Smart gas fire protection linkage method and Internet of Things system based on government safety supervision

Abstract

The present invention provides a smart gas fire linkage method and an Internet of Things system based on government safety supervision. The method is executed through a smart gas government safety supervision management platform, including: determining the production stage information of the enterprise based on the enterprise's gas consumption statistics, current production data and production planning information; obtaining feedback information from the gas company management platform based on the enterprise's production stage information; obtaining the alarm information and / or fault information, working parameters and hidden danger processing data of at least one group of gas fire fighting equipment of the enterprise, and evaluating the fire risk level of the enterprise; determining the fire control parameters of the enterprise based on the fire risk level and hidden danger processing data of the enterprise; determining the update instructions based on the adjustment of the working parameters; sending the update instructions to the corresponding at least one group of gas fire fighting equipment, and controlling the gas fire fighting equipment to update. In this way, fire hazards can be discovered in time, and reasonable response plans can be given for different enterprises to optimize the allocation of fire fighting resources.

Description

Technical Field

[0001] The present invention relates to the field of gas fire fighting technology, and in particular to a smart gas fire fighting linkage method and an Internet of Things system based on government safety supervision. Background Art

[0002] With the acceleration of urbanization and the increase in population density, fire accidents often occur. Among them, fires caused by gas leakage or gas equipment failure are usually explosive, spread rapidly and burn violently, which can easily cause serious casualties and property losses.

[0003] In order to deal with gas fires, CN110515340B proposed a patrol remote control system and method for coordinated protection with a fire protection system. This method combines the SCADA system, video surveillance system, and fire protection system to monitor and control the natural gas concentration, gas pipeline temperature, and smoke concentration within the fire protection zone, so as to timely alarm and adjust the operating status of on-site equipment. However, this method does not take into account the differences in fire protection conditions of different gas users / enterprises, resulting in poor results in gas fire protection control.

[0004] Therefore, we hope to propose a smart gas fire protection linkage method and Internet of Things system based on government safety supervision, and provide reasonable protection plans for different gas users / enterprises from the perspective of the gas management platform to conduct more comprehensive monitoring of the gas fire protection situation. Summary of the invention

[0005] The invention content includes a smart gas fire linkage method based on government safety supervision, which is executed through a smart gas government safety supervision management platform of a smart gas fire linkage Internet of Things system based on government safety supervision. The method includes: obtaining gas usage statistics of one or more enterprises based on one or more flow monitoring devices controlled by a gas equipment object platform; obtaining the current production data and production planning information of the enterprises based on a gas-using enterprise management platform in the smart gas government safety supervision object platform; determining the production stage information of the enterprise based on the gas usage statistics, the current production data and the production planning information of the enterprise; obtaining feedback information from a gas company management platform in the smart gas government safety supervision object platform based on the production stage information of the enterprise; obtaining at least one set of gas fire The gas fire fighting equipment comprises at least one of an alarm device, an alarm self-test device and a gas concentration detection device; based on the production stage information of the enterprise, the feedback information, the alarm information and / or the fault information, the working parameters and the hidden danger handling data of the at least one group of gas fire fighting equipment, the fire risk level of the enterprise is evaluated; based on the fire risk level of the enterprise and the hidden danger handling database, the fire control parameters of the enterprise are determined, and the fire control parameters include at least one group of updated adjusted working parameters of the gas fire fighting equipment and the enterprise fire inspection cycle; based on the adjusted working parameters, an update instruction is determined; the update instruction is sent to the corresponding at least one group of gas fire fighting equipment to control the gas fire fighting equipment to be updated.

[0006] The invention content includes a smart gas fire linkage Internet of Things system based on government safety supervision, the system includes a smart gas government safety supervision service platform, a smart gas government safety supervision management platform, a smart gas government safety supervision sensor network platform, a smart gas government safety supervision object platform, a gas company sensor network platform, a gas equipment object platform, a smart gas user platform and a smart gas service platform. The smart gas government safety supervision object platform includes a gas company management platform and a gas-using enterprise management platform. The gas equipment object platform is configured to: control one or more flow monitoring devices to obtain gas usage statistics of one or more enterprises; the gas-using enterprise management platform is configured to obtain the current production data and production planning information of the enterprise; the smart gas government safety supervision management platform is configured to: determine the production stage information of the enterprise based on the gas usage statistics, current production data and production planning information of the enterprise; based on the production of the enterprise The enterprise obtains the alarm information and / or fault information, working parameters and hidden danger handling data of at least one group of gas fire-fighting equipment of the enterprise, and the gas fire-fighting equipment includes at least one of an alarm device, an alarm self-test device and a gas concentration detection device; based on the production stage information of the enterprise, the feedback information, the alarm information and / or the fault information, the working parameters and the hidden danger handling data of at least one group of gas fire-fighting equipment, the fire risk level of the enterprise is evaluated; based on the fire risk level and the hidden danger handling data of the enterprise, the fire control parameters of the enterprise are determined, and the fire control parameters include at least one group of updated adjusted working parameters of gas fire-fighting equipment and the enterprise fire inspection cycle; based on the adjusted working parameters, an update instruction is determined; the update instruction is sent to the corresponding at least one group of gas fire-fighting equipment to control the gas fire-fighting equipment to be updated.

[0007] This specification includes but is not limited to the following beneficial effects: (1) Through the smart gas-fire linkage Internet of Things system based on government safety supervision, an information operation closed loop is formed between various platforms, unified management and coordination, regular operation, and the informatization and intelligence of gas-fire linkage management are realized; (2) By evaluating the fire risk level of the enterprise, the probability of accidents of gas fire-fighting equipment is estimated, potential safety hazards are discovered in time, and corresponding control measures are taken to improve fire safety; (3) By updating gas fire-fighting equipment and optimizing the allocation of fire-fighting resources, the efficiency and accuracy of emergency response are improved; (4) According to the gas fire hazard risk classification into multiple sub-stages, the fire risk level of different sub-stages is determined, which is more in line with the gas fire supervision requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0009] Figure 1 It is a schematic diagram of an exemplary platform structure of a smart gas-fire linkage Internet of Things system based on government safety supervision according to some embodiments of this specification;

[0010] Figure 2 It is an exemplary flow chart of a smart gas fire protection linkage method based on government safety supervision according to some embodiments of this specification;

[0011] Figure 3 is an exemplary flow chart for determining a fire risk level according to some embodiments of this specification;

[0012] Figure 4 is an exemplary schematic diagram of a fire fighting stage determination model according to some embodiments of this specification;

[0013] Figure 5 is an exemplary schematic diagram of a probability determination model according to some embodiments of the present specification. DETAILED DESCRIPTION

[0014] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0015] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0016] As shown in this specification, unless the context clearly indicates an exception, the words "a", "an", "a kind" and / or "the" do not refer to the singular, but also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0017] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0018] Different gas users / enterprises will face different degrees of fire risk at different production stages. For example, during the peak production period of an enterprise, due to frequent equipment operation, dense operators, rising workshop temperature and other reasons, its fire risk is higher than the fire risk in the early stage of enterprise production. Therefore, fire management needs to take appropriate measures to ensure safety according to the characteristics of the enterprise and changes in production stages. When the community intelligent fire protection system proposed in CN110354432B is used to monitor the gas fire protection situation, it can take into account the fire alarm processing and station control system processing through the linkage of the fire protection system and the SCADA system. However, the system does not involve the differences in fire protection needs of different gas users / enterprises. Therefore, it is necessary to improve the gas fire protection control method. The embodiment of the present invention proposes a smart gas fire protection linkage method and an Internet of Things system based on government safety supervision, which integrates multiple functional platforms such as a smart gas government safety supervision service platform, a smart gas government safety supervision object platform, and a smart gas government safety supervision management platform. Through the synergy between the platforms, the system provides corresponding fire protection management solutions for different gas users / enterprises in different production stages, thereby improving the management level of gas fire protection safety.

[0019] Figure 1 It is a schematic diagram of an exemplary platform structure of a smart gas and fire protection linkage Internet of Things system based on government safety supervision as shown in some embodiments of this specification.

[0020] like Figure 1 As shown, the smart gas and fire protection linkage Internet of Things system 100 based on government safety supervision may include a smart gas government safety supervision service platform 110, a smart gas government safety supervision management platform 120, a smart gas government safety supervision sensor network platform 130, a smart gas government safety supervision object platform 140, a gas company sensor network platform 150, a gas equipment object platform 160, a smart gas user platform 170 and a smart gas service platform 180.

[0021] The smart gas government safety supervision service platform 110 refers to a platform that provides gas safety supervision services to government users. Government users may be managers of gas operating entities, etc.

[0022] The smart gas government safety supervision and management platform 120 refers to a comprehensive management platform for government management information. In some embodiments, the smart gas government safety supervision and management platform 120 can be configured as a processor, such as a combination of one or more of a microcontroller (MCU), an embedded processor (Embedded Processor), and a graphics processing unit (GPU).

[0023] In some embodiments, the smart gas government safety supervision management platform 120 is configured to: determine the production stage information of the enterprise based on the enterprise's gas usage statistics, current production data and production planning information; obtain feedback information from the gas company management platform 141 in the smart gas government safety supervision object platform 140 based on the enterprise's production stage information; obtain the alarm information and / or fault information, working parameters and hidden danger processing data of at least one group of gas fire fighting equipment of the enterprise, and the gas fire fighting equipment includes at least one of an alarm device, an alarm self-test device and a gas concentration detection device; evaluate the fire risk level of the enterprise based on the enterprise's production stage information, feedback information, and the alarm information and / or fault information, working parameters and hidden danger processing data of at least one group of gas fire fighting equipment; determine the fire control parameters of the enterprise based on the fire risk level and hidden danger processing data of the enterprise, and the fire control parameters include at least one group of updated adjusted working parameters of gas fire fighting equipment and the enterprise fire inspection cycle; determine the update instruction based on the adjusted working parameters; send the update instruction to the corresponding at least one group of gas fire fighting equipment to control the gas fire fighting equipment to update. For details, please refer to Figure 2 And related instructions.

[0024] In some embodiments, the smart gas government safety supervision management platform 120 is further configured to: determine at least one firefighting stage of the enterprise based on the enterprise's production stage information and feedback information; determine the number of centralized uploads based on at least one firefighting stage; based on the number of centralized uploads, centrally upload at least one group of gas firefighting equipment's alarm information and / or fault information, and working parameters to the smart gas government safety supervision service platform 110; in response to obtaining monitoring feedback from the smart gas government safety supervision service platform 110 that there is no abnormality, based on at least one firefighting stage of the enterprise, at least one group of gas firefighting equipment's alarm information and / or fault information, working parameters and hidden danger handling data, evaluate the enterprise's fire risk level; in response to obtaining monitoring feedback from the smart gas government safety supervision service platform 110 that there is an abnormality, set the fire risk level to the highest risk level. For details, please refer to Figure 3 And related instructions.

[0025] In some embodiments, the smart gas government safety supervision management platform 120 is further configured to: determine at least one firefighting stage through a firefighting stage determination model based on the basic information, production planning information, production stage information and feedback information of the enterprise, the firefighting stage determination model is a machine learning model, and the basic information of the enterprise is obtained based on the smart gas government safety supervision object platform 140. For details, please refer to Figure 4 And related instructions.

[0026] In some embodiments, the firefighting stage determination model includes at least a first stage of training, and the first stage of training includes: training based on a first training data set; verification based on a first validation set; testing based on a first test set; the first training set, the first test set, and the first validation set include historical production stage information extracted from historical data and its corresponding historical feedback information, historical enterprise basic information, wherein the ratio of the data volume of the first training set, the data volume of the first test set, and the data volume of the first validation set is a first preset ratio, there is no data overlap between the first training set, the first test set, and the first validation set, and the statistical difference of the samples of the first training set is greater than a preset difference threshold, and the preset difference threshold is related to the statistical value of the severity of historical gas fire incidents. For details, please refer to Figure 3 And related instructions.

[0027] In some embodiments, the smart gas government safety supervision and management platform 120 is further configured to: determine the estimated accident probability and estimated accident information of at least one group of gas fire fighting equipment based on hidden danger processing data, working parameters of at least one group of gas fire fighting equipment, at least one fire fighting stage and fire fighting risk level; determine the fire fighting control parameters of the enterprise based on the estimated accident probability, estimated accident information, working parameters and first preset threshold of at least one group of gas fire fighting equipment. For details, please refer to Figure 2 And related instructions.

[0028] In some embodiments, different production stages have different first preset thresholds, and the first preset threshold of the current production stage is related to the number of firefighting stages included in the current production stage. Figure 2 And related instructions.

[0029] In some embodiments, the smart gas government safety supervision and management platform 120 is further configured to: determine the estimated accident probability and estimated accident information of at least one group of gas fire fighting equipment based on at least one group of gas fire fighting equipment working parameters, at least one fire fighting stage, fire fighting risk level and hidden danger handling data based on a preset algorithm. For details, please refer to Figure 2 And related instructions.

[0030] In some embodiments, the smart gas government safety supervision and management platform 120 is further configured to: determine the estimated accident probability of at least one group of gas fire fighting equipment based on the working parameters and fire risk level of at least one group of gas fire fighting equipment through a probability determination model, the probability determination model is trained based on the second training data set, and the second training data set is generated based on the hidden danger processing data. For details, please refer to Figure 5 And related instructions.

[0031] The smart gas government safety supervision sensor network platform 130 refers to a functional platform for transmitting and managing data and information of government-related platforms. For example, the smart gas government safety supervision sensor network platform 130 can be configured as a communication base station, a router, a wireless local area network (WLAN) device, and the like.

[0032] The smart gas government safety supervision object platform 140 refers to a platform for generating government supervision information and controlling information execution.

[0033] In some embodiments, the smart gas government safety supervision object platform 140 includes a gas company management platform 141 and a gas-using enterprise management platform 142 .

[0034] The gas company management platform 141 refers to a platform for managing the gas company's gas-related data and fire-related data.

[0035] The gas-using enterprise management platform 142 refers to a platform for managing relevant information of enterprises that use gas. In some embodiments, the gas-using enterprise management platform 142 is configured to obtain the current production data and production planning information of the enterprise. The smart gas government safety supervision object platform 140 can obtain basic information of the enterprise, current production data and production planning information through the gas-using enterprise management platform 142, and upload it to the smart gas government safety supervision management platform 120. For information about current production data and production planning information, please refer to Figure 2 For more information about basic company information, see Figure 4 Gas-using enterprises refer to enterprises that use a large amount of gas in the production process.

[0036] The gas company sensor network platform 150 refers to a platform for sensing information sensor communication and controlling information sensor communication. For example, the gas company sensor network platform 150 can be configured as a communication base station, a router, a wireless device, and the like.

[0037] The gas equipment object platform 160 refers to a functional platform for sensing information generation and controlling information execution. In some embodiments, the gas equipment object platform 160 can be configured to control one or more flow monitoring devices to obtain gas usage statistics of one or more enterprises. For more information on obtaining gas usage statistics, see Figure 2 and related instructions.

[0038] In some embodiments, the gas equipment object platform 160 may be configured as a gas fire fighting equipment.

[0039] Gas fire fighting equipment refers to equipment used to monitor and deal with problems related to gas fire fighting. In some embodiments, the gas fire fighting equipment includes at least one of an alarm device, an alarm self-checking device, and a gas concentration detection device.

[0040] The alarm device is configured to issue an alarm message.

[0041] The gas concentration detection device is configured to detect the ambient gas concentration. In some embodiments, the gas concentration detection device has a built-in component for communication.

[0042] The alarm self-checking device is configured to detect whether the alarm device and the gas concentration detection device are working properly. The alarm self-checking device can issue a fault message based on detecting that the alarm device and / or the gas concentration detection device are not working properly.

[0043] Flow monitoring equipment refers to a device used to monitor gas flow, such as a flow sensor.

[0044] The smart gas user platform 170 may be a platform that provides gas users with gas usage-related data and gas problem solutions. Gas users may be industrial gas users, commercial gas users, ordinary gas users, etc. In some embodiments, the smart gas user platform 170 may be configured as a user terminal device.

[0045] Smart Gas Service Platform 180 refers to a platform that provides gas services to gas users.

[0046] In some embodiments, the smart gas government safety supervision service platform 110 can interact with the smart gas government safety supervision management platform 120. For example, the smart gas government safety supervision management platform 120 can centrally upload the alarm information and / or fault information and working parameters of the gas fire fighting equipment to the smart gas government safety supervision service platform 110. For another example, the smart gas government safety supervision management platform 120 can obtain monitoring feedback from the smart gas government safety supervision service platform 110.

[0047] In some embodiments, the smart gas government safety supervision management platform 120 can interact with the smart gas government safety supervision object platform 140 through the smart gas government safety supervision sensor network platform 130. For example, the smart gas government safety supervision management platform 120 can upload the production stage information of the enterprise to the gas company management platform 141 through the smart gas government safety supervision sensor network platform 130. For another example, the smart gas government safety supervision management platform 120 can obtain current production data, production planning information, basic enterprise information, etc. from the gas user enterprise management platform 142 through the smart gas government safety supervision sensor network platform 130.

[0048] In some embodiments, the gas company sensor network platform 150 can interact with the gas company management platform 141 and the gas equipment object platform 160 of the smart gas government safety supervision object platform 140. For example, the gas company sensor network platform 150 can obtain the alarm information, fault information and gas usage statistics of the gas fire fighting equipment from the gas equipment object platform 160, and upload them to the gas company management platform 141 of the smart gas government safety supervision object platform 140. The latter transmits the received alarm information, fault information and gas usage statistics to the smart gas government safety supervision management platform 120. For another example, the smart gas government safety supervision management platform 120 can transmit the update instruction to the gas equipment object platform 160.

[0049] In some embodiments of this specification, through the smart gas fire linkage Internet of Things system based on government safety supervision, an information operation closed loop can be formed between the smart gas government safety supervision management platform and the smart gas user platform and other platforms, and coordinated and regularly operated under the unified management of the smart gas government safety supervision management platform, thereby realizing the informatization and intelligence of gas fire linkage management.

[0050] Figure 2 is an exemplary flow chart of a smart gas fire protection linkage method based on government safety supervision according to some embodiments of this specification. In some embodiments, process 200 can be executed by the smart gas government safety supervision management platform 120. Figure 2 As shown, process 200 includes the following steps:

[0051] Step 210, based on one or more flow monitoring devices controlled by the gas equipment object platform, obtain gas usage statistics of one or more enterprises.

[0052] An enterprise refers to an enterprise that uses gas for production activities, such as industrial gas enterprises, commercial gas enterprises, etc.

[0053] Gas usage statistics refer to information obtained by statistically analyzing the gas usage and distribution of an enterprise. In some embodiments, the gas usage statistics may include the production channels of products produced by the enterprise and the gas usage of the channels in a preset time period.

[0054] A production pipeline can include different production lines. For example, gas usage statistics can include (a1, b1), (a2, b2)… (a n , b n ), where a1, a2, ..., a n Indicates different production lines, b1, b2...b n Indicates production lines a1, a2, ... a n The corresponding gas consumption within the preset time period. The preset time period can be set according to demand, for example, the preset time period can be one hour or two hours.

[0055] In some embodiments, the smart gas government safety supervision management platform 120 can obtain gas usage statistics of different production channels in a preset time period through flow monitoring equipment based on the gas equipment object platform 160. For more information about flow monitoring equipment, see Figure 1 And related instructions.

[0056] Step 220, based on the gas-using enterprise management platform in the smart gas government safety supervision object platform, obtain the enterprise's current production data and production planning information.

[0057] The current production data refers to the production status of the product in the current preset time period of the enterprise. In some embodiments, the current production data may include the production channel and the current production of the production channel in the current preset time period. For example, (production line 1, current production 1), (production line 2, current production 2).

[0058] Production planning information refers to information related to the company's production planning. For example, production planning information may include production plans and programs formulated by the company, such as the planned output of products at each stage and the planned gas consumption at each stage. For example, the production planning information of a company that produces parts may include different processing stages, such as: ① transportation and storage of raw materials, ② production preparation, ③ blank manufacturing, ④ machining, ⑤ heat treatment, ⑥ assembly, ⑦ testing, ⑧ debugging, etc.

[0059] In some embodiments, the smart gas government safety supervision management platform 120 can obtain the current production data and production planning information uploaded by enterprise users through the gas use enterprise management platform 142 of the smart gas government safety supervision object platform 140.

[0060] Step 230, based on the enterprise's gas usage statistics, current production data and production planning information, determine the enterprise's production stage information.

[0061] Production stage information refers to information related to the production stage of the enterprise's use of gas. For example, production stage information includes the enterprise's current production stage, production channels, and the standards or requirements for gas use during the current production stage.

[0062] Different production stages may correspond to different gas supply states. In some embodiments, the production stages may be divided based on gas usage parameters. Gas usage parameters refer to data related to gas during the production process, such as whether gas is used, the gas usage rate, the gas usage amount, the gas usage method, etc. Among them, the gas usage method may include continuous gas supply or intermittent gas supply, etc.

[0063] In some embodiments, stages that require the use of gas and have similar or identical gas usage parameters can be divided into the same production stage, and stages that do not require the use of gas and / or have significantly different gas usage parameters can be divided into different production stages.

[0064] For example, in the actual production process, assuming that among the above-mentioned processing stages ①~⑧, only stages ③, ④, ⑤, and ⑦ need to use gas, and stages ①, ②, ⑥, and ⑧ do not need to use gas, then ①, ②, ⑥, and ⑧ are classified as production stage one, and stages ③, ④, ⑤, and ⑦ are further divided; if the gas usage parameters of stages ③, ④, ⑤, and ⑦ are different, the production stages are divided into: production stage two corresponding to ③, production stage two corresponding to ④, production stage three corresponding to ⑤, and production stage four corresponding to ⑦; if the gas usage parameters of stages ③, ④, ⑤, and ⑦ are the same, then ③, ④, ⑤, and ⑦ are classified as production stage two.

[0065] In some embodiments, the smart gas government safety supervision and management platform 120 can determine the production stage information of the enterprise based on the enterprise's gas usage statistics, current production data and the enterprise's production planning information.

[0066] For example, the smart gas government safety supervision and management platform 120 can compare the current production data and the company's gas usage statistics with the company's production planning information, determine similar stages as the same production stage, analyze and determine the company's production stage, and determine the production planning information corresponding to the production stage as the company's production stage information.

[0067] For example, if the current production data and gas usage statistics have reached the company's production planning information, if the current production data and gas usage statistics of production stage S1 have reached the minimum values ​​of the product's planned production and gas usage in the company's production planning information; and at the same time, the current production data and gas usage statistics of the next production stage S2 of production stage S1 do not reach the product's planned production and gas usage in the company's production planning information; then it means that the company is in production stage S2.

[0068] For example, there are three production stages in the production planning information, and the upper limit of the gas consumption corresponding to each production line is 20. There are 4 production lines in the first stage, namely production line a, production line b, production line c, and production line d. The planned output of the products in the first stage is 100~120, the production time is T1~T2, and the products produced include A1, A2, A3, and A4. There are 2 production lines in the second stage, namely production line e and production line f. Among them, the planned gas consumption of production line e is 20, and the planned gas consumption of production line f is 15. The planned output of the products in the second stage is 90~100, the production time is T3~T4, and the products B1 and B2 are produced. There is 1 production line in the third production stage, which is production line g, and the planned gas consumption of production line g is 10. The planned output of the products in the third stage is 120~150, the production time is T5~T6, and product C is produced.

[0069] The current gas usage statistics are as follows: the gas usage of production lines a~g are 20, 20, 20, 20, 12, 10, 0 respectively; the current output data are as follows: the product output of production lines a~g are 110, 115, 100, 120, 70, 65, 0 respectively. The gas usage of production lines a~d has reached the planned gas usage of 20 in the first phase, and the product output is within the planned product output of 100~120 in the first phase, indicating that the production in the first phase has ended. The gas usage of production lines e~f has not reached the planned gas usage of the second phase, and the product output has not reached the planned product output of 90~100 in the second phase, indicating that the production is in the second phase. The gas usage of production line g is 0, and the product output is 0, indicating that the third phase has not yet begun.

[0070] Therefore, it is concluded that the current production is in the second stage, and the smart gas government safety supervision management platform 120 can determine the production planning information corresponding to the second production stage as the production stage information of the enterprise. That is, the production stage information includes: there are 2 production lines in the second stage, namely production line e and production line f, among which, the execution standard of production line e is gas consumption 20, and the execution standard of production line f is gas consumption 15, the second stage product output is 90~100, the production time is T3~T4, and the production products B1 and B2.

[0071] Step 240, based on the enterprise's production stage information, obtain feedback information from the gas company management platform in the smart gas government safety supervision object platform.

[0072] Feedback information refers to the feedback from the gas company on the production stage information. In some embodiments, the feedback information may include the result of comparing the production stage information provided by the gas company with the information monitored by the government, and the result may be expressed as "information consistent" or "information inconsistent". If the production stage information provided by the gas company is consistent with the information monitored by the government, the result is "information consistent", and the feedback information includes the production stage information. Otherwise, the result is "information inconsistent", the gas company needs to update the production stage information, and the feedback information may include the updated production stage information.

[0073] In some embodiments, the smart gas government safety supervision management platform 120 can obtain feedback information uploaded by the gas company through the gas company management platform 141.

[0074] Step 250, obtaining alarm information and / or fault information, working parameters and hidden danger handling data of at least one group of gas fire fighting equipment of the enterprise. The gas fire fighting equipment includes at least one of an alarm device, an alarm self-checking device and a gas concentration detection device.

[0075] Alarm information refers to the alarm signal issued by gas fire fighting equipment when it detects a dangerous situation. Alarm information includes the alarm time and the ambient gas concentration data corresponding to the alarm time. Alarm information can include one or more forms, such as voice information, sound information, light information, etc.

[0076] The ambient gas concentration data refers to the gas concentration information measured by the gas concentration detection device, which can be expressed in numbers or levels.

[0077] Fault information refers to the information recorded when a gas fire fighting equipment fails or is abnormal. Fault information may include records of abnormal equipment operation status, sensor failure, and other problems.

[0078] Working parameters refer to relevant parameters when the gas fire fighting equipment is in operation. In some embodiments, the working parameters of the gas fire fighting equipment include the gas concentration alarm threshold, the hidden danger self-check cycle, and the alarm device self-check cycle. The hidden danger self-check cycle refers to the cycle of checking the gas concentration detection device. The alarm device self-check cycle refers to the cycle of checking the alarm device. The gas concentration alarm threshold refers to the minimum value for the alarm device to alarm.

[0079] Hidden danger handling data refers to case data on handling gas hidden dangers. Hidden danger handling data includes accident records of at least one gas fire-fighting equipment in the historical records of multiple enterprises, and the accident records include historical accident information. Historical accident information refers to information related to historical accidents, such as historical accident types, historical loss levels caused by historical accidents, historical affected scopes, and historical emergency measures triggered. Accident types may include failures and / or alarms, etc.

[0080] In some embodiments, the hidden danger handling data also includes the historical fire protection stage and historical fire protection risk level of the enterprise when the accident handling occurs, the historical working parameters of at least one fire protection equipment, and the historical fire protection control parameters after the accident. The historical fire protection control parameters include historical adjustment working parameters and historical enterprise fire protection spot check cycles.

[0081] For information on fire control parameters, adjustment of working parameters and enterprise fire inspection cycles, please refer to the following text.

[0082] In some embodiments, the smart gas government safety supervision and management platform 120 can obtain the alarm information and / or fault information, working parameters and hidden danger handling data of at least one group of gas fire-fighting equipment of the enterprise through various methods.

[0083] In some embodiments, the smart gas government safety supervision management platform 120 can obtain the alarm information and / or fault information and working parameters uploaded by the smart gas government safety supervision object platform 140 through the smart gas government safety supervision sensor network platform 130. The smart gas government safety supervision object platform 140 can obtain the alarm information and / or fault information and working parameters of at least one group of gas fire fighting equipment based on the gas company management platform 141.

[0084] The gas fire fighting equipment can obtain alarm information based on the alarm device and obtain fault information based on the alarm self-checking device. The alarm device can determine the alarm information based on the ambient gas concentration data and the gas concentration alarm threshold. For example, when the ambient gas concentration data is greater than or equal to the gas concentration alarm threshold, the alarm device records the alarm time and the corresponding ambient gas concentration data as the alarm information.

[0085] In some embodiments, the alarm self-checking device can automatically detect whether the gas concentration detection device is working properly based on the hidden danger self-checking cycle; and automatically detect whether the alarm device is working properly based on the alarm device self-checking cycle. In response to at least one of them being abnormal, the alarm self-checking device sends fault information to the smart gas government safety supervision object platform 140 and / or the smart gas government safety supervision management platform 120.

[0086] The alarm self-checking device can determine whether the gas concentration detection device and / or the alarm device are working properly by various methods. For example, the alarm self-checking device can send a handshake instruction to the gas concentration detection device and / or the alarm device by means of communication. If the gas concentration detection device and / or the alarm device accepts the handshake instruction, it means that the alarm device is communicating normally.

[0087] In some embodiments, the smart gas government safety supervision and management platform 120 can obtain the ambient gas concentration data of the gas concentration detection device, and check whether the frequency of obtaining the gas concentration data meets the preset requirements within the preset time period. If yes, it means that the gas concentration detection device is working normally, otherwise, the gas concentration detection device is working abnormally. When the gas concentration detection device is working normally, it is determined whether the ambient gas concentration in the alarm information issued by the alarm device is consistent with the ambient gas concentration detected by the gas concentration detection device. If they are consistent, it means that the alarm device is working normally, otherwise, the alarm device is working abnormally.

[0088] In some embodiments, the smart gas government safety supervision management platform 120 can determine hidden danger handling data through historical data.

[0089] Step 260, based on the enterprise's production stage information, feedback information, alarm information and / or fault information of at least one group of gas fire fighting equipment, working parameters and hidden danger handling data, evaluate the enterprise's fire risk level.

[0090] The fire risk level is a parameter reflecting the risk resistance of the gas fire fighting equipment. The higher the fire risk level, the stronger the risk resistance of the fire fighting equipment under the working parameters. In some embodiments, the fire risk level may include different levels, such as low risk, medium risk and high risk.

[0091] In some embodiments, the smart gas government safety supervision and management platform 120 can evaluate the enterprise's fire risk level in a variety of ways based on the enterprise's production stage information, feedback information, alarm information and / or fault information of at least one set of gas fire fighting equipment, working parameters and hidden danger handling data.

[0092] For example, the smart gas government safety supervision and management platform 120 can determine the alarm frequency and / or fault frequency based on the alarm information and / or fault information of at least one group of gas fire-fighting equipment; determine the danger factor of the fire-fighting equipment working parameters based on the company's production stage information, feedback information and hidden danger handling data; determine the fire score based on the alarm frequency and / or fault frequency and the danger factor; and determine the fire risk level by searching a preset table based on the fire score.

[0093] The alarm frequency refers to the number of alarms of the gas fire fighting equipment within a preset time period. The fault frequency refers to the number of faults of the gas fire fighting equipment within a preset time period. In some implementations, the smart gas government safety supervision and management platform 120 can count the alarm frequency of the preset time period from the alarm information, and / or count the fault frequency of the preset time period from the equipment fault information.

[0094] The risk factor refers to data used to assess the possibility of an accident under current working parameters. In some embodiments, the smart gas government safety supervision and management platform 120 can determine the actual production stage based on the production stage information and feedback information, find hidden danger processing data based on the actual production stage, and calculate the risk factor. The actual production stage information refers to the actual production stage information of the current stage of the enterprise, such as the updated production stage information obtained based on the feedback information.

[0095] For example, the smart gas government safety supervision and management platform 120 can count the accident frequencies of each enterprise under each historical working parameter in the hidden danger treatment data; compare the first similarity between the current working parameters of each enterprise and the historical working parameters in the hidden danger treatment data, count the historical accident frequencies corresponding to the historical working parameters with the highest first similarity in the hidden danger treatment data, and use the above-determined historical accident frequencies as the risk coefficients corresponding to the current working parameters. The historical accident frequency refers to the number of times a historical accident occurred within a preset historical time period.

[0096] For example, Company A has three records under working parameter x, of which production line 1 has had two accidents, production line 4 has had one accident, and Company A has a total of 10 records of accidents. Then the frequency of accidents under this working parameter is 30%.

[0097] The fire score refers to data used to reflect the safety level of fire protection facilities. The fire score can be expressed in numbers. For example, the fire score can be expressed as a number from 1 to 100. The higher the fire score, the safer the fire protection facilities.

[0098] In some embodiments, the smart gas government safety supervision management platform 120 can determine the firefighting score in a variety of ways based on the alarm frequency and / or failure frequency and the risk factor. For example, the firefighting score can be negatively correlated with the alarm frequency, failure frequency and risk factor.

[0099] For example, the fire protection score can be calculated by formula (1). Formula (1) is as follows:

[0100]

[0101] Among them, P is the fire protection score of the gas fire protection equipment under certain working parameters, and C is the risk factor of the gas fire protection equipment under the working parameters. , is a coefficient greater than 0, is the alarm frequency, The fault frequency.

[0102] In some embodiments, the smart gas government safety supervision management platform 120 can determine the fire risk level based on the fire score by searching a preset table. The preset table includes a mapping association between the fire score and the fire level. For example, 0-20 is level 4, 21-60 is level 3, 61-80 is level 2, and 81-100 is level 1. When the fire risk level of an enterprise is level 1, the enterprise has the highest risk resistance and the corresponding gas fire equipment has the lowest probability of fire risk.

[0103] For more information on how to assess a company's fire risk level, see Figure 3 and related instructions.

[0104] Step 270, determining the fire control parameters of the enterprise based on the fire risk level and hidden danger treatment data of the enterprise.

[0105] Fire control parameters refer to data used to control and manage gas fire equipment. In some embodiments, the fire control parameters may include at least one set of updated adjustment working parameters of gas fire equipment and a fire inspection cycle of an enterprise.

[0106] Adjusting the working parameters refers to the updated working parameters of the gas fire fighting equipment, for example, the updated gas concentration alarm threshold, hidden danger self-check cycle and alarm device self-check cycle.

[0107] The enterprise fire inspection cycle refers to the periodic arrangement of fire safety inspections and inspections on enterprises. For example, the enterprise fire inspection cycle may include the inspection cycle of at least one group of gas fire equipment. The enterprise fire inspection cycle may be a period of data of one or more groups of gas fire equipment automatically obtained by the smart gas government safety supervision and management platform 120, or a manual inspection cycle. For example, the manual inspection cycle is a period in which the government dispatches inspection personnel to conduct mandatory inspections of enterprise fire equipment. For example, the data of gas fire equipment of each enterprise is inspected once every twenty-four hours, and inspection personnel are dispatched to conduct mandatory inspections of enterprises once a month.

[0108] In some embodiments, the smart gas government safety supervision management platform 120 can obtain the enterprise fire inspection cycle uploaded by enterprise users in the gas use enterprise management platform 142 based on the smart gas government safety supervision sensor network platform 130.

[0109] The spot check of enterprise fire protection can include spot check of relevant parameters of gas fire protection equipment. The relevant parameters of gas fire protection equipment can include alarm information, ambient gas concentration data, fault information, etc.

[0110] In some embodiments, the smart gas government safety supervision management platform 120 can determine the fire control parameters of the enterprise based on the fire risk level and hidden danger processing data of the enterprise. For example, for a certain fire risk level of a certain enterprise, the accident records of the enterprise are retrieved from the hidden danger processing data, the number of accident records of each historical fire control parameter corresponding to the enterprise under the fire risk level is counted, and the corresponding historical fire control parameter with the least number of accident records is selected as the fire control parameter of the enterprise.

[0111] In some embodiments, the smart gas government safety supervision and management platform 120 can determine the estimated accident probability and estimated accident information of at least one group of gas fire-fighting equipment based on hidden danger processing data, working parameters of at least one group of gas fire-fighting equipment, at least one fire-fighting stage and fire-fighting risk level; determine the fire control parameters of the enterprise based on the estimated accident probability, estimated accident information, working parameters and a first preset threshold of at least one group of gas fire-fighting equipment.

[0112] Estimating accident probability refers to predicting the likelihood of accidents occurring in the future.

[0113] Predicted accident information refers to information related to the prediction of possible accidents in the future. Predicted accident information may include the type of accident that may occur, the extent of loss that may be caused by the accident, the scope that may be affected, and the emergency measures that may be triggered.

[0114] In some embodiments, the smart gas government safety supervision and management platform 120 can construct a first feature vector based on the working parameters of at least one group of gas fire-fighting equipment of a certain enterprise, at least one fire-fighting stage and fire-fighting risk level; construct a first reference vector based on the historical working parameters of at least one group of gas fire-fighting equipment in the same industry of the enterprise in the historical data of the hidden danger treatment data, at least one historical fire-fighting stage and historical fire-fighting risk level, calculate the second similarity between the first feature vector and the first feature vector, and count the number of accident records corresponding to the second similarity greater than a preset threshold; count the total number of accident records in the same industry of the enterprise in the hidden danger treatment data; determine the estimated accident probability and estimated accident information based on the number of accident records corresponding to the second similarity greater than the preset threshold and the total number of accident records.

[0115] Exemplarily, the total number of accident records is M, and the number of accident records corresponding to the second similarity greater than the preset threshold is N. If N is not equal to 0, the estimated accident probability of the gas fire fighting equipment is the ratio of the number of accident records N to the total number of accident records M. The estimated accident information is the accident information corresponding to the record with the highest second similarity among the N records.

[0116] If N is equal to 0, the estimated accident probability of the gas fire fighting equipment is set to none or the default probability of the accident is confirmed by searching the preset table. The preset table includes the mapping relationship between different accident types and default probabilities. The default probability is the probability of occurrence of different accidents confirmed based on experience and can be preset manually.

[0117] The first preset threshold refers to a preset critical value for judging the possibility of an accident. In some embodiments, the first preset threshold is determined based on the probability of an accident that the gas fire fighting equipment can withstand and is less than the maximum probability of an accident. The maximum probability of an accident can be determined based on the hidden danger processing data. For example, in the hidden danger processing data, the frequency of occurrence of different accident types of different companies in the company's historical records is counted, and the maximum value is used as the maximum probability of an accident.

[0118] In some embodiments, the smart gas government safety supervision management platform 120 can compare the estimated accident probability with the first preset threshold value. When the estimated accident probability is less than the first preset threshold value, the historical fire control parameter corresponding to the accident in the hidden danger handling data is determined as the fire control parameter; when the estimated accident probability is greater than or equal to the first preset threshold value, the preset fire control parameter is set as the fire control parameter. The preset fire control parameter can be preset manually. For example, the highest degree of protection can be set as the preset fire control parameter. When the preset fire control parameter is set to the highest degree of protection, the corresponding gas fire fighting equipment has the lowest probability of an accident.

[0119] In some embodiments of the present specification, the smart gas government safety supervision and management platform can estimate the probability of accidents occurring in gas fire fighting equipment, thereby taking corresponding response measures for gas fire fighting equipment with a high probability of accidents, thereby ensuring the safe operation of gas fire fighting.

[0120] In some embodiments, different production stages have different first preset thresholds, and the first preset threshold of the current production stage is related to the number of firefighting stages included in the current production stage. Figure 3 and Figure 4 And related instructions.

[0121] In some embodiments, the first preset threshold of the current production stage is negatively correlated with the number of firefighting stages included in the current production stage. That is, the more the number of firefighting stages in the current production stage, the smaller the first preset threshold of the current production stage.

[0122] The more firefighting stages there are in the current production stage, the more complex the gas usage is and the higher the frequency of changes. This means that the reliability of gas usage is reduced, so more reliable firefighting control measures need to be taken. In the embodiments of this specification, the firefighting control is made more reliable by adjusting the first preset threshold value to a smaller value, so that a higher degree of protection setting can be adopted.

[0123] In some embodiments, the smart gas government safety supervision and management platform 120 can determine the estimated accident probability and estimated accident information of at least one group of gas fire fighting equipment based on at least one group of gas fire fighting equipment working parameters, at least one fire fighting stage, fire fighting risk level and hidden danger handling data based on a preset algorithm. For more information about the fire fighting stage, please refer to Figure 3 and Figure 4 And related instructions.

[0124] The preset algorithm is a pre-set algorithm program. For example, the preset algorithm may be: constructing a second feature vector based on the working parameters and fire risk level of at least one gas fire fighting device, constructing a second reference vector based on the historical working parameters and historical fire risk level of at least one gas fire fighting device in the hidden danger handling data, calculating the third similarity between the second feature vector and the second reference vector, counting the accident records corresponding to all second reference vectors whose third similarity meets the preset ranking and is higher than the preset threshold, and determining the estimated accident probability and estimated accident information based on the fire fighting stage, the third similarity and the accident records corresponding to all second reference vectors.

[0125] The preset ranking may be the top n of the second similarity ranking, where n is positively correlated with the number of fire fighting stages of the enterprise, for example, n may be equal to the number of fire fighting stages. The preset threshold may be preset according to computing power.

[0126] In some embodiments, the smart gas government safety supervision and management platform 120 can count the frequency of subsequent accidents of the second reference vectors whose third similarity meets the preset ranking and is higher than the preset threshold, and determine the estimated accident probability in a variety of ways. For example, the product of the lowest frequency of accidents and the corresponding third similarity is used as the estimated accident probability of the gas fire fighting equipment, and the historical accident information corresponding to the second reference vector with the lowest frequency of accidents is used as the estimated accident information; for another example, the average value of the frequency of subsequent accidents is used as the estimated accident probability, and the historical accident information corresponding to the second reference vector with the highest third similarity is used as the estimated accident information.

[0127] For example, enterprise I is a parts factory, the fire risk level is the second level, the working parameter of the fire equipment before the accident handling is K1, and the number of fire stages of enterprise I is 3, then the preset number is set to 3. The smart gas government safety supervision and management platform 120 can retrieve the historical records of all parts factories with the second level of fire risk in the hidden danger handling data, and select the accident records corresponding to the parts factories with the top 3 third similarity rankings and greater than the preset threshold.

[0128] If three records are retrieved in total: for accident record 1, the working parameters of the fire-fighting equipment are adjusted to K2 after the accident, and the frequency of accidents caused by the subsequent operation of the fire-fighting equipment according to the working parameters K2 is counted. If two similar accident records appear within three months after the accident, the frequency of accidents is 2 / 3; for accident record 2, similarly, if a similar accident record appears within 4 months, the frequency of accidents is 1 / 4; for record 3, the working parameters of the fire-fighting equipment are adjusted to K4 after the accident, and no accident records of accidents caused by the subsequent operation of the fire-fighting equipment according to the working parameters K4 after the accident are found, the accident frequency can be recorded as the preset frequency a, which is the minimum frequency of subsequent accidents in all accident records corresponding to the working parameters and fire protection levels of record 3 in the hidden danger handling data, assuming that a is 1 / 5. The frequency of subsequent accidents in record 3 is the lowest. Assuming that the second similarity between record 3 and enterprise I is calculated to be 97%, the second similarity is calculated as the product of 97% and the frequency of subsequent accidents in record 3, which is 1 / 5, and the estimated accident probability of gas fire-fighting equipment is 19.4%. The accident information corresponding to record 3 is used as the estimated accident information.

[0129] By determining the estimated accident probability and its estimated accident information through a preset algorithm, the corresponding estimated accident probability and its estimated accident information of the gas fire-fighting equipment under different fire control parameters, different fire-fighting stages and different fire risk levels can be determined, thereby making a more accurate prediction of possible accidents.

[0130] Step 280, determining an update instruction based on adjusting the operating parameters.

[0131] In some embodiments, the smart gas government safety supervision management platform 120 can obtain corresponding adjustment working parameters in the fire control parameters, and determine update instructions based on the adjustment working parameters.

[0132] Update instructions refer to commands that control gas fire-fighting equipment to update relevant parameters.

[0133] In some embodiments, the smart gas government safety supervision management platform 120 can determine the update instructions in a variety of ways based on the adjustment of the working parameters. For example, a standard database is preset, and the standard database contains standard working parameters and corresponding standard update instructions. Among them, the standard working parameters and their corresponding standard update instructions are determined based on historical experience, and serve as reference working parameters and their corresponding update instructions.

[0134] The smart gas government safety supervision management platform 120 can compare the obtained adjusted working parameters with the standard working parameters in the standard database. The similarity comparison can be calculated by Euclidean distance, cosine similarity, etc. When a standard working parameter with a similarity greater than a preset similarity is found, the standard update instruction corresponding to the standard working parameter is determined as the final update instruction.

[0135] Step 290: Send the update instruction to at least one corresponding group of gas fire fighting equipment to control the gas fire fighting equipment to be updated.

[0136] In some embodiments, the smart gas government safety supervision and management platform 120 can send update instructions to at least one corresponding group of gas fire-fighting equipment to control the gas fire-fighting equipment to update. The gas fire-fighting equipment can update the working parameters to adjusted working parameters based on the update instructions and operate according to the updated adjusted working parameters.

[0137] The embodiments of this specification can evaluate the fire risk level of an enterprise by monitoring the enterprise's gas consumption statistics, current production data and production planning information, and timely discover potential safety hazards, take corresponding control measures for enterprises with high fire risk levels, and improve fire safety. By determining fire control parameters and updating gas fire fighting equipment, the deployment of fire fighting resources is optimized, and the efficiency and accuracy of emergency response are improved.

[0138] Figure 3 is an exemplary flow chart for determining a fire risk level according to some embodiments of the present specification.

[0139] In some embodiments, process 300 may be performed by the smart gas government safety supervision management platform 120. Figure 3 As shown, process 300 includes the following steps 310 to 350.

[0140] Step 310: Determine at least one fire protection stage of the enterprise based on the production stage information and feedback information of the enterprise. For more information about the production stage information and feedback information, see Figure 2 .

[0141] Firefighting stages refer to the stages divided according to firefighting-related requirements during the production process of an enterprise. A production stage may correspond to one or more firefighting stages, and the firefighting risks of gas in different firefighting stages in the same production stage are different. For example, in the same heat treatment stage, assuming that the heat treatment stage uses gas periodically to process intermediate products, the firefighting risks of gas during the period of using gas and during the period of not using gas are different; assuming that the heat treatment stage uses gas continuously to process intermediate products, the temperature in the workshop is different when gas is just used for processing and the temperature in the workshop after a period of use. After a period of use, the temperature in the workshop is higher, the use of gas is more dangerous, and the firefighting risk is higher.

[0142] In some embodiments, for an enterprise, the smart gas government safety supervision management platform 120 can obtain the actual production stage information based on the production stage information and its corresponding feedback information, and then search the preset table according to the actual production stage information to obtain the corresponding fire protection stage.

[0143] The preset table includes the corresponding relationship between production stage information and fire protection stage division. The preset table can count the actual frequency of accidents that occurred in each production stage in the historical data of the enterprise after prevention according to different fire protection stage divisions, and store the fire protection stage division with the lowest accident frequency and its corresponding production stage information in the preset table.

[0144] Step 320, determining the number of centralized uploads based on at least one firefighting stage.

[0145] The number of centralized uploads refers to the number of times the relevant parameters of the gas fire-fighting equipment are uploaded to the Smart Gas Government Safety Supervision Service Platform 110.

[0146] In some embodiments, the number of centralized uploads is positively correlated with the number of firefighting stages. For example, if the number of firefighting stages is three, the number of centralized uploads can be determined as three times; if the number of firefighting stages is five, the number of centralized uploads can be determined as five times.

[0147] Step 330, based on the number of centralized uploads, the alarm information and / or fault information and working parameters of at least one group of gas fire-fighting equipment are centrally uploaded to the smart gas government safety supervision service platform.

[0148] In some embodiments, the smart gas government safety supervision management platform 120 can centrally upload the alarm information and / or fault information and working parameters of at least one group of gas fire fighting equipment of at least one enterprise to the smart gas government safety supervision service platform 110. This facilitates the smart gas government safety supervision service platform 110 to perform centralized processing and global monitoring, and determine whether there are potential hidden dangers.

[0149] Step 340, in response to obtaining monitoring feedback from the smart gas government safety supervision service platform that there is no abnormality, evaluate the enterprise's fire risk level based on at least one fire protection stage of the enterprise, alarm information and / or fault information, working parameters and hidden danger handling data of at least one group of gas fire protection equipment.

[0150] For information on firefighting stages, firefighting risk levels, alarm information and / or fault information, operating parameters, hidden danger handling data and firefighting risk levels, see Figure 2 And related instructions.

[0151] Monitoring feedback refers to the feedback from government users on abnormal conditions of gas fire protection. For example, monitoring feedback can be a Boolean value, indicating whether there is an abnormality. For example, an abnormality is represented by 1, and no abnormality is represented by 0.

[0152] In some embodiments, when the monitoring feedback shows that there is no abnormality, the smart gas government safety supervision management platform 120 can determine the enterprise's fire risk level through vector matching based on at least one fire fighting stage of the enterprise, alarm information and / or fault information of at least one group of gas fire fighting equipment, working parameters and hidden danger handling data.

[0153] For example, for an enterprise, the smart gas government safety supervision and management platform 120 can count the number of faults / alarms based on the alarm information and / or fault information of at least one group of gas fire-fighting equipment; retrieve the number of accident records corresponding to the current fire-fighting stage, the number of faults / alarms, and the records whose matching similarity with at least one group of gas fire-fighting equipment working parameters is greater than a preset threshold from the hidden danger handling data as the first case number; retrieve the total number of accident records of all accidents of the enterprise from the hidden danger handling data as the second case number; retrieve the total number of accident records of the same industry of the enterprise from the hidden danger handling data as the third case number; determine the fire-fighting score based on the first case number, the second case number, and the third case number, and determine the fire-fighting risk level based on the fire-fighting score.

[0154] In some embodiments, the smart gas government safety supervision and management platform 120 can construct a feature vector based on the current fire fighting stage, the number of faults / alarms, and at least one set of working parameters of gas fire fighting equipment, and calculate the vector similarity between the feature vector and the reference vector in the hidden danger handling data. The reference vector can be based on the fire fighting stage, the number of faults / alarms, and at least one set of working parameters of gas fire fighting equipment in the historical data.

[0155] In some embodiments, the fire fighting score is positively correlated with the first case number and the third case number, and negatively correlated with the second case number. Exemplarily, the smart gas government safety supervision management platform 120 can determine the fire fighting score based on formula (2). Formula (2) is as follows:

[0156] Firefighting score = k × number of first cases × number of third cases / number of second cases2 (2)

[0157] Where k is a coefficient greater than 0. For more information about fire protection scores, see Figure 2 .

[0158] In some embodiments, the smart gas government safety supervision management platform 120 can determine the fire risk level based on the fire score by searching a preset table. For details, see Figure 2 And related instructions.

[0159] Step 350, in response to obtaining monitoring feedback as abnormal from the smart gas government safety supervision service platform, the fire risk level is set to the highest risk level.

[0160] In some embodiments, when the monitoring feedback is abnormal, the smart gas government safety supervision management platform 120 can set the fire risk level of at least one enterprise to the corresponding highest fire risk level. The highest risk level refers to the fire safety risk level with the strongest prevention and control capabilities for fire risks. For example, the fire risk levels include level 1 to level 4, and level 4 has the strongest prevention and control capabilities for fire risks, so the fire risk level is set to level 4.

[0161] Dividing the stage with higher risk of gas fire hazards into one or more sub-stages, and dividing the stage with lower risk of gas fire hazards into one or more sub-stages, and dividing the fire fighting stages according to fire risks is more in line with gas fire supervision requirements, thereby making the determined fire risk level more realistic.

[0162] Figure 4 is an exemplary schematic diagram of a fire fighting stage determination model according to some embodiments of the present specification.

[0163] In some embodiments, the smart gas government safety supervision management platform 120 can determine at least one firefighting stage 430 through a firefighting stage determination model 420 based on the enterprise's basic information 411, production planning information 412, production stage information 413 and feedback information 414.

[0164] Basic enterprise information refers to information related to the enterprise's own fire safety. For example, enterprise scale, number of enterprise fire drills, and product hazard. Enterprise scale can include the enterprise's land area, number of employees, output value, etc.; the number of enterprise fire drills can be the number of fire drills conducted by the enterprise since its establishment or within a preset time period; product hazard refers to the degree of hazard of the products produced by the enterprise during the production process. Product hazard includes flammability and explosiveness. Products in the production process include intermediate products and final products.

[0165] In some embodiments, basic enterprise information is obtained based on the smart gas government safety supervision object platform 140. For production planning information, production stage information and feedback information, please refer to Figure 2 For the firefighting stage, see Figure 3 Related instructions.

[0166] The fire fighting stage determination model is a model used to determine the fire fighting stage. In some implementations, the fire fighting stage determination model may be a machine learning model, such as a neural network (NN) model, a deep neural network (DNN) model, or at least one of other models.

[0167] In some embodiments, the fire fighting stage determination model can be obtained by training a large number of first training samples and first labels corresponding to the first training samples. In some embodiments, a plurality of first training samples with first labels can be input into the initial fire fighting stage determination model, and a loss function can be constructed by the first labels and the results of the initial fire fighting stage determination model. The parameters of the initial fire fighting stage determination model can be iteratively updated based on the loss function by gradient descent or other methods. When the preset conditions are met, the model training is completed, and a trained fire fighting stage determination model is obtained. The preset conditions can be that the loss function converges, the number of iterations reaches a threshold, etc.

[0168] Each group of training samples in the first training samples may include sample enterprise basic information, sample production planning information, sample production stage information, and sample feedback information in the sample data. The first training samples may be obtained through historical data. In some embodiments, the actual setting of the corresponding firefighting stage when the least accidents occur in subsequent actual firefighting monitoring may be used as the first label corresponding to the first training sample. The first label may be obtained through manual labeling or automatic labeling.

[0169] In some embodiments, the fire fighting stage determination model includes at least a first stage of training, which includes: training based on a first training data set; validating based on a first validation set; and testing based on a first test set.

[0170] In some embodiments, the first training set, the first test set, and the first validation set include historical production stage information extracted from historical data and its corresponding historical feedback information and historical enterprise basic information. The ratio of the data volume of the first training set, the data volume of the first test set, and the data volume of the first validation set is a first preset ratio. The first preset ratio can be set in advance, for example, 8:1:1.

[0171] In some embodiments, there is no data overlap among the first training set, the first test set, and the first validation set. No data overlap means that the same piece of data can only exist in one of the first training set, the first test set, and the first validation set.

[0172] In some embodiments, the sample statistical difference of the first training set is greater than a preset difference threshold. The sample statistical difference reflects the sample diversity of the first training set. The greater the sample diversity, the greater the sample statistical difference.

[0173] In some embodiments, the smart gas government safety supervision management platform 120 can quantify each group of historical production stage information and its corresponding historical feedback information and historical enterprise basic information in the first training set into numbers, and construct a digital vector; calculate the vector distance between two samples in the first training set, such as the cosine distance; calculate the statistical values ​​of multiple vector distances, such as the variance; the larger the variance, the greater the statistical difference of the samples.

[0174] The preset difference threshold is a critical value of the preset sample statistical difference. In some embodiments, the preset difference threshold is related to the statistical value of the severity of historical gas fire events. The statistical value can be a variance, and the larger the variance of the severity of historical gas fire events, the larger the preset difference threshold.

[0175] By determining the statistical differences of the samples, the model can be made more robust and prevent overfitting. The larger the variance of the severity of the gas fire incident, the more uncertain the gas accident is and the more potential impacts involved. Therefore, the preset difference threshold can be increased to enable the fire stage determination model to learn from a wider distribution of data samples to more accurately learn the prediction of the target. Through the first training process, the stability and accuracy of the fire stage determination model can be improved.

[0176] Figure 5 is an exemplary schematic diagram of a probability determination model according to some embodiments of the present specification.

[0177] In some embodiments, the smart gas government safety supervision and management platform 120 can determine the estimated accident probability 530 of at least one group of gas fire-fighting equipment based on the working parameters 511 and fire risk level 512 of at least one group of gas fire-fighting equipment through a probability determination model 520.

[0178] The probability determination model is a model used to determine the estimated accident probability. In some implementations, the probability determination model can be a machine learning model, such as a neural network (NN) model, a deep neural network (DNN) model, or at least one of other models.

[0179] In some embodiments, the probability determination model can be trained based on the second training sample and the second label. The training process of the probability determination model is similar to the training process of the firefighting stage determination model. For details, see Figure 4 And related instructions.

[0180] Each group of training samples in the second training samples may include sample working parameters and sample fire risk levels of sample gas fire fighting equipment of a sample enterprise. The second training data set may be generated based on hidden danger processing data.

[0181] In some embodiments, the smart gas government safety supervision and management platform 120 can match the hidden danger handling data based on the second training sample, and use the obtained accident probability as the second label corresponding to the second training sample.

[0182] For example, for a set of accident records 1 corresponding to the second training data set, a second feature vector is constructed based on accident record 1, and the accident records corresponding to all second reference vectors whose second similarity with the working parameters and fire risk level corresponding to record 1 meets the preset ranking and is higher than the preset threshold are searched in the hidden danger handling data, and the frequency of subsequent accidents is calculated. The lowest accident frequency is used as the label of accident record 1. For another example, the average of the subsequent accident frequencies is used as the label of accident record 1. For more information about the second similarity, see Figure 2 .

[0183] Some embodiments of the present specification determine the estimated accident probability through a probability determination model based on working parameters and fire risk levels, which can improve the accuracy and efficiency of data processing and make the estimated accident probability more accurate.

[0184] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0185] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0186] In addition, the order of processing elements and sequences, the use of alphanumeric characters, or the use of other names described in this specification are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some of the invention embodiments currently considered useful through various examples, it should be understood that such details are only for illustrative purposes. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0187] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. In fact, the features of the embodiment are less than all the features of the single embodiment disclosed above.

[0188] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used for the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification are approximate values, which can be changed according to the required characteristics of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the method of general digit retention. Although the numerical domains and parameters used to confirm the breadth of the range in some embodiments of this specification are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0189] Each patent, patent application, patent application publication and other materials, such as articles, books, specifications, publications, documents, etc., cited in this specification are hereby incorporated by reference in their entirety. Except for application history documents that are inconsistent with or conflicting with the contents of this specification. It should be noted that if the descriptions, definitions, and / or use of terms in the materials attached to this specification are inconsistent or conflicting with the contents described in this specification, the descriptions, definitions and / or use of terms in this specification shall prevail.

[0190] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A smart gas fire protection linkage method based on government safety supervision, characterized in that: The method is executed by a smart gas government safety supervision management platform based on a smart gas-fire linkage Internet of Things system for government safety supervision, and includes: Obtain gas consumption statistics of one or more enterprises based on one or more flow monitoring devices controlled by the gas equipment object platform; Based on the gas user enterprise management platform in the smart gas government safety supervision object platform, the current production data and production planning information of the enterprise are obtained; Determining the production stage information of the enterprise based on the gas usage statistics information of the enterprise, the current production data and the production planning information; Based on the production stage information of the enterprise, feedback information is obtained from the gas company management platform in the smart gas government safety supervision object platform; Acquire alarm information and / or fault information, working parameters and hidden danger handling data of at least one group of gas fire fighting equipment of the enterprise, wherein the gas fire fighting equipment includes at least one of an alarm device, an alarm self-checking device and a gas concentration detection device; Based on the production stage information of the enterprise, the feedback information, the alarm information and / or the fault information of the at least one group of gas fire fighting equipment, the working parameters and the hidden danger handling data, the fire risk level of the enterprise is evaluated, including: Determine at least one fire protection stage of the enterprise based on the production stage information of the enterprise and the feedback information; wherein the fire protection stage refers to a stage divided according to fire protection-related requirements during the production process of the enterprise; Determining the number of concentrated uploads based on the at least one firefighting stage; Based on the number of centralized uploads, the alarm information and / or the fault information and the working parameters of the at least one group of gas fire fighting equipment are centrally uploaded to the smart gas government safety supervision service platform; In response to obtaining monitoring feedback from the smart gas government safety supervision service platform that there is no abnormality, based on the at least one fire fighting stage of the enterprise, the alarm information and / or the fault information of the at least one group of gas fire fighting equipment, the working parameters and the hidden danger handling data, the fire fighting risk level of the enterprise is evaluated; In response to obtaining the monitoring feedback from the smart gas government safety supervision service platform as abnormal, setting the fire risk level to the highest risk level; Determining fire control parameters of the enterprise based on the fire risk level of the enterprise and the hidden danger treatment data includes: Based on the hidden danger processing data, the working parameters of the at least one group of gas fire fighting equipment, at least one fire fighting stage and the fire fighting risk level, determining the estimated accident probability and the estimated accident information of the at least one group of gas fire fighting equipment, including: constructing a second feature vector based on the working parameters and the fire fighting risk level of the at least one group of gas fire fighting equipment, constructing a second reference vector based on the historical working parameters and the historical fire fighting risk level of the at least one group of gas fire fighting equipment in the hidden danger processing data, calculating the third similarity between the second feature vector and the second reference vector, counting the accident records corresponding to the second reference vector whose third similarity meets a preset ranking and is higher than a preset threshold, and determining the estimated accident probability and the estimated accident information of the at least one group of gas fire fighting equipment based on the at least one fire fighting stage, the third similarity and the accident records corresponding to the second reference vector; Determine the fire control parameters of the enterprise based on the estimated accident probability, the estimated accident information, the operating parameters and the first preset threshold of the at least one group of gas fire fighting equipment, wherein the fire control parameters include at least one group of updated adjusted operating parameters of gas fire fighting equipment and the enterprise fire inspection cycle; Based on the adjustment working parameters, determining an update instruction; The update instruction is sent to at least one corresponding group of gas fire fighting equipment to control the gas fire fighting equipment to be updated.

2. The method according to claim 1, characterized in that: Determining at least one firefighting stage of the enterprise based on the production stage information and the feedback information of the enterprise comprises: Based on the basic information of the enterprise, the production planning information, the production stage information and the feedback information, at least one firefighting stage is determined through a firefighting stage determination model, wherein the firefighting stage determination model is a machine learning model, and the basic information of the enterprise is obtained based on the smart gas government safety supervision object platform, wherein the firefighting stage determination model refers to at least one of a neural network model and a deep neural network model; the firefighting stage determination model is obtained by training a large number of first training samples and first labels corresponding to the first training samples.

3. A smart gas-fire linkage Internet of Things system based on government safety supervision, characterized in that: It includes a smart gas government safety supervision service platform, a smart gas government safety supervision management platform, a smart gas government safety supervision sensor network platform, a smart gas government safety supervision object platform, a gas company sensor network platform, a gas equipment object platform, a smart gas user platform and a smart gas service platform. The smart gas government safety supervision object platform includes a gas company management platform and a gas user enterprise management platform. The gas equipment object platform is configured to control one or more flow monitoring devices to obtain gas usage statistics of one or more enterprises; The gas-using enterprise management platform is configured to obtain current production data and production planning information of the enterprise; The smart gas government safety supervision and management platform is configured as follows: Determining the production stage information of the enterprise based on the gas usage statistics information of the enterprise, the current production data and the production planning information; Based on the production stage information of the enterprise, feedback information is obtained from the gas company management platform in the smart gas government safety supervision object platform; Acquire alarm information and / or fault information, working parameters and hidden danger handling data of at least one group of gas fire fighting equipment of the enterprise, wherein the gas fire fighting equipment includes at least one of an alarm device, an alarm self-checking device and a gas concentration detection device; Based on the production stage information of the enterprise, the feedback information, the alarm information and / or the fault information of the at least one group of gas fire fighting equipment, the working parameters and the hidden danger handling data, the fire risk level of the enterprise is evaluated, including: Determine at least one fire protection stage of the enterprise based on the production stage information of the enterprise and the feedback information; wherein the fire protection stage refers to a stage divided according to fire protection-related requirements during the production process of the enterprise; Determining the number of concentrated uploads based on the at least one firefighting stage; Based on the number of centralized uploads, the alarm information and / or the fault information and the working parameters of the at least one group of gas fire fighting equipment are centrally uploaded to the smart gas government safety supervision service platform; In response to obtaining monitoring feedback from the smart gas government safety supervision service platform that there is no abnormality, based on the at least one fire fighting stage of the enterprise, the alarm information and / or the fault information of the at least one group of gas fire fighting equipment, the working parameters and the hidden danger handling data, the fire fighting risk level of the enterprise is evaluated; In response to obtaining the monitoring feedback from the smart gas government safety supervision service platform as abnormal, setting the fire risk level to the highest risk level; Determining fire control parameters of the enterprise based on the fire risk level of the enterprise and the hidden danger treatment data includes: Based on the hidden danger processing data, the working parameters of the at least one group of gas fire fighting equipment, at least one fire fighting stage and the fire fighting risk level, determining the estimated accident probability and the estimated accident information of the at least one group of gas fire fighting equipment, including: constructing a second feature vector based on the working parameters and the fire fighting risk level of the at least one group of gas fire fighting equipment, constructing a second reference vector based on the historical working parameters and the historical fire fighting risk level of the at least one group of gas fire fighting equipment in the hidden danger processing data, calculating the third similarity between the second feature vector and the second reference vector, counting the accident records corresponding to the second reference vector whose third similarity meets a preset ranking and is higher than a preset threshold, and determining the estimated accident probability and the estimated accident information of the at least one group of gas fire fighting equipment based on the at least one fire fighting stage, the third similarity and the accident records corresponding to the second reference vector; Determine the fire control parameters of the enterprise based on the estimated accident probability, the estimated accident information, the operating parameters and the first preset threshold of the at least one group of gas fire fighting equipment, wherein the fire control parameters include at least one group of updated adjusted operating parameters of gas fire fighting equipment and the enterprise fire inspection cycle; Based on the adjustment working parameters, determining an update instruction; The update instruction is sent to at least one corresponding group of gas fire fighting equipment to control the gas fire fighting equipment to be updated.

4. The system according to claim 3, characterized in that The smart gas government safety supervision and management platform is further configured as follows: Based on the basic information of the enterprise, the production planning information, the production stage information and the feedback information, at least one firefighting stage is determined through a firefighting stage determination model, wherein the firefighting stage determination model is a machine learning model, and the basic information of the enterprise is obtained based on the smart gas government safety supervision object platform, wherein the firefighting stage determination model refers to at least one of a neural network model and a deep neural network model; the firefighting stage determination model is obtained by training a large number of first training samples and first labels corresponding to the first training samples.

Images