A new energy hydrogen production station operation monitoring method and system

Abstract

The present application provides an operation monitoring method and system for a new energy hydrogen production station. The method collects the numerical values ​​of predetermined safety factor data, and based on the collected numerical values, determines the operation status of the new energy hydrogen production station from multiple preset operation states, thereby determining the operation status of the new energy hydrogen production station from multiple dimensions and improving the accuracy of operation status monitoring. Moreover, based on the collected numerical values, it is possible to determine not only whether the operation status is an existing risk state, but also whether the operation status is a potential risk state, which can improve the comprehensiveness of operation status monitoring.

Description

Technical Field

[0001] The present application relates to the field of new energy technology, and in particular to an operation monitoring method and system for a new energy hydrogen production station. Background Art

[0002] Hydrogen energy has the characteristics of cleanliness and high efficiency, which makes it occupy an increasingly important position in the field of new energy. Among them, hydrogen production is the primary technical link in the process of hydrogen energy utilization. At present, new energy hydrogen production stations are generally used for hydrogen production, that is, new energy (such as photovoltaic and wind power) is used to generate electricity for hydrogen production to electrolyze water to produce hydrogen.

[0003] However, how to monitor the operation of new energy hydrogen production stations to ensure the safety of hydrogen production becomes a problem. Summary of the invention

[0004] In order to solve the above technical problems, the embodiment of the present application provides an operation monitoring method and system of a new energy hydrogen production station to achieve the purpose of improving the accuracy and comprehensiveness of operation monitoring. The technical solution is as follows:

[0005] A method for monitoring the operation of a new energy hydrogen production station, comprising:

[0006] Collecting the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station;

[0007] Based on the collected values, determining the operating state of the new energy hydrogen production station from a plurality of preset operating states, wherein the plurality of preset operating states at least include: a safe state, a potential risk state, and an existing risk state;

[0008] Output the operating status of the new energy hydrogen production station.

[0009] The step of determining the operating state of the new energy hydrogen production station from a plurality of preset operating states based on the collected values ​​includes:

[0010] Inputting the values ​​of each of the safety factor data into a fuzzy control model, the fuzzy control model uses a membership function to calculate the probability that the values ​​of each of the safety factor data belong to the data of each preset operating state;

[0011] For each of the preset operating states, counting the probability that the values ​​of the plurality of safety factor data belong to the data of the preset operating state, and obtaining a statistical result;

[0012] The preset operating state corresponding to the maximum statistical result among the multiple statistical results is used as the operating state of the new energy hydrogen production station.

[0013] After collecting the predetermined safety factor data values, the method further includes:

[0014] The weight of the predetermined safety factor data is determined according to the severity level of the consequences caused by the predetermined safety factor data and the operational management requirements.

[0015] For each of the preset operating states, the probability that the values ​​of the plurality of safety factor data belong to the data of the preset operating state is counted to obtain the statistical result, including:

[0016] For each of the preset operating states, the probability that the value of each of the safety factor data belongs to the data of the preset operating state is multiplied by the weight of each of the safety factor data, and the results of each multiplication are added to obtain a statistical result.

[0017] The method further comprises:

[0018] When the operation monitoring task changes, update the predetermined safety factor data, the parameters in the fuzzy control model, the weight of the predetermined safety factor data and one or more of the preset operating states, and return to execute the step of collecting the numerical value of the predetermined safety factor data.

[0019] The step of determining the operating state of the new energy hydrogen production station from a plurality of preset operating states based on the collected values ​​includes:

[0020] By searching the preset operating state corresponding to the value of each safety factor data in a preset mapping relationship table, the preset mapping relationship table includes a mapping relationship between the value range of each safety factor data and each preset operating state;

[0021] Among the preset operating states corresponding to the values ​​of the multiple safety factor data, the preset operating state with the highest priority is used as the operating state of the new energy hydrogen production station.

[0022] The method further comprises:

[0023] When the operation monitoring task changes, the predetermined safety factor data and / or the preset mapping relationship table are updated, and the step of collecting the numerical value of the predetermined safety factor data is returned to be executed.

[0024] After determining the operating state of the new energy hydrogen production station from a plurality of preset operating states based on the collected values, the method further includes:

[0025] When the operating state of the new energy hydrogen production station is the potential risk state, performing preventive operations;

[0026] When the operating state of the new energy hydrogen production station is a risky state, a risk elimination operation is performed.

[0027] The predetermined safety factor data includes at least: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0028] An operation monitoring system for a new energy hydrogen production station, comprising:

[0029] A collection module, used to collect the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station;

[0030] An operating state determination module, used to determine the operating state of the new energy hydrogen production station from a plurality of preset operating states based on the collected values, wherein the plurality of preset operating states at least include: a safe state, a potential risk state, and an existing risk state;

[0031] The output module is used to output the operating status of the new energy hydrogen production station.

[0032] The operation status determination module is specifically used for:

[0033] Inputting the values ​​of each of the safety factor data into a fuzzy control model, the fuzzy control model uses a membership function to calculate the probability that the values ​​of each of the safety factor data belong to the data of each preset operating state;

[0034] For each of the preset operating states, counting the probability that the values ​​of the plurality of safety factor data belong to the data of the preset operating state, and obtaining a statistical result;

[0035] The preset operating state corresponding to the maximum statistical result among the multiple statistical results is used as the operating state of the new energy hydrogen production station.

[0036] The system further comprises:

[0037] The weight determination module is used to determine the weight of the predetermined safety factor data according to the severity level of the consequences caused by the predetermined safety factor data and the operation management requirements.

[0038] The operation status determination module is specifically used for:

[0039] For each of the preset operating states, the probability that the value of each of the safety factor data belongs to the data of the preset operating state is multiplied by the weight of each of the safety factor data, and the results of each multiplication are added to obtain a statistical result.

[0040] The system further comprises:

[0041] The first update module is used to update one or more of the predetermined safety factor data, the parameters in the fuzzy control model, the weight of the predetermined safety factor data and the preset operating state when the operation monitoring task changes, and return the value of the predetermined safety factor data collected by the collection module.

[0042] The operation status determination module is specifically used for:

[0043] By searching the preset operating state corresponding to the value of each safety factor data in a preset mapping relationship table, the preset mapping relationship table includes a mapping relationship between the value range of each safety factor data and each preset operating state;

[0044] Among the preset operating states corresponding to the values ​​of the multiple safety factor data, the preset operating state with the highest priority is used as the operating state of the new energy hydrogen production station.

[0045] The system further comprises:

[0046] The second updating module is used to update the predetermined safety factor data and / or the preset mapping relationship table when the operation monitoring task changes, and return the value of the predetermined safety factor data collected by the collection module.

[0047] The system further comprises:

[0048] An operation module, used for performing preventive operations when the operating state of the new energy hydrogen production station is the potential risk state;

[0049] Or, when the operating status of the new energy hydrogen production station is a risky state, a risk elimination operation is performed.

[0050] The predetermined safety factor data includes at least: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0051] Compared with the prior art, the beneficial effects of this application are:

[0052] In the present application, by collecting the numerical values ​​of predetermined safety factor data and determining the operating status of the new energy hydrogen production station from multiple preset operating states based on the collected numerical values, it is possible to determine the operating status of the new energy hydrogen production station from multiple dimensions and improve the accuracy of operating status monitoring.

[0053] Moreover, based on the collected values, it is possible to determine not only whether the operating status is an existing risk state, but also whether the operating status is a potential risk state, thereby improving the comprehensiveness of operating status monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0055] Figure 1 This is a flow chart of Example 1 of an operation monitoring method for a new energy hydrogen production station provided in this application;

[0056] Figure 2 This is a flow chart of Example 2 of an operation monitoring method for a new energy hydrogen production station provided by the present application;

[0057] Figure 3 This is a flow chart of Example 3 of an operation monitoring method for a new energy hydrogen production station provided by the present application;

[0058] Figure 4 This is a flow chart of Example 4 of an operation monitoring method for a new energy hydrogen production station provided by the present application;

[0059] Figure 5 This is a flow chart of Example 5 of an operation monitoring method for a new energy hydrogen production station provided by the present application;

[0060] Figure 6 This is a flow chart of Example 6 of an operation monitoring method for a new energy hydrogen production station provided by the present application;

[0061] Figure 7 This is a flow chart of Example 7 of an operation monitoring method for a new energy hydrogen production station provided by the present application;

[0062] Figure 8 This is a flow chart of Example 8 of an operation monitoring method for a new energy hydrogen production station provided by the present application;

[0063] Fig. 9 This is a logical structure diagram of an operation monitoring system of a new energy hydrogen production station provided by the present application;

[0064] Fig.10 This is another logical structure diagram of an operation monitoring system for a new energy hydrogen production station provided in this application. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0066] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0067] Next, the operation monitoring method of the new energy hydrogen production station disclosed in the embodiment of the present application is introduced. Figure 1 The flowchart shown is a flow chart of Embodiment 1 of an operation monitoring method for a new energy hydrogen production station provided by the present application, which may include the following steps:

[0068] Step S11, collecting the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station, and the predetermined safety factor data at least includes: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0069] In this embodiment, data that may affect the safe operation of the new energy hydrogen production station may be pre-determined during the initialization phase, and the determined data that may affect the safe operation of the new energy hydrogen production station may be used as safety factor data.

[0070] Specifically, data that can affect the safe operation of new energy hydrogen production stations can be determined based on the systematic methodology and the system design drawings, completion drawings, equipment monitoring data, project management regulations, safe operation technical regulations, safety precautions, project or similar project safety accidents, hidden danger data and information. The systematic methodology can be understood as a data analysis theory based on empirical theoretical knowledge.

[0071] The predetermined safety factor data may include but is not limited to: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0072] Equipment operation data can be understood as: equipment telemetry data and telesignaling data. Equipment telemetry data and telesignaling data may include but are not limited to: pressure, temperature, current, voltage, oxygen content in hydrogen, and hydrogen content in oxygen.

[0073] Maintenance data may include but are not limited to: (1) data on regular inspection and calibration management, for example, management data on the inspection and calibration of containers, pressure gauges, safety valves, valves and control instruments once a year; management data on the inspection and calibration of analytical instruments once every six months. (2) Management data on wearing parts and consumables; color change data of silica gel and boric acid tablets of analytical instruments; management data on desiccant-molecular sieves, circulation pumps, water pumps, and exhaust fans. (3) Regular maintenance management data, for example, regular (e.g., every 5 years or more) overhauls, regular overhauls of electrolytic cells, replacement of all diaphragms and sealing gaskets, overhaul of the entire set of equipment, without disassembling the electrolytic cell (1 year), cleaning of the alkali solution filter (before startup, 1 to 2 months, the temperature difference between the hydrogen and oxygen separator is 7 degrees Celsius, and the temperature difference between the cell and the separation is 30 to 40 degrees Celsius).

[0074] Personnel data may include but is not limited to: personnel behavior data and manual inspection data at new energy hydrogen production stations.

[0075] The following example illustrates the behavior data of personnel at new energy hydrogen production stations. For example, when maintenance operations are required, if the device is running, personnel are prohibited from performing any repair work. Personnel must first stop the device operation, and then analyze whether the hydrogen concentration in the hydrogen production room is lower than the explosion limit. At the same time, nitrogen must be passed to replace the hydrogen and oxygen in the device and pipeline. Only after the analysis is qualified can maintenance operations such as welding be performed. After maintenance, personnel need to use soapy water or gas explosion-proof detectors to check whether the hydrogen and oxygen systems, pipelines, and valves are leaking. It is strictly forbidden to use open flames for inspection.

[0076] The behavioral data of personnel at the new energy hydrogen production station can be collected through video surveillance, or uploaded by supervisory personnel.

[0077] Manual inspection data can be understood as data used to supplement computer monitoring data. For example, check that animals, plants, mineral greases and oils do not fall on equipment that comes into contact with oxygen; and prevent any metal conductors or other debris from falling on the electrolytic cell.

[0078] Manual inspection data can be uploaded to the system by inspection personnel.

[0079] Asset management data can be understood as data for managing assets, including but not limited to: basic information of assets (such as equipment manufacturer, production date, spare parts, etc.), regular inspection and calibration management data, management data of wearing parts and consumables, and regular maintenance management data.

[0080] Environmental data may include but is not limited to: video surveillance data and disaster weather forecast data.

[0081] Video surveillance data can be understood as: video data for monitoring new energy hydrogen production stations.

[0082] Disaster weather forecast data can be understood as: disaster weather data such as thunderstorms and earthquakes that may cause safety accidents.

[0083] After the safety factor data is predetermined, the monitoring phase is entered, specifically, the values ​​of the predetermined safety factor data are collected.

[0084] For the equipment operation data, the numerical value of the equipment operation data can be directly collected, for example, the current value of the equipment is 1A, and the voltage value of the equipment is 220V.

[0085] For maintenance data, personnel data, asset management data and environmental data, the correspondence between data and values ​​can be pre-constructed to achieve quantification of maintenance data, personnel data, asset management data and environmental data. For example, the behavior data that prohibits personnel from performing any repair work when the device is running is set to value a, and the correspondence between the behavior data and value a is constructed. On the premise of pre-constructing the correspondence between data and values, the specific process of collecting the values ​​of maintenance data, personnel data, asset management data or environmental data can be: collecting maintenance data, personnel data, asset management data or environmental data; in the pre-constructed correspondence between data and values, searching for the value corresponding to the collected data.

[0086] Step S12: based on the collected values, determine the operating state of the new energy hydrogen production station from a plurality of preset operating states, wherein the plurality of preset operating states at least include: a safe state, a potential risk state and an existing risk state.

[0087] In this embodiment, the potential risk state can be understood as a state where continued operation may result in an operation hazard.

[0088] The existing risk state can be understood as a state where the operation has become dangerous. Among them, the existing risk state can be subdivided into: general risk state, dangerous state and very dangerous state. The degree of danger of the operation of the new energy hydrogen production station represented by the dangerous state is higher than the degree of danger of the operation of the new energy hydrogen production station represented by the general risk state; the degree of danger of the operation of the new energy hydrogen production station represented by the very dangerous state is higher than the degree of danger of the operation of the new energy hydrogen production station represented by the dangerous state.

[0089] Step S13: output the operating status of the new energy hydrogen production station.

[0090] It should be noted that the operation monitoring method of the new energy hydrogen production station introduced in this embodiment is applicable to any stage of the operation of the new energy hydrogen production station, such as the startup stage, the test stage or the shutdown stage.

[0091] In this embodiment, by outputting the operating status of the new energy hydrogen production station, the staff can be prompted to perform corresponding operations based on the operating status of the new energy hydrogen production station, thereby ensuring timely control of the operation of the new energy hydrogen production station.

[0092] In the present application, by collecting the numerical values ​​of predetermined safety factor data and determining the operating status of the new energy hydrogen production station from multiple preset operating states based on the collected numerical values, it is possible to determine the operating status of the new energy hydrogen production station from multiple dimensions and improve the accuracy of operating status monitoring.

[0093] Moreover, based on the collected values, it is possible to determine not only whether the operating status is an existing risk state, but also whether the operating status is a potential risk state, thereby improving the comprehensiveness of operating status monitoring.

[0094] As another optional embodiment of the present application, refer to Figure 2 , is a flow chart of Example 2 of an operation monitoring method for a new energy hydrogen production station provided by the present application. This embodiment is mainly a detailed scheme of the operation monitoring method for a new energy hydrogen production station described in Example 1 above, such as Figure 2 As shown, the method may include but is not limited to the following steps:

[0095] Step S21, collecting the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station, and the predetermined safety factor data at least includes: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0096] The detailed process of step S21 can refer to the relevant introduction of step S11 in embodiment 1, which will not be repeated here.

[0097] Step S22: inputting the values ​​of the various safety factor data into the fuzzy control model, and the fuzzy control model uses the membership function to respectively calculate the probability that the values ​​of the various safety factor data belong to the data of each preset operating state.

[0098] Now, an example is given of inputting the values ​​of each of the safety factor data into the fuzzy control model, and the fuzzy control model uses the membership function to respectively calculate the probability that the values ​​of each of the safety factor data belong to the data of each preset operating state. For example, if each of the preset operating states is: v1, v2, ..., v n , if the safety factor data are U1, U2, ..., U m , let the value of U1 be u1, let the value of U2 be u2, ..., let U m The value is represented by u m , then u1, u2, ..., um are input into the fuzzy control model respectively. The fuzzy control model uses the membership function to calculate the probability that u1 belongs to the data of v1, and the probability that u1 belongs to the data of v2, ... and the probability that u1 belongs to v n The fuzzy control model uses the membership function to calculate the probability that u2 belongs to v1 and the probability that u2 belongs to v2, ... and the probability that u2 belongs to v n The probability of the data; ... and the fuzzy control model uses the membership function to calculate u n The probability of data belonging to v1 and calculation u n The probability of data belonging to v2, ... and calculate u n Belong to v n The probability of data u1 belonging to v1 is expressed as r 11 , the probability that u1 belongs to the data of v2 is expressed as r 12 , ... u1 belongs to v n The probability of the data is expressed as r 1n ; The probability that u2 belongs to the data of v1 is expressed as r 21 , the probability that u2 belongs to the data of v2 is expressed as r 22 , ... u2 belongs to v n The probability of the data is expressed as r 2n ;…will u m The probability of data belonging to v1 is denoted by r m1 , will u m The probability of data belonging to v2 is denoted by r m2 ,...will u m Belong to v n The probability of the data is expressed as r mn The individual probabilities can be stored in the form of a matrix, such as for storage.

[0099] Step S23: for each of the preset operating states, count the probabilities that the values ​​of the plurality of safety factor data belong to the data of the preset operating state to obtain a statistical result.

[0100] For each of the preset operating states, counting the probabilities that the values ​​of the plurality of safety factor data belong to the data of the preset operating state may include but is not limited to: for each of the preset operating states, adding the probabilities that the values ​​of the plurality of safety factor data belong to the data of the preset operating state. Still taking the example in step S22, for each of the preset operating states, counting the probabilities that the values ​​of the plurality of safety factor data belong to the data of the preset operating state is described, for example, Taking v1 as an example, count u1, u2, ..., u m The probability of data belonging to v1 is about r11 +r 21 +…+r m1 , r 11 +r 21 +…+r m1 The result is taken as the statistical result corresponding to v1.

[0101] Step S24: taking the preset operating state corresponding to the maximum statistical result among the plurality of statistical results as the operating state of the new energy hydrogen production station.

[0102] For example, if v n If the corresponding statistical result is the largest among multiple statistical results, then v n As the operating status of a new energy hydrogen production station.

[0103] Steps S22-S24 are a specific implementation of step S12 in Example 1.

[0104] Step S25: output the operating status of the new energy hydrogen production station.

[0105] The detailed process of step S25 can refer to the relevant introduction of step S13 in embodiment 1, which will not be repeated here.

[0106] In this embodiment, the fuzzy control model uses the membership function to calculate the probability that the value of each safety factor data belongs to each preset operating state, which can ensure that in complex scenarios, the probability of the value of each safety factor data belonging to each preset operating state is accurately calculated, thereby improving the accuracy of operation monitoring. In addition, the preset operating state corresponding to the maximum statistical result among the multiple statistical results is used as the operating state of the new energy hydrogen production station, so that the preset operating state with the highest probability is used as the operating state of the new energy hydrogen production station, thereby improving the accuracy of determining the operating state of the new energy hydrogen production station and further improving the accuracy of operation monitoring.

[0107] As another optional embodiment of the present application, refer to Figure 3 , is a flow chart of Example 3 of an operation monitoring method for a new energy hydrogen production station provided by the present application. This embodiment is mainly an extended solution of the operation monitoring method for a new energy hydrogen production station described in Example 2 above, such as Figure 3 As shown, the method may include but is not limited to the following steps:

[0108] Step S31, collecting the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station, and the predetermined safety factor data at least includes: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0109] The detailed process of step S31 can refer to the relevant introduction of step S21 in embodiment 2, which will not be repeated here.

[0110] Step S32: Determine the weight of the predetermined safety factor data according to the severity level of the consequences caused by the predetermined safety factor data and the operational management requirements.

[0111] Operational management needs can be, but are not limited to, prevention first, with disaster relief as a secondary focus.

[0112] The weight of the predetermined safety factor data may be understood as: the degree of importance of the predetermined safety factor data.

[0113] In this embodiment, the weight of the predetermined security factor data is described by still taking the example of step S22 in embodiment 2 as an example. For example, if the predetermined security factor data includes U1, U2, ..., U m , then the weight of U1 is determined to be ρ1, the weight of U2 is determined to be ρ2, ..., and the weight of U m The weight is ρ m .in,

[0114] Step S33: inputting the values ​​of the various safety factor data into the fuzzy control model, and the fuzzy control model uses the membership function to respectively calculate the probability that the values ​​of the various safety factor data belong to the data of each preset operating state.

[0115] The detailed process of step S33 can refer to the relevant introduction of step S22 in embodiment 2, which will not be repeated here.

[0116] Step S34: for each of the preset operating states, multiply the probability that the value of each of the safety factor data belongs to the data of the preset operating state by the weight of each of the safety factor data, and add the results of each multiplication to obtain a statistical result.

[0117] In this embodiment, taking the preset running state v1 as an example, for each of the preset running states, the probability that the value of each of the safety factor data belongs to the data of the preset running state is multiplied by the weight of each of the safety factor data, and the results of each multiplication are added to obtain the statistical result for explanation. For example, for v1, the probability r that u1 belongs to the data of v1 is 11 Multiplying by ρ1, the probability that u2 belongs to the data of v1 is r 21 With ρ2,… m The probability r of the data belonging to v1 m1 and ρ m Multiply and r 11 *ρ1+r 21*ρ2+…+r m1 *ρ m , and obtain the statistical results.

[0118] Step S35: taking the preset operating state corresponding to the maximum statistical result among the multiple statistical results as the operating state of the new energy hydrogen production station.

[0119] Step S36: output the operating status of the new energy hydrogen production station.

[0120] The detailed process of steps S35-S36 can be found in the relevant introduction of steps S24-S25 in Example 2, which will not be repeated here.

[0121] In this embodiment, by determining the weight of predetermined safety factor data, the importance of the safety factor data is screened, and the operating status of the new energy hydrogen production station is determined by combining the weight of the predetermined safety factor data with the probability that the value of the safety factor data belongs to the preset operating status. This can more accurately determine the operating status and improve the accuracy of operation monitoring.

[0122] As another optional embodiment of the present application, refer to Figure 4 , is a flow chart of Example 4 of an operation monitoring method for a new energy hydrogen production station provided by the present application. This embodiment is mainly an extended solution of the operation monitoring method for a new energy hydrogen production station described in Example 2 above, such as Figure 4 As shown, the method may include but is not limited to the following steps:

[0123] Step S41, collecting the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station, and the predetermined safety factor data at least includes: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0124] Step S42, inputting the values ​​of each of the safety factor data into the fuzzy control model, and the fuzzy control model uses the membership function to respectively calculate the probability that the values ​​of each of the safety factor data belong to the data of each preset operating state;

[0125] Step S43: for each of the preset operating states, counting the probability that the values ​​of the plurality of safety factor data belong to the data of the preset operating state, and obtaining a statistical result;

[0126] Step S44: taking the preset operating state corresponding to the maximum statistical result among the plurality of statistical results as the operating state of the new energy hydrogen production station.

[0127] Step S45: output the operating status of the new energy hydrogen production station.

[0128] Step S46: When the operation monitoring task changes, update one or more of the predetermined safety factor data, the parameters in the fuzzy control model and the preset operation state, and return to execute step S41.

[0129] In this embodiment, when the operation monitoring task changes, the predetermined safety factor data, the parameters in the fuzzy control model and one or more of the preset operating states are updated, which can ensure that the operating state of the new energy hydrogen production station can be determined in real time and accurately as needed, thereby further improving the accuracy of operating state monitoring.

[0130] As another optional embodiment of the present application, refer to Figure 5 , is a flow chart of Example 5 of an operation monitoring method for a new energy hydrogen production station provided by the present application. This embodiment is mainly an extended solution of the operation monitoring method for a new energy hydrogen production station described in Example 3 above, such as Figure 5 As shown, the method may include but is not limited to the following steps:

[0131] Step S51, collecting the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station, and the predetermined safety factor data at least includes: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0132] Step S52: Determine the weight of the predetermined safety factor data according to the severity level of the consequences caused by the predetermined safety factor data and the operational management requirements.

[0133] Step S53: inputting the values ​​of the various safety factor data into the fuzzy control model, and the fuzzy control model uses the membership function to respectively calculate the probability that the values ​​of the various safety factor data belong to the data of each preset operating state.

[0134] Step S54: for each of the preset operating states, multiply the probability that the value of each of the safety factor data belongs to the data of the preset operating state by the weight of each of the safety factor data, and add the results of each multiplication to obtain a statistical result.

[0135] Step S55: taking the preset operating state corresponding to the maximum statistical result among the plurality of statistical results as the operating state of the new energy hydrogen production station.

[0136] Step S56: output the operating status of the new energy hydrogen production station.

[0137] The detailed process of steps S51-S56 can refer to the relevant introduction of steps S31-S36 in Example 3, which will not be repeated here.

[0138] Step S57, when the operation monitoring task changes, update one or more of the predetermined safety factor data, the parameters in the fuzzy control model, the weight of the predetermined safety factor data and the preset operation state, and return to execute step S51.

[0139] In this embodiment, when the operation monitoring task changes, the predetermined safety factor data, the parameters in the fuzzy control model, the weight of the predetermined safety factor data and one or more of the preset operating states are updated, which can ensure that the operating state of the new energy hydrogen production station can be determined in real time and accurately as needed, thereby further improving the accuracy of operating state monitoring.

[0140] As another optional embodiment of the present application, refer to Figure 6 , is a flow chart of Example 6 of an operation monitoring method for a new energy hydrogen production station provided in this application. This embodiment is mainly a detailed scheme of the operation monitoring method for a new energy hydrogen production station described in Example 1 above, such as Figure 6 As shown, the method may include but is not limited to the following steps:

[0141] Step S61, collecting the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station, and the predetermined safety factor data at least includes: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0142] The detailed process of step S61 can refer to the relevant introduction of step S11 in embodiment 1, which will not be repeated here.

[0143] Step S62: searching for the preset operating state corresponding to the value of each safety factor data in a preset mapping relationship table, wherein the preset mapping relationship table includes a mapping relationship between the value range of each safety factor data and each preset operating state.

[0144] It is understandable that each safety factor data may have different values. The values ​​of each safety factor data will be different in different operating states of the new energy hydrogen production station. Therefore, a preset mapping relationship table can be pre-constructed, wherein the preset mapping relationship table includes the mapping relationship between the value range of each safety factor data and each preset operating state.

[0145] After the preset mapping relationship table is pre-built, the preset operating state corresponding to the value of each safety factor data can be searched in the preset mapping relationship table.

[0146] Step S63: taking the preset operating state with the highest priority among the preset operating states corresponding to the values ​​of the plurality of safety factor data as the operating state of the new energy hydrogen production station.

[0147] Among the values ​​of multiple safety factor data, some of the values ​​of the safety factor data may correspond to the same preset operating state, or the values ​​of each safety factor data may correspond to different preset operating states. In this case, it is possible but not limited to: taking the preset operating state with the highest priority among the preset operating states corresponding to the values ​​of the multiple safety factor data as the operating state of the new energy hydrogen production station.

[0148] In this embodiment, the priority of the preset operating state may be set according to the danger level. Specifically, the priority of the preset operating state with a higher danger level may be set higher.

[0149] Steps S62-S63 are a specific implementation of step S12 in Example 1.

[0150] Step S64: output the operating status of the new energy hydrogen production station.

[0151] The detailed process of step S64 can refer to the relevant introduction of step S13 in embodiment 1, which will not be repeated here.

[0152] In this embodiment, by pre-constructing a preset mapping relationship table and searching for the preset operating state corresponding to the numerical value of each safety factor data in the preset mapping relationship table, the time for determining the preset operating state can be shortened, the efficiency of determining the operating state of the new energy hydrogen production station can be improved, and the efficiency of operation monitoring can be improved.

[0153] As another optional embodiment of the present application, refer to Figure 7 , is a flow chart of Example 7 of an operation monitoring method for a new energy hydrogen production station provided by the present application. This embodiment is mainly an extended solution of the operation monitoring method for a new energy hydrogen production station described in Example 6 above, such as Figure 7 As shown, the method may include but is not limited to the following steps:

[0154] Step S71, collecting the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station, and the predetermined safety factor data at least includes: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0155] Step S72: searching for the preset operating state corresponding to the value of each safety factor data in a preset mapping relationship table, wherein the preset mapping relationship table includes a mapping relationship between the value range of each safety factor data and each preset operating state.

[0156] Step S73: taking the preset operating state with the highest priority among the preset operating states corresponding to the values ​​of the multiple safety factor data as the operating state of the new energy hydrogen production station.

[0157] Step S74: output the operating status of the new energy hydrogen production station.

[0158] The detailed process of steps S71-S74 can be found in the relevant introduction of steps S61-S64 in Example 6, which will not be repeated here.

[0159] Step S75: When the operation monitoring task changes, update the predetermined safety factor data and / or the preset mapping relationship table, and return to execute step S71.

[0160] When the operation monitoring task changes, the predetermined safety factor data is updated, and / or the preset mapping relationship table can ensure that the information based on which the operating status of the new energy hydrogen production station is determined is real-time and accurate, thereby ensuring the accuracy of determining the operating status of the new energy hydrogen production station and the accuracy of operation monitoring.

[0161] As another optional embodiment of the present application, refer to Figure 8 , is a flow chart of Example 8 of an operation monitoring method for a new energy hydrogen production station provided by the present application. This embodiment is mainly an extended solution of the operation monitoring method for a new energy hydrogen production station described in Example 1 above, such as Figure 8 As shown, the method may include but is not limited to the following steps:

[0162] Step S81, collecting the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station, and the predetermined safety factor data at least includes: equipment operation data, maintenance data, personnel data, asset management data and environmental data.

[0163] Step S82: Based on the collected values, determine the operating state of the new energy hydrogen production station from a plurality of preset operating states, wherein the plurality of preset operating states at least include: a safe state, a potential risk state, and an existing risk state.

[0164] Step S83: output the operating status of the new energy hydrogen production station.

[0165] The detailed process of steps S81-S83 can be found in the relevant introduction of steps S11-S13 in Example 1, and will not be repeated here.

[0166] Step S84: When the operating state of the new energy hydrogen production station is the potential risk state, perform preventive operations.

[0167] Step S85: When the operating state of the new energy hydrogen production station is a risky state, perform a risk elimination operation.

[0168] When the existing risk status is a general risk status, the risk elimination operation may be an operation to maintain the new energy hydrogen production station; when the existing risk status is a dangerous status, the risk elimination operation may be an operation to correct a fault or error; when the existing risk status is a very dangerous status, the risk elimination operation may be a disaster relief operation.

[0169] In this embodiment, different operations can be performed according to different operating states of the new energy hydrogen production station to ensure the safe operation of the new energy hydrogen production station.

[0170] Next, the operation monitoring system of the new energy hydrogen production station provided in the present application is introduced. The operation monitoring system of the new energy hydrogen production station introduced below and the operation monitoring system of the new energy hydrogen production station introduced above can correspond to each other.

[0171] See also Fig. 9 The operation monitoring system of the new energy hydrogen production station includes: a collection module 100, an operation status determination module 200 and an output module 300.

[0172] The collection module 100 is used to collect the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station, and the predetermined safety factor data at least includes: equipment operation data, maintenance data, personnel data, asset management data and environmental data;

[0173] The operating state determination module 200 is used to determine the operating state of the new energy hydrogen production station from a plurality of preset operating states based on the collected values, wherein the plurality of preset operating states at least include: a safe state, a potential risk state, and an existing risk state;

[0174] The output module 300 is used to output the operating status of the new energy hydrogen production station.

[0175] In this embodiment, the operating state determination module 200 may be specifically used for:

[0176] Inputting the values ​​of each of the safety factor data into a fuzzy control model, the fuzzy control model uses a membership function to calculate the probability that the values ​​of each of the safety factor data belong to the data of each preset operating state;

[0177] For each of the preset operating states, counting the probability that the values ​​of the plurality of safety factor data belong to the data of the preset operating state, and obtaining a statistical result;

[0178] The preset operating state corresponding to the maximum statistical result among the multiple statistical results is used as the operating state of the new energy hydrogen production station.

[0179] In this embodiment, the operation monitoring system of the new energy hydrogen production station may also include:

[0180] A weight determination module, for determining the weight of the predetermined safety factor data according to the severity level of the consequences caused by the predetermined safety factor data and the operational management requirements;

[0181] In this embodiment, the operating state determination module 200 may be specifically used for:

[0182] For each of the preset operating states, the probability that the value of each of the safety factor data belongs to the data of the preset operating state is multiplied by the weight of each of the safety factor data, and the results of each multiplication are added to obtain a statistical result.

[0183] In this embodiment, the operation monitoring system of the new energy hydrogen production station may also include:

[0184] The first update module is used to update one or more of the predetermined safety factor data, the parameters in the fuzzy control model, the weight of the predetermined safety factor data and the preset operating state when the operation monitoring task changes, and return the value of the predetermined safety factor data collected by the collection module 100.

[0185] In this embodiment, the operating state determination module 200 may be specifically used for:

[0186] By searching the preset operating state corresponding to the value of each safety factor data in a preset mapping relationship table, the preset mapping relationship table includes a mapping relationship between the value range of each safety factor data and each preset operating state;

[0187] Among the preset operating states corresponding to the values ​​of the multiple safety factor data, the preset operating state with the highest priority is used as the operating state of the new energy hydrogen production station.

[0188] In this embodiment, the operation monitoring system of the new energy hydrogen production station may also include:

[0189] The second updating module is used to update the predetermined safety factor data and / or the preset mapping relationship table when the operation monitoring task changes, and return the value of the predetermined safety factor data collected by the collection module 100.

[0190] In another embodiment of the present application, another operation monitoring system of a new energy hydrogen production station is provided, such as Fig.10 As shown, in Fig. 9 On the basis of the operation monitoring system of the new energy hydrogen production station shown, the operation monitoring system of the new energy hydrogen production station further includes: an operation module 400 .

[0191] The operation module 400 can be used to:

[0192] When the operating state of the new energy hydrogen production station is the potential risk state, performing preventive operations;

[0193] Or, when the operating status of the new energy hydrogen production station is a risky state, a risk elimination operation is performed.

[0194] It should be noted that each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0195] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0196] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0197] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly contributed to the prior art in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.

[0198] The above is a detailed introduction to the operation monitoring method and system of a new energy hydrogen production station provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for monitoring the operation of a new energy hydrogen production station, characterized in that: include: Collecting the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station; The predetermined safety factor data at least include: equipment operation data, maintenance data, personnel data, asset management data and environmental data; wherein, according to the systematic methodology and the system design drawings, completion drawings, equipment monitoring data, project management regulations, safe operation technical regulations, safety precautions, project or similar project safety accidents, hidden danger data and information of the new energy hydrogen production station, the data that can affect the safe operation of the new energy hydrogen production station are determined, and the determined data that can affect the safe operation of the new energy hydrogen production station are used as the predetermined safety factor data; For maintenance data, personnel data, asset management data, and environmental data, the correspondence between data and values ​​is pre-built, and the values ​​corresponding to the collected data are searched in the pre-built correspondence between data and values; Based on the collected values, determining the operating state of the new energy hydrogen production station from a plurality of preset operating states, wherein the plurality of preset operating states at least include: a safe state, a potential risk state, and an existing risk state; Outputting the operating status of the new energy hydrogen production station; Wherein, determining the operating state of the new energy hydrogen production station from a plurality of preset operating states based on the collected values ​​includes: Inputting the values ​​of each of the safety factor data into a fuzzy control model, the fuzzy control model uses a membership function to calculate the probability that the values ​​of each of the safety factor data belong to the data of each preset operating state; For each of the preset operating states, counting the probability that the values ​​of the plurality of safety factor data belong to the data of the preset operating state, and obtaining a statistical result; The preset operating state corresponding to the maximum statistical result among the plurality of statistical results is used as the operating state of the new energy hydrogen production station; After collecting the predetermined value of the safety factor data, the method further includes: Determining the weight of the predetermined safety factor data according to the severity level of the consequences caused by the predetermined safety factor data and the operational management requirements; Wherein, for each of the preset operating states, counting the probability that the values ​​of the plurality of safety factor data belong to the data of the preset operating state to obtain the statistical result includes: For each of the preset operating states, the probability that the value of each of the safety factor data belongs to the data of the preset operating state is multiplied by the weight of each of the safety factor data, and the results of each multiplication are added to obtain a statistical result; The method further comprises: When the operation monitoring task changes, update the predetermined safety factor data, the parameters in the fuzzy control model, the weight of the predetermined safety factor data and one or more of the preset operating states, and return to execute the step of collecting the numerical value of the predetermined safety factor data.

2. The method according to claim 1, characterized in that After determining the operating state of the new energy hydrogen production station from a plurality of preset operating states based on the collected values, the method further includes: When the operating state of the new energy hydrogen production station is the potential risk state, performing preventive operations; When the operating state of the new energy hydrogen production station is a risky state, a risk elimination operation is performed.

3. An operation monitoring system for a new energy hydrogen production station, characterized in that: include: A collection module, used to collect the value of predetermined safety factor data, wherein the predetermined safety factor data is data that affects the safe operation of the new energy hydrogen production station; The predetermined safety factor data at least include: equipment operation data, maintenance data, personnel data, asset management data and environmental data; wherein, according to the systematic methodology and the system design drawings, completion drawings, equipment monitoring data, project management regulations, safe operation technical regulations, safety precautions, project or similar project safety accidents, hidden danger data and information of the new energy hydrogen production station, the data that can affect the safe operation of the new energy hydrogen production station are determined, and the determined data that can affect the safe operation of the new energy hydrogen production station are used as the predetermined safety factor data; for the maintenance data, personnel data, asset management data and environmental data, the corresponding relationship between the data and the value is pre-constructed, and the value corresponding to the collected data is found in the pre-constructed corresponding relationship between the data and the value; An operating state determination module, used to determine the operating state of the new energy hydrogen production station from a plurality of preset operating states based on the collected values, wherein the plurality of preset operating states at least include: a safe state, a potential risk state, and an existing risk state; An output module, used to output the operating status of the new energy hydrogen production station; Wherein, the operation status determination module is specifically used for: Inputting the values ​​of each of the safety factor data into a fuzzy control model, the fuzzy control model uses a membership function to calculate the probability that the values ​​of each of the safety factor data belong to the data of each preset operating state; For each of the preset operating states, counting the probability that the values ​​of the plurality of safety factor data belong to the data of the preset operating state, and obtaining a statistical result; The preset operating state corresponding to the maximum statistical result among the plurality of statistical results is used as the operating state of the new energy hydrogen production station; The system further comprises: A weight determination module, for determining the weight of the predetermined safety factor data according to the severity level of the consequences caused by the predetermined safety factor data and the operational management requirements; Wherein, the operation status determination module is specifically used for: For each of the preset operating states, the probability that the value of each of the safety factor data belongs to the data of the preset operating state is multiplied by the weight of each of the safety factor data, and the results of each multiplication are added to obtain a statistical result; The system further comprises: The first updating module is used to update one or more of the predetermined safety factor data, the parameters in the fuzzy control model, the weight of the predetermined safety factor data and the preset operating state when the operation monitoring task changes, and return the value of the predetermined safety factor data collected by the collection module.

4. The system according to claim 3, characterized in that The system further comprises: An operation module, used for performing preventive operations when the operating state of the new energy hydrogen production station is the potential risk state; Or, when the operating status of the new energy hydrogen production station is a risky state, a risk elimination operation is performed.

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