reflected optical signal returned after the detection optical signal passes through a plurality of fiber grating sensing modules; the plurality of fiber bragg grating sensing modules are arranged in the optical fiber; performing spectrum demodulation on the reflected light signal, and determining a plurality of corresponding actual reflection wavelengths in the reflected light signal; according to each actual reflection wavelength and a theoretical reflection wavelength corresponding to each fiber grating sensing module, determining the fiber grating sensing module to which each reflection light sub-signal belongs; based on the respective wavelength offset of each fiber grating sensing module, determining operation parameter information of the electrolysis equipment; and the wavelength offset is determined by the wavelength difference between the initial reflection wavelength and the actual reflection wavelength. The method can improve the monitoring effect of the electrolysis equipment.

Description

Technical Field

[0001] This application relates to the field of electrolysis technology, and in particular to an electrolysis equipment monitoring method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] With the rapid development of electrolysis technology, electrolysis equipment is being used more and more widely in key industrial scenarios such as hydrogen production and metal refining. To ensure the safe and efficient operation of electrolysis equipment, real-time monitoring of its internal parameters such as temperature, stress, and corrosion has become a core requirement.

[0003] In traditional technologies, conventional sensors are mostly based on the principle of electrical signal transmission and need to be connected to an external data acquisition system via metal wires or cables. However, the complex mechanical structure inside electrolysis equipment limits the installation space for sensors. For example, in narrow gaps in electrolytic cells, high-temperature molten salt areas, or near rotating electrodes, the rigid probes and cables of traditional sensors are difficult to lay out flexibly, and sometimes structural modifications to the equipment are required to complete the installation, resulting in poor monitoring performance of electrolysis equipment. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for monitoring electrolysis equipment that can improve the monitoring effect of electrolysis equipment, in order to address the above-mentioned technical problems.

[0005] In a first aspect, this application provides a method for monitoring electrolysis equipment, including:

[0006] A detection light signal is emitted into an optical fiber arranged in a spatially staggered manner inside the electrolysis equipment, and the reflected light signal returned after the detection light signal passes through multiple fiber Bragg grating sensing modules is acquired; the multiple fiber Bragg grating sensing modules are disposed in the optical fiber.

[0007] The reflected light signal is spectrally demodulated to determine multiple actual reflected wavelengths corresponding to the reflected light signal; the reflected light signal includes multiple reflected photon signals.

[0008] Based on the actual reflection wavelengths and the theoretical reflection wavelengths corresponding to each fiber Bragg grating sensing module, the fiber Bragg grating sensing module to which each reflected photon signal belongs is determined.

[0009] The operating parameters of the electrolysis equipment are determined based on the wavelength offset of each fiber Bragg grating sensing module; the wavelength offset is determined by the wavelength difference between the initial reflection wavelength and the actual reflection wavelength.

[0010] In one embodiment, determining the fiber grating sensing module to which each reflected photon signal belongs based on each actual reflection wavelength and the theoretical reflection wavelength corresponding to each fiber grating sensing module includes:

[0011] If any two actual reflection wavelengths among the actual reflection wavelengths do not satisfy the similarity condition, for each reflected photon signal, based on the wavelength difference between the actual reflection wavelength of the reflected photon signal and each theoretical reflection wavelength, candidate wavelengths whose wavelength differences satisfy the matching condition are determined from each of the theoretical reflection wavelengths.

[0012] Based on the fiber Bragg grating sensing module corresponding to the candidate wavelength, the fiber Bragg grating sensing module to which the reflected photon signal belongs is determined.

[0013] In one embodiment, determining the fiber Bragg grating sensing module to which the reflected photon signal belongs based on the candidate fiber Bragg grating sensing module corresponding to the candidate wavelength includes:

[0014] When there is only one candidate wavelength, the fiber grating sensing module corresponding to the candidate wavelength is determined as the fiber grating sensing module to which the reflected photon signal belongs.

[0015] When there are two candidate wavelengths, candidate modules with unmatched reflected photon signals are determined from each of the fiber Bragg grating sensing modules;

[0016] From the candidate wavelengths, determine the target wavelength that differs significantly from the theoretical reflection wavelength of the candidate module;

[0017] The fiber grating sensing module corresponding to the target wavelength is used to determine the fiber grating sensing module to which the reflected photon signal belongs.

[0018] In one embodiment, determining the fiber grating sensing module to which each reflected photon signal belongs based on each actual reflection wavelength and the theoretical reflection wavelength corresponding to each fiber grating sensing module includes:

[0019] If at least two of the actual reflected wavelengths satisfy the similarity condition, the sensing device type corresponding to the at least two actual reflected wavelengths is determined based on the matching relationship between the at least two actual reflected wavelengths and each of the theoretical reflected wavelengths.

[0020] Obtain the signal phase of the reflected photon signal corresponding to each of the at least two actual reflected wavelengths;

[0021] Based on the phase difference between the phases of each signal and the type of the sensing device, at least two reflected photon signals are identified to their respective fiber Bragg grating sensing modules; the signal phases of the reflected photon signals are different depending on the device position of the fiber Bragg grating sensing module.

[0022] In one embodiment, the electrolysis equipment includes multiple detection areas; the operating parameter information includes the regional parameter information of each detection area; and fiber optic segments of different sensing types are evenly distributed in the fiber optic segments within the range of each detection area.

[0023] The determination of the operating parameter information of the electrolysis equipment based on the wavelength offset of each of the fiber Bragg grating sensing modules includes:

[0024] For each detection area, determine the wavelength offset of each of the multiple fiber Bragg grating sensing modules deployed in the fiber segment within the detection area.

[0025] Based on the wavelength offset of each fiber Bragg grating sensing module in the detection area, the regional parameter information of the detection area is determined.

[0026] In one embodiment, the region parameter information includes parameter variation values ​​of multiple operating parameters; determining the region parameter information of the detection region based on the wavelength offset of each fiber Bragg grating sensing module in the detection region includes:

[0027] Obtain the parameter sensitivity coefficient of each fiber Bragg grating sensing module in the detection area corresponding to each of the operating parameters;

[0028] Decoupling is performed based on the sensitivity coefficients and wavelength offsets of each parameter to determine the parameter change values ​​corresponding to each of the operating parameters in the detection area.

[0029] In one embodiment, the method further includes:

[0030] For the interval region between two adjacent detection regions that meet the interval condition, information filling is performed on the interval region parameter information of the interval region according to the region parameter information of the two detection regions respectively;

[0031] Based on the location and parameter information of each detection area, and the location and parameter information of each interval area, a three-dimensional parameter model is constructed; the three-dimensional parameter model is used to characterize the parameter continuity state inside the electrolysis equipment.

[0032] Secondly, this application also provides an electrolysis equipment monitoring device, comprising:

[0033] The reflected light signal acquisition module is used to transmit a detection light signal to an optical fiber arranged in a spatially staggered manner inside the electrolysis equipment, and to acquire the reflected light signal returned after the detection light signal passes through multiple fiber Bragg grating sensing modules; the multiple fiber Bragg grating sensing modules are disposed in the optical fiber.

[0034] A spectral demodulation module is used to perform spectral demodulation on the reflected light signal to determine multiple actual reflected wavelengths corresponding to the reflected light signal; the reflected light signal includes multiple reflected photon signals.

[0035] The sensing module determination module is used to determine the fiber grating sensing module to which each reflected photon signal belongs based on the actual reflection wavelength and the theoretical reflection wavelength corresponding to each fiber grating sensing module.

[0036] The operating parameter information determination module is used to determine the operating parameter information of the electrolysis equipment based on the wavelength offset of each of the fiber Bragg grating sensing modules; the wavelength offset is determined by the wavelength difference between the initial reflection wavelength and the actual reflection wavelength.

[0037] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described above.

[0038] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the method described above.

[0039] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the method described above.

[0040] The aforementioned electrolysis equipment monitoring methods, devices, computer equipment, computer-readable storage media, and computer program products employ fiber Bragg grating sensing technology. By integrating multiple fiber Bragg grating sensing modules into a single flexible optical fiber, and utilizing the fiber's narrow diameter and bendability, it can easily traverse narrow channels, curved pipes, or complex electrode gaps within the electrolysis equipment. In-situ installation can be completed without structural modifications to the equipment, significantly reducing the difficulty and cost of sensor deployment. Through spectral demodulation technology, the actual reflected wavelengths of each sensing module in the reflected light signal are accurately identified, enabling distributed synchronous measurement of multiple parameters. Finally, based on the quantitative relationship between wavelength offset and equipment operating parameters, real-time feedback on changes in the internal state of the electrolytic cell can be provided, improving the monitoring effect of the electrolysis equipment. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is an application environment diagram of the electrolysis equipment monitoring method in one embodiment;

[0043] Figure 2 This is a flowchart illustrating a monitoring method for an electrolysis device in one embodiment;

[0044] Figure 3 This is a flowchart illustrating the electrolysis equipment monitoring method in another embodiment;

[0045] Figure 4 This is a structural block diagram of the monitoring device for an electrolysis equipment in one embodiment;

[0046] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0048] The electrolysis equipment monitoring method provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, server 102 communicates with electrolysis equipment 104 via a network. A data storage system can store the data that server 102 needs to process. The data storage system can be integrated onto server 102, or it can be located in the cloud or on other network servers. Server 102 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. Electrolysis equipment 104 is an industrial device that uses electrical energy to drive chemical reactions. By passing direct current into the electrolyte, substances undergo oxidation-reduction reactions on the electrode surfaces, thereby achieving the separation, purification, synthesis, or energy conversion of substances. For example, electrolysis equipment 104 may include an electrolytic cell, an electrolytic furnace, etc. Specifically, during the monitoring of the electrolysis equipment, the server 102 transmits detection light signals to the optical fibers arranged in a spatially staggered manner inside the electrolysis equipment 104, and acquires the reflected light signals returned after the detection light signals pass through multiple fiber Bragg grating sensing modules; the multiple fiber Bragg grating sensing modules are set in the optical fibers; the reflected light signals are spectrally demodulated to determine the multiple actual reflection wavelengths corresponding to the reflected light signals; the reflected light signals include multiple reflected photon signals; based on each actual reflection wavelength and the theoretical reflection wavelength corresponding to each fiber Bragg grating sensing module, the fiber Bragg grating sensing module to which each reflected photon signal belongs is determined; based on the wavelength offset of each fiber Bragg grating sensing module, the operating parameter information of the electrolysis equipment 104 is determined; the wavelength offset is determined by the wavelength difference between the initial reflection wavelength and the actual reflection wavelength.

[0049] In one exemplary embodiment, such as Figure 2 As shown, a method for monitoring electrolysis equipment is provided, which can be applied to... Figure 1 Taking server 102 as an example, the explanation includes the following steps S202 to S208. Wherein:

[0050] Step S202: A detection light signal is transmitted to an optical fiber arranged in a spatially staggered manner inside the electrolysis equipment, and the reflected light signal returned after the detection light signal passes through multiple fiber optic grating sensing modules is acquired.

[0051] Multiple fiber Bragg grating (FBG) sensing modules are embedded within optical fibers. Optical fiber is a flexible light transmission medium made of glass or plastic, which transmits light signals through total internal reflection, enabling long-distance transmission with low loss, and is commonly used in sensing and communication fields. FBG sensing modules are periodic refractive index modulation structures formed within the fiber core through ultraviolet etching. They reflect light signals of specific wavelengths, with each module having a unique theoretical reflection wavelength, used to sense environmental changes such as temperature and stress. The detection light signal is a light signal emitted by a broadband light source (such as a laser) covering a certain wavelength range, used to excite the reflection response of the FBG sensing modules. The reflected light signal is the light signal reflected back by each FBG sensing module after the detection light signal has passed through it, containing multiple reflected photon signals (corresponding to different modules).

[0052] Specifically, firstly, optical fibers are laid out in a spatially staggered manner along key monitoring paths inside the electrolysis equipment (such as the walls of the electrolytic cell, pipes, and near the electrodes) to ensure that the fiber Bragg grating sensing modules cover the areas to be monitored. The optical fibers must be heat-resistant and corrosion-resistant to adapt to the high-temperature and strong acid / alkali environment inside the electrolysis equipment. Next, a detection light signal is injected into the optical fiber through a broadband light source. The light signal propagates along the optical fiber and passes sequentially through each fiber Bragg grating sensing module. Each fiber Bragg grating sensing module reflects light of a specific wavelength, and the reflected light signal returns along the original path to the optical fiber entry end, where it is received by a photodetector. Since different modules have different theoretical reflection wavelengths, the reflected light signal contains multiple reflected photon signals, and each reflected photon signal corresponds to the reflection response of one module. Furthermore, taking the electrolysis equipment as an example, optical fibers can be arranged in a spatially staggered manner along the flow field area, plate gap, bipolar plate channel, diaphragm boundary, etc. of the electrolysis cell to form a three-dimensional monitoring network. Even if different types of fiber Bragg grating sensing modules are far apart along the length of the optical fiber, they can still be arranged in a spatially staggered manner so that different types of fiber Bragg grating sensing modules are arranged in the optical fiber segment within the range of each detection area.

[0053] Step S204: Perform spectral demodulation on the reflected light signal to determine the multiple actual reflected wavelengths corresponding to the reflected light signal.

[0054] The reflected light signal comprises multiple reflected photon signals. A reflected photon signal is a specific wavelength light signal reflected by a single fiber Bragg grating sensing module within the reflected light signal; it is the smallest unit for spectral demodulation. Spectral demodulation involves using a spectral analyzer to decompose the reflected light signal into intensity distributions of different wavelengths, thereby extracting the actual reflected wavelength of each fiber Bragg grating sensing module. The actual reflected wavelength is the light wavelength reflected by the fiber Bragg grating sensing module under current environmental conditions and may deviate from the theoretical reflected wavelength due to changes in temperature, stress, etc.

[0055] Specifically, the reflected light signal received by the photodetector is fed into a spectrum analyzer, which decomposes the reflected light signal into light intensity distribution curves at different wavelengths. Each peak on the curve corresponds to the actual reflected wavelength of a fiber Bragg grating sensing module. A peak detection algorithm extracts the wavelength value corresponding to each peak from the light intensity distribution curve as the actual reflected wavelength. Because environmental changes can cause variations in the refractive index of the sensing module, the actual reflected wavelength will deviate from the theoretical value; therefore, spectral demodulation is necessary to accurately capture these deviations.

[0056] Step S206: Based on the actual reflection wavelengths and the theoretical reflection wavelengths corresponding to each fiber Bragg grating sensing module, determine the fiber Bragg grating sensing module to which each reflected photon signal belongs.

[0057] The theoretical reflection wavelength is the preset reflection wavelength of the sensing module in its initial state (without external interference), which is determined by the manufacturing process.

[0058] Specifically, the actual reflected wavelength extracted in step S204 is compared with the theoretical reflected wavelength of each sensing module. By matching the actual reflected wavelength with the theoretical reflected wavelength, the fiber Bragg grating sensing module corresponding to each reflected photon signal can be determined. Optionally, if any two actual reflected wavelengths do not satisfy the similarity condition, for each reflected photon signal, based on the wavelength difference between the actual reflected wavelength and each theoretical reflected wavelength, candidate wavelengths whose wavelength differences satisfy the matching condition are determined from each theoretical reflected wavelength. Based on the fiber Bragg grating sensing module corresponding to the candidate wavelength, the fiber Bragg grating sensing module to which the reflected photon signal belongs is determined. Conversely, if at least two actual reflected wavelengths satisfy the similarity condition, based on the matching relationship between the at least two actual reflected wavelengths and each theoretical reflected wavelength, the sensing device type corresponding to the at least two actual reflected wavelengths is determined. The signal phases of the reflected photon signals corresponding to the at least two actual reflected wavelengths are obtained. Based on the phase difference between each signal phase and the sensing device type, the fiber Bragg grating sensing module to which the at least two reflected photon signals belong is determined.

[0059] Step S208: Determine the operating parameter information of the electrolysis equipment based on the wavelength offset of each fiber Bragg grating sensing module.

[0060] The wavelength offset, determined by the wavelength difference between the initial reflected wavelength and the actual reflected wavelength, is the difference between the actual and theoretical reflected wavelengths and is used to quantify the impact of environmental changes on the sensing module. Operating parameter information consists of physical quantities within the electrolysis equipment (such as temperature, stress, and liquid level), calculated through the mapping relationship between the wavelength offset and these physical quantities.

[0061] Specifically, the wavelength offset of a fiber Bragg grating (FBG) sensing module can reflect the environmental influences it experiences. Therefore, based on the wavelength offset of each FBG sensing module, the operating parameters of the electrolysis equipment can be determined. For example, the operating parameters of the entire electrolysis equipment can be analyzed, or the electrolysis equipment can be divided into multiple detection areas, and the operating parameters of each detection area can be analyzed.

[0062] The aforementioned electrolysis equipment monitoring method employs fiber Bragg grating sensing technology. By integrating multiple fiber Bragg grating sensing modules into a single flexible optical fiber, and utilizing the fiber's narrow diameter and bendability, it can easily traverse narrow channels, curved pipes, or complex electrode gaps within the electrolysis equipment. This allows for in-situ installation without structural modifications to the equipment, significantly reducing the difficulty and cost of sensor deployment. Furthermore, by using spectral demodulation technology to accurately identify the actual reflected wavelengths of each sensing module in the reflected light signal, distributed synchronous measurement of multiple parameters can be achieved. Finally, based on the quantitative relationship between wavelength offset and equipment operating parameters, real-time feedback on changes in the internal state of the electrolytic cell can be provided, improving the monitoring effect of the electrolysis equipment.

[0063] In an exemplary embodiment, determining the fiber Bragg grating sensing module to which each reflected photon signal belongs, based on each actual reflection wavelength and the theoretical reflection wavelength corresponding to each fiber Bragg grating sensing module, includes: when any two actual reflection wavelengths do not satisfy the similarity condition, for each reflected photon signal, determining candidate wavelengths whose wavelength differences satisfy the matching condition from each theoretical reflection wavelength based on the wavelength difference between the actual reflection wavelength of the reflected photon signal and each theoretical reflection wavelength; and determining the fiber Bragg grating sensing module to which the reflected photon signal belongs based on the fiber Bragg grating sensing module corresponding to the candidate wavelength.

[0064] The similarity condition is a set standard for judging whether two actual reflected wavelengths are similar, such as the difference between the two actual reflected wavelengths being less than a certain value. The candidate wavelength is a wavelength that meets the matching condition and is selected from the theoretical reflected wavelengths based on the wavelength difference between the actual reflected wavelength of the reflected photon signal and each theoretical reflected wavelength.

[0065] Specifically, when no two of the actual reflected wavelengths satisfy the similarity condition, it indicates a significant difference between the actual reflected wavelengths. This means that the fiber Bragg grating sensing modules corresponding to each actual reflected wavelength are of different types. Therefore, for each reflected photon signal, the wavelength difference between its actual reflected wavelength and each theoretical reflected wavelength can be calculated first. Then, from all theoretical reflected wavelengths, those whose wavelength differences satisfy the matching condition are selected as candidate wavelengths. Finally, based on the fiber Bragg grating sensing module corresponding to the candidate wavelength, it is determined which fiber Bragg grating sensing module the reflected photon signal belongs to. For example, satisfying the matching condition for wavelength differences can mean that the wavelength differences are small, satisfying a preset, small threshold.

[0066] In this embodiment, when there are significant differences in the actual reflected wavelengths, the fiber grating sensing module to which each reflected photon signal belongs can be accurately and quickly determined by wavelength difference matching, thereby improving the accuracy and efficiency of signal recognition.

[0067] In an exemplary embodiment, determining the fiber Bragg grating sensing module to which the reflected photon signal belongs based on the candidate fiber Bragg grating sensing module corresponding to the candidate wavelength includes: when there is only one candidate wavelength, determining the fiber Bragg grating sensing module corresponding to the candidate wavelength as the fiber Bragg grating sensing module to which the reflected photon signal belongs; when there are two candidate wavelengths, determining the candidate module that does not match the reflected photon signal from each fiber Bragg grating sensing module; determining the target wavelength that differs significantly from the theoretical reflection wavelength of the candidate module from each candidate wavelength; and determining the fiber Bragg grating sensing module to which the reflected photon signal belongs from the fiber Bragg grating sensing module corresponding to the target wavelength.

[0068] Among them, the candidate module is the fiber grating sensing module corresponding to the candidate wavelength.

[0069] Specifically, after determining the candidate wavelength based on the previous embodiment, if there is only one candidate wavelength, the fiber Bragg grating sensing module corresponding to this candidate wavelength is directly identified as the module to which the reflected photon signal belongs. If there are two candidate wavelengths, first, the candidate modules that have not yet matched a reflected photon signal are identified from all fiber Bragg grating sensing modules. Then, from these two candidate wavelengths, the target wavelength that differs significantly from the theoretical reflection wavelength of the candidate module is identified, and finally, the fiber Bragg grating sensing module corresponding to the target wavelength is identified as the module to which the reflected photon signal belongs. For example, if the actual reflected wavelength is 1300nm, and the determined candidate wavelengths are 1200nm and 1400nm, since these two candidate wavelengths have the same wavelength difference from the actual reflected wavelength, it is impossible to determine which candidate wavelength corresponds to the actual reflected wavelength. However, since the actual reflected wavelength and the theoretical reflected wavelength will always correspond one-to-one, we can find the candidate module that has not yet matched the reflected photon signal from all fiber optic grating sensing modules. The theoretical reflected wavelength of this candidate module is 1500nm. Therefore, the target wavelength that has the largest difference from the theoretical reflected wavelength of the candidate module is 1200nm. The fiber optic grating sensing module corresponding to the target wavelength of 1200nm is the module to which the reflected photon signal belongs.

[0070] In this embodiment, when the number of candidate wavelengths is not unique, this embodiment provides an effective differentiation method. By introducing unmatched candidate modules and comparing them with the actual reflected wavelengths of the candidate modules, the target wavelength that truly corresponds to the reflected photon signal can be accurately selected from multiple candidate wavelengths, further improving the accuracy of signal recognition in complex situations and reducing the possibility of misjudgment.

[0071] In an exemplary embodiment, determining the fiber Bragg grating sensing module to which each reflected photon signal belongs, based on each actual reflection wavelength and the theoretical reflection wavelength corresponding to each fiber Bragg grating sensing module, includes: when at least two actual reflection wavelengths satisfy similar conditions, determining the sensing device type corresponding to at least two actual reflection wavelengths based on the matching relationship between the at least two actual reflection wavelengths and each theoretical reflection wavelength; obtaining the signal phase of each reflected photon signal corresponding to the at least two actual reflection wavelengths; and determining the fiber Bragg grating sensing module to which each of the at least two reflected photon signals belongs based on the phase difference between each signal phase and the sensing device type.

[0072] The signal phase of the reflected photon signal varies depending on the device location of the fiber Bragg grating sensing module. Signal phase refers to the temporal phase information of the reflected photon signal; different locations of the fiber Bragg grating sensing module correspond to different reflected photon signal phases. The sensing device type is a classification of fiber Bragg grating sensing modules based on their detection functions, etc.

[0073] Specifically, when at least two actual reflected wavelengths satisfy the similarity condition, the sensing device type corresponding to these actual reflected wavelengths is first determined based on the matching relationship between these actual reflected wavelengths and each theoretical reflected wavelength. Since the signal phase of the reflected photon signal varies depending on the device location of the fiber Bragg grating sensing module, the signal phase of the reflected photon signal corresponding to each of these actual reflected wavelengths can be obtained. Based on the phase difference between each signal phase and the previously determined sensing device type, the fiber Bragg grating sensing module to which each of these reflected photon signals belongs is determined.

[0074] In this embodiment, when similar actual reflected wavelengths exist, the module to which the reflected photon signal belongs is determined by combining the sensor type and signal phase difference, effectively solving the problem of difficulty in distinguishing similar wavelengths and improving the reliability of signal recognition.

[0075] In one exemplary embodiment, the electrolysis equipment includes multiple detection zones; the operating parameter information includes the regional parameter information of each detection zone; fiber optic grating sensor modules of different sensing types are evenly distributed in the fiber optic segment within the range of each detection zone; the operating parameter information of the electrolysis equipment is determined based on the wavelength offset of each fiber optic grating sensor module, including: for each detection zone, determining the wavelength offset of each of the multiple fiber optic grating sensor modules distributed in the fiber optic segment within the range of the detection zone; and determining the regional parameter information of the detection zone based on the wavelength offset of each fiber optic grating sensor module in the detection zone.

[0076] The detection area is a designated region within the electrolysis equipment used to detect specific information. The area parameter information consists of various parameters related to the operation of the electrolysis equipment detected in each detection area.

[0077] Specifically, the electrolysis equipment is divided into multiple detection zones, and the operating parameter information includes the regional parameter information for each detection zone. Within the fiber optic segment of each detection zone, fiber Bragg grating (FBG) sensor modules of different sensing types are arranged. To determine the operating parameter information of the electrolysis equipment, for each detection zone, it is necessary to first determine the wavelength offset of each of the multiple FBG sensor modules arranged in the fiber optic segment of that detection zone. Then, the regional parameter information of that detection zone is determined based on these wavelength offsets. It can be understood that the optical fiber is three-dimensionally deployed inside the electrolysis equipment. That is, taking the electrolysis equipment as an example, the optical fiber can be spatially staggered along the flow field region, electrode gaps, bipolar channels, diaphragm boundaries, etc., forming a three-dimensional monitoring network. Therefore, even if different types of FBG sensor modules are far apart along the length of the optical fiber, the spatial staggered arrangement ensures that each detection zone has FBG sensor modules of different sensing types arranged in the fiber optic segment.

[0078] In this embodiment, by dividing the detection area within the electrolysis equipment and arranging different types of fiber Bragg grating sensing modules, the operating parameter information of different parts of the equipment can be obtained more accurately, providing detailed data support for a comprehensive understanding of the equipment's operating status.

[0079] In an exemplary embodiment, the regional parameter information includes parameter change values ​​of multiple operating parameters; based on the wavelength offset of each fiber Bragg grating sensing module in the detection area, the regional parameter information of the detection area is determined, including: obtaining the parameter sensitivity coefficient of each fiber Bragg grating sensing module in the detection area corresponding to each operating parameter; and performing decoupling processing according to each parameter sensitivity coefficient and each wavelength offset to determine the parameter change value corresponding to each operating parameter in the detection area.

[0080] The parameter sensitivity coefficient represents the sensitivity of the fiber Bragg grating sensing module to changes in different operating parameters. It is a fixed value determined in advance through experiments and calibration. Different sensing modules have different sensitivity coefficients for different parameters.

[0081] Specifically, to determine the regional parameter information of the detection area, the sensitivity coefficient of each fiber Bragg grating sensor module for each operating parameter in that area must first be obtained. This coefficient, obtained in advance through experiments and calibration, reflects the sensitivity of the sensor module to changes in different parameters. Next, decoupling processing is performed based on these sensitivity coefficients and the previously measured wavelength offsets of each fiber Bragg grating sensor module. Because the wavelength offset of a sensor module may be affected by multiple operating parameters simultaneously, decoupling allows the comprehensive information to be broken down, accurately determining the parameter changes corresponding to each operating parameter in the detection area.

[0082] In this embodiment, the introduction of parameter sensitivity coefficients and decoupling processing can accurately separate the parameter change values ​​corresponding to each operating parameter, solving the problem that it is difficult to accurately obtain the changes of each parameter because the output of a sensor module is affected by multiple parameters. This improves the accuracy and precision of parameter detection and provides strong support for a deeper understanding of the equipment's operating status.

[0083] In an exemplary embodiment, the electrolysis equipment monitoring method further includes: filling in the interval region parameter information of the interval region between two adjacent detection regions that meet the interval conditions, according to the region parameter information of each of the two detection regions; constructing a parameter three-dimensional model based on the region location and region parameter information of each detection region, the interval region location and interval region parameter information of each interval region; the parameter three-dimensional model is used to characterize the parameter continuity state inside the electrolysis equipment.

[0084] The interval region is the area existing between two adjacent detection regions. These regions may be formed because they were not included when the detection regions were divided. The interval condition is used to determine whether the conditions for subsequent interval region parameter information filling operations are met between two adjacent detection regions, such as the distance range between the two detection regions. Information filling involves reasonably inferring and supplementing the parameter information of the interval region based on the regional parameter information of the two adjacent detection regions, so that the parameter information of the interval region is complete. The parameter 3D model is a three-dimensional model constructed using computer modeling technology based on the position and parameter information of each detection region, as well as the position and filled parameter information of the interval region. It can intuitively display the parameter distribution inside the electrolysis equipment. Parameter continuity state: This refers to the fact that the parameters inside the electrolysis equipment do not exist in isolation between different regions, but rather exhibit a certain continuous change pattern. The parameter 3D model can reflect this continuity.

[0085] Specifically, considering the potential gaps between detection areas, the lack of parameter information in these gaps can affect the understanding of the overall parameter distribution within the equipment. Therefore, it is necessary to first process the gaps between two adjacent detection areas that meet the gap condition. Specifically, based on the regional parameter information of each of the two detection areas, appropriate methods, such as interpolation, are used to fill in the gap region's parameter information, making the gap region's parameter information complete. Then, based on the regional location of each detection area, the determined regional parameter information, and the gap region's location and the filled-in gap region's parameter information, a three-dimensional parameter model is constructed using computer modeling technology. This three-dimensional parameter model can display the parameter distribution inside the electrolysis equipment in a three-dimensional form, reflecting the continuity of the equipment's internal parameters.

[0086] In this embodiment, by filling in the parameter information of the interval area and constructing a three-dimensional parameter model, the distribution and changes of the internal parameters of the electrolysis equipment can be displayed more comprehensively and intuitively. This makes up for the deficiency of incomplete understanding of the overall status of the equipment caused by the lack of parameters in the interval area, which helps operators to understand the overall operating status of the equipment more clearly, discover abnormal areas in a timely manner, and provide a more effective reference for the optimized operation and maintenance of the equipment.

[0087] In a specific embodiment, the electrolysis equipment monitoring method is applied to the electrolytic cell and is mainly implemented based on the following internal parameter detection system of the electrolytic cell. This detection system primarily includes: a three-dimensional fiber optic grating sensor network, composed of multi-core or single-core FBGs (Fiber Bragg Grating sensors), which are spatially staggered and deployed along the flow field region, electrode gaps, bipolar plate channels, and diaphragm boundaries of the electrolytic cell to form a three-dimensional monitoring network; a high-precision demodulator and data acquisition module, which demodulates the reflected light signal to obtain the wavelength offsets corresponding to parameters such as temperature, pressure, strain, and gas concentration; a multi-parameter fusion algorithm module, which achieves accurate separation and solution of multiple physical quantities through an FBG wavelength demodulation model, a temperature / pressure / strain compensation algorithm, and a strain-based gas concentration inference algorithm; and a three-dimensional digital twin visualization software platform, which generates a cloud map of the internal parameter distribution of the electrolytic cell through real-time data mapping, interpolation algorithms, and a three-dimensional reconstruction model, i.e., a three-dimensional parameter model, including: a three-dimensional cloud map of the temperature field, a three-dimensional cloud map of the pressure field, a strain field distribution map, and a gas concentration distribution map (oxygen in hydrogen, hydrogen in oxygen). The safety early warning module, based on the acquired real-time parameters, enables functions such as leak sign monitoring, abnormal strain determination of membrane modules, early warning of local high temperature of fuel cell stack, and risk assessment of hydrogen-oxygen cross-permeation.

[0088] Specifically, the three-dimensional fiber Bragg grating network proposed in this embodiment adopts a staggered three-dimensional layout structure. By performing multi-dimensional path planning inside the electrolyzer, the optical fibers form composite paths in space, thereby constructing a three-dimensional sensing network covering the entire internal space of the electrolyzer. This structure can achieve high-density real-time monitoring of multiple key operating parameters within the electrolyzer without affecting the internal flow field and electrochemical processes. First, this embodiment precisely designs the three-dimensional paths of the optical fibers inside the electrolyzer, enabling the fibers to form staggered spatial layout trajectories at key locations such as the electrode gap region, diaphragm edge region, gas-liquid separation region, and dense gas evolution region. This creates a multi-level, segmented, and continuously staggered three-dimensional mesh structure in space. Second, multiple spatial bends and intersections are set in the path planning. These structural nodes not only realize the conversion of optical fiber path direction but also serve as spatial anchor points inside the electrolyzer, providing stable and high-precision three-dimensional positioning references, improving the geometric stability and spatial reconstruction accuracy of the overall measurement data. Furthermore, by deploying high-density detection areas at key fiber optic turning points, regions with significant flow field gradients, or areas of structural stress concentration, each detection area includes multiple fiber Bragg grating (FBG) sensor modules of different sensing types. This allows the FBG sensor modules to form an effective dense discrete lattice in three-dimensional space. Compared to traditional optical fibers deployed along a single direction or surface, the staggered structure of this invention significantly improves spatial resolution and avoids monitoring blind spots through three-dimensional cross-coverage. Simultaneously, the redundant cross-point distribution in multiple directions improves the stability of three-dimensional parameter inversion based on interpolation and optimization algorithms, enhancing noise suppression and decoupling capabilities. Moreover, multiple FBG sensor modules can be simultaneously deployed on the same fiber for the detection of temperature, pressure / strain, and gas concentration, achieving simultaneous measurement of multiple physical quantities through spectral demodulation and decoupling algorithms.

[0089] Furthermore, considering the significant coupling, large variation range, and complex spatial gradients of multiple parameters such as temperature, pressure, strain, and gas concentration within the electrolytic cell, a multi-physical quantity fusion measurement method based on the wavelength shift law of fiber Bragg gratings is proposed. This method utilizes the differences in the spectral response of fiber Bragg gratings under changes in temperature, axial strain, transverse pressure, and the refractive index of the surrounding medium. Through mathematical models and multi-parameter decoupling algorithms, it achieves high-precision separation and real-time acquisition of multiple physical quantities. First, based on the characteristics of fiber Bragg gratings (FBGs), a temperature-strain coupling model, a strain-pressure response model, and a model corresponding to refractive index change and gas concentration are constructed. Second, through a three-dimensional staggered fiber layout structure, temperature-type FBGs, pressure / strain-type FBGs, and refractive index-sensitive microstructure FBGs are arranged at different positions on each fiber. The differences in the spectral response of different types of FBGs provide a measurement basis for multi-parameter separation; simultaneously, multiple spatially adjacent or intersecting fiber Bragg grating sensing modules constitute a miniature local sensing array, enabling the local parameter gradients to be obtained through differential calculation, thus improving the stability of multi-physical quantity inversion. Finally, to improve the system's real-time performance and robustness, the above calculation process was processed online. Through algorithms such as sliding window filtering, noise suppression, and adaptive sensitivity compensation, real-time monitoring of multiple parameters at high sampling rates was achieved. Furthermore, when constructing a three-dimensional distribution cloud map (parameter three-dimensional model) of multiple physical quantities, a three-dimensional parameter field reconstruction method for electrolytic cells with complex internal structures was proposed based on the spatial coordinate system obtained from the staggered three-dimensional fiber optic layout and multi-point sensing data. This method enables spatial visualization of multiple key parameters within the electrolytic cell. First, a spatial grid model of the fiber optic network within the electrolytic cell was established by calibrating the three-dimensional coordinates of all fiber optic sensing modules. Since the fiber positions are path-planned and form clear three-dimensional curve trajectories, each fiber optic sensing module has unique spatial coordinates, allowing each detection area to form a dense, irregularly distributed set of sampling points. Second, based on the decoupled parameter data of multiple physical quantities, temperature, pressure, strain, and gas concentration values ​​were synchronously written into the point cloud structure at a given time step. Furthermore, a multi-level interpolation and mesh reconstruction method was adopted, including triangulation, voxel interpolation, and radial basis interpolation. By combining the regional parameter information of two adjacent detection areas that meet the interval conditions, a continuous, multi-dimensional three-dimensional parameter field was generated, thereby drawing a clear and intuitive three-dimensional cloud map.

[0090] In a specific embodiment, such as Figure 3 As shown, a method for monitoring electrolysis equipment is also provided, including:

[0091] Step S301: Transmit a detection light signal to the optical fiber arranged inside the electrolysis equipment in a spatially staggered manner, and acquire the reflected light signal returned after the detection light signal passes through multiple fiber optic grating sensing modules.

[0092] Step S302: Perform spectral demodulation on the reflected light signal to determine the multiple actual reflected wavelengths corresponding to the reflected light signal;

[0093] Multiple fiber Bragg grating sensing modules are disposed within the optical fiber; the reflected optical signal includes multiple reflected photon signals.

[0094] Step S303: When any two actual reflection wavelengths among the actual reflection wavelengths do not satisfy the similarity condition, for each reflected photon signal, based on the wavelength difference between the actual reflection wavelength of the reflected photon signal and each theoretical reflection wavelength, candidate wavelengths whose wavelength differences satisfy the matching condition are determined from each theoretical reflection wavelength.

[0095] Step S304: When there is only one candidate wavelength, the fiber grating sensing module corresponding to the candidate wavelength is determined as the fiber grating sensing module to which the reflected photon signal belongs.

[0096] Step S305: When there are two candidate wavelengths, determine the candidate module with unmatched reflected photon signal from each fiber grating sensing module.

[0097] Step S306: From each candidate wavelength, determine the target wavelength that differs significantly from the theoretical reflection wavelength of the candidate module;

[0098] Step S307: Determine the fiber grating sensing module to which the reflected photon signal belongs by the fiber grating sensing module corresponding to the target wavelength.

[0099] Step S308: If at least two actual reflection wavelengths among the actual reflection wavelengths satisfy similar conditions, determine the sensing device type corresponding to the at least two actual reflection wavelengths based on the matching relationship between the at least two actual reflection wavelengths and each theoretical reflection wavelength.

[0100] Step S309: Obtain the signal phase of the reflected photon signal corresponding to at least two actual reflected wavelengths;

[0101] Step S310: Based on the phase difference between the phases of each signal and the type of sensing device, determine the fiber grating sensing module to which each of the at least two reflected photon signals belongs.

[0102] The signal phase of the reflected photon signal varies depending on the device position of the fiber Bragg grating sensing module.

[0103] Step S311: For each detection area, determine the wavelength offset of each of the multiple fiber optic grating sensing modules deployed in the fiber optic segment within the detection area.

[0104] Step S312: Obtain the parameter sensitivity coefficient of each fiber grating sensing module in the detection area corresponding to each operating parameter.

[0105] Step S313: Decoupling is performed according to the sensitivity coefficients of each parameter and the wavelength offset to determine the parameter change values ​​corresponding to each operating parameter in the detection area.

[0106] The wavelength offset is determined by the wavelength difference between the initial reflection wavelength and the actual reflection wavelength.

[0107] Step S314: For the interval region between two adjacent detection regions that meet the interval condition, fill in the interval region parameter information of the interval region according to the region parameter information of each of the two detection regions.

[0108] Step S315: Based on the regional location and regional parameter information of each detection area, and the interval region location and interval region parameter information of each interval region, construct a three-dimensional parameter model;

[0109] Among them, the parametric three-dimensional model is used to characterize the parameter continuity state inside the electrolysis equipment.

[0110] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0111] Based on the same inventive concept, this application also provides an electrolysis equipment monitoring device for implementing the electrolysis equipment monitoring method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the electrolysis equipment monitoring device provided below can be found in the limitations of the electrolysis equipment monitoring method described above, and will not be repeated here.

[0112] In one exemplary embodiment, such as Figure 4 As shown, an electrolysis equipment monitoring device 400 is provided, including: a reflected light signal acquisition module 402, a spectrum demodulation module 404, a sensor module determination module 406, and an operating parameter information determination module 408, wherein:

[0113] The reflected light signal acquisition module 402 is used to transmit a detection light signal to an optical fiber arranged in a spatially staggered manner inside the electrolysis equipment, and to acquire the reflected light signal returned after the detection light signal passes through multiple fiber Bragg grating sensing modules; the multiple fiber Bragg grating sensing modules are disposed in the optical fiber.

[0114] The spectral demodulation module 404 is used to perform spectral demodulation on the reflected light signal to determine the multiple actual reflected wavelengths corresponding to the reflected light signal; the reflected light signal includes multiple reflected photon signals.

[0115] The sensing module determination module 406 is used to determine the fiber grating sensing module to which each reflected photon signal belongs based on each actual reflection wavelength and the theoretical reflection wavelength corresponding to each fiber grating sensing module.

[0116] The operating parameter information determination module 408 is used to determine the operating parameter information of the electrolysis equipment based on the wavelength offset of each fiber Bragg grating sensing module; the wavelength offset is determined by the wavelength difference between the initial reflection wavelength and the actual reflection wavelength.

[0117] In one exemplary embodiment, the sensing module determination module 406 includes:

[0118] The candidate wavelength determination unit is used to determine, for each reflected photon signal, a candidate wavelength whose wavelength difference satisfies the matching condition, based on the wavelength difference between the actual reflected wavelength of the reflected photon signal and each theoretical reflected wavelength, when no two actual reflected wavelengths satisfy the similarity condition.

[0119] The sensing module determination unit is used to determine the fiber grating sensing module to which the reflected photon signal belongs based on the fiber grating sensing module corresponding to the candidate wavelength.

[0120] In one exemplary embodiment, the sensing module determining unit is specifically used for:

[0121] When there is only one candidate wavelength, the fiber grating sensing module corresponding to the candidate wavelength is identified as the fiber grating sensing module to which the reflected photon signal belongs.

[0122] When there are two candidate wavelengths, candidate modules with unmatched reflected photon signals are identified from each fiber Bragg grating sensing module.

[0123] From the candidate wavelengths, the target wavelength that differs significantly from the theoretical reflection wavelength of the candidate module is determined;

[0124] The fiber grating sensing module corresponding to the target wavelength is used to determine the fiber grating sensing module to which the reflected photon signal belongs.

[0125] In one exemplary embodiment, the sensing module determination module 406 is further configured to:

[0126] If at least two actual reflection wavelengths satisfy similarity conditions, the sensing device type corresponding to the at least two actual reflection wavelengths is determined based on the matching relationship between the at least two actual reflection wavelengths and each theoretical reflection wavelength.

[0127] Obtain the signal phase of the reflected photon signal corresponding to at least two actual reflected wavelengths;

[0128] Based on the phase difference between each signal phase and the type of sensing device, at least two reflected photon signals are identified to their respective fiber Bragg grating sensing modules; the signal phases of the reflected photon signals are different depending on the device position of the fiber Bragg grating sensing module.

[0129] In an exemplary embodiment, the electrolysis equipment includes multiple detection zones; the operating parameter information includes the regional parameter information of each detection zone; and fiber Bragg grating sensing modules of different sensing types are evenly distributed in the fiber optic segment within the range of each detection zone. In this embodiment, the operating parameter information determination module 408 includes:

[0130] The wavelength offset determination unit is used to determine the wavelength offset of each of the multiple fiber optic grating sensing modules deployed in the fiber optic segment within the detection area for each detection area.

[0131] The region parameter information determination unit is used to determine the region parameter information of the detection area based on the wavelength offset of each fiber grating sensing module in the detection area.

[0132] In an exemplary embodiment, the region parameter information determination unit is specifically used for:

[0133] Obtain the parameter sensitivity coefficient of each fiber Bragg grating sensing module in the detection area for each operating parameter;

[0134] Decoupling is performed based on the sensitivity coefficients and wavelength offsets of each parameter to determine the parameter change values ​​corresponding to each operating parameter in the detection area.

[0135] In one exemplary embodiment, the electrolysis equipment monitoring device 400 further includes a region information filling module, specifically used for:

[0136] For the interval region between two adjacent detection regions that meet the interval condition, information filling is performed on the interval region parameter information of the interval region according to the region parameter information of each of the two detection regions;

[0137] Based on the location and parameter information of each detection area, and the location and parameter information of each interval area, a three-dimensional parameter model is constructed; the three-dimensional parameter model is used to characterize the parameter continuity state inside the electrolysis equipment.

[0138] Each module in the aforementioned electrolysis equipment monitoring device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0139] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a method for monitoring electrolytic equipment. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0140] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0141] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described above.

[0142] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0143] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described above.

[0144] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0145] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0146] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0147] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for monitoring electrolysis equipment, characterized in that, The method includes: A detection light signal is emitted into an optical fiber arranged in a spatially staggered manner inside the electrolysis equipment, and the reflected light signal returned after the detection light signal passes through multiple fiber Bragg grating sensing modules is acquired; the multiple fiber Bragg grating sensing modules are disposed in the optical fiber. The reflected light signal is spectrally demodulated to determine multiple actual reflected wavelengths corresponding to the reflected light signal; the reflected light signal includes multiple reflected photon signals. Based on the actual reflection wavelengths and the theoretical reflection wavelengths corresponding to each fiber Bragg grating sensing module, the fiber Bragg grating sensing module to which each reflected photon signal belongs is determined. The operating parameters of the electrolysis equipment are determined based on the wavelength offset of each fiber Bragg grating sensing module; the wavelength offset is determined by the wavelength difference between the initial reflection wavelength and the actual reflection wavelength.

2. The method according to claim 1, characterized in that, The step of determining the fiber grating sensing module to which each reflected photon signal belongs based on the actual reflection wavelength and the theoretical reflection wavelength corresponding to each fiber grating sensing module includes: If any two actual reflection wavelengths among the actual reflection wavelengths do not satisfy the similarity condition, for each reflected photon signal, based on the wavelength difference between the actual reflection wavelength of the reflected photon signal and each theoretical reflection wavelength, candidate wavelengths whose wavelength differences satisfy the matching condition are determined from each of the theoretical reflection wavelengths. Based on the fiber Bragg grating sensing module corresponding to the candidate wavelength, the fiber Bragg grating sensing module to which the reflected photon signal belongs is determined.

3. The method according to claim 2, characterized in that, The step of determining the fiber grating sensing module to which the reflected photon signal belongs based on the candidate fiber grating sensing module corresponding to the candidate wavelength includes: When there is only one candidate wavelength, the fiber grating sensing module corresponding to the candidate wavelength is determined as the fiber grating sensing module to which the reflected photon signal belongs. When there are two candidate wavelengths, candidate modules with unmatched reflected photon signals are determined from each of the fiber Bragg grating sensing modules; From the candidate wavelengths, determine the target wavelength that differs significantly from the theoretical reflection wavelength of the candidate module; The fiber grating sensing module corresponding to the target wavelength is used to determine the fiber grating sensing module to which the reflected photon signal belongs.

4. The method according to claim 2, characterized in that, The step of determining the fiber grating sensing module to which each reflected photon signal belongs based on the actual reflection wavelength and the theoretical reflection wavelength corresponding to each fiber grating sensing module includes: If at least two of the actual reflected wavelengths satisfy the similarity condition, the sensing device type corresponding to the at least two actual reflected wavelengths is determined based on the matching relationship between the at least two actual reflected wavelengths and each of the theoretical reflected wavelengths. Obtain the signal phase of the reflected photon signal corresponding to each of the at least two actual reflected wavelengths; Based on the phase difference between the phases of each signal and the type of the sensing device, at least two reflected photon signals are identified to their respective fiber Bragg grating sensing modules; the signal phases of the reflected photon signals are different depending on the device position of the fiber Bragg grating sensing module.

5. The method according to claim 1, characterized in that, The electrolysis equipment includes multiple detection zones; the operating parameter information includes the regional parameter information of each detection zone; and fiber optic segments within the range of each detection zone are uniformly equipped with fiber optic grating sensor modules of different sensing types. The determination of the operating parameter information of the electrolysis equipment based on the wavelength offset of each of the fiber Bragg grating sensing modules includes: For each detection area, determine the wavelength offset of each of the multiple fiber Bragg grating sensing modules deployed in the fiber segment within the detection area. Based on the wavelength offset of each fiber Bragg grating sensing module in the detection area, the regional parameter information of the detection area is determined.

6. The method according to claim 5, characterized in that, The regional parameter information includes the parameter variation values ​​of multiple operating parameters; determining the regional parameter information of the detection area based on the wavelength offset of each fiber Bragg grating sensing module in the detection area includes: Obtain the parameter sensitivity coefficient of each fiber Bragg grating sensing module in the detection area corresponding to each of the operating parameters; Decoupling is performed based on the sensitivity coefficients and wavelength offsets of each parameter to determine the parameter change values ​​corresponding to each of the operating parameters in the detection area.

7. The method according to claim 6, characterized in that, The method further includes: For the interval region between two adjacent detection regions that meet the interval condition, information filling is performed on the interval region parameter information of the interval region according to the region parameter information of the two detection regions respectively; Based on the location and parameter information of each detection area, and the location and parameter information of each interval area, a three-dimensional parameter model is constructed; the three-dimensional parameter model is used to characterize the parameter continuity state inside the electrolysis equipment.

8. A monitoring device for electrolysis equipment, characterized in that, The device includes: The reflected light signal acquisition module is used to transmit a detection light signal to an optical fiber arranged in a spatially staggered manner inside the electrolysis equipment, and to acquire the reflected light signal returned after the detection light signal passes through multiple fiber Bragg grating sensing modules; the multiple fiber Bragg grating sensing modules are disposed in the optical fiber. A spectral demodulation module is used to perform spectral demodulation on the reflected light signal to determine multiple actual reflected wavelengths corresponding to the reflected light signal; the reflected light signal includes multiple reflected photon signals. The sensing module determination module is used to determine the fiber grating sensing module to which each reflected photon signal belongs based on the actual reflection wavelength and the theoretical reflection wavelength corresponding to each fiber grating sensing module. The operating parameter information determination module is used to determine the operating parameter information of the electrolysis equipment based on the wavelength offset of each of the fiber Bragg grating sensing modules; the wavelength offset is determined by the wavelength difference between the initial reflection wavelength and the actual reflection wavelength.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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