CN115522227A - Electrolytic bath working state monitoring method, system, controller and medium - Google Patents
Electrolytic bath working state monitoring method, system, controller and medium Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 57
- 238000012544 monitoring process Methods 0.000 title claims abstract description 48
- 230000036541 health Effects 0.000 claims abstract description 98
- 239000011159 matrix material Substances 0.000 claims abstract description 91
- 238000001514 detection method Methods 0.000 claims abstract description 22
- 238000003745 diagnosis Methods 0.000 claims abstract description 21
- 230000005856 abnormality Effects 0.000 claims abstract description 15
- 230000002159 abnormal effect Effects 0.000 claims description 28
- 238000004590 computer program Methods 0.000 claims description 22
- 238000012163 sequencing technique Methods 0.000 claims description 6
- 229910052739 hydrogen Inorganic materials 0.000 abstract description 11
- 239000001257 hydrogen Substances 0.000 abstract description 11
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 abstract description 10
- 238000004519 manufacturing process Methods 0.000 abstract description 7
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- 238000002474 experimental method Methods 0.000 description 7
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- 238000009825 accumulation Methods 0.000 description 2
- 239000012528 membrane Substances 0.000 description 2
- 239000000523 sample Substances 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 239000003054 catalyst Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005868 electrolysis reaction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 150000002431 hydrogen Chemical class 0.000 description 1
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- 238000010248 power generation Methods 0.000 description 1
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- C—CHEMISTRY; METALLURGY
- C25—ELECTROLYTIC OR ELECTROPHORETIC PROCESSES; APPARATUS THEREFOR
- C25B—ELECTROLYTIC OR ELECTROPHORETIC PROCESSES FOR THE PRODUCTION OF COMPOUNDS OR NON-METALS; APPARATUS THEREFOR
- C25B15/00—Operating or servicing cells
- C25B15/02—Process control or regulation
- C25B15/023—Measuring, analysing or testing during electrolytic production
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/30—Hydrogen technology
- Y02E60/50—Fuel cells
Abstract
The invention discloses a method, a system, a controller and a computer readable storage medium for monitoring the working state of an electrolytic cell, belonging to the technical field of hydrogen production, wherein the method comprises the following steps: dividing the working load of the electrolytic cell in normal operation into a preset first number of load grades; constructing a health degree reference matrix of each small cell of the electrolytic cell according to the cell voltage of each small cell of the electrolytic cell in the preset first time period when the small cell of the electrolytic cell normally works under different load grades; and carrying out fault diagnosis and/or abnormality detection on each small cell of the electrolytic cell according to the health degree reference matrix so as to monitor the working state of the electrolytic cell. The full life cycle monitoring of the working state of the electrolytic cell is realized safely, accurately and at low cost.
Description
Technical Field
The invention relates to the technical field of hydrogen production, in particular to a method, a system, a controller and a computer readable storage medium for monitoring the working state of an electrolytic cell.
Background
The hydrogen energy has the advantages of low carbon, environmental protection, storability, transportability and the like, so the hydrogen energy gradually gains attention of the energy industry and becomes new power in the field of new energy power generation. An electrolytic cell in the hydrogen production device is a core conversion device for producing hydrogen, and real-time monitoring and fault diagnosis of the electrolytic cell are important for safe and efficient operation of a hydrogen production system. Many faults in the electrolysis cell can lead to variations in cell voltage, such as reduced catalyst activity, increased membrane electrode contact resistance, lower operating temperatures leading to increased cell voltage, perforation of the proton exchange membrane leading to reduced cell voltage, etc. Therefore, the cell voltage is detected and data are analyzed, and fault diagnosis and health analysis can be performed on the electrolytic cell.
However, to determine the cell voltage characteristic parameters at various faults under various workloads requires extensive experimentation. Due to the uniqueness of the hydrogen production system, accumulating data through conventional experimental methods is time and economic costly and may damage the electrolyzer causing danger. In addition, as the operating life of the electrolytic cell is accumulated, the performance index may change, which may cause the cell voltage characteristic parameter to change when a fault occurs, and the fault characteristic parameter accumulated in the early stage may no longer be suitable for fault diagnosis.
Disclosure of Invention
The invention mainly aims to provide a method for monitoring the working state of an electrolytic cell, and aims to solve the technical problem that the full life cycle monitoring on the working state of the electrolytic cell is difficult to carry out safely, accurately and at low cost in the prior art.
In order to achieve the purpose, the invention provides a method for monitoring the working state of an electrolytic cell, which comprises the following steps:
dividing the working load of the electrolytic cell in normal operation into a preset first number of load grades;
constructing a health degree reference matrix of each small cell of the electrolytic cell according to the cell voltage of each small cell of the electrolytic cell in the preset first time period when the small cell of the electrolytic cell normally works under different load grades;
and carrying out fault diagnosis and/or abnormality detection on each small cell of the electrolytic cell according to the health degree reference matrix so as to monitor the working state of the electrolytic cell.
Optionally, the step of constructing a health level reference matrix for each cell based on cell voltages at which each cell normally operates at different load levels for a predetermined first duration comprises:
extracting characteristic parameters of the cell voltage, wherein the characteristic parameters comprise time domain characteristic parameters and/or frequency domain characteristic parameters of the cell voltage;
determining a reasonable fluctuation range of the characteristic parameters when the small cells of the electrolytic cells work normally under different load grades within the preset first time period, wherein the reasonable fluctuation range at least comprises the maximum value and the minimum value of the characteristic parameters;
and constructing the health degree reference matrix according to the corresponding relation between the load grade and the reasonable fluctuation range.
Optionally, the time-domain characteristic parameter includes at least one of a maximum value, a minimum value, a standard deviation, a kurtosis, a skewness, a form factor, a peak factor, and a pulse factor; the frequency domain characteristic parameters at least comprise one of average frequency, barycentric frequency, frequency root mean square and frequency standard deviation.
Optionally, after the step of constructing the health reference matrix of each cell chamber, the method further comprises:
and executing a step of constructing a health degree reference matrix of each electrolytic cell according to cell voltages of each electrolytic cell in the preset first time period when the electrolytic cell cells normally work at different load levels so as to update the health degree reference matrix every other preset second time period, wherein the preset second time period is far longer than the preset first time period.
Optionally, the step of performing fault diagnosis on each cell chamber according to the health reference matrix includes:
collecting real-time cell voltage and real-time load grade of the small cell of the electrolytic cell, and extracting the characteristic parameters of the real-time cell voltage;
comparing the characteristic parameters of the real-time cell voltage with the reasonable fluctuation range corresponding to the real-time load grade;
if the characteristic parameters of the real-time cell voltage are within the reasonable fluctuation range, determining that the electrolytic cell has no fault;
and if the characteristic parameter of the real-time cell voltage is not in the reasonable fluctuation range, determining that the electrolytic cell has a fault.
Optionally, after the step of comparing the characteristic parameter of the real-time cell voltage with the reasonable fluctuation range corresponding to the real-time load level, the method further includes:
if the characteristic parameter of the real-time cell voltage is in the reasonable fluctuation range, determining that the corresponding state value of the characteristic parameter of the real-time cell voltage is a preset first state value;
if the characteristic parameter of the real-time cell voltage is larger than the maximum value of the reasonable fluctuation range, determining that the state value corresponding to the characteristic parameter of the real-time cell voltage is a preset second state value;
and if the characteristic parameter of the real-time cell voltage is smaller than the minimum value of the reasonable fluctuation range, determining that the state value corresponding to the characteristic parameter of the real-time cell voltage is a preset third state value.
Optionally, the step of performing fault diagnosis on each cell chamber according to the health reference matrix includes:
if the corresponding state value of the characteristic parameter of the real-time cell voltage is a preset second state value or a preset third state value, retrieving a fault database according to the real-time load level and the corresponding state value of the characteristic parameter of the real-time cell voltage;
if the real-time load grade and the corresponding state values of the characteristic parameters of the real-time cell voltage correspond to faults which have already occurred in the fault database, directly matching the fault type of the cell of the electrolytic cell;
and if the real-time load grade and the state value corresponding to the characteristic parameter of the real-time cell voltage correspond to a new fault which does not occur in the fault database, after determining a new fault type, newly adding the current fault type of the electrolytic cell in the fault database.
Optionally, the step of performing abnormality detection on each of the electrolyzer cells according to the health reference matrix includes:
and performing abnormity detection on the small cells of the electrolytic cell under each load grade by adopting a K proximity algorithm every other preset third time according to the health degree reference matrix.
Optionally, the step of performing anomaly detection on the electrolyzer cells at each load level by using a K-nearest neighbor algorithm every preset third time period according to the health degree reference matrix includes:
under the current load level, obtaining the average value of the characteristic parameters of the small chamber of the electrolytic cell as the characteristic parameters of the K-neighborhood algorithm;
calculating the cell distances between the current electrolytic cell cells and all the rest electrolytic cell cells based on the characteristic parameters of the K-neighborhood algorithm;
selecting a K value in the K proximity algorithm according to the total number of the small chambers of the electrolytic cell;
sequencing all cell distances corresponding to the current electrolytic cell cells, determining K-value electrolytic cell cells closest to the current electrolytic cell cells, and calculating the average distance of the cell distances between the current electrolytic cell cells and the K-value electrolytic cell cells closest to the current electrolytic cell cells;
calculating the average distance of all the rest small cells of the electrolytic cell;
and sorting the average distances of all the electrolytic cell small chambers from large to small, and determining that a second number of electrolytic cell small chambers which are arranged in the average distance ranking in the top are abnormal small chambers under the current load grade.
Optionally, after the step of determining that the electrolytic cell cells arranged in the average distance ranking in the first preset second number are abnormal cells at the current load level, the method further includes:
obtaining abnormal small chambers under each load grade;
and determining the electrolytic cell chambers which are abnormal chambers under the preset third number of load grades as chambers to be overhauled, and overhauling the chambers to be overhauled.
In addition, in order to achieve the above object, the present invention also provides an electrolytic cell operating condition monitoring system, including: the device comprises an electrolytic cell, a voltage acquisition device, a controller and a database;
the voltage acquisition device is used for acquiring cell voltage of each electrolytic cell in the electrolytic cell and transmitting the cell voltage to the controller;
the controller is used for storing the cell voltage into the database, calling the cell voltage from the database to extract characteristic parameters, construct a health degree reference matrix and update a fault database;
the database comprises the fault database, and is used for storing the cell voltage, the characteristic parameters and the health degree reference matrix.
Further, to achieve the above object, the present invention also provides a controller comprising: a memory, a processor and a computer program stored on said memory and executable on said processor, said computer program being configured to implement the steps of the method of monitoring the operating condition of an electrolytic cell as defined in any one of the preceding claims.
Furthermore, in order to achieve the above object, the present invention also provides a computer-readable storage medium, on which a computer program is stored, the computer program, when being executed by a processor, implementing the steps of the monitoring method for the operational state of the electrolytic cell according to any one of the above.
The embodiment of the invention provides a method, a system, a controller and a computer readable storage medium for monitoring the working state of an electrolytic cell, wherein the method comprises the following steps: dividing the working load of the electrolytic cell in normal operation into a preset first number of load grades; constructing a health degree reference matrix of each small cell of the electrolytic cell according to the cell voltage of each small cell of the electrolytic cell in the preset first time period when the small cell of the electrolytic cell normally works under different load grades; and carrying out fault diagnosis and/or abnormality detection on each small cell of the electrolytic cell according to the health degree reference matrix so as to monitor the working state of the electrolytic cell.
When the electrolytic cell works, the voltage data of the cells which normally work under different load levels are accumulated, and a health degree reference matrix is constructed for each cell. And comparing the real-time cell voltage characteristic parameters of the small cell of the electrolytic cell during working with the health degree reference matrix, judging whether a fault occurs or not, and establishing a fault database. The health degree reference matrix has self-adaptability, an independent health degree reference matrix is customized for each small electrolytic cell, individual difference among the small electrolytic cells can be adapted, and fault diagnosis and/or abnormal detection under the full load level can be realized. Therefore, a large number of experiments are not needed to determine the cell voltage characteristic parameters when various faults occur under various working loads, the time and economic cost of accumulating data of the hydrogen production system through an experimental method are avoided, and the electrolytic cell cannot be damaged and danger cannot be caused. In conclusion, the full life cycle monitoring of the working state of the electrolytic cell is realized safely, accurately and at low cost.
Drawings
Fig. 1 is a schematic structural diagram of an operating device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart showing an embodiment of a method for monitoring the operating condition of an electrolytic cell according to the present invention;
FIG. 3 is a schematic diagram of a health level reference matrix constructed according to an embodiment of the method for monitoring the operating condition of an electrolytic cell of the present invention;
FIG. 4 is a schematic diagram of fault diagnosis using a health level reference matrix according to an embodiment of the method for monitoring the operating condition of an electrolytic cell of the present invention;
FIG. 5 is a schematic diagram of an embodiment of a method for monitoring the operating condition of an electrolytic cell according to the present invention, in which a health criterion matrix is used for anomaly detection;
FIG. 6 is a schematic system diagram illustrating an embodiment of a method for monitoring the operating condition of an electrolytic cell according to the present invention;
FIG. 7 is a schematic view of an electrolytic cell structure according to an embodiment of the method for monitoring the operating condition of the electrolytic cell of the present invention.
Reference numerals and description:
an electrolytic cell 1; cell 1.1 of the electrolytic cell; an insulating fixing frame 2; and the voltage polling instrument sampling probes 3 correspond to the small chambers of the electrolytic cell one by one.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an operating device of a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the operation device may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to implement connection communication among these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001 described previously.
Those skilled in the art will appreciate that the configuration shown in FIG. 1 does not constitute a limitation of the operating device and may include more or fewer components than shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of storage medium, may include therein an operating system, a data storage module, a network communication module, a user interface module, and a computer program.
In the operating device shown in fig. 1, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the execution apparatus of the present invention may be provided in an execution apparatus that calls a computer program stored in the memory 1005 by the processor 1001 and performs the following operations:
dividing the working load of the electrolytic cell in normal operation into a preset first number of load grades;
constructing a health degree reference matrix of each small cell of the electrolytic cell according to the cell voltage of each small cell of the electrolytic cell in the preset first time period when the small cell of the electrolytic cell normally works under different load grades;
and carrying out fault diagnosis and/or abnormality detection on each small cell of the electrolytic cell according to the health degree reference matrix so as to monitor the working state of the electrolytic cell.
Further, the processor 1001 may call the computer program stored in the memory 1005, and also perform the following operations:
the step of constructing the health degree reference matrix of each electrolytic cell chamber according to the chamber voltage of each electrolytic cell chamber in the preset first time period when the electrolytic cell chambers normally work under different load grades comprises the following steps:
extracting characteristic parameters of the cell voltage, wherein the characteristic parameters comprise time domain characteristic parameters and/or frequency domain characteristic parameters of the cell voltage;
determining a reasonable fluctuation range of the characteristic parameters when the small cells of the electrolytic cells work normally under different load grades within the preset first time period, wherein the reasonable fluctuation range at least comprises the maximum value and the minimum value of the characteristic parameters;
and constructing the health degree reference matrix according to the corresponding relation between the load grade and the reasonable fluctuation range.
Optionally, the time-domain characteristic parameter includes at least one of a maximum value, a minimum value, a standard deviation, a kurtosis, a skewness, a form factor, a peak factor, and a pulse factor; the frequency domain characteristic parameters at least comprise one of average frequency, barycentric frequency, frequency root mean square and frequency standard deviation.
Further, the processor 1001 may call the computer program stored in the memory 1005, and also perform the following operations:
after the step of constructing the health degree reference matrix of each cell chamber, the method further comprises the following steps:
and executing the step of constructing the health degree reference matrix of each electrolytic cell according to the cell voltage of each electrolytic cell in the preset first time length when the electrolytic cell cells normally work under different load grades so as to update the health degree reference matrix every other preset second time length, wherein the preset second time length is far longer than the preset first time length.
Further, the processor 1001 may call the computer program stored in the memory 1005, and also perform the following operations:
the step of performing fault diagnosis on each cell chamber according to the health degree reference matrix comprises the following steps:
collecting real-time cell voltage and real-time load grade of the small cell of the electrolytic cell, and extracting the characteristic parameters of the real-time cell voltage;
comparing the characteristic parameters of the real-time cell voltage with the reasonable fluctuation range corresponding to the real-time load grade;
if the characteristic parameters of the real-time cell voltage are within the reasonable fluctuation range, determining that the electrolytic cell has no fault;
and if the characteristic parameter of the real-time cell voltage is not in the reasonable fluctuation range, determining that the electrolytic cell has a fault.
Further, the processor 1001 may call the computer program stored in the memory 1005, and also perform the following operations:
after the step of comparing the characteristic parameter of the real-time cell voltage with the reasonable fluctuation range corresponding to the real-time load level, the method further comprises the following steps:
if the characteristic parameter of the real-time cell voltage is in the reasonable fluctuation range, determining that the corresponding state value of the characteristic parameter of the real-time cell voltage is a preset first state value;
if the characteristic parameter of the real-time cell voltage is larger than the maximum value of the reasonable fluctuation range, determining that the state value corresponding to the characteristic parameter of the real-time cell voltage is a preset second state value;
and if the characteristic parameter of the real-time cell voltage is smaller than the minimum value of the reasonable fluctuation range, determining that the state value corresponding to the characteristic parameter of the real-time cell voltage is a preset third state value.
Further, the processor 1001 may call the computer program stored in the memory 1005, and also perform the following operations:
the step of performing fault diagnosis on each cell chamber according to the health degree reference matrix comprises the following steps:
if the state value corresponding to the characteristic parameter of the real-time cell voltage is a preset second state value or a preset third state value, retrieving a fault database according to the real-time load level and the state value corresponding to the characteristic parameter of the real-time cell voltage;
if the real-time load grade and the corresponding state values of the characteristic parameters of the real-time cell voltage correspond to faults which have already occurred in the fault database, directly matching the fault type of the cell of the electrolytic cell;
and if the real-time load grade and the state value corresponding to the characteristic parameter of the real-time cell voltage correspond to a new fault which does not occur in the fault database, after determining a new fault type, newly adding the current fault type of the electrolytic cell in the fault database.
Further, the processor 1001 may call the computer program stored in the memory 1005, and also perform the following operations:
the step of performing abnormality detection on each of the electrolytic cell cells based on the health level reference matrix includes:
and performing abnormity detection on the small electrolytic cell chambers under each load grade by adopting a K proximity algorithm every other preset third time according to the health degree reference matrix.
Further, the processor 1001 may call the computer program stored in the memory 1005, and also perform the following operations:
the step of performing anomaly detection on the small electrolytic cell chambers under each load grade by adopting a K proximity algorithm every other preset third time length according to the health degree reference matrix comprises the following steps of:
under the current load level, obtaining the average value of the characteristic parameters of the small chamber of the electrolytic cell as the characteristic parameters of the K-neighborhood algorithm;
calculating the cell distances between the current electrolytic cell cells and all the rest electrolytic cell cells based on the characteristic parameters of the K-neighborhood algorithm;
selecting a K value in the K proximity algorithm according to the total number of the small chambers of the electrolytic cell;
sequencing all cell distances corresponding to the current electrolytic cell, determining K-value electrolytic cell cells closest to the current electrolytic cell, and calculating the average distance of the cell distances between the current electrolytic cell cells and the K-value electrolytic cell cells closest to the current electrolytic cell cells;
calculating the average distance for all the rest small chambers of the electrolytic cell;
and sorting the average distances of all the electrolytic cell small chambers from large to small, and determining that a second number of electrolytic cell small chambers which are arranged in the average distance ranking in the top are abnormal small chambers under the current load grade.
Further, the processor 1001 may call the computer program stored in the memory 1005, and also perform the following operations:
after the step of determining that the electrolytic cell cells in the average distance ranking, which are arranged in the front of the preset second number, are abnormal cells at the current load level, the method further comprises the following steps:
obtaining abnormal cells under each load grade;
and determining the electrolytic cell chambers which are abnormal chambers under the preset third number of load grades as chambers to be overhauled, and overhauling the chambers to be overhauled.
An embodiment of the invention provides a method for monitoring the working state of an electrolytic cell, and referring to fig. 2, fig. 2 is a schematic flow chart of an embodiment of the method for monitoring the working state of the electrolytic cell.
In this embodiment, the method for monitoring the operating state of the electrolytic cell includes:
step S10: the working load of the electrolytic cell in normal operation is divided into a preset first number of load levels.
Referring to FIG. 7, FIG. 7 is a schematic view of an electrolytic cell structure according to an embodiment of the method for monitoring the operating condition of the electrolytic cell of the present invention. And collecting cell voltage second-level data of each electrolytic cell 1.1 fixed on the insulating fixing frame 2 in real time, and storing the cell voltage second-level data into a database. According to the power range of the electrolytic cell 1 in normal operation, dividing the working load into a first number of preset load levels: p1, P2, \ 8230, pn, each load grade comprises the upper limit and the lower limit of the power of the electrolytic cell under the grade, namely each load grade is a power range comprising the corresponding upper limit and lower limit of power, for example, the power range corresponding to the load grade P1 is 0-10KW, the power range corresponding to the load grade P2 is 10-20KW, and the like.
Step S20: and constructing a health degree reference matrix of each cell of the electrolytic cell according to the cell voltage of each cell of the electrolytic cell in the preset first time length when the cell normally works under different load grades.
For example, a corresponding health reference matrix may be constructed for each cell based on the historical cell voltages of each cell during normal operation at different load levels for a predetermined first duration.
Optionally, the step of constructing a health level reference matrix for each cell based on cell voltages at which each cell normally operates at different load levels for a predetermined first duration comprises:
extracting characteristic parameters of the cell voltage, wherein the characteristic parameters comprise time domain characteristic parameters and/or frequency domain characteristic parameters of the cell voltage;
determining a reasonable fluctuation range of the characteristic parameters when the small cells of the electrolytic cell normally work under different load levels within the preset first time period, wherein the reasonable fluctuation range at least comprises the maximum value and the minimum value of the characteristic parameters;
and constructing the health degree reference matrix according to the corresponding relation between the load grade and the reasonable fluctuation range.
Optionally, the time-domain characteristic parameter includes at least one of a maximum value, a minimum value, a standard deviation, a kurtosis, a skewness, a form factor, a peak factor, and a pulse factor; the frequency domain characteristic parameters at least comprise one of average frequency, barycentric frequency, frequency root mean square and frequency standard deviation.
Referring to fig. 3, fig. 3 is a schematic diagram of a health degree reference matrix constructed according to an embodiment of the method for monitoring the operating condition of the electrolytic cell. Under each load grade in normal work, respectively extracting time domain characteristic parameters of the cell voltage, such as a maximum value, a minimum value, a standard deviation, a kurtosis, a skewness, a wave form factor, a peak value factor, a pulse factor and the like; then, performing fast Fourier transform on the cell voltage, and extracting frequency domain characteristic parameters such as average frequency, center-of-gravity frequency, frequency root-mean-square, frequency standard deviation and the like; continuously monitoring the characteristic parameters within a preset first time period T1, and determining the maximum value and the minimum value of each characteristic parameter under each load grade when the system works normally, namely the reasonable fluctuation range of each characteristic parameter; if the fault occurs within a preset first time period T1, rejecting feature parameter data detected in the fault time period; according to the reasonable fluctuation range of the characteristic parameters, constructing a cell health degree reference matrix in the following form:
wherein, taking the maximum value reference under the P1 working load as an example, vmax _ r1_ P1_ min represents the minimum value of the maximum value reference in the cell voltage when the electrolyzer cell 1 normally works under the P1 working load within the preset first time length T1, vmax _ r1_ P1_ max represents the maximum value of the maximum value reference in the cell voltage when the electrolyzer cell 1 normally works under the P1 working load within the preset first time length T1,
represents the average value of the reference of the maximum value of the cell voltage when the cell 1 of the electrolytic cell is normally operated under the P1 operation load for a preset first time period T1. The reason why the minimum value, the maximum value and the average value of the maximum value reference appear is that the appearance parameters such as the cell voltage fluctuate to a small extent even if the electrolytic cell is in a normal stable operation state, and the corresponding statistical characteristic parameters such as the maximum value reference fluctuate to a small extent. In addition, due to P1 workload and the likeThe stage is also an interval and is not a fixed value, so that the maximum value reference has a corresponding change interval in normal operation.
Step S30: and carrying out fault diagnosis and/or abnormality detection on each small cell of the electrolytic cell according to the health degree reference matrix so as to monitor the working state of the electrolytic cell.
And then based on the health degree reference matrix, comparing the characteristic parameters of real-time cell voltage when the electrolytic cell works with the health degree reference matrix to judge whether a fault occurs, and/or detecting the electrolytic cell with abnormal working state by using a KNN (K-nearest neighbor) algorithm, thereby monitoring the working state of the electrolytic cell.
In the embodiment, the working load of the electrolytic cell is divided into a preset first number of load grades according to the power range of the electrolytic cell in normal operation; constructing a health degree reference matrix of the electrolytic cell according to cell voltages of all electrolytic cell cells in a preset first time period when the electrolytic cell cells normally work under different load grades; and carrying out fault diagnosis and/or abnormality detection on each small cell of the electrolytic cell according to the health degree reference matrix so as to monitor the working state of the electrolytic cell.
And when the electrolytic cell works, accumulating the voltage data of the cells which normally work under different load levels, and constructing a health degree reference matrix for each cell. And comparing the real-time cell voltage characteristic parameters of the small cell of the electrolytic cell during working with the health degree reference matrix, judging whether a fault occurs or not, and establishing a fault database. The health degree reference matrix has self-adaptability, and the independent health degree reference matrix is customized for each small cell of the electrolytic cell, so that the individual difference among the small cells of the electrolytic cell can be adapted, and fault diagnosis and/or abnormal detection under the full load level can be realized. Therefore, a large number of experiments are not needed to determine the cell voltage characteristic parameters when various faults occur under various working loads, the time and economic cost of accumulating data of the hydrogen production system through an experimental method are avoided, and the electrolytic cell cannot be damaged and danger cannot be caused. In conclusion, the full life cycle monitoring of the working state of the electrolytic cell is realized safely, accurately and at low cost.
Optionally, after the step of constructing the health reference matrix of each cell chamber, the method further comprises:
and executing the step of constructing the health degree reference matrix of each electrolytic cell according to the cell voltage of each electrolytic cell in the preset first time length when the electrolytic cell cells normally work under different load grades so as to update the health degree reference matrix every other preset second time length, wherein the preset second time length is far longer than the preset first time length.
In the case that the cell voltage characteristic parameters are changed when faults occur due to the fact that performance indexes of the cells are likely to change and attenuate along with the accumulation of the working years of the electrolytic cell, the working state of the electrolytic cell can be monitored without using the fault characteristic parameters accumulated in the early stage, and the performance attenuation and the health degree reference change caused by the accumulation of the working years of the cells of the electrolytic cell are adapted in a mode of updating the health degree reference matrix of each cell of the electrolytic cell regularly and automatically, so that the accuracy of detection of the working state of the electrolytic cell is improved. And as time goes on, the health degree reference matrix is continuously updated, a fault database is enriched, and the working state monitoring of the self-adaptive electrolytic cell with the full life cycle is realized. That is, the health level reference matrix proposed in this embodiment can be updated autonomously, and the health level reference change of the cell of the electrolytic cell is tracked in real time, thereby realizing the fault diagnosis in the whole life cycle. Continuously accumulating data when the small electrolytic cell works, automatically constructing and updating the health degree reference matrix and the fault database without stopping the experiment, and avoiding potential loss caused by the experiment.
Specifically, the health degree reference matrix of the electrolytic cell cells is updated every other preset second time length T2, wherein the preset second time length T2> is the preset first time length T1, the preset second time length T2 and the preset first time length T1 can be determined by designers or operation and maintenance personnel according to experience, and if the preset second time length T2 is about one year > is about one month or about two months, the historical health degree reference matrix of each electrolytic cell is stored in the health degree reference database. Typically, hydrogen plants are designed for years of use over ten years, so that the health benchmark matrix for the electrolyzer cells need not be updated too frequently.
Optionally, the step of performing fault diagnosis on each cell chamber according to the health reference matrix includes:
collecting real-time cell voltage and real-time load grade of the small cell of the electrolytic cell, and extracting the characteristic parameters of the real-time cell voltage;
comparing the characteristic parameters of the real-time cell voltage with the reasonable fluctuation range corresponding to the real-time load grade;
if the characteristic parameters of the real-time cell voltage are in the reasonable fluctuation range, determining that the cell of the electrolytic cell has no fault;
and if the characteristic parameter of the real-time cell voltage is not in the reasonable fluctuation range, determining that the cell of the electrolytic cell has a fault.
Referring to fig. 4, fig. 4 is a schematic diagram of fault diagnosis by using a health level reference matrix according to an embodiment of the method for monitoring the operating condition of the electrolytic cell of the present invention. And acquiring real-time cell voltage and real-time load grade of the cell of the electrolytic cell in real time, extracting characteristic parameters of the real-time cell voltage, and comparing the characteristic parameters with reasonable fluctuation ranges of the characteristic parameters corresponding to the real-time load grade in the health degree reference matrix to obtain state values of the characteristic parameters of the real-time cell voltage.
Optionally, after the step of comparing the characteristic parameter of the real-time cell voltage with the reasonable fluctuation range corresponding to the real-time load level, the method further includes:
if the characteristic parameter of the real-time cell voltage is in the reasonable fluctuation range, determining that the corresponding state value of the characteristic parameter of the real-time cell voltage is a preset first state value;
if the characteristic parameter of the real-time cell voltage is larger than the maximum value of the reasonable fluctuation range, determining that the state value corresponding to the characteristic parameter of the real-time cell voltage is a preset second state value;
and if the characteristic parameter of the real-time cell voltage is smaller than the minimum value of the reasonable fluctuation range, determining that the state value corresponding to the characteristic parameter of the real-time cell voltage is a preset third state value.
For a certain characteristic parameter of the real-time cell voltage: if the fluctuation range does not exceed the corresponding reasonable fluctuation range in the health degree reference matrix, the state value is a preset first state value: 0; if the maximum value of the corresponding reasonable fluctuation range in the health degree reference matrix is exceeded and the characteristic parameter deviates from the health degree reference, the state value is a preset second state value: 1; if the characteristic parameter is lower than the minimum value of the corresponding reasonable fluctuation range in the health degree reference matrix and deviates from the health degree reference, the state value is a preset third state value: -1.
Optionally, the step of performing fault diagnosis on each cell chamber according to the health reference matrix includes:
if the corresponding state value of the characteristic parameter of the real-time cell voltage is a preset second state value or a preset third state value, retrieving a fault database according to the real-time load level and the corresponding state value of the characteristic parameter of the real-time cell voltage;
if the real-time load grade and the corresponding state values of the characteristic parameters of the real-time cell voltage correspond to faults which have already occurred in the fault database, directly matching the fault type of the cell of the electrolytic cell;
and if the real-time load grade and the state value corresponding to the characteristic parameter of the real-time cell voltage correspond to a new fault which does not occur in the fault database, after determining a new fault type, newly adding the current fault type of the electrolytic cell in the fault database.
If the state value of a certain characteristic parameter of the real-time cell voltage is a preset second state value: 1 or preset third state value: and 1, recording the fault characteristics of the electrolytic cell chamber at the moment, including the working load grade and the corresponding state value, forming a fault record, and then reporting the fault state and stopping the electrolytic cell. A certain fault record format is as follows:
and then retrieving a fault database according to the working load grade in the fault record table and the characteristic parameter corresponding state value of the real-time cell voltage: if the fault which has occurred and the fault characteristics are contained in the fault database, the fault type of the current small chamber of the electrolytic cell can be directly matched; if the fault which does not occur and the fault characteristics are not contained in the fault database, manually checking a new fault reason, determining a new fault type, and newly adding and recording the fault type of the new fault in the fault database.
Optionally, the step of performing abnormality detection on each of the electrolyzer cells according to the health reference matrix includes:
and performing abnormity detection on the small cells of the electrolytic cell under each load grade by adopting a K proximity algorithm every other preset third time according to the health degree reference matrix.
Referring to fig. 5, fig. 5 is a schematic diagram of abnormality detection using a health level reference matrix according to an embodiment of the method for monitoring the operating condition of an electrolytic cell of the present invention. In the embodiment, the K-proximity algorithm is used to detect the cells of the electrolytic cell with abnormal working conditions based on the health degree reference matrix, that is, the K-proximity algorithm is used to detect the cells with abnormal working conditions at each load level every preset third time period T3 according to the established health degree reference matrix. The K-neighborhood algorithm can comprehensively consider the mutual influence among the voltage characteristic parameters of the small chambers of the electrolytic cell, and screen out the small chambers of the electrolytic cell with abnormal working state for key overhaul. The preset third time length T3> is larger than the preset first time length T1, the value of the preset third time length T3 may be equal to or different from the value of the preset second time length T2, and the specific value of the preset third time length T3 may be determined by a designer or an operation and maintenance worker according to experience, which is not limited herein.
Optionally, the step of performing anomaly detection on the cell compartments under each load class by using a K-nearest neighbor algorithm every preset third time period according to the health degree reference matrix includes:
under the current load level, obtaining the average value of the characteristic parameters of the small chamber of the electrolytic cell as the characteristic parameters of the K-neighborhood algorithm;
calculating the cell distances between the current electrolytic cell and all the rest electrolytic cell cells based on the characteristic parameters of the K-neighborhood algorithm;
selecting a K value in the K proximity algorithm according to the total number of the small chambers of the electrolytic cell;
sequencing all cell distances corresponding to the current electrolytic cell, determining K-value electrolytic cell cells closest to the current electrolytic cell, and calculating the average distance of the cell distances between the current electrolytic cell cells and the K-value electrolytic cell cells closest to the current electrolytic cell cells;
calculating the average distance for all the rest small chambers of the electrolytic cell;
and sequencing the average distances of all the electrolytic cell cells from large to small, and determining a preset second number of electrolytic cell cells arranged in the average distance ranking as abnormal cells under the current load level.
Specifically, a) at the load level P1, the average value of the cell voltage characteristic parameters of each cell of the electrolytic cell is taken
Characteristic parameters in the K-neighbor algorithm;
b) And selecting the K value in the K-adjacent algorithm according to the total number of the cells of the electrolytic cell. Assuming a total of 100 cell chambers, K =5; the reason why the value of K is usually small is that when K is small, when the cell distance between one cell and other cells is measured and the average distance is calculated, only the nearest points close to the current cell are considered, so that the interference of the cell with a larger difference between the working state and the current cell or an abnormal cell can be avoided. Assuming K =99, the distances between the current cell and all other cell cells are taken into account when calculating the average distance at this time. If a certain electrolytic cell chamber is in a completely abnormal state and is far away from the current electrolytic cell chamber, the calculated average distance is interfered;
c) The cell distances of the current cell and all the remaining cell cells were calculated as D1_2_p1, D1_3_p1, D1_4_p1, \8230;, D1_100_p1, respectively, wherein
d) Sequencing D1_2_p1, D1_3_p1, D1_4_p1, \8230, D1_100 _p1from low to high, finding the 5 cell compartments nearest to the cell compartment, assuming cell compartment 3, cell compartment 8, cell compartment 9, cell compartment 13, and cell compartment 24;
e) The average distance between the current cell (cell 1) and the cell cells 3, 8, 9, 13, 24 is calculated, i.e.:
D1_p1＝(D1_3_p1+D1_8_p1+D1_9_p1+D1_13_p1+D1_24_p1)/5；
f) Repeating steps c) -e) for the remaining cell compartments, the average distance between each cell compartment and the 5 cell compartments closest to itself then being: d1_ p1, D2_ p1, D3_ p1, \ 8230;, D100_ p1;
g) Sorting D1_ p1, D2_ p1, D3_ p1, \8230; and D100_ p1 from high to low, and determining that the electrolytic cell cells ranked in the top in all average distances are preset in a second number, for example, selecting the first 10% of the electrolytic cell cells to be marked as abnormal cells under the current load level. Because: if the average distance of an electrolytic cell is larger, it indicates that it is farther from the nearest 5 points of proximity, it indicates that it is less similar to other electrolytic cell, or that its operating state is deviated from other electrolytic cell, and it may be in an abnormal state.
Optionally, after the step of determining that the electrolytic cell cells in the average distance ranking that are arranged in the top preset second number are abnormal cells at the current load level, the method further includes:
obtaining abnormal small chambers under each load grade;
and determining the electrolytic cell chambers which are abnormal chambers under the preset third number of load grades as chambers to be overhauled, and overhauling the chambers to be overhauled.
Repeating the above steps a) -g) for the remaining load levels. And acquiring an abnormal cell list under each load grade, and selecting the electrolytic cell cells which appear for multiple times and appear with a preset third number of times of abnormality (namely the electrolytic cell cells which appear with abnormality under multiple load grades) from the abnormal cell list for maintenance.
In addition, an embodiment of the present invention further provides a monitoring system for an operating state of an electrolytic cell, where the monitoring system for an operating state of an electrolytic cell includes: the device comprises an electrolytic cell, a voltage acquisition device, a controller and a database;
the voltage acquisition device is used for acquiring cell voltages of all small cells of the electrolytic cell in the electrolytic cell and transmitting the cell voltages to the controller;
the controller is used for storing the cell voltage into the database, calling the cell voltage from the database to extract characteristic parameters, construct a health degree reference matrix and update a fault database;
the database comprises the fault database, and the database is used for storing the cell voltage, the characteristic parameters and the health degree reference matrix.
Referring to FIG. 6, FIG. 6 is a system diagram of an embodiment of the method for monitoring the operating condition of the electrolytic cell according to the present invention. The voltage acquisition device acquires cell voltages of all small cells of the electrolytic cell in the electrolytic cell through the voltage acquisition device sampling probe 3 which is in one-to-one correspondence with the small cells of the electrolytic cell and is shown in fig. 7, the voltage acquisition device uploads the acquired cell voltage data to the controller, the controller stores the cell voltage data in the database, the controller calls the data from the database for analysis, and the cell voltage characteristic parameters, the health degree reference matrix and the fault database which are generated after the analysis are stored in the database.
In addition, an embodiment of the present invention further provides a controller, where the controller includes: a memory, a processor and a computer program stored on said memory and executable on said processor, said computer program being configured to implement the steps of the method of monitoring the operating condition of an electrolytic cell as defined in any one of the preceding claims.
In addition, the embodiment of the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is used for realizing the steps of the monitoring method for the working state of the electrolytic cell as described in any one of the above when being executed by a processor.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or system comprising the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the description of the foregoing embodiments, it is clear to those skilled in the art that the method of the foregoing embodiments may be implemented by software plus a necessary general hardware platform, and certainly may also be implemented by hardware, but in many cases, the former is a better implementation. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes performed by the present invention or directly or indirectly applied to other related technical fields are also included in the scope of the present invention.
Claims (13)
1. The method for monitoring the working state of the electrolytic cell is characterized by comprising the following steps of:
dividing the working load of the electrolytic cell in normal operation into a preset first number of load grades;
constructing a health degree reference matrix of each small cell of the electrolytic cell according to the cell voltage of each small cell of the electrolytic cell in the preset first time period when the small cell of the electrolytic cell normally works under different load grades;
and carrying out fault diagnosis and/or abnormality detection on each small cell of the electrolytic cell according to the health degree reference matrix so as to monitor the working state of the electrolytic cell.
2. The method of monitoring the operating conditions of an electrolytic cell according to claim 1, wherein said step of constructing a health reference matrix for each cell based on cell voltages at which each cell normally operates at different said load levels for a predetermined first duration comprises:
extracting characteristic parameters of the cell voltage, wherein the characteristic parameters comprise time domain characteristic parameters and/or frequency domain characteristic parameters of the cell voltage;
determining a reasonable fluctuation range of the characteristic parameters when the small cells of the electrolytic cells work normally under different load grades within the preset first time period, wherein the reasonable fluctuation range at least comprises the maximum value and the minimum value of the characteristic parameters;
and constructing the health degree reference matrix according to the corresponding relation between the load grade and the reasonable fluctuation range.
3. The method of claim 2, wherein the time-domain characteristic parameters include at least one of a maximum, a minimum, a standard deviation, a kurtosis, a skewness, a form factor, a crest factor, and a pulse factor; the frequency domain characteristic parameters at least comprise one of average frequency, barycentric frequency, frequency root mean square and frequency standard deviation.
4. The method of monitoring the operating conditions of an electrolytic cell according to claim 1, wherein said step of constructing a baseline matrix of health for each cell further comprises:
and executing the step of constructing the health degree reference matrix of each electrolytic cell according to the cell voltage of each electrolytic cell in the preset first time length when the electrolytic cell cells normally work under different load grades so as to update the health degree reference matrix every other preset second time length, wherein the preset second time length is far longer than the preset first time length.
5. The method of monitoring the operating conditions of an electrolytic cell according to claim 2, wherein said step of diagnosing a fault in each of said cells based on said baseline of health comprises:
collecting real-time cell voltage and real-time load grade of the small cell of the electrolytic cell, and extracting the characteristic parameters of the real-time cell voltage;
comparing the characteristic parameters of the real-time cell voltage with the reasonable fluctuation range corresponding to the real-time load grade;
if the characteristic parameters of the real-time cell voltage are in the reasonable fluctuation range, determining that the cell of the electrolytic cell has no fault;
and if the characteristic parameter of the real-time cell voltage is not in the reasonable fluctuation range, determining that the cell of the electrolytic cell has a fault.
6. The method of monitoring the operating conditions of an electrolytic cell according to claim 5, wherein said step of comparing said characteristic parameter of said real-time cell voltage with said reasonable fluctuation range corresponding to said real-time load level is followed by the steps of:
if the characteristic parameter of the real-time cell voltage is in the reasonable fluctuation range, determining that the corresponding state value of the characteristic parameter of the real-time cell voltage is a preset first state value;
if the characteristic parameter of the real-time cell voltage is larger than the maximum value of the reasonable fluctuation range, determining that the state value corresponding to the characteristic parameter of the real-time cell voltage is a preset second state value;
and if the characteristic parameter of the real-time cell voltage is smaller than the minimum value of the reasonable fluctuation range, determining that the state value corresponding to the characteristic parameter of the real-time cell voltage is a preset third state value.
7. The method of monitoring the operating conditions of an electrolytic cell of claim 6, wherein said step of diagnosing a fault in each of said cells based on said health benchmark matrix comprises:
if the state value corresponding to the characteristic parameter of the real-time cell voltage is a preset second state value or a preset third state value, retrieving a fault database according to the real-time load level and the state value corresponding to the characteristic parameter of the real-time cell voltage;
if the real-time load grade and the corresponding state values of the characteristic parameters of the real-time cell voltage correspond to faults which have already occurred in the fault database, directly matching the fault type of the cell of the electrolytic cell;
and if the real-time load grade and the state value corresponding to the characteristic parameter of the real-time cell voltage correspond to a new fault which does not occur in the fault database, after determining a new fault type, newly adding the current fault type of the electrolytic cell in the fault database.
8. The method of monitoring the operating conditions of an electrolytic cell according to claim 2, wherein said step of detecting abnormalities in each of said cells of the electrolytic cell based on said reference matrix of health level comprises:
and performing abnormity detection on the small electrolytic cell chambers under each load grade by adopting a K proximity algorithm every other preset third time according to the health degree reference matrix.
9. The method of claim 8, wherein said step of detecting abnormalities in said cell compartments at each of said load levels using a K-nearest neighbor algorithm at predetermined third time intervals based on said health benchmark matrix comprises:
under the current load level, obtaining the average value of the characteristic parameters of the small chamber of the electrolytic cell as the characteristic parameters of the K-neighbor algorithm;
calculating the cell distances between the current electrolytic cell and all the rest electrolytic cell cells based on the characteristic parameters of the K-neighborhood algorithm;
selecting a K value in the K proximity algorithm according to the total number of the small chambers of the electrolytic cell;
sequencing all cell distances corresponding to the current electrolytic cell, determining K-value electrolytic cell cells closest to the current electrolytic cell, and calculating the average distance of the cell distances between the current electrolytic cell cells and the K-value electrolytic cell cells closest to the current electrolytic cell cells;
calculating the average distance of all the rest small cells of the electrolytic cell;
and sorting the average distances of all the electrolytic cell small chambers from large to small, and determining that a second number of electrolytic cell small chambers which are arranged in the average distance ranking in the top are abnormal small chambers under the current load grade.
10. The method of monitoring the operating conditions of an electrolytic cell according to claim 9, wherein said step of determining that a second predetermined number of cells in said average distance ranking that are previously ranked as abnormal cells at said current load level further comprises:
obtaining abnormal small chambers under each load grade;
and determining the electrolytic cell small chambers which are abnormal small chambers under the load grade of the preset third quantity as small chambers to be overhauled, and overhauling the small chambers to be overhauled.
11. An electrolytic cell operating condition monitoring system, characterized in that the electrolytic cell operating condition monitoring system comprises: the device comprises an electrolytic cell, a voltage acquisition device, a controller and a database;
the voltage acquisition device is used for acquiring cell voltage of each electrolytic cell in the electrolytic cell and transmitting the cell voltage to the controller;
the controller is used for storing the cell voltage into the database, calling the cell voltage from the database to extract characteristic parameters, construct a health degree reference matrix and update a fault database;
the database comprises the fault database, and is used for storing the cell voltage, the characteristic parameters and the health degree reference matrix.
12. A controller, characterized in that the controller comprises: memory, processor and computer program stored on said memory and executable on said processor, said computer program being configured to implement the steps of the method of monitoring the operating condition of an electrolytic cell according to any one of claims 1 to 10.
13. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method for monitoring the operational state of an electrolytic cell according to any one of claims 1 to 10.
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