Intelligent fuel gas distribution pipeline purification method and Internet of Things system

Abstract

The invention provides an intelligent gas distribution pipeline purification method and an Internet of Things system. The method comprises the steps that the actual cleanliness of a target branch conveying pipeline is determined based on the initial cleanliness of gas to be conveyed, a first pipeline feature and a first gas feature related to a main pipeline, and a second pipeline feature and a second gas feature related to the target branch conveying pipeline; determining a target cleanliness based on the terminal user features; on the basis of the initial cleanliness and the target cleanliness, cleanliness deviation is determined, then a purification instruction is generated, and a purification device in the target branch conveying pipeline is controlled to conduct fuel gas purification; and responding to execution of the purification instruction, generating a flow speed regulation and control instruction, and regulating and controlling the opening degrees of speed regulation valves in the main pipeline and the target branch pipeline. By means of the method and the Internet of Things system, the fuel gas can be purified in time, and the fuel gas cleanliness of a terminal user is guaranteed; the opening degree of the speed regulating valve is regulated and controlled in time, interference of the purification device on gas transportation is reduced, and normal gas transportation is guaranteed.

Description

Technical Field

[0001] This specification relates to the field of gas purification, and particularly to a purification method for intelligent gas transmission pipelines and an Internet of Things system. Background Art

[0002] In the process of gas transmission management, gas metering stations or pressure regulating stations will purify gas impurities, but it is still possible that the impurities are not completely removed, so there is a certain amount of impurity residue in the gas transported out of the station. In addition, during the process of transporting gas through the pipeline network to users, due to reasons such as long service life of some gas pipelines, pipeline aging, and microbial corrosion, impurities in the pipeline are mixed into the transported gas, resulting in poor gas cleanliness. And some users, especially industrial users, need gas with better cleanliness to reduce the impact on equipment and products. How to purify the gas in the pipeline network to enable users to obtain gas that meets the requirements is an urgent problem to be solved.

[0003] Regarding the problem of gas purification, the invention patent application of CN105132060A discloses a device and method for purifying CO2 in natural gas by a cryogenic pressure swing adsorption process. This method mainly purifies CO2 in natural gas produced in oil and gas fields and does not involve the purification of gas during transportation at gas metering stations.

[0004] Therefore, it is desirable to provide a purification method for intelligent gas transmission pipelines and an Internet of Things system to enable users to obtain gas with better cleanliness. Summary of the Invention

[0005] The invention content includes a purification method for intelligent gas distribution pipelines based on the Internet of Things. The purification method for intelligent gas distribution pipelines based on the Internet of Things includes: determining the actual cleanliness of the target distribution pipeline based on the initial cleanliness of the gas to be transported, the first pipeline characteristics, the first gas characteristics, the second pipeline characteristics, and the second gas characteristics; the first pipeline characteristics and the first gas characteristics are related to the main pipeline in the gas pipeline network, the second pipeline characteristics and the second gas characteristics are related to the target distribution pipeline in the gas pipeline network, and the first pipeline characteristics, the first gas characteristics, the second pipeline characteristics, and the second gas characteristics are obtained from the intelligent gas device object platform; determining the target cleanliness based on the terminal user characteristics; the terminal user characteristics are obtained from the intelligent gas government safety supervision and management platform; determining the cleanliness deviation based on the initial cleanliness and the target cleanliness; generating a purification instruction based on the cleanliness deviation and sending the purification instruction to the intelligent gas device object platform to control the purification device in the target fraction pipeline to perform gas purification; in response to the start of execution of the purification instruction, obtaining the first flow rate data of the main pipeline and the second flow rate data of the target distribution pipeline during the purification period from the intelligent gas device object platform; generating a flow rate regulation instruction based on the first flow rate data and the second flow rate data and sending the flow rate regulation instruction to the intelligent gas device object platform to regulate the opening degree of the speed regulating valves in the main pipeline and the target distribution pipeline.

[0006] The invention content also includes an intelligent gas distribution pipeline purification Internet of Things system, including an intelligent gas government safety supervision and management platform, an intelligent gas government safety supervision sensor network platform, an intelligent gas government safety supervision object platform, an intelligent gas company sensor network platform, and an intelligent gas device object platform; the intelligent gas government safety supervision object platform includes an intelligent gas company management platform, and the intelligent gas company management platform is configured to execute the foregoing intelligent gas distribution pipeline purification method.

[0007] The foregoing intelligent gas distribution pipeline purification method and Internet of Things system can achieve the following beneficial effects including but not limited to: through the formation of an information operation closed-loop among the functional platforms based on the Internet of Things, the government department can effectively supervise and cooperate with the gas company, and coordinate and operate regularly under the unified management of the gas company management platform, realizing the informatization and intelligence of gas safety supervision and gas purification; timely generating a purification instruction to control the purification device to purify the gas, ensuring the gas cleanliness at the terminal user; timely regulating the opening degree of the speed regulating valve to reduce the interference of the purification device on the gas movement direction and ensure the normal transportation of the gas. Description of the Drawings

[0008] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same reference numerals represent the same structures, where: Figure 1 is a platform structure diagram of the intelligent gas transmission pipeline purification Internet of Things system shown in some embodiments of this specification; Figure 2 is an exemplary flowchart of an intelligent gas transmission pipeline purification method based on the Internet of Things shown in some embodiments of this specification; Figure 3 is a schematic diagram of determining the actual cleanliness shown in some embodiments of this specification; Figure 4 is an exemplary flowchart of a method for generating a purification instruction shown in some embodiments of this specification.

[0009] Description of reference numerals: 100 - intelligent gas transmission pipeline purification Internet of Things system; 110 - intelligent gas government safety supervision management platform; 120 - intelligent gas government safety supervision sensor network platform; 130 - intelligent gas government safety supervision object platform; 131 - intelligent gas company management platform; 140 - intelligent gas company sensor network platform; 150 - intelligent gas equipment object platform; 160 - intelligent gas company service platform; 170 - gas user platform; 310 - first pipeline feature; 320 - second pipeline feature; 330 - pipeline network gas feature; 340 - gas feature map; 350 - prediction model; 360 - actual cleanliness. Detailed implementation manners

[0010] To more clearly illustrate the technical solutions of the embodiments of this specification, the accompanying drawings required for the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some examples or embodiments of this specification. For those of ordinary skill in the art, without creative efforts, this specification can also be applied to other similar scenarios based on these drawings. Unless obvious from the language context or otherwise stated, the same reference numerals in the figures represent the same structures or operations.

[0011] It should be understood that the "system", "device", "unit" and / or "module" used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the said words can be replaced by other expressions.

[0012] Unless the context clearly indicates otherwise, the words "a", "an", "one", and / or "the" are not intended to refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" merely indicate the inclusion of the steps and elements that have been expressly identified, and these steps and elements do not constitute an exclusive listing. A method or apparatus may also include other steps or elements.

[0013] Flowcharts are used in this specification to illustrate the operations performed by a system according to an embodiment of this specification. It should be understood that the operations before or after may not necessarily be executed precisely in sequence. On the contrary, the steps may be processed in reverse order or simultaneously. Also, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0014] Figure 1 is a platform structure diagram of the intelligent gas distribution pipeline purification Internet of Things system shown in some embodiments of this specification. As Figure 1 shown, the intelligent gas distribution pipeline purification Internet of Things system 100 includes an intelligent gas government safety supervision management platform 110, an intelligent gas government safety supervision sensor network platform 120, an intelligent gas government safety supervision object platform 130, an intelligent gas company sensor network platform 140, an intelligent gas equipment object platform 150, an intelligent gas company service platform 160, and a gas user platform 170. Among them, the intelligent gas government safety supervision object platform 130 includes an intelligent gas company management platform 131.

[0015] The intelligent gas government safety supervision management platform 110 is a digital monitoring and management platform for the government to supervise the safety of gas production, transportation, and use. In some embodiments, the intelligent gas government safety supervision management platform 110 may be configured in a processor and / or a server.

[0016] In some embodiments, the intelligent gas government safety supervision management platform 110 may include a government supervision comprehensive database. The government supervision comprehensive database may be a system for integrating and storing relevant data generated during the government supervision process. In some embodiments, the government supervision comprehensive database may integrate and store data information such as the licensing qualifications of gas enterprises, the inspection and maintenance of gas facilities, and the operation of equipment; for end-users, in some embodiments, the government supervision comprehensive database may also integrate and store data information such as end-user characteristics. For example, end-user characteristics may include one or more of the civilian user scale, industrial user scale, and industrial user type of the target distribution pipeline.

[0017] In some embodiments, the intelligent gas government safety supervision management platform 110 may perform two-way information interaction with the intelligent gas government safety supervision sensor network platform 120.

[0018] The Intelligent Gas Government Safety Supervision Sensing Network Platform 120 refers to a communication transmission platform that enables two-way data interaction between platforms.

[0019] In some embodiments, the Intelligent Gas Government Safety Supervision Sensing Network Platform 120 can be configured as a communication network and a gateway to implement functions such as network management, protocol management, instruction management, and data parsing.

[0020] In some embodiments, the Intelligent Gas Government Safety Supervision Sensing Network Platform 120 can be connected to the Intelligent Gas Government Safety Supervision Management Platform 110 and the Intelligent Gas Government Safety Supervision Object Platform 130 to achieve the information intercommunication function between the two platforms of the Intelligent Gas Government Safety Supervision Management Platform 110 and the Intelligent Gas Government Safety Supervision Object Platform 130.

[0021] The Intelligent Gas Government Safety Supervision Object Platform 130 can refer to an information processing platform used by the government to conduct safety supervision on various supervision objects related to gas safety. In some embodiments, the Intelligent Gas Government Safety Supervision Object Platform 130 can obtain information such as the gas operation status, gas usage information, and gas maintenance status of the supervision objects, and after processing, upload it to the Intelligent Gas Government Safety Supervision Management Platform 110 through the network sensing platform; and send down information such as safety supervision requirements. The supervision objects can be various enterprises, institutions, and individuals involved in gas production, transportation, and use. In some embodiments, the Intelligent Gas Government Safety Supervision Object Platform 130 is provided with an Intelligent Gas Company Management Platform 131.

[0022] The Intelligent Gas Company Management Platform 131 can refer to a comprehensive platform that coordinates and collaborates the connections between the various functional platforms of the gas company, gathers all the information of the Internet of Things, generates instructions and executes them by analyzing and processing the data / and information generated during the operation of the gas company. In some embodiments, the platforms with which the Intelligent Gas Company Management Platform 131 can conduct two-way information interaction are the Intelligent Gas Government Safety Supervision Object Platform 130, the Intelligent Gas Company Sensing Network Platform 140, and the Intelligent Gas Company Service Platform 160.

[0023] In some embodiments, the Intelligent Gas Company Management Platform 131 can obtain information such as terminal user characteristics, user gas usage characteristics, and risk levels through the Intelligent Gas Government Safety Supervision Object Platform 130. In some embodiments, the Intelligent Gas Company Management Platform 131 can upload information such as equipment operation status, purification parameters, and feedback on supervision requirements to the Intelligent Gas Government Safety Supervision Object Platform 130.

[0024] In some embodiments, the intelligent gas company management platform 131 may obtain information such as pipeline characteristics, gas characteristics, and flow rate data through the intelligent gas company sensor network platform 140; comprehensively analyze and process the relevant information to generate purification instructions and send them to the relevant platforms for execution.

[0025] In some embodiments, the intelligent gas company management platform 131 may further include a processor. The processor may process the data and / or information obtained from other platforms. The processor may execute program instructions based on these data, information, and / or processing results to perform one or more functions described in this application.

[0026] The intelligent gas company sensor network platform 140 may be a communication transmission platform that enables two-way data interaction between the functional platforms managed by the gas company. The intelligent gas company sensor network platform 140 may be configured as a communication network and a gateway to implement functions such as network management, protocol management, instruction management, and data parsing.

[0027] In some embodiments, the intelligent gas company sensor network platform 140 may be connected to the intelligent gas equipment object platform 150, the intelligent gas company service platform 160, and the intelligent gas company management platform 131 to implement the functions of sensing information sensing communication and control information sensing communication. For example, the intelligent gas company sensor network platform 140 may receive the data related to the operation of the gas purification device uploaded by the intelligent gas equipment object platform 150; send the purification instructions obtained from the intelligent gas company management platform 131 to the intelligent gas equipment object platform 150 and the intelligent gas company service platform 160.

[0028] The intelligent gas equipment object platform 150 may be a functional platform for generating sensing information. In some embodiments, the intelligent gas equipment object platform 150 may be configured as various gas equipment. For example, the gas equipment may include a gas purification device, a gas flow meter, a valve control device, a thermometer, a barometer, etc. In some embodiments, the intelligent gas equipment object platform 150 may perform data interaction with the intelligent gas company sensor network platform 140. For example, the intelligent gas equipment object platform 150 may upload data such as data related to the operation of the gas purification device, gas pipeline characteristic data, and gas flow rate to the intelligent gas company sensor network platform 140.

[0029] The intelligent gas equipment object platform 150 can also be used for gas user terminal monitoring / detection and information generation. In some embodiments, the intelligent gas equipment object platform 150 can also be configured as various gas monitoring / detection devices. For example, the gas monitoring / detection devices can include gas flow meters, thermometers, gas detectors, etc. In some embodiments, the intelligent gas equipment object platform 150 can interact with the intelligent gas company sensing network platform 140 in terms of data. For example, the intelligent gas equipment object platform 150 can upload the monitored gas usage data, detected gas component data, combustion gas emission data, etc. to the intelligent gas company sensing network platform 140.

[0030] The intelligent gas company service platform 160 can be a platform for the gas company to receive and transmit data and / or information. The intelligent gas company service platform 160 can interact with the intelligent gas user platform 170 and the intelligent gas company management platform 131 in terms of data. For example, the intelligent gas company service platform 160 can send the operation management information of the gas purification device to the intelligent gas user platform 170. For another example, the intelligent gas company service platform 160 can send the gas usage data obtained from the intelligent gas user platform 170 to the intelligent gas company management platform 131.

[0031] The gas user platform 170 can be a platform for interacting with users. In some embodiments, the gas user platform 170 can be configured as a terminal device. For example, the terminal device can include a mobile device, a tablet computer, etc. or any combination thereof. In some embodiments, the intelligent gas company service platform 160 can communicate with users through the terminal device. For example, the intelligent gas company service platform 160 can feedback information such as gas purification to users through the terminal device; for another example, users can upload information such as gas cleanliness threshold requirements and abnormal gas supply to the intelligent gas company service platform 160 through the terminal device.

[0032] By forming an information operation closed-loop among the functional platforms based on the Internet of Things, the government department can effectively supervise and cooperate with the gas company, and coordinate and operate regularly under the unified management of the gas company management platform, realizing gas safety supervision and the informatization and intelligentization of gas purification.

[0033] It should be noted that the above description of the intelligent gas transmission pipeline purification system and its modules based on the Internet of Things is only for the convenience of description and does not limit this specification within the scope of the cited embodiments. It can be understood that for those skilled in the art, after understanding the principle of the system, they may, without departing from this principle, make any combination of the various modules, or form a subsystem and connect it with other modules.

[0034] In some embodiments, when implementing the intelligent gas distribution pipeline purification method, the intelligent gas company management platform can determine the actual cleanliness of the target distribution pipeline based on the initial cleanliness of the gas to be transported, the first pipeline characteristics, the first gas characteristics, the second pipeline characteristics, and the second gas characteristics; determine the target cleanliness based on the end-user characteristics; determine the cleanliness deviation based on the initial cleanliness and the target cleanliness; generate a purification instruction based on the cleanliness deviation, and send the purification instruction to the intelligent gas equipment object platform to control the purification device in the target fractionation pipeline to purify the gas; determine the cleanliness deviation based on the initial cleanliness and the target cleanliness; generate a purification instruction based on the cleanliness deviation, and send the purification instruction to the intelligent gas equipment object platform to control the purification device in the target fractionation pipeline to purify the gas; in response to the start of execution of the purification instruction, obtain the first flow rate data of the main pipeline and the second flow rate data of the target distribution pipeline from the intelligent gas equipment object platform during the purification period; generate a flow rate regulation instruction according to the first flow rate data and the second flow rate data, and send the flow rate regulation instruction to the intelligent gas equipment object platform to regulate the opening degrees of the speed regulating valves in the main pipeline and the target distribution pipeline.

[0035] Figure 2 is an exemplary flowchart of an Internet-of-Things-based intelligent gas distribution pipeline purification method shown in some embodiments of this specification. As Figure 2 shown, process 200 includes the following steps. In some embodiments, process 200 can be executed by the intelligent gas company management platform of the Internet-of-Things-based intelligent gas distribution pipeline purification system.

[0036] Step 210, determine the actual cleanliness of the target distribution pipeline based on the initial cleanliness of the gas to be transported, the first pipeline characteristics, the first gas characteristics, the second pipeline characteristics, and the second gas characteristics.

[0037] The initial cleanliness refers to the gas cleanliness at the gas gate station to which the target distribution pipeline belongs.

[0038] The gas gate station can store gas and transport gas to gas users through the gas distribution pipeline. In some embodiments, the gas cleanliness of the gas gate station is a preset value, which can be determined based on the input of the staff at the gas gate station and stored in the government supervision comprehensive database of the intelligent gas government safety supervision management platform.

[0039] In some embodiments, the intelligent gas company management platform can query the initial cleanliness of the gas to be transported from the intelligent gas government safety supervision management platform based on the gas gate station to which the target distribution pipeline belongs.

[0040] The gas cleanliness refers to the purity of the gas, which can be expressed as a percentage or in other ways. The higher the value of the gas cleanliness, the less the impurity content in the gas.

[0041] The sum of the gas cleanliness and the percentage of impurity content is 1. In some embodiments, the intelligent gas company management platform can determine the gas cleanliness based on the content of impurities in the gas. Among them, the impurities include, but are not limited to, one or more of moisture, sulfides, silicides, solid particles, etc., and their content can be determined by one or more of spectroscopy, chromatography, and chemical adsorption methods.

[0042] The first pipeline feature refers to the pipeline feature at the pressure regulating station or gas gate station closest to the target branch pipeline in the main pipeline. Among them, the closest to the target branch pipeline means the smallest pipeline distance from the target branch pipeline. The second pipeline feature refers to the pipeline feature of the target branch pipeline.

[0043] The pipeline feature is a feature that characterizes the inherent properties of the gas pipeline. The pipeline feature includes, but is not limited to, at least one of the pipeline wall material, the length of the gas transportation path, the service life, the cleaning time, and the soil pH value around the pipeline.

[0044] In some embodiments, the intelligent gas object platform can obtain pipeline information based on user input. Among them, the user input can include, but is not limited to, at least one of the pipeline wall material, the length of the gas transportation path, the service life, and the cleaning time determined by the gas pipeline operation and maintenance personnel.

[0045] In some embodiments, the intelligent gas company management platform can obtain pipeline information from the intelligent gas equipment object platform, determine the pipeline wall material, the length of the gas transportation path, the service life, the cleaning time, etc. based on the pipeline information; the intelligent gas company management platform can also obtain the soil pH value around the pipeline based on the pH sensor set on the gas pipeline.

[0046] The main pipeline refers to the main part of the gas pipeline. The branch pipeline is a branch of the gas pipeline connected to the main pipeline, connecting to the end users. The target branch pipeline is the branch pipeline that needs to be purified.

[0047] The first gas feature refers to the gas feature of the main pipeline. The second gas feature refers to the gas feature of the target branch pipeline.

[0048] The gas feature is a feature that characterizes the properties of the gas. The gas feature includes, but is not limited to, at least one of the gas flow rate, pipeline pressure, temperature, etc.

[0049] In some embodiments, the intelligent gas company management platform can obtain the first gas characteristic and the second gas characteristic from the intelligent gas equipment object platform. For example, the intelligent gas company management platform can obtain the first gas characteristic and the second gas characteristic through the sensors configured in the intelligent gas equipment object platform, such as obtaining the gas flow rate based on the flow rate sensor set in the gas pipeline, obtaining the pipeline pressure based on the pressure sensor set in the gas pipeline, and obtaining the temperature based on the temperature sensor set in the gas pipeline.

[0050] The actual cleanliness refers to the gas cleanliness at the input end of the purification device in the target subtransmission pipeline.

[0051] The purification device is used to remove impurities in the gas. In some embodiments, the purification device is arranged at multiple positions in the gas pipeline. For example, the purification device is arranged in each subtransmission pipeline, etc.

[0052] In some embodiments, the purification device is an annular purification device arranged inside the pipeline wall. Filtering substances (such as activated carbon, silica gel, iron oxide, etc.) are arranged inside the purification device. When the purification device is turned on, the gas is input from the input end of the purification device and output from the output end of the purification device, thereby realizing the purification of the gas.

[0053] In some embodiments, the intelligent gas company management platform can determine the actual cleanliness through clustering analysis based on the initial cleanliness, the first pipeline characteristic, the first gas characteristic, the second pipeline characteristic, and the second gas characteristic.

[0054] In some embodiments, the intelligent gas company management platform constructs multiple clustering vectors based on historical data. Each element of each clustering vector includes historical initial cleanliness, historical first pipeline characteristic, historical first gas characteristic, historical second pipeline characteristic, historical second gas characteristic, and the corresponding historical actual cleanliness.

[0055] In some embodiments, the intelligent gas company management platform constructs a target clustering vector based on the initial cleanliness, the first pipeline characteristic, the first gas characteristic, the second pipeline characteristic, and the second gas characteristic of the gas to be transported. The intelligent gas company management platform clusters the clustering vectors and the target clustering vector based on the initial cleanliness, the first pipeline characteristic, the first gas characteristic, the second pipeline characteristic, and the second gas characteristic to obtain multiple clustering clusters. The clustering methods include but are not limited to K-Means clustering, mean shift clustering, DBSCAN clustering, etc.

[0056] In some embodiments, the intelligent gas company management platform can determine the clustering cluster containing the clustering target vector from the foregoing multiple clustering clusters, and determine the average value of the historical actual cleanliness of all clustering vectors in the clustering cluster as the actual cleanliness corresponding to the target clustering vector.

[0057] In some embodiments, the intelligent gas company management platform can obtain the gas usage data of the end-users corresponding to the target gas transmission pipeline from the intelligent gas equipment object platform; based on the initial cleanliness, the first pipeline characteristics, the first gas characteristics, the second pipeline characteristics, the second gas characteristics, and the gas usage data, determine the actual cleanliness.

[0058] The gas usage data refers to the data related to the end-users' gas usage. In some embodiments, the target gas transmission pipeline corresponds to multiple end-users, and each end-user corresponds to a gas usage data. The gas usage data includes, but is not limited to, at least one of the daily average gas usage, the gas combustion color, the emission gas components, etc.

[0059] In some embodiments, the intelligent gas company management platform can obtain the emission gas components of multiple end-users through the gas analyzer set by the intelligent gas equipment object platform, obtain the daily gas usage data through the gas flowmeter, and obtain the gas combustion image through user input. The intelligent gas company management platform can calculate the daily average gas usage based on the daily gas usage data and determine the gas combustion color based on the gas combustion image.

[0060] In some embodiments, the intelligent gas company management platform determines the actual cleanliness by means of vector matching.

[0061] In some embodiments, the intelligent gas company management platform constructs a gas feature vector based on the historical gas usage data in the historical data, determines the historical gas cleanliness of the gas transmission pipeline corresponding to the gas feature vector as the label corresponding to the gas feature vector, and obtains a gas usage database. The elements of the feature vector include the daily average gas usage, the gas combustion color, and the emission gas components of the historical end-users in the historical data.

[0062] In some embodiments, the intelligent gas company management platform constructs a target usage vector based on the gas usage data of the end-users corresponding to the target gas transmission pipeline, and matches in the gas usage database based on the target usage vector to obtain multiple feature vectors whose similarity to the target usage vector is greater than the similarity threshold. The elements in the target usage vector can include the daily average gas usage, the gas combustion color, and the emission gas components of the end-users. The similarity can be determined by the vector distance, and the vector distance includes, but is not limited to, the Euclidean distance, the cosine distance, etc. The similarity threshold can be a preset value or set manually.

[0063] In some embodiments, the intelligent gas company management platform determines multiple feature vectors whose similarity to the target usage vector is greater than the similarity threshold, determines the mean of the labels corresponding to the multiple feature vectors as the first cleanliness level, and determines the mean of the first cleanliness level and the second cleanliness level as the actual cleanliness level. The second cleanliness level can be determined through cluster analysis based on the initial cleanliness level, the first pipeline feature, the first gas feature, the second pipeline feature, and the second gas feature. For more detailed descriptions, please refer to the relevant content of the previous cluster analysis.

[0064] In some embodiments, the intelligent gas company management platform determines a reference distribution pipeline of the target distribution pipeline in the gas pipeline network, and obtains the corresponding reference usage data from the intelligent gas equipment object platform; determines an individual interference factor based on the gas usage data and the reference usage data; and determines the actual cleanliness level based on the initial cleanliness level, the first pipeline feature, the first gas feature, the second pipeline feature, the second gas feature, the gas usage data, and the individual interference factor.

[0065] In some embodiments, the gas pipeline network may include multiple main pipelines, and one main pipeline corresponds to multiple distribution pipelines. The main pipeline corresponding to the target distribution pipeline may be referred to as the target main pipeline.

[0066] The reference distribution pipeline refers to other distribution pipelines corresponding to the target main pipeline except the target distribution pipeline.

[0067] The reference usage data refers to the gas usage data of the end users corresponding to the reference distribution pipeline.

[0068] The individual interference factor reflects the influence degree of at least one end user corresponding to the target distribution pipeline on the gas usage amount.

[0069] In some embodiments, the intelligent gas company management platform determines the difference between the mean of the daily average gas usage change rates of multiple reference distribution pipelines and the daily average gas usage change rate of the target distribution pipeline as the individual interference factor.

[0070] In some embodiments, the daily average gas usage change rate is expressed as the ratio of the difference between the daily average gas usages of the previous two days to the daily average gas usage of the previous day.

[0071] In some embodiments, the intelligent gas company management platform updates the daily average gas usage amount corresponding to the target distribution pipeline based on the individual interference factor, and determines the updated daily average gas usage amount as the gas usage data; determines the actual cleanliness level based on the initial cleanliness level, the first pipeline feature, the first gas feature, the second pipeline feature, and the second gas feature. For more detailed descriptions, please refer to the previous relevant descriptions.

[0072] In some embodiments, the daily average gas usage corresponding to the target branch pipeline is positively correlated with the individual interference factor. For example, the intelligent gas company management platform calculates the updated daily average gas usage through the following formula (1).

[0073] (1) Wherein, is the updated daily average gas usage, is the change rate of the daily average gas usage of the target branch pipeline, is the individual interference factor, is the daily average gas usage of the target branch pipeline on the previous day.

[0074] The daily average gas usage corresponding to the end user will fluctuate due to actual situations, resulting in changes in the gas usage corresponding to the target branch pipeline. In some embodiments of this specification, considering the influence of end user factors on gas usage, the gas usage of the target branch pipeline is updated, and the actual cleanliness is determined based on the updated gas usage, which is more in line with the actual gas usage situation and makes the obtained actual cleanliness more accurate.

[0075] In some embodiments of this specification, the actual gas cleanliness is determined based on the gas usage data of the user side, and the calculation result is more accurate.

[0076] In some embodiments, the intelligent gas company management platform obtains the gas network gas characteristics collected by the monitoring equipment in the gas network from the intelligent gas equipment object platform; constructs a gas characteristic map based on the first pipeline characteristic, the second pipeline characteristic, and the gas network gas characteristics; and determines the actual cleanliness through a prediction model according to the gas characteristic map. For more content, see Figure 3 the relevant description.

[0077] Step 220, determine the target cleanliness based on the end user characteristics.

[0078] The end user characteristics refer to the user characteristics of the end users connected to the target branch pipeline. In some embodiments, the end users include residential users, commercial users, industrial users, etc. The end user characteristics include at least one of the residential user scale, commercial user scale, industrial user scale, industrial user type, etc.

[0079] In some embodiments, the intelligent gas company management platform obtains the residential user scale, industrial user scale, and industrial user type corresponding to each branch pipeline from the intelligent gas government safety supervision management platform, and then obtains the end user characteristics. The intelligent gas government safety supervision management platform counts the multiple end users corresponding to each branch pipeline and calculates the residential user scale, industrial user scale, and industrial user type corresponding to each branch pipeline.

[0080] The gas cleanliness requirements vary among different types of end-users. For example, commercial and industrial users have relatively high requirements for gas cleanliness to ensure equipment lifespan and / or production quality, while residential users have relatively lower requirements for gas cleanliness, but still need to ensure that there are no impurities in the gas to guarantee gas usage safety. In addition, different types of industrial users may have different requirements for gas cleanliness due to different processes and production standards. Therefore, it is necessary to provide gas that meets the gas usage requirements of end-users according to their characteristics.

[0081] The target cleanliness refers to the minimum gas cleanliness of the target transmission pipeline to meet the gas usage requirements of end-users.

[0082] In some embodiments, the intelligent gas company management platform determines the target cleanliness by querying the characteristic comparison table based on the characteristics of end-users.

[0083] The characteristic comparison table includes the correspondence between end-user characteristics and target cleanliness. In some embodiments, the intelligent gas company management platform determines the average value of the gas cleanliness when users have better feedback on gas usage experience in historical data as the target cleanliness corresponding to the historical end-user characteristics. Among them, the feedback from users can be obtained by distributing questionnaires through the intelligent gas government safety supervision management platform. Better feedback means that the user evaluation meets the preset conditions. For example, the user score is greater than the preset threshold, the user evaluation is good, etc. If the feedback from users is good, it means that the gas cleanliness output by the transmission pipeline can meet the user requirements.

[0084] Step 230: Determine the cleanliness deviation based on the initial cleanliness and the target cleanliness.

[0085] The cleanliness deviation refers to the gap between the initial cleanliness and the target cleanliness.

[0086] In some embodiments, the cleanliness deviation can be determined based on the difference between the target cleanliness and the initial cleanliness.

[0087] Step 240: Generate a purification instruction based on the cleanliness deviation.

[0088] The purification instruction is an instruction used to control the purification device to purify the gas. In some embodiments, the purification instruction includes the purification parameters of the purification device.

[0089] The purification parameters refer to the parameters when the purification device purifies the gas. The purification parameters include but are not limited to at least one of the purification power, purification duration, etc. of the purification device.

[0090] In some embodiments, in response to the cleanliness deviation being greater than the cleanliness deviation threshold, the intelligent gas company management platform generates a purification instruction to control the purification device to purify the gas, so that the gas cleanliness in the target distribution pipeline reaches the target cleanliness.

[0091] The cleanliness deviation threshold is a threshold used to determine whether to generate a purification instruction. In some embodiments, the cleanliness deviation threshold is related to the pipeline distance between the target distribution pipeline and the end user. The greater the pipeline distance, the smaller the cleanliness deviation threshold.

[0092] During the transportation of gas from the target distribution pipeline to the end user, the gas cleanliness will further decrease. The greater the pipeline distance between the target distribution pipeline and the end user, the more the gas cleanliness decreases. To improve the gas cleanliness at the end user, it is necessary to improve the gas cleanliness at the target distribution pipeline, and correspondingly, the cleanliness deviation threshold needs to be reduced.

[0093] In some embodiments, the intelligent gas company management platform determines the initial purification parameters of the purification device in the target distribution pipeline based on the cleanliness deviation; determines the terminal cleanliness based on the processed cleanliness, the downstream pipeline characteristics corresponding to the downstream pipeline of the purification device, and the second gas characteristics; updates the initial purification parameters in response to the terminal cleanliness being less than the desired cleanliness to determine the target purification parameters; and generates a purification instruction based on the target purification parameters. For more details, see Figure 4 the relevant description.

[0094] In some embodiments, the intelligent gas company management platform can send the purification instruction to the intelligent gas equipment object platform to control the purification device in the target distribution pipeline to purify the gas according to the purification parameters.

[0095] Step 250, in response to the start of execution of the purification instruction, obtain the first flow rate data of the main pipeline and the second flow rate data of the target distribution pipeline from the intelligent gas equipment object platform during the purification period.

[0096] The purification period refers to the time period during which the local purification device performs purification.

[0097] The first flow rate data refers to the gas flow rate near the target distribution pipeline in the main pipeline. In some embodiments, the intelligent gas company management platform obtains multiple gas flow rates within a preset period based on the flow rate sensor closest to the target distribution pipeline in the main pipeline, and determines the average value of the multiple gas flow rates as the first flow rate data.

[0098] The second flow rate data refers to the gas flow rate at the output end of the local purification device in the target branch pipeline. In some embodiments, the intelligent gas company management platform obtains multiple gas flow rates within a preset period based on the flow rate sensor closest to the downstream of the local purification device in the target branch pipeline, and determines the average value of the multiple gas flow rates as the second flow rate data.

[0099] The preset period can be set according to actual needs. For example, the preset period is 30s, 1min, 2min, etc.

[0100] Step 260, generate a flow rate regulation instruction according to the first flow rate data and the second flow rate data.

[0101] The flow rate regulation instruction refers to an instruction for regulating the gas flow rate. In some embodiments, the flow rate regulation instruction includes the speed regulating valves that need to be regulated in the main pipeline and the target branch pipeline, and the corresponding opening degrees of the speed regulating valves.

[0102] The speed regulating valve is used to regulate the gas flow rate in the gas pipeline. The opening degree of the speed regulating valve is the angle at which the speed regulating valve opens. The gas flow rate is positively correlated with the opening degree of the speed regulating valve.

[0103] In some embodiments, in response to the difference between the first flow rate data and the second flow rate data being greater than the flow rate deviation threshold, the intelligent gas company management platform generates a flow rate regulation instruction to regulate the opening degrees of the speed regulating valves in the main pipeline and the target branch pipeline until the difference between the first flow rate data and the second flow rate data is less than the flow rate deviation threshold. Exemplarily, when the second flow rate data is less than the first flow rate data, the opening degree of the speed regulating valve at the connection of the main pipeline and the target branch pipeline is gradually increased in a preset step to increase the gas flow rate flowing into the target branch pipeline, so as to ensure that the flow rate of the gas after purification reaches the standard. Among them, the preset step can be determined based on prior experience.

[0104] The flow rate deviation threshold is a threshold for determining whether to generate a flow rate regulation instruction. The flow rate deviation threshold can be set based on experience.

[0105] In some embodiments, the flow rate deviation threshold is related to the density of the shunt nodes in the target branch pipeline. The greater the density of the shunt nodes, the smaller the flow rate deviation threshold.

[0106] The greater the density of the shunt nodes in the target branch pipeline, the greater the impact of the possible disorder of the gas movement direction after the negative pressure is turned on. At this time, it is necessary to appropriately reduce the flow rate deviation threshold to ensure the sensitivity of the flow rate regulation instruction.

[0107] In some embodiments, the intelligent gas company management platform sends the flow rate regulation instruction to the intelligent gas equipment object platform, and the intelligent gas equipment object platform adjusts the speed regulating valves in the main pipeline and the target branch pipeline to the set opening degrees.

[0108] In some embodiments of this specification, when the cleanliness deviation is relatively large, a purification instruction can be generated in a timely manner to control the purification device to purify the gas, ensuring the gas cleanliness at the end-user side. During the purification process, the gas flow rates in the main pipeline and the target branch pipeline are monitored in real time. When the difference in gas flow rates is relatively large, the opening degree of the speed regulating valve is adjusted in a timely manner to reduce the interference of the purification device on the gas movement direction and ensure the normal transportation of the gas.

[0109] Figure 3 is an exemplary schematic diagram of determining the actual cleanliness shown in some embodiments of this specification. As Figure 3 shown, in some embodiments, the intelligent gas company management platform obtains the pipeline network gas characteristics 330 collected by the monitoring equipment in the gas pipeline network from the intelligent gas equipment object platform; based on the first pipeline characteristics 310, the second pipeline characteristics 320, and the pipeline network gas characteristics 330, constructs a gas characteristic map 340; and determines the actual cleanliness 360 through the prediction model 350 according to the gas characteristic map 340. For more information about the first pipeline characteristics, the second pipeline characteristics, and the actual cleanliness, see Figure 2 the relevant description.

[0110] The pipeline network gas characteristics include the gas characteristics at multiple points in the gas pipeline network. For more information about the gas characteristics, see Figure 2 the relevant description.

[0111] In some embodiments, monitoring equipment is arranged at multiple preset points in the gas pipeline network, and the monitoring equipment is used to collect the gas characteristics of each point. The monitoring equipment may include, but is not limited to, at least one of a flow rate sensor, a pressure sensor, a temperature sensor, etc., and can be set according to actual monitoring requirements.

[0112] The gas characteristic map is a directed graph representing the gas transportation route, which can reflect the connection relationship between the main pipeline and multiple branch pipelines, as well as the gas characteristics at each point in the gas pipeline network.

[0113] In some embodiments, the intelligent gas company management platform can construct a gas characteristic map based on the first pipeline characteristics, the second pipeline characteristics, and the pipeline network gas characteristics.

[0114] In some embodiments, the gas characteristic map includes multiple nodes.

[0115] In some embodiments, the intelligent gas company management platform can determine the diversion point between the main pipeline and multiple branch pipelines as a node in the gas characteristic map.

[0116] In some embodiments, the nodes in the gas characteristic map have node characteristics. The node characteristics are the gas characteristics corresponding to each node.

[0117] In some embodiments, the intelligent gas company management platform determines the node features of each node in the gas feature map based on the gas network characteristics. For example, when there is a monitoring device at a node, the intelligent gas company management platform determines the gas characteristics at the monitoring device as the node features of that node. For another example, when there is no monitoring device at a node, the intelligent gas company management platform determines the gas characteristics at the monitoring device closest to the node in terms of pipeline distance as the node features of that node.

[0118] In some embodiments, the nodes in the gas feature map can be divided according to their positions in the gas pipeline network. For example, the nodes in the gas feature map can be divided into the most upstream node, the most downstream node, and the intermediate nodes.

[0119] In some embodiments, the node features of the most upstream node in the gas feature map further include the gas cleanliness corresponding to the most upstream node. Among them, the most upstream node is the node corresponding to the monitoring device closest to the gas gate station where the initial cleanliness is obtained. The gas cleanliness corresponding to the most upstream node can be obtained through the aforementioned monitoring device.

[0120] In some embodiments, the gas feature map includes multiple directed edges connecting the nodes. The direction of the edge is from the upstream node to the downstream node.

[0121] In some embodiments, the intelligent gas company management platform determines the edge between two nodes based on the direct connection of the gas pipelines between the two nodes, and determines the direction of the edge based on the gas transmission direction between the two nodes.

[0122] In some embodiments, the edges in the gas feature map have edge features. The edge feature is the pipeline feature of the gas pipeline corresponding to the edge.

[0123] In some embodiments, the intelligent gas company management platform determines the edge features of each edge in the gas feature map based on the first pipeline feature and the second pipeline feature. When the gas pipeline connecting node A and node B is the main pipeline, the edge feature is the first pipeline feature corresponding to the main pipeline. When the gas pipeline connecting node A and node B is the target distribution pipeline, the edge feature is the second pipeline feature corresponding to the target distribution pipeline. When the gas pipeline connecting node A and node B is other distribution pipelines, the edge feature is the pipeline feature corresponding to the other distribution pipelines.

[0124] In some embodiments, the gas feature map further includes end-user nodes, and the node features of the end-user nodes include the gas usage data of the end-users.

[0125] The end-user node is the node corresponding to the end-user, and the node features of the end-user node are the gas usage data of the end-user. For more information about end-users and gas usage data, see Figure 2Related description.

[0126] In some embodiments, the end - user node is connected to the most downstream node of the corresponding branch pipeline by an edge, and the direction of the edge is from the most downstream node to the end - user node. The edge feature is the pipeline feature of the gas pipeline connecting the end - user node and the most downstream node. Among them, the most downstream node refers to the node directly connected to the end - user.

[0127] In some embodiments of this specification, the end - user node is added to the gas feature map, and the gas cleanliness of the most downstream node is predicted through a prediction model, and the obtained gas cleanliness is more accurate.

[0128] The prediction model is used to predict the gas cleanliness at the most downstream node in the gas feature map. In some embodiments, the prediction model is a machine - learning model, for example, a Graph Neural Networks (GNN) model, etc.

[0129] The input of the prediction model is the gas feature map, and the output is the gas cleanliness at the most downstream node in the gas feature map. The gas cleanliness at the most downstream node can characterize the cleanliness of the gas input to the end - user.

[0130] In some embodiments, the intelligent gas company management platform trains a prediction model based on multiple labeled training samples. For example, the intelligent gas company management platform inputs the training samples into the initial prediction model, constructs a loss function based on the output of the initial prediction model and the label, iteratively updates the parameters of the initial prediction model based on the loss function, and when the iteration completion condition is met, ends the iteration to obtain the trained prediction model. Among them, the method of iterative update includes but is not limited to the gradient - descent method, and the iteration completion condition can be that the loss function converges or the number of iterations reaches a threshold.

[0131] The training samples include sample gas feature maps. In some embodiments, the intelligent gas company management platform constructs sample gas feature maps based on the historical first pipeline feature, historical second pipeline feature, and historical pipeline network gas feature in the historical data. The label corresponding to the training sample is the actual gas cleanliness at the most downstream node in the sample gas feature map, and this label can be determined based on the data actually measured by the monitoring device at the most downstream node in the historical data.

[0132] In some embodiments, the intelligent gas company management platform performs multiple rounds of training on the initial prediction model based on multiple tagged training samples. The multiple rounds of training include at least one training phase, and one training phase includes a preset number of training rounds. After one training phase ends, the current learning rate used in the training phase is adjusted based on a decay factor to obtain an updated learning rate, and the next phase of training is performed based on the updated learning rate. In response to triggering the training completion condition, the training ends, and a trained prediction model is obtained.

[0133] In some embodiments, the intelligent gas company management platform determines the preset number based on the complexity of the gas characteristic map. The greater the complexity of the gas characteristic map, the greater the preset number.

[0134] The complexity of the gas characteristic map reflects the degree of complexity of the gas characteristic map. In some embodiments, the complexity of the gas characteristic map is positively correlated with both the in-degree and out-degree of all nodes in the gas characteristic map.

[0135] The in-degree refers to the number of edges pointing to a node, and the out-degree refers to the number of edges emitted by a node.

[0136] The learning rate determines the speed and direction of updating the parameters of the initial prediction model during training.

[0137] In some embodiments, after one training phase ends, the intelligent gas company management platform uses the product of the learning rate of this training phase and the decay factor as the updated learning rate, and performs the next phase of training based on the updated learning rate. The decay factor is a number between 0 and 1, and the decay factor can be set based on experience.

[0138] As the training process progresses, the parameters of the initial prediction model gradually approach the optimal solution. To avoid parameter oscillation or divergence caused by too large a learning rate, in some embodiments of this specification, the learning rate is gradually decreased through the decay factor, which can make the parameters converge to the optimal solution.

[0139] In some embodiments, the intelligent gas company management platform may determine the actual cleanliness 360 as the gas cleanliness at the most downstream node corresponding to the target distribution pipeline in the gas characteristic map 340.

[0140] In some embodiments of this specification, by predicting the actual cleanliness through the prediction model, a more accurate prediction result can be obtained, making the prediction result closer to the actual situation.

[0141] Figure 4 is an exemplary flowchart for generating a purification instruction shown in some embodiments of this specification. As Figure 4 shown, process 400 includes the following steps. In some embodiments, process 400 may be executed by the intelligent gas company management platform of the intelligent gas distribution pipeline purification system based on the Internet of Things.

[0142] Step 410: Based on the cleanliness deviation, determine the initial purification parameters of the purification device in the target distribution pipeline. For more information on the cleanliness deviation, see Figure 2 the relevant description.

[0143] The initial purification parameters refer to the purification parameters initially set for the purification device. After purifying the gas according to the initial purification parameters, the gas cleanliness can reach the target cleanliness.

[0144] In some embodiments, in response to the cleanliness deviation being greater than the cleanliness deviation threshold, the intelligent gas company management platform can determine the initial purification parameters of the purification device in the target distribution pipeline. For more detailed content, see Figure 2 the relevant description in

[0145] Step 420: Based on the post-treatment cleanliness, the downstream pipeline characteristics corresponding to the downstream pipeline of the purification device, and the second gas characteristic, determine the terminal cleanliness.

[0146] The post-treatment cleanliness refers to the cleanliness of the gas after being purified by the purification device. In some embodiments, the value of the post-treatment cleanliness can be equal to the target cleanliness.

[0147] The downstream pipeline of the purification device refers to the gas pipeline between the purification device and the end user.

[0148] The downstream pipeline characteristics refer to the pipeline characteristics of the downstream pipeline of the purification device. For the acquisition of the downstream pipeline characteristics, see Figure 2 the relevant description of pipeline characteristics in

[0149] The terminal cleanliness refers to the gas cleanliness at the end user. For more information on gas cleanliness, see Figure 2 the relevant description.

[0150] In some embodiments, the intelligent gas company management platform determines the terminal cleanliness through Figure 2 the method of determining similar actual cleanliness through cluster analysis described above. The difference is that each element of the cluster vector includes the historical post-treatment cleanliness, the historical downstream pipeline characteristics, and the historical second gas characteristic, and each element of the target vector includes the expected cleanliness, the downstream pipeline characteristics, and the second gas characteristic. The intelligent gas company management platform clusters the cluster vector and the target vector based on the gas cleanliness, the downstream pipeline characteristics, and the second gas characteristic.

[0151] In some embodiments, the intelligent gas company management platform determines the terminal cleanliness based on the gas characteristic map through a prediction model. For more information on the gas characteristic map and the prediction model, see Figure 3 the relevant description.

[0152] In some embodiments, when the gas characteristic map includes an end-user node, the output of the prediction model further includes the end cleanliness at the end-user node. At this time, the training label further includes the actual gas cleanliness at the end-user node in the historical data.

[0153] In some embodiments of this specification, by predicting the end cleanliness through a prediction model, the obtained end cleanliness is more accurate.

[0154] Step 430, in response to the end cleanliness being less than the desired cleanliness, update the initial purification parameters to determine the target purification parameters.

[0155] The desired cleanliness refers to the minimum gas cleanliness at the end-user to meet the gas usage requirements of the end-user. In some embodiments, the value of the desired cleanliness is equal to the target cleanliness.

[0156] In some embodiments, during the process of gas transmission from the purification device to the end-user, the gas cleanliness may further decrease. At this time, the end cleanliness is less than the desired cleanliness, and the gas usage requirements of the end-user cannot be met. Therefore, it is necessary to adjust based on the initial purification parameters to determine the target purification parameters to increase the end cleanliness above the desired cleanliness.

[0157] In some embodiments, in response to the end cleanliness being less than the desired cleanliness, the intelligent gas company management platform updates the initial purification parameters through computational simulation to obtain the target purification parameters.

[0158] For example, the intelligent gas company management platform can determine a calculation model and set initial parameters according to the actual situation of the purification device. The initial parameters can include the initial power and the initial duration; perform simulation operations based on the aforementioned calculation model, analyze the simulation results, evaluate whether the purification results under the initial power and the initial duration meet the requirements. If not, gradually adjust the initial parameters according to the preset rules and re-perform the simulation until the obtained purification results can meet the requirements.

[0159] Among them, meeting the requirements means that the gas cleanliness after purification is not less than the desired cleanliness. The preset rules can include: if the gas cleanliness after purification is lower than the requirements, the working power can be appropriately increased; if the cleanliness is too high resulting in increased energy consumption, the working power can be appropriately decreased; if the gas cleanliness after purification still does not meet the requirements, the working duration can be extended; if the cleanliness already meets the requirements and further increasing the duration has little improvement on the cleanliness, the working duration can be shortened to save energy consumption.

[0160] In some embodiments, the target purification parameter includes sub-target purification parameters for at least one preset time period, and the desired cleanliness includes sub-desired cleanliness levels for at least one preset time period. The intelligent gas company management platform obtains the gas usage characteristics of the end-users corresponding to the target transmission pipeline from the intelligent gas government safety supervision management platform; based on the gas usage characteristics, it determines the sub-target purification parameters for at least one preset time period; for a preset time period, in response to the terminal cleanliness being less than the sub-desired cleanliness, it updates the initial purification parameters to determine the sub-target purification parameters.

[0161] In some embodiments, the intelligent gas company management platform divides a day into multiple preset time periods according to a preset duration. For example, if the preset duration is 1 hour, the preset time periods include 0:00~1:00, 1:00~2:00, …, 23:00~24:00. The preset time periods can also be obtained by other means of division.

[0162] The gas usage characteristics of the end-users refer to the characteristics related to the end-users' use of gas. The gas usage characteristics of the end-users include the gas usage time periods and cleanliness requirement thresholds of each end-user, etc.

[0163] The cleanliness requirement threshold refers to the lowest gas cleanliness that can meet the needs of the end-users.

[0164] In some embodiments, the intelligent gas company management platform obtains the gas usage time periods of the end-users from the intelligent gas equipment object platform.

[0165] In some embodiments, the intelligent gas company management platform obtains the cleanliness requirement threshold from the intelligent gas government safety supervision management platform. The intelligent gas government safety supervision management platform determines the terminal cleanliness corresponding to the general user experience as the cleanliness requirement threshold by distributing questionnaires to the end-users. For more details, please refer to Figure 2 the relevant descriptions in

[0166] In some embodiments, for a preset time period, the intelligent gas company management platform determines the cleanliness requirement thresholds of multiple end-users who need to use gas during this preset time period, and determines the maximum value of the cleanliness requirement thresholds as the sub-desired cleanliness for this preset time period.

[0167] In some embodiments, in response to the terminal cleanliness being less than the sub-desired cleanliness, the intelligent gas company management platform updates the sub-initial purification parameters by the method of updating the target purification parameters as described above to determine the sub-target purification parameters.

[0168] In some embodiments of this specification, setting different purification parameters according to different requirements can reduce the usage and replacement frequency of consumables (such as filters) in the purification device, reduce the electrical energy consumed by the purification device, and save costs.

[0169] Step 440: Generate a purification instruction based on the target purification parameter.

[0170] In some embodiments, the intelligent gas company management platform may send the target purification parameter to the intelligent gas government safety supervision management platform to obtain the purification risk degree; based on the purification risk degree and the target purification parameter, generate a purification instruction.

[0171] The purification risk degree refers to the risk degree during the purification by the purification device and / or the impact degree on the normal life of surrounding residents.

[0172] In some embodiments, the intelligent gas government safety supervision management platform evaluates the risk degree of potential safety hazards during the purification process and the impact degree on the normal life of surrounding residents based on the working power and working duration of the purification device, and determines the purification risk degree according to the risk degree and the impact degree. The purification risk degree is positively correlated with the aforementioned risk degree and impact degree. The intelligent gas company management platform can obtain the purification risk degree from the intelligent gas government safety supervision management platform.

[0173] In some embodiments, the gas government safety supervision management platform can evaluate the aforementioned risk degree and impact degree according to the frequency, duration, noise level, noise duration, etc. of the pipeline vibration caused by the purification device. The risk degree and the impact degree are positively correlated with the frequency, duration, noise level, and noise duration of the pipeline vibration.

[0174] In some embodiments, in response to the purification risk degree being greater than the risk degree threshold, the intelligent gas company management platform appropriately reduces the cleanliness requirement, reduces the working power of the purification device, and extends the working duration until the new purification risk degree is less than the flow rate deviation threshold. Among them, the reduced cleanliness requirement can be the desired cleanliness minus the cleanliness deviation threshold. For more information about the cleanliness deviation threshold and the flow rate deviation threshold, see Figure 2 the relevant description.

[0175] In some embodiments of this specification, the target purification parameter is determined based on the requirements of the end user for the gas cleanliness, and the gas is purified based on the target purification parameter. The purified gas can meet the gas usage requirements of the end user. When the purification risk degree is relatively high, the cleanliness requirement is appropriately reduced, and the working power of the purification device is reduced, so as to reduce the risk caused by gas purification while ensuring a relatively high gas cleanliness.

[0176] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only an example and does not constitute a limitation to 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 fall within the spirit and scope of the exemplary embodiments of this specification.

[0177] Meanwhile, this specification uses specific terms to describe the embodiments of this specification. Such as "one embodiment", "an embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that the "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more at 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.

[0178] In addition, unless clearly stated in the claims, the order of the processing elements and sequences, the use of numerical letters, or the use of other names in this specification are not used to limit the order of the processes and methods of this specification. Although some currently considered useful invention embodiments are discussed through various examples in the above disclosure, it should be understood that such details only serve the purpose of illustration. The appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that conform to the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only through software solutions, such as installing the described system on existing servers or mobile devices.

[0179] Similarly, it should be noted that, in order to simplify the expression of the disclosure of this specification and thus help the understanding of one or more invention embodiments, in the previous description of the embodiments of this specification, sometimes multiple features are merged into one embodiment, drawing, or description thereof. However, this disclosure method does not mean that the features required by the object of this specification are more than those mentioned in the claims. In fact, the features of the embodiment are less than all the features of the individual embodiments disclosed above.

[0180] In some embodiments, numbers are used to describe components and quantitative attributes. It should be understood that such numbers used in the description of embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the said numbers allow a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may vary according to the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account the specified significant digits and adopt the method of retaining general digits. Although the numerical ranges and parameters used in some embodiments of this specification to confirm the breadth of their scope are approximate values, in specific embodiments, such numerical settings are as precise as possible within the feasible range.

[0181] For each patent, patent application, patent application publication and other materials cited in this specification, such as articles, books, specifications, publications, documents, etc., their entire contents are hereby incorporated into this specification by reference. Except for the application history documents that are inconsistent with or conflict with the content of this specification, and except for the documents that limit the broadest scope of the claims of this specification (currently or subsequently attached to this specification). It should be noted that if there are inconsistencies or conflicts between the descriptions, definitions, and / or uses of terms in the supplementary materials of this specification and the content described in this specification, the descriptions, definitions, and / or uses of terms in this specification shall prevail.

[0182] 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, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered to be 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 purification method for intelligent gas transmission pipelines, characterized in that The method is executed by the intelligent gas company management platform of the intelligent gas distribution pipeline purification system based on the Internet of Things, and includes: Determine the actual cleanliness of the target distribution pipeline based on the initial cleanliness of the gas to be transported, the first pipeline characteristics and the first gas characteristics related to the main pipeline, the second pipeline characteristics and the second gas characteristics related to the target distribution pipeline; Determine the target cleanliness based on the characteristics of the end users; Determine the cleanliness deviation based on the initial cleanliness and the target cleanliness; Generate a purification instruction based on the cleanliness deviation, and control the purification device in the target distribution pipeline to perform gas purification based on the purification instruction; In response to the start of execution of the purification instruction, generate a flow rate regulation instruction according to the first flow rate data of the main pipeline and the second flow rate data of the target distribution pipeline during the purification period, and regulate the opening degrees of the speed regulating valves in the main pipeline and the target distribution pipeline based on the flow rate regulation instruction.

2. The method according to claim 1, wherein The method further includes: Obtain the gas usage data of the end users corresponding to the target distribution pipeline; Determine the actual cleanliness based on the initial cleanliness, the first pipeline characteristics, the first gas characteristics, the second pipeline characteristics, the second gas characteristics and the gas usage data.

3. The method according to claim 2, wherein The method further includes: Obtain the gas network gas characteristics collected by the monitoring devices in the gas pipeline network; Construct a gas characteristic map based on the first pipeline characteristics, the second pipeline characteristics and the gas network gas characteristics; Determine the actual cleanliness according to the gas characteristic map through a prediction model; the prediction model is a machine learning model.

4. The method according to claim 3, wherein The gas characteristic map includes end user nodes, and the node characteristics of the end user nodes include the gas usage data.

5. The method according to claim 1, wherein The method further includes: Determine the initial purification parameters of the purification device in the target distribution pipeline based on the cleanliness deviation; Determine the end cleanliness based on the processed cleanliness, the downstream pipeline characteristics corresponding to the downstream pipeline of the purification device and the second gas characteristics; the end cleanliness refers to the cleanliness of the gas at the end user; In response to the end cleanliness being less than the desired cleanliness, update the initial purification parameters to determine the target purification parameters; Generate the purification instruction based on the target purification parameters.

6. A purifying Internet of Things system for intelligent gas transmission pipelines, characterized in that, Includes an intelligent gas government safety supervision management platform, an intelligent gas government safety supervision sensor network platform, an intelligent gas government safety supervision object platform, an intelligent gas company sensor network platform, and an intelligent gas equipment object platform; The intelligent gas government safety supervision object platform includes an intelligent gas company management platform, and the intelligent gas company management platform is configured to execute the intelligent gas distribution pipeline purification method as claimed in claim 1.

7. The Internet of Things system according to claim 6, characterized in that, The system further includes a gas user platform and an intelligent gas company service platform.

8. The Internet of Things system according to claim 6, wherein The intelligent gas company management platform is further configured to: Obtain the gas usage data of the end users corresponding to the target distribution pipeline; Determine the actual cleanliness based on the initial cleanliness, the first pipeline feature, the first gas feature, the second pipeline feature, the second gas feature, and the gas usage data.

9. The Internet of Things system according to claim 8, wherein The intelligent gas company management platform is further configured to: Obtain the gas network gas features collected by monitoring devices in the gas pipeline network; Construct a gas feature map based on the first pipeline feature, the second pipeline feature, and the gas network gas features; Determine the actual cleanliness according to the gas feature map through a prediction model; the prediction model is a machine learning model.

10. The Internet of Things system according to claim 6, characterized in that, The intelligent gas company management platform is further configured to: Determine the initial purification parameters of the purification device in the target subtransmission pipeline based on the cleanliness deviation; Determine the terminal cleanliness based on the processed cleanliness, the downstream pipeline feature corresponding to the downstream pipeline of the purification device, and the second gas feature; the terminal cleanliness refers to the cleanliness of the gas at the terminal user; In response to the terminal cleanliness being less than the desired cleanliness, update the initial purification parameters to determine the target purification parameters; Generate the purification instruction based on the target purification parameters.

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