Gas pipe network assembly safe replacement method based on supervision network and Internet of Things system

Abstract

The invention provides a gas pipe network assembly safe replacement method based on a supervision network and an Internet of Things system, and relates to the field of pipe network assembly replacement. The Internet of Things system comprises a gas company management platform. The method is realized based on a gas company management platform, and comprises the following steps: acquiring component characteristics of a gas numerical control component; based on the component characteristics, determining the replacement necessity of the gas numerical control component; determining replacement parameters based on the replacement necessity; on the basis of the replacement parameters, a replacement task instruction and gas stopping parameters are generated and sent to the maintenance user sub-platform and the government safety supervision management platform; in response to the received parameter stopping determination instruction, generating a gas stopping instruction and sending the gas stopping instruction to the gas supply control equipment; and in response to received replacement completion information sent by the maintenance user sub-platform, determining a replaced component and updating the data center. According to the method, the replacement necessity degree of the gas numerical control assembly can be judged, assembly replacement is accurately carried out, and normal operation of a gas pipe network is guaranteed.

Description

Technical Field

[0001] This specification relates to the field of pipe network component replacement, and in particular to a method for safely replacing gas pipe network components based on a supervision network and an Internet of Things system. Background Art

[0002] As a critical component of urban energy supply, gas pipeline networks are equipped with numerous gas CNC components for gas monitoring. However, over the long-term operation of gas pipeline networks, component failure or performance degradation may occur due to various factors. Therefore, timely replacement of gas CNC components is crucial for maintaining safe network operation. Currently, component replacement often relies on periodic inspections or determination of complete component failure, making it difficult to ensure timely and accurate replacement.

[0003] Therefore, it is necessary to provide a safe replacement method for gas pipeline network components based on the supervision network and an Internet of Things system, which can determine the degree of necessity of replacement of each gas CNC component, accurately determine the components that need to be replaced and replace them, to ensure the normal operation of the gas pipeline network. Summary of the Invention

[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 invention provides a gas pipeline component safe replacement method based on a supervision network and an Internet of Things system.

[0005] The invention content includes a method for safe replacement of gas pipeline network components based on a supervision network, which is executed by a gas company management platform in an Internet of Things system for safe replacement of gas pipeline network components based on a supervision network, and the method includes: obtaining component characteristics of a gas digital control component, wherein the component characteristics include at least one of data processing characteristics, working characteristics and environmental characteristics; based on the component characteristics, determining the necessity of replacing the gas digital control component; based on the necessity of replacement, determining replacement parameters; based on the replacement parameters, generating replacement task instructions and gas outage 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 outage instruction and sending it to a gas supply control device to control the opening and closing state of the gas supply control device; in response to receiving a replacement completion information issued by the maintenance user sub-platform, determining that the component has been replaced and updating the data center.

[0006] The invention includes an Internet of Things (IoT) system for safely replacing gas pipe network components based on a regulatory network, comprising a government safety regulatory management platform and a government safety regulatory target platform; the government safety regulatory target platform includes a gas company management platform; and the gas company management platform is configured to execute a method for safely replacing gas pipe network components based on the regulatory network. The IoT system also includes a government safety regulatory service platform, a government safety regulatory sensor network platform, a gas company sensor network platform, a smart gas equipment target platform, a citizen user platform, a gas user platform, and a gas user service platform; the smart gas equipment target 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 about by the above invention include but are not limited to: (1) determining the necessity of gas CNC component replacement based on component characteristics, and then determining the components to be replaced and the corresponding replacement methods, so as to generate replacement task instructions and gas stop instructions for executing component replacement, stopping gas supply and gas stop reminder, 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 acquisition confidence of the gas CNC component through gas monitoring data, and then determining the operating stability of the gas CNC component based on the acquisition confidence at multiple moments, and then comparing the acquisition confidence and operating stability with the corresponding preset values to reasonably adjust the necessity of component replacement, so that the necessity of component replacement is more reliable and accurate, which is conducive to accurately determining whether the gas CNC component needs to be replaced, and saving replacement costs while ensuring the normal operation of the gas CNC component; (3) by determining the low-power components among the qualified components, lowering the data acquisition parameters of the low-power components and increasing the data acquisition parameters of the replaced components to keep the total acquisition amount meeting the preset requirements, it is possible to ensure that sufficient gas monitoring data is collected while extending the working time of the gas CNC component as much as possible. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The present invention will be further described 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, like numbers represent like structures, wherein: Figure 1 This is a schematic diagram of the platform structure of the Internet of Things system for safe replacement of gas network components based on the supervision network according to some embodiments of this specification; Figure 2 is an exemplary flow chart of a method for safely replacing gas network components based on a supervisory network according to some embodiments of this specification; Figure 3is an exemplary flow chart for determining the necessity of replacement according to some embodiments of this specification; Figure 4 is an exemplary schematic diagram of an evaluation model according to some embodiments of this specification; Figure 5 is an exemplary flow chart for determining replacement parameters of a gas zone according to some embodiments of the present specification. DETAILED DESCRIPTION

[0009] The following is a brief introduction to the drawings used in the description of the embodiments, which do not represent all embodiments.

[0010] When operations are described in steps in the embodiments of the present invention, unless otherwise specified, the order of the steps is interchangeable, steps may be omitted, and other steps may be included in the operation process.

[0011] Figure 1 This is a schematic diagram of the platform structure of the Internet of Things system for safe replacement of gas pipeline network components based on the supervision network according to some embodiments of this specification.

[0012] In some embodiments, as Figure 1 As shown, the gas pipeline component safety replacement Internet of Things system 100 based on the supervision network can include a government safety supervision service platform 110, a government safety supervision management platform 120, a government safety supervision sensor network platform 130, a government safety supervision object platform 140, a gas company sensor 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.

[0013] The government security supervision service platform 110 refers to a platform that provides security supervision services to the government. It can be configured as a server and can interact with the government security supervision management platform 120 and the citizen user platform 170 for data.

[0014] The government safety supervision and management platform 120 refers to a platform for supervision and safety management of the gas pipeline network, and can be configured as a server.

[0015] The government security supervision sensor network platform 130 refers to a functional platform for security management of government sensor communications, and can be configured as communication equipment and gateways, etc.

[0016] In some embodiments, the government safety supervision sensor 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 gas outage parameter determination instruction to the gas company management platform 141 via the government safety supervision sensor network platform 130. For another example, the gas company management platform 141 can send gas outage parameters to the government safety supervision management platform 120 via the government safety supervision sensor network platform 130.

[0017] The government safety supervision object platform 140 refers to an object platform for generating perception information and executing control information, and may include a gas company management platform 141 .

[0018] The gas company management platform 141 refers to a comprehensive management platform for relevant information of the gas company, and can be configured as a server and a storage.

[0019] In some embodiments, the gas company management platform 141 may be configured to execute a gas network component safety replacement method based on a supervisory network.

[0020] In some embodiments, the gas company management platform 141 includes a data center, which is a module that centrally stores and processes data.

[0021] In some embodiments, the gas company management platform 141 may also include a processor. The processor may process data and / or information obtained from other platforms. The processor may execute program instructions based on this data, information, and / or processing results to perform one or more functions described herein. By way of example only, the processor may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), and the like.

[0022] The gas company sensor network platform 150 refers to a comprehensive management platform for the gas company's sensor information, and can be configured as a communication network and a gateway, etc.

[0023] In some embodiments, the gas company sensor network platform 150 can be used for communication between the gas company management platform 141 and the smart gas equipment object platform 160 in the government safety supervision object platform 140 .

[0024] The smart gas equipment object platform 160 refers to a functional platform for real-time monitoring and intelligent regulation of the gas pipeline network, which may include gas CNC components and gas supply control equipment.

[0025] Gas CNC components refer to devices that utilize CNC technology to control and monitor gas. Examples include gas flow sensors, gas pressure sensors, and gas temperature sensors. In some embodiments, these components can be deployed within multiple gas pipelines within a gas network to monitor gas conditions within these pipelines.

[0026] It should be noted that the gas CNC assembly in this manual is a battery-powered device, that is, a battery is provided inside the gas CNC assembly.

[0027] Gas supply control equipment refers to equipment that regulates gas supply. In some embodiments, gas supply control equipment can be deployed inside or at entrances and exits of multiple gas pipelines in a gas network to regulate and control gas flow, gas pressure, and gas delivery direction. For example, gas valves can be used.

[0028] The citizen user platform 170 is a platform for interacting with citizens and can be configured as a public media terminal device, for example, a television media facing all citizens.

[0029] The gas user platform 180 is a platform for interacting with gas users, and can be configured as a terminal device of the gas user, such as a mobile phone or computer of the gas user.

[0030] In some embodiments, the gas user platform 180 may include a maintenance user sub-platform and a gas user sub-platform.

[0031] The maintenance user sub-platform is a functional platform that provides maintenance services and user support, for example, the work terminal used by gas maintenance personnel.

[0032] The gas user sub-platform refers to the sub-platform that interacts with gas users, such as the terminal devices used by gas users.

[0033] The gas user service platform 190 refers to a platform for receiving and transmitting gas user-related data and / or information, and may be configured as a server.

[0034] In some embodiments, the gas user service platform 190 may include a maintenance service sub-platform. The maintenance service sub-platform may refer to a platform for receiving and transmitting maintenance information.

[0035] 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 a replacement task instruction from the gas company management platform 141 and send it to the maintenance user sub-platform. In another example, the gas company management platform 141 can send a gas outage reminder to the gas user sub-platform via the maintenance service sub-platform.

[0036] In some embodiments of this specification, the Internet of Things system for safe replacement of gas pipeline network components based on the supervision network can form an information operation closed loop between various functional platforms, and coordinate and operate regularly under the unified management of the gas company management platform, thereby realizing the informatization and intelligence of the safe replacement of gas pipeline network components.

[0037] It should be noted that the above description of the IoT system and platform for safely replacing gas pipeline network components based on a supervisory network is for illustrative purposes only and does not limit this specification to the exemplary embodiments described. It is understood that those skilled in the art, once they understand the principles of this system, may arbitrarily combine the various platforms or construct subsystems that connect to other platforms without departing from these principles.

[0038] Figure 2 This is an exemplary flow chart of a method for safely replacing gas pipe network components based on a supervision network according to some embodiments of this specification.

[0039] In some embodiments, the process 200 may be executed by the gas company management platform 141 in the gas pipe network component safety replacement IoT system 100 based on the supervision network, for example, by a processor in the gas company management platform 141 .

[0040] like Figure 2 As shown, the process 200 includes the following steps 210 to 260.

[0041] Step 210: Acquire component characteristics of the gas numerical control component.

[0042] The component characteristics refer to the relevant characteristics of the gas digital control component. In some embodiments, the component characteristics may include at least one of data processing characteristics, working characteristics, and environmental characteristics.

[0043] Data processing characteristics refer to the characteristics related to data processing by gas CNC components, such as data acquisition parameters and data transmission parameters.

[0044] Data collection parameters refer to the parameters used by the gas CNC component to collect data. For example, data collection frequency and data collection volume. Data collection frequency refers to the number of times the gas CNC component collects data per unit time. Data collection volume refers to the amount of data collected by the gas CNC component in a single transaction.

[0045] Data transmission parameters refer to the parameters used by the gas CNC component to transmit data. For example, data transmission frequency and data transmission volume. Data transmission frequency refers to the number of times the gas CNC component transmits data per unit time. Data transmission volume refers to the amount of data transmitted by the gas CNC component in a single transmission.

[0046] Working characteristics refer to the relevant characteristics of the operation of gas CNC components, such as start and stop frequency and working duration.

[0047] Start-stop frequency refers to the total number of times the gas CNC component is started or stopped. Working duration refers to the length of time the gas CNC component continues to work after a single start.

[0048] Environmental characteristics refer to the characteristics of the environment in which the gas CNC components are located, such as ambient temperature, ambient humidity, and ambient pH value.

[0049] In some embodiments, the component characteristics of the gas digital control components can be obtained by the smart gas equipment object platform, uploaded to the gas company management platform via the gas company sensor network platform, and stored in the data center. The processor can directly retrieve the component characteristics of the gas digital control components from the data center.

[0050] Step 220 : Determine the necessity of replacing the gas numerical control component based on the component characteristics.

[0051] The degree of necessity for replacement refers to a measure of the degree to which the gas numerical control component needs to be replaced. In some embodiments, the degree of necessity for replacement can be represented by a value between 0 and 1, where a higher value indicates a higher degree of necessity for replacement.

[0052] In some embodiments, the processor may determine the necessity of replacement in a variety of ways based on component characteristics.

[0053] For example, the processor can construct a current first vector based on current data processing characteristics, working characteristics, and environmental characteristics; retrieve the historical first vector with the highest first similarity to the current first vector from the first vector database, and use it as a reference first vector, where the reference first vector is composed of reference data processing characteristics, reference working characteristics, and reference environmental characteristics; 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 smaller than the corresponding component in the reference first vector, then the first similarity is used as the current degree of necessity for replacement; if there is a component in the current first vector that is larger than the corresponding component in the reference first vector, then the one or more components in the current first vector are replaced with the corresponding components of the reference first vector to reconstruct the current first vector; repeat the above steps until the current degree of necessity for replacement is determined.

[0054] The comparison of the magnitude of the components in the current first vector with the corresponding components in the reference first vector includes a comparison of the magnitude of the current data processing characteristics with the reference data processing characteristics, a comparison of the magnitude of the current operating characteristics with the reference operating characteristics, and a comparison of the severity of the current environmental characteristics with the severity of the reference environmental characteristics. The severity can be represented by the difference between the actual environmental characteristics and the ideal environmental characteristics, with the greater the absolute value of the difference, the greater the severity. For example, the severity of the reference environmental characteristics can be represented by the difference between the historical actual environmental characteristics and the historical ideal environmental characteristics.

[0055] In some embodiments, the first vector database can be constructed by a processor or a technician based on historical data, and the first vector database includes historical first vectors of multiple replaced gas digital control components and corresponding historical replacement necessity degrees.

[0056] In some embodiments, the first similarity may be represented by Euclidean distance, cosine similarity, etc. The first similarity threshold may be set by default by the processor or preset by a technician based on experience.

[0057] In some embodiments, the processor can also determine the remaining battery power based on the initial battery power, data processing characteristics, first operating characteristics, and first environmental characteristics of the gas digital control component, and thus determine the necessity of battery replacement; and determine the degree of component wear based on the second operating characteristics, second environmental characteristics, and average gas characteristics, and thus determine the necessity of component replacement. For more information on this part, please refer to Figure 3 and its related descriptions.

[0058] Step 230: Determine replacement parameters based on the degree of replacement necessity.

[0059] The replacement parameters refer to parameters related to the replacement of the gas numerical control component. In some embodiments, the replacement parameters may include the component to be replaced and the replacement method of the component to be replaced.

[0060] The components to be replaced refer to the gas CNC components that are determined to need to be replaced.

[0061] The replacement method refers to the method of replacing the gas numerical control component. In some embodiments, the replacement method can include battery replacement and component replacement.

[0062] In some embodiments, the processor can determine replacement parameters based on the degree of replacement necessity using a variety of methods. For example, the first database can further include multiple historical first vectors of replaced gas digital control components, along with their corresponding historical degrees of replacement necessity and historical replacement methods. The processor can then select gas digital control components with a replacement necessity greater than a reference degree of replacement necessity as components to be replaced; retrieve the reference first vector of the component to be replaced from the first vector database, and use the historical replacement method corresponding to the reference first vector as the replacement method for the component to be replaced.

[0063] In some embodiments, the processor may statistically determine a minimum value of the historical replacement necessity of multiple historical gas digital control components in the first vector database, and use the minimum value as a reference replacement necessity.

[0064] In some embodiments, the processor can also determine the replacement parameters of multiple gas areas of the gas network based on the network location information and the degree of replacement necessity of the gas digital control components in the gas network. For more information about this part, please refer to Figure 5 and its related descriptions.

[0065] Step 240: Generate a replacement task instruction and gas outage parameters based on the replacement parameters, and send them to the maintenance user sub-platform and the government safety supervision management platform respectively.

[0066] The replacement task instruction refers to an instruction for executing a replacement task on a component to be replaced. In some embodiments, the replacement task instruction may include the component to be replaced and a replacement method and a replacement period of the component to be replaced.

[0067] In some embodiments, the replacement parameters may also include a replacement period for the component to be replaced. The replacement period may be determined by the processor based on the queue of pending replacement tasks. For example, if the queue length of a pending replacement task is 8 hours, the replacement period for this replacement task is a period after 8 hours. The duration of the replacement period is represented by the product of the total number of components to be replaced in this replacement task and the average replacement time for a single component. The average replacement time for a single component may be obtained by the processor or a technician based on historical data statistics.

[0068] In some embodiments, the processor may autonomously generate a replacement task instruction based on the replacement parameters and in accordance with a preset template.

[0069] The gas stop parameters refer to parameters related to stopping the gas supply. In some embodiments, the gas stop parameters may include a gas stop pipeline and a gas stop period.

[0070] A gas outage pipeline refers to a gas pipeline where gas supply is stopped. A gas outage period refers to the time period during which gas supply is stopped.

[0071] In some embodiments, the processor may generate a gas outage parameter based on the replacement parameter according to a preset rule. For example, the processor may use the gas pipeline where the component to be replaced is located as the gas outage pipeline and the replacement period of the component to be replaced as the gas outage period.

[0072] 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 can respond to the replacement task instruction and perform the replacement task on the component to be replaced; the processor can also send the gas outage parameters to the government safety supervision management platform via the government safety supervision sensor network platform, and the government safety supervision management platform will determine and generate the outage parameter determination instruction.

[0073] Step 250, in response to receiving the stop parameter determination instruction from the government safety supervision management platform, generate a gas stop instruction and send it to the gas supply control device to control the opening and closing state of the gas supply control device.

[0074] The gas outage parameter determination instruction refers to an instruction for determining gas outage parameters. In some embodiments, the gas outage parameter determination instruction may include a determined gas outage pipeline and gas outage period.

[0075] In some embodiments, after receiving the replacement task instruction, the maintenance personnel can adjust the replacement period in the replacement parameters on the maintenance user sub-platform according to actual conditions (for example, if there is a replacement task to be executed and the queue is canceled, the replacement period can be appropriately advanced). The maintenance user sub-platform sends the adjusted replacement parameters to the government safety supervision and management platform. The government safety supervision and management platform automatically updates the gas outage period in the gas outage parameters based on the adjusted replacement parameters to determine the outage parameter determination instruction.

[0076] The gas stop instruction refers to an instruction to stop the gas supply of the gas pipeline. In some embodiments, the gas stop instruction may include the gas supply control device corresponding to the gas stop pipeline and the shutdown period of the gas supply control device.

[0077] In some embodiments, the processor can obtain the stop parameter determination instruction through the government safety supervision and management platform, determine the gas supply control equipment corresponding to the gas stop pipeline based on the gas stop pipeline in the stop parameter determination instruction, and determine the shutdown period of the gas supply control equipment based on the gas stop period, so as to determine the gas stop instruction; and send the gas stop instruction to the gas supply control equipment via the gas company's sensor network platform to control the opening and closing status of the gas supply control equipment.

[0078] Among them, the gas supply control device being in the open state represents that the gas pipeline is supplying gas, and the gas supply control device being in the closed state represents that the gas pipeline stops supplying gas.

[0079] In some embodiments, the processor may control the on / off state of the gas supply control device based on the gas stop period in the gas stop instruction.

[0080] In some embodiments, the processor can also autonomously generate gas outage reminder information based on the outage parameter determination instruction and send it to the gas user sub-platform and the citizen user platform.

[0081] In some embodiments, the gas outage reminder information may be in the form of a telephone notification, a text message notification, a television notification, a gas outage reminder sign, etc.

[0082] In some embodiments, the processor can determine the gas outage period in the outage parameter determination instruction and send the gas outage reminder information to the gas user sub-platform in advance to remind gas users to make preparations for gas outages in advance. The gas outage reminder information can also be sent to the citizen user platform to increase notification channels, further expand the notification coverage, and increase the probability of gas users receiving gas outage reminder information.

[0083] Step 260: In response to receiving the replacement completion information sent by the maintenance user sub-platform, determine that the component has been replaced and update the data center.

[0084] The replacement completion information is a notification message indicating that the component to be replaced has been replaced.

[0085] In some embodiments, after the maintenance personnel completes the replacement of the components to be replaced, they can perform the replacement completion operation on the maintenance user sub-platform (such as clicking the battery replacement completion button, entering the replaced components, etc.). The maintenance user sub-platform can generate replacement completion information and send it to the gas company management platform through the maintenance service sub-platform.

[0086] The replaced component refers to the gas CNC component after replacing the component to be replaced.

[0087] It should be noted that if the replacement method of the component to be replaced is battery replacement, the data corresponding to the component to be replaced will be compressed and stored to save space; if the replacement method of the component to be replaced is replacement of the entire component, the data corresponding to the component to be replaced will be cleared and reset to avoid unlimited data accumulation and increase the system operation load.

[0088] In some embodiments of this specification, the degree of necessity for replacement of gas CNC components is determined based on component characteristics, and then the components to be replaced and the corresponding replacement methods are determined to generate replacement task instructions and gas stop instructions for executing component replacement, stopping gas supply, and gas stop reminders, etc., thereby 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.

[0089] Figure 3300 is an exemplary flow chart for determining the degree of replacement necessity according to some embodiments of this specification. In some embodiments, process 300 may be executed by the gas company management platform 141. For example, it may be executed by a processor in the gas company management platform 141.

[0090] In some embodiments, the operating characteristic may include a first operating characteristic and a second operating characteristic; and the environmental characteristic may include a first environmental characteristic and a second environmental characteristic.

[0091] The first working characteristic and the second working characteristic are respectively working characteristics of the time period related to the historical moments of battery replacement and component replacement; the first environmental characteristic and the second environmental characteristic are respectively environmental characteristics of the time period related to the historical moments of battery replacement and component replacement.

[0092] That is, the first operating characteristic is the operating characteristic of the gas digital control component during the first period, and the second operating characteristic is the operating characteristic of the gas digital control component during the second period. The first environmental characteristic is the environmental characteristic of the gas digital control component during the first period, and the second environmental characteristic is the environmental characteristic of the gas digital control component during the second period. The first period is the period from the last battery replacement to the current moment, and the second period is the period from the last component replacement to the current moment.

[0093] The historical time when the battery was last replaced and the historical time when the component was last replaced can be determined based on the upload time of the historical replacement completion information.

[0094] In some embodiments, the degree of replacement necessity may include the degree of battery replacement necessity and the degree of component replacement necessity.

[0095] The battery replacement necessity refers to the degree to which batteries in the gas CNC components need to be replaced. The component replacement necessity refers to the degree to which the gas CNC components need to be replaced as a whole.

[0096] In some embodiments, both the battery replacement necessity and the component replacement necessity can be represented by a numerical value from 0 to 1, where the higher the numerical value, the higher the battery replacement necessity and the component replacement necessity.

[0097] like Figure 3 As shown, the process 300 may include the following steps 310 to 320.

[0098] Step 310 , based on the initial battery power, data processing characteristics, first operating characteristics and first environmental characteristics of the gas digital control component, determine the remaining battery power of the gas digital control component and determine the necessity of battery replacement.

[0099] In some embodiments, the processor can search the power consumption database to determine the historical first environmental feature with the highest similarity to the current first environmental feature, use it as the reference first environmental feature, and determine the historical power consumption speed corresponding to the reference first environmental feature as the power consumption speed of the current gas digital control component; determine the data acquisition frequency and data acquisition volume in the data processing feature of the current gas digital control component, and the start-stop frequency and working duration in the first working feature, and the product of the four as the total data acquisition volume of the gas digital control component; determine the data transmission frequency and data transmission volume in the data processing feature of the current gas digital control component, and the start-stop frequency and working duration in the first working feature, and the product of the four as the total data transmission volume of the gas digital control component; determine the battery consumption by multiplying the sum of the total data acquisition volume and the total data transmission volume by the power consumption speed; and determine the remaining battery power by subtracting the battery consumption from the initial battery power.

[0100] The power consumption database includes historical first environmental characteristics of a plurality of replaced historical gas numerical control components and corresponding historical power consumption speeds.

[0101] Power consumption rate refers to the battery power consumed by collecting and / or transmitting a unit of data. The historical power consumption rate in the power consumption database can be represented by the ratio of the historical battery consumption of the gas CNC component under the historical first environment characteristics to the total amount of historical data. The total amount of historical data is the sum of the total amount of historical data collected and the total amount of historical data transmitted.

[0102] In some embodiments, the processor may determine the necessity of battery replacement based on the remaining battery charge.

[0103] In some embodiments, the processor can construct a current second vector based on the remaining battery power, working characteristics and environmental characteristics, and determine the historical second vector with the second highest similarity to the current second vector by searching in the second vector database, and use it as a reference second vector, and determine the historical remaining working time corresponding to the reference second vector as the remaining working time of the battery of the current gas digital control component; the necessity of battery replacement is negatively correlated with the remaining working time, and the shorter the remaining working time, the higher the necessity of battery replacement.

[0104] In some embodiments, a second vector database can be constructed by a processor or technician based on historical data. The second vector database includes multiple historical second vectors of gas digital control components and corresponding historical remaining operating hours. For the setting of the second similarity, see the first similarity.

[0105] Step 320 : Based on the second working characteristic, the second environmental characteristic, and the average gas characteristic, determine the degree of component wear of the gas numerical control component and determine the necessity of component replacement.

[0106] Average gas characteristics refer to the average values of gas-related parameters. For example, average gas characteristics may include average gas volume, average gas flow rate, average gas temperature, average gas pressure, and average gas impurity content. In some embodiments, the gas digital control component can collect and obtain gas-related parameters, and the processor can calculate the average gas characteristics based on the gas-related parameters.

[0107] The degree of component wear refers to the degree of component performance degradation or functional loss. In some embodiments, the degree of component wear can be represented by a percentage between 0 and 1, where a larger percentage indicates a higher degree of component wear.

[0108] In some embodiments, the processor can determine the loss coefficient of the gas digital control component based on the second working characteristic, the second environmental characteristic, the average gas characteristic, and the reference usage data; and determine the degree of component loss based on the component usage time, design service life and loss coefficient of the gas digital control component.

[0109] Reference usage data refers to data related to a gas digital control component whose service life has reached its designed service life, including a reference second operating characteristic, a reference second environmental characteristic, and a reference average gas characteristic. In some embodiments, the reference usage data can be obtained based on historical data.

[0110] The loss coefficient is a coefficient that measures the speed at which a gas digital control component wears out. In some embodiments, the faster the gas digital control component wears out, the higher the loss coefficient.

[0111] In some embodiments, the processor can calculate the ratios of the second working characteristic, the second environmental characteristic, and the average gas characteristic of the gas digital control component with the second working characteristic, the second environmental characteristic, and the average gas characteristic in the reference usage data, respectively, to obtain the working characteristic ratio, the environmental characteristic ratio, and the gas characteristic ratio, respectively, and perform weighted summation of the above three ratios according to the load weight to obtain the loss coefficient.

[0112] The load weight can represent the degree of influence of different characteristic data on the loss coefficient. For example, if the environment has the greatest impact on the loss coefficient, then the load weight of the environmental characteristic ratio will be the largest. In some embodiments, the load weights of different characteristic ratios can be preset by the system or technicians.

[0113] In some embodiments, the processor may further determine the load weight using a control variable method. The processor may group multiple replaced historical gas digital control components using control variables, where the variables may include a second operating characteristic, a second environmental characteristic, and an average gas characteristic; group historical gas digital control components that have two identical variables and one different variable into one group, i.e., multiple historical gas digital control components may be divided into three groups, each group of historical gas digital control components corresponding to a different variable; calculate the variable influence values of the different variables corresponding to each group of historical gas digital control components; and use the ratio of the variable influence values as the load weight ratio, where the sum of the load weights is 1.

[0114] For example, the processor may group historical gas digital control components having the same second operating characteristic and second environmental characteristic but different average gas characteristics, where the different variables corresponding to the historical gas digital control components in the group are average gas characteristics; determine a first difference between the maximum average gas characteristic and the minimum average gas characteristic in the average gas characteristics (such as the average gas temperature) of the historical gas digital control components in the group, and determine a second difference between the actual life of the historical gas digital control components corresponding to the maximum average gas characteristic and the actual life of the historical gas digital control components corresponding to the minimum average gas characteristic; determine the ratio of the first difference to the second difference as the variable influence value of the average gas characteristic; similarly, determine the variable influence value of the second operating characteristic and the variable influence value of the second environmental characteristic; determine the ratio of the variable influence values of the second operating characteristic, the second environmental characteristic, and the average gas characteristic as the ratio of the load weights of the operating characteristic ratio, the environmental characteristic ratio, and the gas characteristic ratio; and determine the load weights of the operating characteristic ratio, the environmental characteristic ratio, and the gas characteristic ratio based on the sum of the load weights being 1.

[0115] The component usage time refers to the actual running time of the gas CNC component from the start of use to the current moment.

[0116] The designed service life refers to the normal working time preset by the gas CNC components in the factory settings.

[0117] In some embodiments, the processor may determine the degree of component wear based on the component usage time, design service life, and loss coefficient of the gas digital control component. For example, the degree of component wear may be calculated using the following formula (1): (1) Among them, W is the degree of component loss, C is the loss coefficient, T is the component usage time, and U is the designed service life.

[0118] In some embodiments of this specification, by comprehensively considering the second working characteristics, the second environmental characteristics, the average gas characteristics and the reference usage data, the importance and influence of each factor are calculated more accurately, and then the loss coefficient is calculated more accurately in combination with the component usage time and the design service life, the loss degree of the gas CNC component is accurately evaluated.

[0119] In some embodiments, the processor may determine the necessity of component replacement based on the degree of component wear. For example, the processor may calculate the difference between the degree of component wear and the average historical degree of wear, where the greater the difference, the greater the necessity of component replacement.

[0120] The average historical wear level refers to the average value of the historical component wear levels in historical replacement records.

[0121] In some embodiments of the present specification, by comprehensively analyzing the working characteristics, environmental characteristics, data processing characteristics, and average gas characteristics of the gas CNC components, the remaining battery power and the degree of component loss can be accurately assessed, thereby determining the necessity of battery replacement and the necessity of component replacement, providing data support for making reasonable replacement decisions later, which is conducive to optimizing maintenance costs and ensuring the safe operation of the gas pipeline network.

[0122] In some embodiments, the processor can also obtain gas monitoring data collected by the gas digital control component based on the data center; determine the collection confidence of the gas digital control component based on the gas monitoring data; determine the operation stability of the gas digital control component based on multiple collection confidences corresponding to the gas digital control component at multiple moments; and adjust the necessity of component replacement based on the collection confidence and operation stability.

[0123] For more information on gas CNC components, data centers, gas monitoring data, and the necessity of component replacement, see Figure 2-Figure 3 Related instructions.

[0124] Gas monitoring data refers to the data collected by the gas digital control component, such as gas flow, gas pressure, and gas temperature.

[0125] In some embodiments, the gas digital control component can upload the collected gas monitoring data to the data center of the gas company management platform through the gas company's sensor network platform, and the processor can directly retrieve the gas monitoring data from the data center.

[0126] The collection confidence level refers to the reliability of the gas digital control component in performing the collection work. In some embodiments, the collection confidence level can be represented by a value between 0 and 1. The larger the value, the higher the collection confidence level of the gas digital control component and the more reliable the gas monitoring data collected by the gas digital control component.

[0127] Figure 4This is an exemplary schematic diagram of determining acquisition confidence according to some embodiments of this specification.

[0128] In some embodiments, as Figure 4 As shown, the processor can construct a data association map 450 based on multiple gas CNC components 410 located on the same gas pipeline, as well as gas monitoring data 420 collected by the multiple gas CNC components, pipeline information 430 between the multiple gas CNC components, and CNC component types 440 of the multiple gas CNC components; based on the data association map 450, the collection confidence 470 is determined through the evaluation model 460.

[0129] The pipeline information between gas CNC components refers to the relevant information of the gas pipelines between gas CNC components, such as the interval pipeline length, pipeline inner diameter, pipeline cleaning time, etc.

[0130] The interval pipe length refers to the length of the gas pipeline between two gas CNC assemblies. In some embodiments, the interval pipe length can be determined by a processor based on the installation location coordinates of the gas CNC assemblies and a gas pipeline network map. For example, the gas CNC assemblies can be marked on the gas pipeline network map according to their installation location coordinates, and the length of the gas pipeline between the two gas CNC assemblies can be measured to obtain the interval pipe length. The installation location coordinates of the gas CNC assemblies can be obtained from a positioning device on the gas CNC assemblies or from installation log data.

[0131] The inner diameter of a pipeline refers to the diameter of the internal cross-section of a gas pipeline. The pipeline cleaning time refers to the time it takes to clean the pipeline. In some embodiments, the gas pipeline network distribution map, the inner diameter of the pipeline, and the pipeline cleaning time can all be obtained by the processor based on the data center.

[0132] The CNC component type refers to the type of gas CNC component. For example, gas CNC components can be divided into temperature CNC components, flow data components, and other CNC component types based on their functions.

[0133] A data association graph is a graph that displays the relationship between gas CNC components, gas monitoring data, pipeline information, and CNC component types. In some embodiments, the data association graph is composed of multiple nodes and multiple edges.

[0134] The multiple nodes of a data association graph are multiple gas CNC components located on the same gas pipeline. One node corresponds to one gas CNC component, and the node characteristics are the gas monitoring data and CNC component type of the gas CNC component.

[0135] The edges of the data association graph are gas pipelines between gas CNC components, and the edge features are pipeline information between gas CNC components.

[0136] 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.

[0137] 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).

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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 .

[0142] In some embodiments, after the component to be replaced is replaced, the processor can determine the acquisition confidence of the replaced component through the evaluation model; in response to the replacement, if there are still more than a preset number of gas CNC components whose acquisition 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 incrementally update the evaluation model.

[0143] The processor can collect gas monitoring data multiple times based on the gas CNC components and reconstruct a large number of data association maps as incremental training samples; adjust the collection confidence of the replaced components to the reference confidence, and keep the collection confidence of other gas CNC components unchanged to obtain the labels corresponding to the incremental training samples; based on the incremental training set consisting of a large number of incremental training samples and their labels, the current evaluation model is incrementally trained. The training method can be found in the training process above. Among them, the preset number and preset confidence threshold can be pre-set by technical personnel. The reference confidence refers to the average collection confidence of the gas CNC components with accurate gas monitoring data.

[0144] In some embodiments of the present specification, a data association map is constructed by combining multiple data and information through multiple gas CNC components on the same gas pipeline, and based on the data association map, the collection confidence of multiple gas CNC components is accurately and efficiently determined through a machine learning model, thereby effectively evaluating the reliability of the data collected by the gas CNC components, so as to reasonably determine the necessity of component replacement later.

[0145] Operation smoothness refers to the stability of the operation of gas CNC components.

[0146] In some embodiments, the processor can determine the stable duration of the gas digital control component based on the collection confidence of the gas digital control component at multiple moments and multiple confidence fluctuation values relative to the reference confidence at multiple moments; and determine the operating stability based on the stable duration and multiple confidence fluctuation values at multiple moments.

[0147] The confidence fluctuation value refers to the range of fluctuation of the collection confidence level relative to the reference confidence level. For example, the confidence fluctuation value can be the difference between the collection confidence level and the reference confidence level.

[0148] Stability duration refers to the length of time that the acquisition confidence remains stable. In some embodiments, the processor may determine multiple confidence fluctuation values corresponding to the acquisition confidence at multiple moments; define the longest period of time consisting of multiple consecutive moments in which the confidence fluctuation value remains positive as the stability duration; and define the average duration of the multiple stability periods as the stability duration.

[0149] In some embodiments, the longer the stable period and the smaller the mean of the confidence fluctuation value, the higher the operational stability. For example, the processor may calculate the operational stability based on the following formula (2): (2) in, is the operating stability, k is the stability coefficient, For stable duration, is the mean of multiple confidence fluctuation values, and the stability coefficient k can be preset by the processor or technicians.

[0150] In some embodiments, the processor adjusts the necessity of component replacement in a variety of ways based on the acquisition confidence and operational stability. For example, in response to the acquisition confidence being lower than a preset confidence threshold, the processor may increase the necessity of component replacement, and the increase in the necessity of component replacement may be consistent with the difference between the acquisition confidence and the preset confidence threshold. For another example, in response to the acquisition confidence being higher than the confidence threshold and the operational stability being lower than a preset stability threshold, the processor may increase the necessity of component replacement, and the increase in the necessity of component replacement may be consistent with the difference between the operational stability and the preset stability threshold. The preset stability threshold may be pre-set by the processor or a technician.

[0151] In some embodiments of the present specification, the acquisition confidence of the gas CNC component is accurately evaluated through gas monitoring data, and then the operating stability of the gas CNC component is determined based on the acquisition confidence at multiple moments, and then the acquisition confidence and operating stability are compared with the corresponding preset values to reasonably adjust the necessity of component replacement, so that the necessity of component replacement is more reliable and accurate, which is conducive to accurately determining whether the gas CNC component needs to be replaced, and saving replacement costs while ensuring the normal operation of the gas CNC component.

[0152] In some embodiments, the processor may determine replacement parameters for multiple gas areas of the gas pipeline network based on pipeline location information and replacement necessity of the gas digital control components in the gas pipeline network.

[0153] For more information about gas CNC components, replacement necessity and replacement parameters, please refer to Figure 2-Figure 4 Related instructions.

[0154] The pipe network location information refers to the location information of the gas digital control component in the gas pipe network. In some embodiments, the pipe network location information of the gas digital control component may include the pipe level and installation location coordinates of the gas digital control component.

[0155] 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 may include a main pipeline, a primary branch, a secondary branch, etc. In some embodiments, the pipeline level can be directly obtained by the processor based on the data center.

[0156] For more information about the installation location coordinates, see Figure 4 Related description.

[0157] A gas zone refers to a sub-area in a gas network. In some embodiments, the gas network can be divided into multiple gas zones. The division of the gas zones can be done by technicians or by a processor according to a preset rule (e.g., an equal area rule).

[0158] Figure 5 5 is an exemplary flow chart for determining replacement parameters for a gas zone according to some embodiments of this specification. In some embodiments, process 500 may be executed by the gas company management platform 141. For example, it may be executed by a processor in the gas company management platform 141.

[0159] like Figure 5 As shown, process 500 may include step 510 and step 520 .

[0160] Step 510 , based on the network location information of the gas numerical control components in the gas network and the gas usage data of the gas pipelines where the gas numerical control components are located, a plurality of gas areas of the gas network are determined by a clustering algorithm.

[0161] Gas usage data refers to data related to gas consumption by gas users. For example, the gas usage data for the gas pipeline where the gas digital control component is located may include the total amount of gas used and the duration of gas use by the gas user of the gas pipeline where the gas digital control component is located. In some embodiments, the processor may obtain the gas usage data based on the gas user platform.

[0162] In some embodiments, the clustering algorithm may be a clustering algorithm with a given number of clusters, such as a K-means clustering algorithm and its derivative clustering algorithms.

[0163] In some embodiments, the processor determines multiple gas areas of the gas network based on the network location information of the gas CNC components in the gas network and the gas usage data of the gas pipelines where the gas CNC 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 network location information of a gas CNC component and the gas usage data of the pipeline where it is located, and multiple gas CNC components correspond to multiple third vectors; randomly determine K cluster centers from the multiple third vectors; for each third vector, calculate its vector distance with the K cluster centers respectively, and divide it into the cluster where the cluster center with the closest vector distance is located; traverse all third vectors to form K clusters; for each cluster, calculate the mean of the third vectors in the cluster, and use the mean as the new cluster center of the cluster; repeat the above steps until the cluster center no longer changes, clustering is completed, and K clusters are determined, and the network location information of the gas components in each cluster corresponds to each gas area.

[0164] The number of cluster centers, i.e., the aforementioned K value, can be set by default by the processor or by technicians based on experience. For example, a large number of historical gas CNC component replacement thresholds in historical data can be clustered using a clustering algorithm that does not specify the number of clusters, and the number of clusters formed is determined as the K value. Clustering algorithms that do not specify the number of clusters can include the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm.

[0165] Step 520: For each gas zone, execute steps 521 and 522.

[0166] Step 521 : determining replacement thresholds for gas CNC components of different CNC component types within the gas area based on the gas usage data of the gas area.

[0167] The replacement threshold refers to the minimum value of the degree of necessity for replacing the gas digital control component that needs to be replaced. When the degree of necessity for replacing the gas digital control component is greater than or equal to the replacement threshold, the gas digital control component is a component to be replaced. In some embodiments, the replacement threshold may include a battery replacement threshold and a component replacement threshold.

[0168] The battery replacement threshold is the minimum value of the battery replacement necessity of the component to be replaced. The component replacement threshold is the minimum value of the component replacement necessity of the component to be replaced.

[0169] In some embodiments, the replacement thresholds of gas digital control components of the same digital control component type in different gas areas may be different, and the replacement thresholds of gas digital control components of different digital control component types in the same gas area may also be different.

[0170] In some embodiments, for each gas area, the processor can determine the replacement thresholds of gas CNC components of different CNC component types in the gas area in a variety of ways based on the gas usage data of the gas area. For example, for a certain gas area, the processor can count the average of the historical battery replacement necessity and the average of the historical component replacement necessity of multiple historical gas CNC components with multiple pipeline location information in the same gas area in the first vector database, and determine them as the reference battery replacement necessity and the reference component replacement necessity respectively; based on the gas usage data of the gas area, the reference battery replacement necessity and the reference component replacement necessity are adjusted to determine them as the battery replacement threshold and the component replacement threshold, and the adjustment method can be that the greater the total amount of gas usage, the higher the replacement threshold. For more information about the first vector database, please refer to Figure 2 Related description.

[0171] Step 522: Determine the replacement parameters of the gas zone based on the replacement threshold and the degree of replacement necessity.

[0172] In some embodiments, the processor can determine the replacement parameters of the gas zone in a variety of ways based on the replacement threshold and the degree of necessity for replacement. For example, for each gas zone, the processor can compare the replacement threshold and the degree of necessity for replacement of each gas digital control component in the gas zone; in response to the battery replacement necessity of the gas digital control component being greater than or equal to the battery replacement threshold, and the component replacement necessity being less than the component replacement threshold, the gas digital control component is determined to be a gas to be replaced, and the replacement method is battery replacement; in response to the component replacement necessity of the gas digital control component being greater than or equal to the component replacement threshold, the gas digital control component is determined to be a gas to be replaced, and the replacement method is complete component replacement.

[0173] In some embodiments of the present specification, a clustering algorithm can be used to accurately divide a gas network into multiple gas areas, thereby determining the replacement thresholds corresponding to gas CNC components of different CNC component types in different gas areas, which is conducive to accurately determining the replacement parameters of each gas area, and can more quickly and accurately determine the components to be replaced and the replacement method, thereby ensuring that the gas data in the gas area is accurately and adequately monitored.

[0174] In some embodiments of this specification, based on the pipeline location information and replacement necessity of the gas CNC components in the gas pipeline network, the replacement parameters of multiple gas areas of the gas pipeline network can be accurately determined by region, which is conducive to more accurate replacement of the gas CNC components.

[0175] In some embodiments, the processor can determine qualified components based on replacement parameters; determine the synchronous acquisition parameters of the gas digital control component in response to receiving the replacement completion information, and send the synchronous acquisition parameters to the gas digital control component; determine the acquisition confidence of the gas digital control component based on the gas monitoring data collected by the gas digital control component according to the synchronous acquisition parameters, and verify the acquisition confidence.

[0176] For more information about replacement parameters, replacement completion information, gas CNC components, gas monitoring data, and collection confidence, please refer to Figure 2-Figure 5 Related instructions.

[0177] Qualified components refer to gas digital control components that do not need to be replaced. In some embodiments, the gas digital control components before replacement include qualified components and components to be replaced; and the gas digital control components after replacement include qualified components and replaced components.

[0178] In some embodiments, the processor may determine the components to be replaced based on the replacement parameters, and determine other gas digital control components except the components to be replaced as qualified components.

[0179] Synchronous collection parameters refer to the unified collection parameters of the gas CNC components after replacement, that is, the unified collection parameters of qualified components and replaced components.

[0180] In some embodiments, the synchronous acquisition parameters may include a synchronous acquisition period and a synchronous acquisition frequency. The synchronous acquisition period refers to a unified period of time during which data from the qualified component and the replaced component are collected. The synchronous acquisition frequency refers to a unified frequency during which data from the qualified component and the replaced component are collected.

[0181] In some embodiments, in response to receiving the replacement completion information, the processor may determine the preset synchronous acquisition parameters as the synchronous acquisition parameters of the gas digital control component. The preset synchronous acquisition parameters may be manually set parameters or the average value of historical synchronous acquisition parameters determined by statistical calculations of the processor.

[0182] In some embodiments, the processor can send synchronization acquisition parameters to the gas digital control component, and the gas digital control component collects gas monitoring data according to the synchronization acquisition parameters. The gas digital control component includes replaced components and qualified components.

[0183] In some embodiments, the processor can determine the collection confidence level of the gas digital control component based on the gas monitoring data collected by the gas digital control component according to the synchronous collection parameters. The process of determining the collection confidence level based on the gas monitoring data can be found in the relevant description above and will not be repeated here.

[0184] In some embodiments, the processor can verify the acquisition confidence in various ways. For example, in response to the acquisition confidence being greater than a preset confidence threshold, the verification is determined to be successful; in response to the acquisition confidence being less than the preset confidence threshold, the verification is determined to have failed, and the gas digital control component is repaired and inspected. If a problem is determined with the gas digital control component, it is replaced.

[0185] In some embodiments of the present specification, based on the gas monitoring data collected by the gas CNC component according to the synchronous collection parameters, the collection confidence of the gas CNC component 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 CNC component and ensuring the normal operation of the gas pipeline.

[0186] In some embodiments, in response to completing the verification of the collection confidence, the processor can determine the low-power components among the qualified components; lower the data collection parameters of the low-power components, and increase the data collection parameters of the replaced components to keep the total collection amount meeting the preset requirements.

[0187] For more information about collection confidence, qualified components, replaced components, and data collection parameters, see the relevant instructions above.

[0188] A low-battery component is a qualified component with a low battery level.

[0189] In some embodiments, the processor may determine a qualified component whose remaining battery power is lower than a preset power value as a low-power component.

[0190] The preset power value refers to the minimum battery power required for the gas CNC component to continue to operate normally. The preset power value can be set by the processor by default or manually preset based on experience. For example, it can be 60% of the full power.

[0191] The total amount of data collected refers to the total amount of gas monitoring data collected by all gas CNC components.

[0192] In some embodiments, the preset requirement may be set by default by the processor or manually preset based on experience. For example, the preset requirement may be that the change in the total amount of data collected does not exceed a preset change threshold. The preset change threshold may also be set by default by the processor or manually preset based on experience.

[0193] In some embodiments, the processor may lower the data collection parameters of low-power components and increase the data collection parameters of replaced components to ensure that the total amount collected meets preset requirements.

[0194] In some embodiments of the present specification, by determining low-power components among qualified components, lowering the data collection parameters of the low-power components, and increasing the data collection parameters of the replaced components to keep the total collection amount meeting the preset requirements, it is possible to extend the working time of the gas CNC components as much as possible while ensuring that sufficient gas monitoring data is collected, thereby reducing the replacement cost of the gas CNC components while ensuring the normal operation of the gas official website.

[0195] The embodiments of the present invention are only for illustration and description, and do not limit the scope of application of the present invention. For those skilled in the art, various modifications and changes that can be made under the guidance of the present invention are still within the scope of the present invention.

[0196] Furthermore, certain features, structures, or characteristics of one or more embodiments of the present invention may be appropriately combined.

[0197] If there is any inconsistency or conflict between the descriptions, definitions, and / or usage of terms in the accompanying materials of this invention and the content of this invention, the descriptions, definitions, and / or usage of terms in this invention 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: Acquiring component characteristics of the gas numerical control component, wherein the component characteristics include at least one of a data processing characteristic, an operating characteristic, and an environmental characteristic; Determining the necessity of replacing the gas numerical control component based on the component characteristics; 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, it is determined that the component has been replaced and the data center is updated.

2. The method according to claim 1, characterized in that The degree of necessity for replacement includes the degree of necessity for battery replacement and the degree of necessity for component replacement; and the determination of the degree of necessity for replacement of the gas numerical control component based on the component characteristics includes: 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 characteristics, the first operating characteristics, and the first environmental characteristics; 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; Among them, the first working characteristic and the second working characteristic are respectively the working characteristics of the time period related to the historical moments of replacing batteries and replacing components; the first environmental characteristic and the second environmental characteristic are respectively the environmental characteristics of the time period related to the historical moments of replacing batteries and replacing components.

3. The method according to claim 2, characterized in that The method further comprises: Based on the data center, obtaining 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.

4. The method according to claim 1, wherein 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.

5. 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: Acquiring component characteristics of the gas numerical control component, wherein the component characteristics include at least one of a data processing characteristic, an operating characteristic, and an environmental characteristic; Determining the necessity of replacing the gas numerical control component based on the component characteristics; 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 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, it is determined that the component has been replaced and the data center is updated.

6. The Internet of Things system according to claim 5, characterized in that: The degree of necessity for replacement includes the degree of necessity for battery replacement and the degree of necessity for component replacement; The gas company management platform is further configured to: 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; Among them, the first working characteristic and the second working characteristic are respectively the working characteristics of the time period related to the historical moments of replacing batteries and replacing components; the first environmental characteristic and the second environmental characteristic are respectively the environmental characteristics of the time period related to the historical moments of replacing batteries and replacing components.

7. The Internet of Things system according to claim 6, 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.

8. The Internet of Things system according to claim 5, 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.

9. The Internet of Things system according to claim 5, 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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