Gas pipe network component safety replacement method based on regulatory network and internet of things system

Abstract

The application provides a gas pipe network component safety replacement method based on a regulatory network and an Internet of Things system, and relates to the field of pipe network component replacement. The Internet of Things system comprises a gas company management platform. The method is realized based on the gas company management platform, comprising: acquiring component characteristics of a gas numerical control component; determining a replacement necessity degree of the gas numerical control component based on the component characteristics; determining replacement parameters based on the replacement necessity degree; generating replacement task instructions and gas stop parameters based on the replacement parameters, and sending the replacement task instructions and the gas stop parameters to a maintenance user sub-platform and a government safety supervision and management platform respectively; in response to receiving the gas stop parameter determination instructions, generating a gas stop instruction and sending the gas stop instruction to a gas supply control device; and in response to receiving replacement completion information sent by the maintenance user sub-platform, determining that the component has been replaced and updating a data center. The application can determine the replacement necessity degree of the gas numerical control component, accurately replace the component, and ensure the normal operation of the gas pipe network.

Description

TECHNICAL FIELD

[0001] The present specification relates to the field of pipe network component replacement, in particular to a gas pipe network component safety replacement method based on a supervision network and an Internet of Things system. BACKGROUND

[0002] As a key component of urban energy supply, the gas pipe network is equipped with multiple gas numerical control components for gas monitoring. During the long-term operation of the gas pipe network, the components may fail or their performance may decline due to various factors. Therefore, timely replacement of the gas numerical control components is of great significance to maintaining the safe operation of the pipe network. At present, the replacement of the components often relies on periodic inspection or determination of complete failure of the components, which makes it difficult to ensure the timeliness and accuracy of the replacement.

[0003] Therefore, it is necessary to provide a gas pipe network component safety replacement method based on a supervision network and an Internet of Things system, which can determine the necessity of replacing each gas numerical control component, accurately determine the components that need to be replaced, and ensure the normal operation of the gas pipe network. SUMMARY

[0004] In order to solve the problem of how to accurately determine the gas numerical control components that need to be replaced and replace them, the present application provides a gas pipe network component safety replacement method based on a supervision network and an Internet of Things system.

[0005] The summary includes a gas pipe network component safety replacement method based on a supervision network, which is executed by a gas company management platform in a gas pipe network component safety replacement Internet of Things system based on a supervision network. The method includes: obtaining component characteristics of a gas numerical control component, the component characteristics including at least one of data processing characteristics, working characteristics, and environmental characteristics; determining the necessity of replacing the gas numerical control component based on the component characteristics; determining replacement parameters based on the necessity of replacing; generating replacement task instructions and gas stop parameters based on the replacement parameters, and sending them to a maintenance user sub-platform and a government safety supervision management platform, respectively; in response to receiving a stop parameter determination instruction from the government safety supervision management platform, generating a gas stop instruction and sending it to a gas supply control device to control the opening and closing state of the gas supply control device; and in response to receiving replacement completion information from the maintenance user sub-platform, determining that the component has been replaced and updating the data center.

[0006] The invention includes a gas pipeline network component safety replacement Internet of Things system based on a regulatory network, including a government safety supervision management platform and a government safety supervision object platform; the government safety supervision object platform includes a gas company management platform; the gas company management platform is configured to execute a gas pipeline network component safety replacement method based on a regulatory network. The Internet of Things system also includes a government safety supervision service platform, a government safety supervision sensing network platform, a gas company sensing network platform, a smart gas equipment object platform, a citizen user platform, a gas user platform, and a gas user service platform; the smart gas equipment object platform includes a gas supply control device; the gas user platform includes a maintenance user sub-platform and a gas user sub-platform; the gas user service platform includes a maintenance service sub-platform; and the gas company management platform includes a data center.

[0007] The beneficial effects brought by the above invention include but are not limited to: (1) determining the necessity of gas numerical control component replacement according to component characteristics, and then determining the components to be replaced and the corresponding replacement method to generate replacement task instructions and gas stop instructions for executing component replacement, stopping gas supply, and gas stop reminders, etc., realizing dynamic monitoring and intelligent decision-making of gas pipeline network component replacement, thereby improving the safety and efficiency of gas supply and ensuring the stable operation of the gas pipeline network; (2) accurately evaluating the collection confidence of the gas numerical control component through gas monitoring data, and then determining the operation stability of the gas numerical control component according to the collection confidence at multiple times, and then comparing the collection confidence and the operation stability with the corresponding preset values to reasonably adjust the component replacement necessity, making the component replacement necessity more reliable and accurate, which is conducive to accurately determining whether the gas numerical control component needs to be replaced, while saving replacement costs while ensuring the normal operation of the gas numerical control component; (3) by determining the low-power components in the qualified components, adjusting the data collection parameters of the low-power components, and adjusting the data collection parameters of the replaced components to maintain the total amount of collection to meet the preset requirements, it is possible to extend the working time of the gas numerical control component as much as possible while ensuring sufficient gas monitoring data collection. BRIEF DESCRIPTION OF DRAWINGS

[0008] The invention will be further illustrated in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, the same numbers represent the same structures, wherein:

[0009] Figure 1 is a platform structure schematic diagram of a gas pipeline network component safety replacement Internet of Things system based on a regulatory network according to some embodiments of the present specification;

[0010] Figure 2 is an exemplary flowchart of a gas pipeline network component safety replacement method based on a regulatory network according to some embodiments of the present specification;

[0011] Figure 3 is an example flowchart for determining the necessity of replacement according to some embodiments of the present specification;

[0012] Figure 4 is an example schematic diagram of an evaluation model according to some embodiments of the present specification;

[0013] Figure 5 is an example flowchart for determining the replacement parameter of the gas area according to some embodiments of the present specification. DETAILED DESCRIPTION

[0014] The drawings needed to be used in the description of the embodiments will be briefly introduced below. The drawings do not represent all the embodiments.

[0015] In the embodiments of the present application, the operations performed in steps are described. If not specially stated, the order of the steps is exchangeable, the steps can be omitted, and other steps can be included in the operation process.

[0016] Figure 1 is a schematic diagram of the platform structure of the gas pipe network component safety replacement Internet of Things system based on the regulatory network according to some embodiments of the present specification.

[0017] In some embodiments, as shown in Figure 1 , the gas pipe network component safety replacement Internet of Things system based on the regulatory network 100 can include a government safety regulatory service platform 110, a government safety regulatory management platform 120, a government safety regulatory sensing network platform 130, a government safety regulatory object platform 140, a gas company sensing network platform 150, a smart gas equipment object platform 160, a citizen user platform 170, a gas user platform 180, and a gas user service platform 190.

[0018] The government safety regulatory service platform 110 refers to a platform for providing safety regulatory services for the government, which can be configured as a server, and can interact with the government safety regulatory management platform 120 and the citizen user platform 170.

[0019] The government safety regulatory management platform 120 refers to a platform for safety management and regulation of the gas pipe network, which can be configured as a server.

[0020] The government safety regulatory sensing network platform 130 refers to a functional platform for safety management of the sensing communication of the government, which can be configured as a communication device and a gateway, etc.

[0021] In some embodiments, the government safety supervision sensing network platform 130 can be used for communication between the government safety supervision management platform 120 and the gas company management platform 141 in the government safety supervision object platform 140. For example, the government safety supervision management platform 120 can send a stop participation determination instruction to the gas company management platform 141 through the government safety supervision sensing network platform 130. For another example, the gas company management platform 141 can send a gas stop parameter to the government safety supervision management platform 120 through the government safety supervision sensing network platform 130.

[0022] The government safety supervision object platform 140 refers to an object platform for generating perception information and executing control information, and can include the gas company management platform 141.

[0023] The gas company management platform 141 refers to a comprehensive management platform for related information of a gas company, and can be configured as a server and a memory.

[0024] In some embodiments, the gas company management platform 141 can be configured to execute a gas pipe network component safety replacement method based on a regulatory network.

[0025] In some embodiments, the gas company management platform 141 includes a data center. The data center refers to a module for centrally storing and processing data.

[0026] In some embodiments, the gas company management platform 141 can also include a processor. The processor can process data and / or information obtained from other platforms. The processor can execute program instructions based on these data, information and / or processing results to perform one or more functions described in the present application. For example only, the processor can include a central processing unit (CPU), an application specific integrated circuit (ASIC), etc.

[0027] The gas company sensing network platform 150 refers to a comprehensive management platform for sensing information of a gas company, and can be configured as a communication network, a gateway, etc.

[0028] In some embodiments, the gas company sensing network platform 150 can be used for communication between the gas company management platform 141 in the government safety supervision object platform 140 and the smart gas equipment object platform 160.

[0029] The smart gas equipment object platform 160 refers to a functional platform for real-time monitoring and intelligent regulation of a gas pipe network, and can include a gas numerical control component and a gas supply control device.

[0030] Gas numerical control assembly refers to a device that uses numerical control technology to control and monitor gas. For example, gas flow sensor, gas pressure sensor, gas temperature sensor. In some embodiments, the gas numerical control assembly can be deployed in the pipeline of multiple gas pipelines in the gas pipeline network to monitor the gas in the pipeline.

[0031] It should be noted that the gas numerical control assembly in the present specification is a battery-powered device, that is, a battery is arranged inside the gas numerical control assembly.

[0032] Gas supply control device refers to a device related to adjusting gas supply. In some embodiments, the gas supply control device can be deployed in the pipeline of multiple gas pipelines in the gas pipeline network or at the entrance and exit of the pipeline, etc., for adjusting and controlling the gas flow, gas pressure and gas delivery direction, etc. For example, gas valve, etc.

[0033] Citizen user platform 170 refers to a platform for interacting with citizens, which can be configured as a terminal device of public media. For example, a television medium that faces all citizens.

[0034] Gas user platform 180 refers to a platform for interacting with gas users, which can be configured as a terminal device of gas users. For example, a mobile phone, a computer, etc. of a gas user.

[0035] In some embodiments, the gas user platform 180 can include a maintenance user sub-platform and a gas user sub-platform.

[0036] Maintenance user sub-platform refers to a functional platform that provides maintenance services and user support. For example, a work terminal used by a gas maintenance personnel.

[0037] Gas user sub-platform refers to a sub-platform for interacting with gas use users. For example, a terminal device used by a gas use user.

[0038] Gas user service platform 190 refers to a platform for receiving and transmitting gas user related data and / or information, which can be configured as a server.

[0039] In some embodiments, the gas user service platform 190 can include a maintenance service sub-platform. The maintenance service sub-platform refers to a platform that can be used to receive and transmit maintenance information.

[0040] In some embodiments, the gas user platform 180 can interact with the gas company management platform 141 through the gas user service platform 190. For example, the maintenance service sub-platform can receive replacement task instructions from the gas company management platform 141 and send them to the maintenance user sub-platform. For another example, the gas company management platform 141 sends a gas stop reminder information to the gas user sub-platform through the maintenance service sub-platform.

[0041] In some embodiments of the present specification, the gas pipeline network component safety replacement Internet of Things system based on the regulatory network can form an information operation closed loop between various functional platforms and coordinate and regularly operate under the unified management of the gas company management platform, so as to realize the informatization and intelligentization of the gas pipeline network component safety replacement.

[0042] It should be noted that the above description of the gas pipeline network component safety replacement Internet of Things system based on the regulatory network and its platform is for the convenience of description, and cannot limit the present specification to the scope of the embodiments. It can be understood that for those skilled in the art, after understanding the principle of the system, any combination of the platforms or connection of the sub-systems with other platforms can be made without departing from the principle.

[0043] Figure 2 is an exemplary flowchart of the gas pipeline network component safety replacement method based on the regulatory network according to some embodiments of the present specification.

[0044] In some embodiments, the flow 200 can be executed by the gas company management platform 141 in the gas pipeline network component safety replacement Internet of Things system based on the regulatory network 100. For example, by the processor in the gas company management platform 141.

[0045] As shown in Figure 2 The flow 200 includes the following steps 210-260.

[0046] Step 210, obtaining component characteristics of the gas numerical control component.

[0047] The component characteristics refer to the related characteristics of the gas numerical control component. In some embodiments, the component characteristics can include at least one of data processing characteristics, working characteristics and environmental characteristics.

[0048] The data processing characteristics refer to the related characteristics of the gas numerical control component processing data. For example, data acquisition parameters and data transmission parameters.

[0049] The data acquisition parameters refer to the parameters of the gas numerical control component acquiring data. For example, data acquisition frequency and data acquisition amount. The data acquisition frequency refers to the number of times of data acquisition of the gas numerical control component per unit time. The data acquisition amount refers to the amount of data acquired by the gas numerical control component at a time.

[0050] The data transmission parameters refer to the parameters of the gas numerical control component transmitting data. For example, data transmission frequency and data transmission amount. The data transmission frequency refers to the number of times of data transmission of the gas numerical control component per unit time. The data transmission amount refers to the amount of data transmitted by the gas numerical control component at a time.

[0051] The working feature refers to the relevant features of the working operation of the gas numerical control assembly. For example, the start-stop frequency and the working duration.

[0052] The start-stop frequency refers to the total number of times of starting or stopping of the gas numerical control assembly. The working duration refers to the length of time of continuous working after a single start of the gas numerical control assembly.

[0053] The environmental feature refers to the relevant features of the environmental conditions in which the gas numerical control assembly is located. For example, the environmental temperature, the environmental humidity, the environmental pH value, etc.

[0054] In some embodiments, the component features of the gas numerical control assembly can be acquired by the smart gas equipment object platform, uploaded to the gas company management platform via the gas company sensing network platform, and stored in the data center. The processor can directly call the component features of the gas numerical control assembly from the data center.

[0055] In step 220, the necessity of replacement of the gas numerical control assembly is determined based on the component features.

[0056] The necessity of replacement refers to the necessary degree of the gas numerical control assembly needing to be replaced. In some embodiments, the necessity of replacement can be represented by a numerical value of 0-1, and the higher the numerical value, the higher the necessity of replacement.

[0057] In some embodiments, the processor can determine the necessity of replacement in multiple ways based on the component features.

[0058] For example, the processor can construct a current first vector based on the current data processing feature, the working feature, and the environmental feature; retrieve the historical first vector with the highest first similarity with the current first vector in the first vector database, and take it as a reference first vector, the reference first vector being composed of a reference data processing feature, a reference working feature, and a reference environmental feature; in response to the first similarity between the current first vector and the reference first vector being greater than a first similarity threshold, if any component in the current first vector is less than the corresponding component in the reference first vector, the first similarity is taken as the current necessity of replacement; if there is a component in the current first vector greater than the corresponding component in the reference first vector, the one or more components in the current first vector are replaced with the corresponding components in the reference first vector to reconstruct the current first vector; and the above steps are repeated until the current necessity of replacement is determined.

[0059] The comparison of the size of the component in the current first vector with the corresponding component in the reference first vector includes a comparison of the size of the current data processing feature with the reference data processing feature, a comparison of the size of the current working feature with the reference working feature, and a comparison of the severity of the current environment feature with the severity of the reference environment feature. The severity can be represented by the difference between the actual environment feature and the ideal environment feature. The greater the absolute value of the difference, the higher the severity. For example, the severity of the reference environment feature can be represented by the difference between the historical actual environment feature and the historical ideal environment feature.

[0060] In some embodiments, the first vector database can be constructed by the processor or the technician based on historical data, and the first vector database includes historical first vectors of a plurality of replaced historical gas CNC components and corresponding historical replacement necessities.

[0061] In some embodiments, the first similarity can be represented by the Euclidean distance, the cosine similarity, etc. The first similarity threshold can be set by default by the processor or preset by the technician according to experience.

[0062] In some embodiments, the processor can further determine the battery replacement necessity based on the initial battery power, the data processing feature, the first working feature and the first environment feature of the gas CNC component, and determine the component wear degree based on the second working feature, the second environment feature and the average gas feature, and then determine the component replacement necessity. For more information about this part, please refer to Figure 3 and the related description thereof.

[0063] Step 230, determining the replacement parameter based on the replacement necessity.

[0064] The replacement parameter refers to the relevant parameter about the replacement of the gas CNC component. In some embodiments, the replacement parameter can include the component to be replaced and the replacement mode of the component to be replaced.

[0065] The component to be replaced refers to the gas CNC component determined to be replaced.

[0066] The replacement mode refers to the mode of replacing the gas CNC component. In some embodiments, the replacement mode can include battery replacement and component overall replacement.

[0067] In some embodiments, the processor can determine the replacement parameter in multiple ways based on the replacement necessity. For example, the first database can further include a plurality of historical first vectors of the replaced historical gas CNC components, and the processor can determine the gas CNC component with a replacement necessity higher than the reference replacement necessity as the component to be replaced; retrieve the reference first vector of the component to be replaced from the first vector database, and determine the replacement mode corresponding to the reference first vector as the replacement mode of the component to be replaced.

[0068] In some embodiments, the processor can determine the minimum value of the historical replacement necessity of the plurality of historical gas CNC components in the first vector database as the reference replacement necessity.

[0069] In some embodiments, the processor can further determine the replacement parameter of a plurality of gas areas of the gas pipeline network based on the pipeline location information and the replacement necessity of the gas CNC components in the gas pipeline network. For more information about this part, please refer to Figure 5 and the related description thereof.

[0070] At step 240, the replacement task instruction and the gas stop parameter are generated based on the replacement parameter and sent to the maintenance user sub-platform and the government safety supervision and management platform, respectively.

[0071] The replacement task instruction refers to the instruction for performing the replacement task on the component to be replaced. In some embodiments, the replacement task instruction can include the component to be replaced, the replacement mode of the component to be replaced, and the replacement period of the component to be replaced.

[0072] In some embodiments, the replacement parameter can further include the replacement period of the component to be replaced. The replacement period can be determined by the processor based on the queuing situation of the replacement task to be performed. For example, if the queuing time of the replacement task to be performed is 8h, the replacement period of the current replacement task is a certain period of time after 8h. The length of the replacement period is represented by the product of the total number of components to be replaced in the current replacement task and the average replacement time of a single component. The average replacement time of a single component can be obtained by the processor or the technician based on historical data statistics.

[0073] In some embodiments, the processor can generate the replacement task instruction autonomously according to a preset template based on the replacement parameter.

[0074] The gas stop parameter refers to the related parameter about stopping the gas supply. In some embodiments, the gas stop parameter can include the gas stop pipeline and the gas stop period.

[0075] The gas stop pipeline refers to the gas pipeline where the gas supply is stopped. The gas stop period refers to the time period during which the gas supply is stopped.

[0076] In some embodiments, the processor can generate the gas stop parameter according to a preset rule based on the replacement parameter. For example, the processor can take the gas pipeline where the component to be replaced is located as the gas stop pipeline, and take the replacement time period of the component to be replaced as the gas stop time period.

[0077] In some embodiments, the processor can send the replacement task instruction to the maintenance user sub-platform via the maintenance service sub-platform, so that the maintenance personnel perform the replacement task on the component to be replaced in response to the replacement task instruction; and the processor can also send the gas stop parameter to the government safety supervision management platform via the government safety supervision sensing network platform, so that the government safety supervision management platform determines and generates the stop parameter determination instruction.

[0078] In step 250, in response to receiving the stop parameter determination instruction of the government safety supervision management platform, a gas stop instruction is generated and sent to the gas supply control device to control the opening and closing state of the gas supply control device.

[0079] The stop parameter determination instruction refers to an instruction for determining the gas stop parameter. In some embodiments, the stop parameter determination instruction can include the determined gas stop pipeline and the gas stop time period.

[0080] In some embodiments, after receiving the replacement task instruction, the maintenance personnel can adjust the replacement time period in the replacement parameter on the maintenance user sub-platform according to the actual situation (for example, there is a replacement task to be performed to cancel the queue, and the replacement time period can be appropriately advanced), and the maintenance user sub-platform sends the adjusted replacement parameter to the government safety supervision management platform. The government safety supervision management platform automatically updates the gas stop time period in the gas stop parameter based on the adjusted replacement parameter to determine the stop parameter determination instruction.

[0081] The gas stop instruction refers to an instruction for stopping the gas supply of the gas pipeline. In some embodiments, the gas stop instruction can include the gas supply control device corresponding to the gas stop pipeline and the closing time period of the gas supply control device.

[0082] In some embodiments, the processor can obtain the stop parameter determination instruction through the government safety supervision management platform, determine the gas supply control device corresponding to the gas stop pipeline based on the gas stop pipeline in the stop parameter determination instruction, determine the closing time period of the gas supply control device based on the gas stop time period, and thus determine the gas stop instruction; and send the gas stop instruction to the gas supply control device via the gas company sensing network platform to control the opening and closing state of the gas supply control device.

[0083] In some embodiments, the processor can control the opening and closing state of the gas supply control device based on the gas stop time period in the gas stop instruction.

[0084] In some embodiments, the processor can control the opening and closing state of the gas supply control device based on the gas stop time period in the gas stop instruction.

[0085] In some embodiments, the processor can also determine the gas stop reminding information based on the stop parameter determination instruction, and send the gas stop reminding information to the gas user sub-platform and the citizen user platform.

[0086] In some embodiments, the form of the gas stop reminding information can include telephone notification, SMS notification, television notification, gas stop reminding identification, etc.

[0087] In some embodiments, the processor can send the gas stop reminding information to the gas user sub-platform in advance based on the gas stop period in the stop parameter determination instruction, to remind the gas user to make preparations in advance for the gas stop, and can also send the gas stop reminding information to the citizen user platform, to increase the notification channel and further expand the notification coverage, and improve the probability of the gas user obtaining the gas stop reminding information.

[0088] In step 260, the replaced component is determined and the data center is updated in response to receiving the replacement completion information sent by the repair user sub-platform.

[0089] The replacement completion information refers to the notification information that the to-be-replaced component has completed replacement.

[0090] In some embodiments, after the repair personnel complete the replacement of the to-be-replaced component, the repair personnel can perform a replacement completion operation (such as clicking a battery replacement completion button, inputting the replaced component, etc.) on the repair user sub-platform. The repair user sub-platform can generate the replacement completion information and send the replacement completion information to the gas company management platform through the repair service sub-platform.

[0091] The replaced component refers to the gas numerical control component after the replacement of the to-be-replaced component.

[0092] It should be noted that if the replacement mode of the to-be-replaced component after the replacement is completed is battery replacement, the data corresponding to the to-be-replaced component is compressed and stored to save space. If the replacement mode of the to-be-replaced component after the replacement is completed is that the entire component is replaced, the data corresponding to the to-be-replaced component is reset to avoid unlimited data accumulation and increase the system operation load.

[0093] In some embodiments of the present specification, the necessity of replacing the gas numerical control component is determined according to the component characteristics, and then the to-be-replaced component and the corresponding replacement mode are determined, to generate the replacement task instruction and the gas stop instruction, for performing component replacement, stopping gas supply, and gas stop reminding, etc. The dynamic monitoring and intelligent decision-making of the gas pipe network component replacement are realized, thereby improving the safety and efficiency of the gas supply and ensuring the stable operation of the gas pipe network.

[0094] Figure 3is an exemplary flowchart of determining the necessity of replacement according to some embodiments of the present specification. In some embodiments, the flow 300 can be executed by the gas company management platform 141. For example, by the processor in the gas company management platform 141.

[0095] In some embodiments, the working features can include first working features and second working features; and the environmental features can include first environmental features and second environmental features.

[0096] The first working features and the second working features are working features of time periods respectively related to historical time points of replacing the battery and replacing the component; and the first environmental features and the second environmental features are environmental features of time periods respectively related to historical time points of replacing the battery and replacing the component.

[0097] That is, the first working features are working features of the gas numerical control component in a first time period, and the second working features are working features of the gas numerical control component in a second time period; and the first environmental features are environmental features of the gas numerical control component in the first time period, and the second environmental features are environmental features of the gas numerical control component in the second time period. Wherein, the first time period is a time period from a historical time point of last replacing the battery to a current time point, and the second time period is a time period from a historical time point of last replacing the component to the current time point.

[0098] The historical time point of last replacing the battery and the historical time point of last replacing the component can be determined based on uploading time of historical replacement completion information.

[0099] In some embodiments, the necessity of replacement can include a battery replacement necessity and a component replacement necessity.

[0100] The battery replacement necessity refers to a necessary degree of replacing the battery of the gas numerical control component. The component replacement necessity refers to a necessary degree of replacing the whole gas numerical control component.

[0101] In some embodiments, the battery replacement necessity and the component replacement necessity can be represented by a numerical value of 0-1, and the higher the numerical value, the higher the battery replacement necessity and the component replacement necessity.

[0102] As shown in FIG. 3, the flow 300 can include the following steps 310-320. Figure 3

[0103] Step 310, based on the initial battery capacity of the gas numerical control component, the data processing feature, the first working feature and the first environmental feature, determining the remaining battery capacity of the gas numerical control component, and determining the battery replacement necessity.

[0104] ​In some embodiments, the processor can retrieve in the power consumption database, determine the historical first environmental feature with the highest similarity to the current first environmental feature, take it as the reference first environmental feature, determine the historical power consumption speed corresponding to the reference first environmental feature as the power consumption speed of the current gas CNC assembly; determine the product of the data acquisition frequency and the data acquisition amount in the data processing feature of the current gas CNC assembly, and the start-stop frequency and the working duration in the first working feature as the total data acquisition amount of the gas CNC assembly; determine the product of the data transmission frequency and the data transmission amount in the data processing feature of the current gas CNC assembly, and the start-stop frequency and the working duration in the first working feature as the total data transmission amount of the gas CNC assembly; determine the product of the sum of the total data acquisition amount and the total data transmission amount, and the power consumption speed as the battery power consumption amount; determine the difference between the initial battery power amount and the battery power consumption amount as the battery residual power amount.

[0105] The power consumption database includes historical first environmental features of a plurality of replaced historical gas CNC assemblies and corresponding historical power consumption speeds.

[0106] The power consumption speed refers to the battery power amount consumed for collecting and / or transmitting unit data. The historical power consumption speed in the power consumption database can be represented by the ratio of the historical battery power consumption amount of the historical gas CNC assembly to the historical total data amount under the historical first environmental feature. The historical total data amount is the sum of the historical total data acquisition amount and the historical total data transmission amount.

[0107] In some embodiments, the processor can determine the necessity of battery replacement based on the battery residual power amount.

[0108] In some embodiments, the processor can construct a current second vector based on the battery residual power amount, the working feature and the environmental feature, determine the historical second vector with the highest second similarity to the current second vector in the second vector database, take it as the reference second vector, and determine the historical residual working duration corresponding to the reference second vector as the residual working duration of the battery of the current gas CNC assembly; the necessity of battery replacement is negatively correlated with the residual working duration, and the shorter the residual working duration, the higher the necessity of battery replacement.

[0109] In some embodiments, the second vector database can be constructed by the processor or a technician based on historical data, and the second vector database includes historical second vectors of a plurality of historical gas CNC assemblies and corresponding historical residual working durations. The setting of the second similarity can refer to the first similarity.

[0110] Step 320, determining the assembly wear degree of the gas CNC assembly based on the second working feature, the second environmental feature and the gas average feature, and determining the necessity of assembly replacement.

[0111] The gas average characteristic refers to an average amount of a gas-related parameter. For example, the gas average characteristic can include a gas average amount, a gas average flow rate, a gas average temperature, a gas average pressure, a gas average impurity content. In some embodiments, the gas numerical control assembly can collect the gas-related parameters, and the processor can calculate the gas average characteristic based on the gas-related parameters.

[0112] The component wear degree refers to the degree of performance degradation or function loss of the component. In some embodiments, the component wear degree can be represented by a percentage between 0 and 1, and the greater the percentage, the higher the component wear degree.

[0113] In some embodiments, the processor can determine a wear coefficient of the gas numerical control assembly based on the second working characteristic, the second environmental characteristic, and the gas average characteristic, in combination with the reference use data; and determine the component wear degree based on the component use duration, the design service life, and the wear coefficient of the gas numerical control assembly.

[0114] The reference use data refers to related data of the gas numerical control assembly whose service life reaches the design service life, including a reference second working characteristic, a reference second environmental characteristic, and a reference gas average characteristic. In some embodiments, the reference use data can be obtained based on historical data.

[0115] The wear coefficient refers to a coefficient for measuring the speed of wear of the gas numerical control assembly. In some embodiments, the faster the wear of the gas numerical control assembly, the higher the wear coefficient.

[0116] In some embodiments, the processor can obtain a working characteristic ratio, an environmental characteristic ratio, and a gas characteristic ratio by respectively corresponding the second working characteristic, the second environmental characteristic, and the gas average characteristic of the gas numerical control assembly to the second working characteristic, the second environmental characteristic, and the gas average characteristic in the reference use data; and obtain the wear coefficient by weighting and summing the three ratios according to load weights.

[0117] The load weight can represent the influence degree of different characteristic data on the wear coefficient. For example, the environment has the greatest influence on the wear coefficient, and thus the load weight of the environmental characteristic ratio is the greatest. In some embodiments, the load weights of different characteristic ratios can be preset by the system or the technician.

[0118] In some embodiments, the processor can also determine the load weight by a control variable method. The processor can group the plurality of replaced historical gas CNC components by controlling variables, the variables can include the second working feature, the second environmental feature and the gas average feature; the historical gas CNC components with two same variables and one different variable are divided into a group, that is, the plurality of historical gas CNC components can be divided into 3 groups, and each group of historical gas CNC components corresponds to a different variable; the variable influence value of the different variable corresponding to each group of historical gas CNC components is calculated; the ratio of the variable influence values is taken as the ratio of the load weights, and the sum of the load weights is 1.

[0119] For example, the processor can divide the historical gas CNC components with the same second working feature and second environmental feature and different gas average features into a group, and the different variable corresponding to the group of historical gas CNC components is the gas average feature; determine the first difference value between the maximum gas average feature and the minimum gas average feature in the gas average feature (such as the gas average temperature) of the group of historical gas CNC components, and determine the second difference value between the actual service life of the historical gas CNC component corresponding to the maximum gas average feature and the actual service life of the historical gas CNC component corresponding to the minimum gas average feature; the ratio of the first difference value and the second difference value is determined as the variable influence value of the gas average feature; similarly, the variable influence value of the second working feature and the variable influence value of the second environmental feature are determined, and the ratio of the variable influence values of the second working feature, the second environmental feature and the gas average feature is determined as the ratio of the load weights of the working feature ratio, the environmental feature ratio and the gas feature ratio, and the sum of the load weights is 1, to determine the load weights of the working feature ratio, the environmental feature ratio and the gas feature ratio.

[0120] The component use duration refers to the actual running time of the gas CNC component from the start of use to the current time.

[0121] The design service life refers to the normal working duration preset by the gas CNC component in the factory setting.

[0122] In some embodiments, the processor can determine the component wear degree based on the component use duration, the design service life and the wear coefficient of the gas CNC component. For example, the component wear degree can be calculated by the following formula (1):

[0123] (1)

[0124] Wherein, W is the component wear degree, C is the wear coefficient, T is the component use duration, and U is the design service life.

[0125] In some embodiments of the present disclosure, by comprehensively considering the second working feature, the second environmental feature, the gas average feature and the reference use data, the importance and influence of each factor are calculated more accurately to evaluate the loss degree of the gas numerical control assembly.

[0126] In some embodiments, the processor can determine the necessity of replacing the assembly based on the loss degree of the assembly. For example, the processor can calculate the difference between the loss degree of the assembly and the average historical loss degree. The larger the difference, the higher the necessity of replacing the assembly.

[0127] The average historical loss degree refers to the average value of the historical loss degree of the historical assembly in the historical replacement record.

[0128] In some embodiments of the present disclosure, by comprehensively analyzing the working feature, the environmental feature, the data processing feature and the gas average feature of the gas numerical control assembly, the battery remaining capacity and the loss degree of the assembly can be accurately evaluated, and the necessity of replacing the battery and the necessity of replacing the assembly can be determined, thereby providing data support for making reasonable replacement decisions, which is beneficial to optimizing maintenance cost and ensuring safe operation of the gas pipeline network.

[0129] In some embodiments, the processor can also obtain the gas monitoring data collected by the gas numerical control assembly based on the data center; determine the collection confidence of the gas numerical control assembly based on the gas monitoring data; determine the operation stability of the gas numerical control assembly based on the plurality of collection confidences corresponding to the plurality of time points; and adjust the necessity of replacing the assembly based on the collection confidence and the operation stability.

[0130] For more information about the gas numerical control assembly, the data center, the gas monitoring data and the necessity of replacing the assembly, please refer to the related description of Figures 2-3 .

[0131] The gas monitoring data refers to the data collected by the gas numerical control assembly. For example, gas flow, gas pressure, gas temperature, etc.

[0132] In some embodiments, the gas numerical control assembly can upload the collected gas monitoring data to the data center of the gas company management platform through the gas company sensing network platform, and the processor can directly retrieve the gas monitoring data from the data center.

[0133] The collection confidence refers to the reliability of the collection work of the gas numerical control assembly. In some embodiments, the collection confidence can be represented by a value between 0 and 1. The larger the value, the higher the collection confidence of the gas numerical control assembly, and the more reliable the gas monitoring data collected by the gas numerical control assembly.

[0134] Figure 4is an exemplary schematic diagram for determining collection confidence according to some embodiments of the present specification.

[0135] In some embodiments, as shown in Figure 4 the processor can construct a data correlation graph 450 based on the plurality of gas numerical control components 410 located on the same gas pipeline, the gas monitoring data 420 collected by the plurality of gas numerical control components, the pipeline information 430 between the plurality of gas numerical control components, and the numerical control component types 440 of the plurality of gas numerical control components; and determine the collection confidence 470 by evaluating the model 460 based on the data correlation graph 450.

[0136] The pipeline information between the gas numerical control components refers to the relevant information of the gas pipeline between the gas numerical control components. For example, the interval pipeline length, the pipeline inner diameter, the pipeline cleaning time, etc.

[0137] The interval pipeline length refers to the length of the gas pipeline between two gas numerical control components. In some embodiments, the interval pipeline length can be determined by the processor based on the installation position coordinates of the gas numerical control components and the gas pipeline network distribution map. For example, the length of the gas pipeline between two gas numerical control components is measured according to the installation position coordinates marked on the gas pipeline network distribution map, which is the interval pipeline length. The installation position coordinates of the gas numerical control components can be obtained by the positioning device of the gas numerical control components or the installation record data during installation.

[0138] The pipeline inner diameter refers to the diameter of the cross section inside the gas pipeline. The pipeline cleaning time refers to the time for cleaning the pipeline. In some embodiments, the gas pipeline network distribution map, the pipeline inner diameter, and the pipeline cleaning time can be obtained by the processor based on the data center.

[0139] The numerical control component type refers to the type of the gas numerical control component. For example, the gas numerical control component can be divided into temperature numerical control components, flow data components, and other numerical control component types according to functions.

[0140] The data correlation graph refers to a graph that shows the relationship between the gas numerical control components, the gas monitoring data, the pipeline information, and the numerical control component types. In some embodiments, the data correlation graph is composed of multiple nodes and multiple edges.

[0141] The multiple nodes of a data correlation graph are multiple gas numerical control components located on the same gas pipeline, one node corresponds to one gas numerical control component, and the node features are the gas monitoring data and the numerical control component type of the gas numerical control component.

[0142] The edge of the data correlation graph is the gas pipeline between the gas numerical control components, and the edge features are the pipeline information between the gas numerical control components.

[0143] In some embodiments, multiple gas digital control components on a gas pipeline and the gas pipelines between the multiple gas digital control components constitute a data association graph.

[0144] The evaluation model refers to a model used to determine acquisition confidence. In some embodiments, the evaluation model can be a machine learning model, such as a graph neural network (GNN).

[0145] In some embodiments, as Figure 4 As shown, the input of the evaluation model 460 can be a data association graph 450, and the output can be a collection confidence 470 of a node in the data association graph. The data association graph 450 can be determined by a processor based on the gas digital control component 410, gas monitoring data 420, pipeline information 430, and digital control component type 440.

[0146] In some embodiments, the evaluation model can be trained and acquired through various methods. For example, the evaluation model can be trained and acquired using multiple training samples with training labels. A set of training samples for training the evaluation model may include a sample data association graph, where the training labels corresponding to the training samples are the actual acquisition confidence levels of the sample gas CNC components corresponding to multiple nodes in the sample data association graph.

[0147] In some embodiments, the processor can obtain multiple training samples based on historical data, wherein one historical data association map can serve as a training sample. For each sample gas CNC component in each training sample, the processor can obtain from a data center a historical gas CNC component of the same model and with accurate data as the sample gas CNC component, use it as a reference gas CNC component for the sample gas CNC component, and obtain multiple reference gas monitoring data collected by the reference gas CNC component at the same location and time. The processor can calculate multiple differences between the multiple sample gas monitoring data of the sample gas CNC component and the multiple reference gas monitoring data of the reference gas CNC component. If the difference is within an allowable error range, the sample gas monitoring data is considered accurate. The processor determines the ratio of the number of accurate sample gas monitoring data to the number of all sample gas monitoring data as the actual acquisition confidence. The allowable error range can be obtained from the factory setting value of the gas CNC component.

[0148] For example, the multiple sample gas monitoring data of the sample gas CNC component include sample gas temperature, sample gas flow, and sample gas pressure, and the multiple reference gas monitoring data of the reference gas CNC component include reference gas temperature, reference gas flow, and reference gas pressure. If the difference between the sample gas temperature and the reference gas temperature is within the allowable error range, the sample gas temperature is accurate. Similarly, if the sample gas flow and sample gas pressure are determined to be inaccurate, the actual acquisition confidence of the sample gas CNC component is .

[0149] In some embodiments, after the to-be-replaced component is replaced, the processor can determine the collection confidence of the replaced component by evaluating the model; in response to the fact that, after the replacement is performed, there are still more than a preset number of gas numerical control components whose collection confidence is less than a preset confidence threshold, it is determined that the output result of the evaluation model is not accurate enough, and therefore an incremental training set needs to be generated to perform incremental update on the evaluation model.

[0150] The processor can collect gas monitoring data of the gas numerical control component for multiple times, and reconstruct a large number of data correlation graphs as incremental training samples; adjust the collection confidence of the replaced component to a reference confidence, and keep the collection confidence of other non-replaced gas numerical control components unchanged to obtain labels corresponding to the incremental training samples; based on an incremental training set composed of a large number of incremental training samples and their labels, perform incremental training on the current evaluation model, and the training method can refer to the training process described above. The preset number and the preset confidence threshold can be set by the technician in advance. The reference confidence refers to the mean value of the collection confidence of the gas monitoring data of the accurate gas numerical control component.

[0151] In some embodiments of the present specification, through multiple gas numerical control components on the same gas pipeline, a data correlation graph is constructed in combination with multiple data and information, and based on the data correlation graph, the collection confidence of multiple gas numerical control components is accurately and efficiently determined through a machine learning model, so as to effectively evaluate the reliability of the data collected by the gas numerical control component, so as to reasonably determine the necessity of component replacement in the subsequent process.

[0152] The running stability refers to the stability of the operation of the gas numerical control component.

[0153] In some embodiments, the processor can determine the stable duration of the gas numerical control component based on the collection confidence of the gas numerical control component at multiple time points and multiple confidence fluctuation values relative to the reference confidence at the multiple time points; and determine the running stability based on the stable duration and the multiple confidence fluctuation values at the multiple time points.

[0154] The confidence fluctuation value refers to the fluctuation range of the collection confidence relative to the reference confidence. For example, the confidence fluctuation value can be the difference between the collection confidence and the reference confidence.

[0155] The stable duration refers to the length of time during which the collection confidence remains stable. In some embodiments, the processor can determine multiple confidence fluctuation values corresponding to the collection confidence at multiple time points; take the longest period of time formed by multiple continuous time points during which the confidence fluctuation value is continuously positive as the stable period, and take the average duration of the multiple stable periods as the stable duration.

[0156] In some embodiments, the longer the stability duration, the smaller the mean value of the confidence fluctuation value, the higher the running stability. For example, the processor can calculate the running stability based on the following formula (2):

[0157] (2)

[0158] wherein, is the running stability, k is the stability coefficient, is the stability duration, is the mean value of the plurality of confidence fluctuation values, and the stability coefficient k can be pre-set by the processor or the technician.

[0159] In some embodiments, the processor adjusts the component replacement necessity in multiple ways based on the acquisition confidence and the running stability. For example, in response to the acquisition confidence being lower than a pre-set confidence threshold, the processor can increase the component replacement necessity, and the increase in the component replacement necessity can be consistent with the difference in the acquisition confidence from the pre-set confidence threshold. For another example, in response to the acquisition confidence being higher than the confidence threshold and the running stability being lower than a pre-set stability threshold, the processor can increase the component replacement necessity, and the increase in the component replacement necessity can be consistent with the difference in the running stability from the pre-set stability threshold. The pre-set stability threshold can be pre-set by the processor or the technician.

[0160] In some embodiments of the present specification, the acquisition confidence of the gas numerical control component is accurately evaluated based on the gas monitoring data, the running stability of the gas numerical control component is determined according to the acquisition confidence at multiple time points, and then the component replacement necessity is reasonably adjusted by comparing the acquisition confidence and the running stability with the corresponding pre-set values, so that the component replacement necessity is more reliable and accurate, which is conducive to accurately determining whether the gas numerical control component needs to be replaced, ensuring the normal operation of the gas numerical control component while saving replacement costs.

[0161] In some embodiments, the processor can determine the replacement parameters of a plurality of gas regions of the gas pipe network based on the pipe network location information and the replacement necessity of the gas numerical control component in the gas pipe network.

[0162] For more information about the gas numerical control component, the replacement necessity, and the replacement parameters, please refer to the related description of Figures 2-4 .

[0163] The pipe network location information refers to the location information of the gas numerical control component in the gas pipe network. In some embodiments, the pipe network location information of the gas numerical control component can include the pipe level where the gas numerical control component is located and the installation position coordinates.

[0164] The pipeline level refers to the classification level of the gas pipeline where the gas digital control component is located. For example, the pipeline level can include the main pipeline, the first branch, the second branch, etc. In some embodiments, the pipeline level can be directly obtained by the processor based on the data center.

[0165] For more information about the installation location coordinates, see the relevant description of Figure 4 .

[0166] The gas area refers to a sub-area in the gas pipeline network. In some embodiments, the gas pipeline network can be divided into multiple gas areas, and the division of the gas area can be divided by the technician or divided by the processor according to the preset rule (such as the equal area rule).

[0167] Figure 5 is an exemplary flowchart for determining the replacement parameter of the gas area according to some embodiments of the present specification. In some embodiments, the flow 500 can be executed by the gas company management platform 141. For example, executed by the processor in the gas company management platform 141.

[0168] As shown in Figure 5 , the flow 500 can include steps 510 and 520.

[0169] Step 510, based on the pipeline location information of the gas digital control component in the gas pipeline network, the gas use data of the gas pipeline where the gas digital control component is located, determining multiple gas areas of the gas pipeline network through a clustering algorithm.

[0170] The gas use data refers to the relevant data of the gas user using the gas. For example, the gas use data of the gas pipeline where the gas digital control component is located can include the total amount of gas use, the gas use time length, etc. of the gas user of the gas pipeline where the gas digital control component is located. In some embodiments, the processor can obtain the gas use data based on the gas user platform.

[0171] In some embodiments, the clustering algorithm can be a clustering algorithm for a given number of clusters. For example, the K-means clustering algorithm and its derivative clustering algorithm, etc.

[0172] In some embodiments, the processor determines a plurality of gas regions of the gas pipe network based on the pipe network location information of the gas numerical control components in the gas pipe network, the gas usage data of the gas pipe where the gas numerical control components are located, through a clustering algorithm. Taking the K-means clustering algorithm as an example, the processor can form a third vector based on the pipe network location information of a gas numerical control component and the gas usage data of the pipe where the gas numerical control component is located, and a plurality of third vectors correspond to a plurality of gas numerical control components; K cluster centers are randomly determined from the plurality of third vectors; for each third vector, the vector distance between the third vector and the K cluster centers is calculated respectively, and the third vector is divided into a cluster where the cluster center with the nearest vector distance is located; all third vectors are traversed to form K clusters; for each cluster, the mean of the third vectors in the cluster is calculated, and the mean is taken as the new cluster center of the cluster; the above steps are repeated until the cluster center no longer changes, the clustering is completed, K clusters are determined, and the pipe network location information of the gas components in each cluster corresponds to form each gas region.

[0173] The number of cluster centers, i.e., the above K value, can be set by default by the processor or set by the technician according to experience. For example, for a large number of historical replacement thresholds of historical gas numerical control components in historical data, a clustering algorithm without specifying the number of clusters is used for clustering, and the number of clusters formed by clustering is determined as the K value. The clustering algorithm without specifying the number of clusters can include a DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm and the like.

[0174] Step 520, for each gas region, steps 521 and 522 are performed.

[0175] Step 521, based on the gas usage data of the gas region, the replacement threshold of the gas numerical control component of different numerical control component types in the gas region is determined.

[0176] The replacement threshold refers to the minimum value of the replacement necessity of the gas numerical control component that needs to be replaced. When the replacement necessity of the gas numerical control component is greater than or equal to the replacement threshold, the gas numerical control component is a component to be replaced. In some embodiments, the replacement threshold can include a battery replacement threshold and a component replacement threshold.

[0177] The battery replacement threshold refers to the minimum value of the battery replacement necessity of the component to be replaced. The component replacement threshold refers to the minimum value of the component replacement necessity of the component to be replaced.

[0178] In some embodiments, the replacement thresholds of the gas numerical control components of the same numerical control component type in different gas regions can be different, and the replacement thresholds of the gas numerical control components of different numerical control component types in the same gas region can also be different.

[0179] In some embodiments, for each gas region, the processor can determine the replacement threshold of the gas number control component of different number control component types in the gas region in multiple ways based on the gas usage data of the gas region. For example, for a certain gas region, the processor can calculate the mean of the historical battery replacement necessity of a plurality of historical gas number control components and the mean of the historical component replacement necessity of a plurality of historical gas number control components in the same gas region in the first vector database to determine the reference battery replacement necessity and the reference component replacement necessity, respectively; based on the gas usage data of the gas region, the reference battery replacement necessity and the reference component replacement necessity are adjusted to determine the battery replacement threshold and the component replacement threshold, and the adjustment manner can be that the larger the total amount of gas usage is, the higher the replacement threshold is. For more information about the first vector database, please refer to the related description of Figure 2 .

[0180] In step 522, the replacement parameter of the gas region is determined based on the replacement threshold and the replacement necessity.

[0181] In some embodiments, the processor can determine the replacement parameter of the gas region in multiple ways based on the replacement threshold and the replacement necessity. For example, for each gas region, the processor can compare the replacement threshold and the replacement necessity of each gas number control component in the gas region; in response to the battery replacement necessity of the gas number control component being greater than or equal to the battery replacement threshold and the component replacement necessity being less than the component replacement threshold, it is determined that the gas number control component is the gas to be replaced, and the replacement manner is battery replacement; in response to the component replacement necessity of the gas number control component being greater than or equal to the component replacement threshold, it is determined that the gas number control component is the gas to be replaced, and the replacement manner is the whole component replacement.

[0182] In some embodiments of the present specification, by using the clustering algorithm, the plurality of gas regions of the gas pipeline network can be accurately divided, and the replacement threshold of the gas number control component of different number control component types in different gas regions is determined, which is beneficial to accurately determine the replacement parameter of each gas region, and can more quickly and accurately determine the component to be replaced and the replacement manner, so as to ensure that the gas data in the gas region is accurately and sufficiently monitored.

[0183] In some embodiments of the present specification, according to the pipeline location information and the replacement necessity of the gas number control component in the gas pipeline network, the replacement parameter of the plurality of gas regions of the gas pipeline network can be accurately determined regionally, which is beneficial to more accurately replace the gas number control component.

[0184] In some embodiments, the processor can determine the qualified components based on the replacement parameters; in response to receiving the replacement completion information, determine the synchronous collection parameters of the gas CNC components, and distribute the synchronous collection parameters to the gas CNC components; determine the collection confidence of the gas CNC components based on the gas monitoring data collected by the gas CNC components according to the synchronous collection parameters, and verify the collection confidence.

[0185] For more information about the replacement parameters, the replacement completion information, the gas CNC components, the gas monitoring data, and the collection confidence, please refer to the related description of Figures 2-5 .

[0186] The qualified components refer to the gas CNC components that do not need to be replaced. In some embodiments, the gas CNC components before replacement are composed of the qualified components and the components to be replaced; and the gas CNC components after replacement are composed of the qualified components and the replaced components.

[0187] In some embodiments, the processor can determine the components to be replaced based on the replacement parameters, and determine the qualified components as the other gas CNC components except the components to be replaced.

[0188] The synchronous collection parameters refer to the unified collection parameters of the gas CNC components after replacement, i.e., the unified collection parameters of the qualified components and the replaced components.

[0189] In some embodiments, the synchronous collection parameters can include a synchronous collection period and a synchronous collection frequency. The synchronous collection period refers to the unified period of data collection of the qualified components and the replaced components. The synchronous collection frequency refers to the unified frequency of data collection of the qualified components and the replaced components.

[0190] In some embodiments, the processor can determine the preset synchronous collection parameters as the synchronous collection parameters of the gas CNC components in response to receiving the replacement completion information. The preset synchronous collection parameters can be artificially set parameters, or the average value of historical synchronous collection parameters determined by the processor.

[0191] In some embodiments, the processor can distribute the synchronous collection parameters to the gas CNC components, and the gas CNC components collect the gas monitoring data according to the synchronous collection parameters. The gas CNC components include the replaced components and the qualified components.

[0192] In some embodiments, the processor can determine the collection confidence of the gas CNC components based on the gas monitoring data collected by the gas CNC components according to the synchronous collection parameters. For the process of determining the collection confidence based on the gas monitoring data, please refer to the related description in the foregoing, which will not be repeated here.

[0193] In some embodiments, the processor can verify the collection confidence in various ways. For example, in response to the collection confidence being greater than a preset confidence threshold, it is determined that the verification is successful; in response to the collection confidence not being greater than the preset confidence threshold, it is determined that the verification fails, and the gas numerical control assembly is subjected to maintenance detection, and if it is determined that the gas numerical control assembly has a problem, it is replaced.

[0194] In some embodiments of the present specification, based on the gas monitoring data collected by the gas numerical control assembly according to the synchronous collection parameters, the collection confidence of the gas numerical control assembly is determined, and the collection confidence is verified, which can further ensure the reliability of the collection confidence, thereby ensuring the accuracy of replacing the gas numerical control assembly and ensuring the normal operation of the gas pipeline.

[0195] In some embodiments, in response to completing the verification of the collection confidence, the processor can determine the low-power component in the qualified component; the data collection parameters of the low-power component are adjusted lower, and the data collection parameters of the replaced component are adjusted higher to maintain the total collection amount meeting the preset requirement.

[0196] For more information about collection confidence, qualified components, replaced components, and data collection parameters, see the relevant description above.

[0197] The low-power component refers to a qualified component with low power.

[0198] In some embodiments, the processor can determine the qualified component with a battery remaining power lower than a preset power value as a low-power component.

[0199] The preset power value refers to the preset minimum battery power of the gas numerical control assembly that can continue to work normally. The preset power value can be set by default by the processor or preset by a person according to experience. For example, 60% of the full power.

[0200] The total collection amount refers to the total data collection amount of all gas numerical control assemblies collecting gas monitoring data.

[0201] In some embodiments, the preset requirement can be set by default by the processor or preset in advance by a person according to experience. For example, the preset requirement can be that the variation amount of the total collection amount does not exceed a preset variation amount threshold. The preset variation amount threshold can also be set by default by the processor or preset in advance by a person according to experience.

[0202] In some embodiments, the processor can maintain the total collection amount meeting the preset requirement by adjusting the data collection parameters of the low-power component lower and adjusting the data collection parameters of the replaced component higher.

[0203] In some embodiments of the present application, by determining the low-power components in the qualified components, adjusting the data acquisition parameters of the low-power components, and adjusting the data acquisition parameters of the replaced components, the total amount of data acquisition can meet the preset requirements, the working time of the gas numerical control components can be prolonged as much as possible while ensuring sufficient gas monitoring data is acquired, and the replacement cost of the gas numerical control components can be reduced while ensuring the normal operation of the gas website.

[0204] The embodiments in the present application are only for example and illustration, and do not limit the application range of the present application. Various modifications and changes made by those skilled in the art under the guidance of the present application are still within the scope of the present application.

[0205] In addition, some features, structures or characteristics in one or more embodiments of the present application can be properly combined.

[0206] If the description, definition and / or the use of terms in the accompanying materials of the present application are inconsistent or conflicting with the description, definition and / or the use of terms in the present application, the description, definition and / or the use of terms in the present application shall prevail.

Claims

1. A method for safely replacing gas pipe network components based on a supervision network, characterized in that: The method is executed by a gas company management platform in a gas pipe network component safe replacement Internet of Things system based on a supervision network, and includes: Obtaining component characteristics of a gas CNC component; the gas CNC component is a device that uses CNC technology to control and monitor gas and is internally provided with a battery; the component characteristics include at least one of data processing characteristics, operating characteristics, and environmental characteristics; the data processing characteristics are relevant characteristics of the gas CNC component when processing data, including data acquisition parameters and data transmission parameters; the operating characteristics are relevant characteristics of the gas CNC component when operating, including start and stop frequency and operating duration; the environmental characteristics are relevant characteristics of the environment in which the gas CNC component is located, including ambient temperature, ambient humidity, and ambient pH value; Determining the necessity of replacing the gas numerical control component based on the component characteristics includes: The degree of necessity for replacement includes the degree of necessity for battery replacement and the degree of necessity for component replacement; Determining the remaining battery capacity of the gas digital control component and the necessity of replacing the battery based on the initial battery capacity of the gas digital control component, the data processing characteristic, the first operating characteristic, and the first environmental characteristic; Determining the degree of component wear of the gas numerical control component and the necessity of component replacement based on the second operating characteristic, the second environmental characteristic, and the average gas characteristic; The first operating characteristic and the second operating characteristic are the operating characteristics of the time period related to the historical moment of battery replacement and overall component replacement, respectively; the first environmental characteristic and the second environmental characteristic are the environmental characteristics of the time period related to the historical moment of battery replacement and overall component replacement, respectively; the average gas characteristic is the average value of gas-related parameters, including average gas volume, average gas flow rate, average gas temperature, average gas pressure, and average gas impurity content; determining replacement parameters based on the degree of replacement necessity; Based on the replacement parameters, a replacement task instruction and a gas outage parameter are generated and sent to the maintenance user sub-platform and the government safety supervision management platform respectively; In response to receiving a stop parameter determination instruction from the government safety supervision and management platform, generating a gas stop instruction and sending it to the gas supply control device to control the on / off state of the gas supply control device; In response to receiving the replacement completion information sent by the maintenance user sub-platform, the replaced component is determined and the data center is updated; the replaced component is the gas CNC component after replacement, and the replacement method includes battery replacement and overall component replacement.

2. The method according to claim 1, characterized in that The method further comprises: Based on the data center, obtaining the gas monitoring data collected by the gas digital control component; Determining the collection confidence of the gas numerical control component based on the gas monitoring data; Determining the operation stability of the gas digital control component based on the multiple acquisition confidences corresponding to the gas digital control component at multiple moments; The necessity of component replacement is adjusted based on the acquisition confidence and the operation stability.

3. The method according to claim 1, characterized in that The determining of replacement parameters based on the degree of replacement necessity includes: Based on the pipeline location information of the gas numerical control component in the gas pipeline network and the degree of necessity for replacement, the replacement parameters of the multiple gas areas of the gas pipeline network are determined.

4. The IoT system for safe replacement of gas pipe network components based on the supervision network is characterized by: The Internet of Things system includes a government safety supervision management platform and a government safety supervision object platform; the government safety supervision object platform includes a gas company management platform; The gas company management platform is configured to: Obtaining component characteristics of a gas CNC component; the gas CNC component is a device that uses CNC technology to control and monitor gas and is internally provided with a battery; the component characteristics include at least one of data processing characteristics, operating characteristics, and environmental characteristics; the data processing characteristics are relevant characteristics of the gas CNC component when processing data, including data acquisition parameters and data transmission parameters; the operating characteristics are relevant characteristics of the gas CNC component when operating, including start and stop frequency and operating duration; the environmental characteristics are relevant characteristics of the environment in which the gas CNC component is located, including ambient temperature, ambient humidity, and ambient pH value; Determining the necessity of replacing the gas numerical control component based on the component characteristics includes: The degree of necessity for replacement includes the degree of necessity for battery replacement and the degree of necessity for component replacement; Determining the remaining battery capacity of the gas digital control component and the necessity of replacing the battery based on the initial battery capacity of the gas digital control component, the data processing characteristic, the first operating characteristic, and the first environmental characteristic; Determining the degree of component wear of the gas numerical control component and the necessity of component replacement based on the second operating characteristic, the second environmental characteristic, and the average gas characteristic; The first operating characteristic and the second operating characteristic are the operating characteristics of the time period related to the historical moment of battery replacement and overall component replacement, respectively; the first environmental characteristic and the second environmental characteristic are the environmental characteristics of the time period related to the historical moment of battery replacement and overall component replacement, respectively; the average gas characteristic is the average value of gas-related parameters, including average gas volume, average gas flow rate, average gas temperature, average gas pressure, and average gas impurity content; determining replacement parameters based on the degree of replacement necessity; Based on the replacement parameters, a replacement task instruction and a gas outage parameter are generated and sent to the maintenance user sub-platform and the government safety supervision and management platform respectively; In response to receiving a stop parameter determination instruction from the government safety supervision and management platform, generating a gas stop instruction and sending it to the gas supply control device to control the on / off state of the gas supply control device; In response to receiving the replacement completion information sent by the maintenance user sub-platform, the replaced component is determined and the data center is updated; the replaced component is the gas CNC component after replacement, and the replacement method includes battery replacement and overall component replacement.

5. The Internet of Things system according to claim 4, characterized in that: The gas company management platform is further configured to: Obtaining gas monitoring data collected by the gas digital control component based on the data center; Determining the collection confidence of the gas numerical control component based on the gas monitoring data; Determining the operation stability of the gas digital control component based on the multiple acquisition confidences corresponding to the gas digital control component at multiple moments; The necessity of component replacement is adjusted based on the acquisition confidence and the operation stability.

6. The Internet of Things system according to claim 4, characterized in that: The gas company management platform is further configured to: Based on the pipeline location information of the gas numerical control component in the gas pipeline network and the degree of necessity for replacement, the replacement parameters of the multiple gas areas of the gas pipeline network are determined.

7. The Internet of Things system according to claim 4, characterized in that: The Internet of Things system also includes a government safety supervision service platform, a government safety supervision sensor network platform, a gas company sensor network platform, a smart gas equipment object platform, a citizen user platform, a gas user platform, and a gas user service platform; The smart gas equipment object platform includes the gas supply control device; the gas user platform includes the maintenance user sub-platform and the gas user sub-platform; the gas user service platform includes the maintenance service sub-platform; and the gas company management platform includes the data center.

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