Pipeline repairing method based on smart gas, Internet of Things system and medium

Abstract

The invention provides a pipeline repairing method based on intelligent gas, an Internet of Things system and a medium, the method belongs to the field of gas pipeline repairing, the method is executed by a government supervision management platform of the Internet of Things system, and the method comprises the steps of obtaining pipeline repairing equipment information and to-be-repaired pipeline data; determining a pipeline repair sequence based on the pipeline repair equipment information and the to-be-repaired pipeline data; based on the repair instruction, executing at least one operation of receiving feedback information collected by the citizen user platform; based on the feedback information, determining the updated acquisition frequency of the pressure regulating equipment and the gas metering device deployed on the target gas pipeline; and based on the to-be-repaired pipeline data, the pressure regulating parameters, the gas supply parameters and the monitoring data, a repair updating instruction is generated. The pipeline repairing method serves as a gas pipeline repairing means, a reasonable pipeline repairing sequence can be determined, the gas pipeline with faults is repaired, and the gas supply requirement of citizen users is met.

Description

Technical Field

[0001] This specification relates to the field of gas pipeline repair, and in particular to a pipeline repair method, Internet of Things system and medium based on smart gas. Background Art

[0002] Gas pipelines are affected by external factors (such as corrosion, vibration, accidental collision, etc.) and may fail or have accidents. When a gas pipeline fails or has an accident, the gas company needs to send professional technicians to use professional repair equipment to inspect and repair the gas pipeline. Since the gas supply tension of the gas pipeline varies at different time points, and professional repair equipment is limited, how to reasonably dispatch professional repair equipment and arrange the repair time of the gas pipeline while meeting the gas supply needs of gas users is an issue that needs to be considered. At present, gas companies mainly dispatch professional repair equipment and arrange the repair time of gas pipelines based on management experience, but there may be situations where manual processing is untimely, inefficient or unreasonable, which causes trouble for the overall gas pipeline operation management of the government regulatory management platform.

[0003] Therefore, it is hoped to provide a pipeline repair method, Internet of Things system and medium based on smart gas, which can be used as a means of gas pipeline repair, determine a reasonable pipeline repair sequence, repair faulty gas pipelines, and ensure the gas supply needs of citizen users. Summary of the invention

[0004] One or more embodiments of the present specification provide a pipeline repair method based on smart gas. The method is executed by a government supervision and management platform based on a pipeline repair IoT system for smart gas. The pipeline repair IoT system based on smart gas includes a citizen user platform, a government supervision service platform, a government supervision management platform, a gas company management platform and a gas equipment object platform. The method includes: obtaining pipeline repair equipment information and pipeline data to be repaired from the gas company management platform; determining a pipeline repair sequence based on the pipeline repair equipment information and the pipeline data to be repaired; the pipeline repair sequence includes multiple repair instructions, each of which is executed by at least one target pipeline repair device, and each of the repair instructions includes a target repair pipeline and its corresponding repair parameters; based on the repair instruction, perform at least one of the following operations: receive the citizen user information through the government supervision service platform; The method comprises the following steps: collecting feedback information collected by the user platform; determining the update collection frequency of the pressure regulating equipment and the gas metering device deployed on the target gas pipeline based on the feedback information, and sending the update collection frequency to the pressure regulating equipment and the gas metering device for execution; obtaining the pressure regulating parameters collected by the pressure regulating equipment during the repair process and the gas supply parameters collected by the gas metering device during the repair process; obtaining the monitoring data collected by the monitoring components deployed on the remaining target repair pipelines from the gas company management platform; and generating a repair update instruction based on the pipeline data to be repaired, the pressure regulating parameters during the repair process, the gas supply parameters during the repair process and the monitoring data, wherein the repair update instruction is used to control the update of the pipeline repair sequence.

[0005] One of the embodiments of the present specification provides an Internet of Things system for pipeline repair based on smart gas, including a citizen user platform, a government supervision service platform, a government supervision management platform, a government supervision sensor network platform, a government supervision object platform, a gas company sensor network platform and a gas equipment object platform; the government supervision service platform includes a citizen cloud service sub-platform and a government safety supervision service sub-platform, the government supervision management platform includes a government gas management sub-platform and a government safety management sub-platform, the government supervision sensor network platform includes a government gas management sensor network sub-platform and a government safety management sensor network sub-platform, the government supervision object platform includes a gas company management sub-platform, and a government safety management sub-platform. management platform; the citizen user platform is configured to interact with the citizen cloud service sub-platform and the government safety supervision service sub-platform for data exchange; the government gas management sub-platform is configured to interact with the citizen cloud service sub-platform and the government gas management sensor network sub-platform for data exchange; the government safety management sub-platform is configured to interact with the government safety supervision service sub-platform and the government safety management sensor network sub-platform for data exchange; the gas company management platform is configured to interact with the government gas management sensor network sub-platform and the government safety management sensor network sub-platform respectively; the gas company sensor network platform is configured to interact with the The gas equipment object platform and the gas company management platform perform data interaction; the government supervision management platform is configured to: obtain pipeline repair equipment information and pipeline data to be repaired from the gas company management platform; determine the pipeline repair sequence based on the pipeline repair equipment information and the pipeline data to be repaired; the pipeline repair sequence includes multiple repair instructions, each of which is executed by at least one target pipeline repair equipment, and each of which includes a target repair pipeline and its corresponding repair parameters; based on the repair instruction, perform at least one of the following operations: receive feedback collected by the citizen user platform through the government supervision service platform information; based on the feedback information, determine the update collection frequency of the pressure regulating equipment and the gas metering device deployed on the target gas pipeline, and send them to the pressure regulating equipment and the gas metering device for execution; obtain the pressure regulating parameters during the repair process collected by the pressure regulating equipment and the gas supply parameters during the repair process collected by the gas metering device; obtain the monitoring data collected by the monitoring components deployed on the remaining target repair pipelines; and based on the pipeline data to be repaired, the pressure regulating parameters during the repair process, the gas supply parameters during the repair process and the monitoring data, generate a repair update instruction, the repair update instruction is used to control the update of the pipeline repair sequence.

[0006] One or more embodiments of the present specification provide a computer-readable storage medium, wherein the storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes a pipeline repair method based on smart gas.

[0007] Through the pipeline repair method based on smart gas and the Internet of Things system, a reasonable pipeline repair sequence can be determined as a means of repairing the gas pipeline, and the faulty gas pipeline can be repaired to ensure the gas supply needs of citizen users. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein: Figure 1 is an exemplary platform structure diagram of a pipeline repair system based on smart gas according to some embodiments of this specification; Figure 2 is an exemplary flow chart of a pipeline repair method based on smart gas according to some embodiments of this specification; Figure 3 is an exemplary flow chart for determining a pipeline repair sequence according to some embodiments of the present specification; Figure 4 This is an exemplary schematic diagram of generating repair update instructions according to some embodiments of this specification. DETAILED DESCRIPTION

[0009] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0010] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0011] Figure 1 It is an exemplary platform structure diagram of a smart gas-based pipeline repair system according to some embodiments of this specification.

[0012] like Figure 1As shown, the smart gas-based pipeline repair Internet of Things system 100 may include a citizen user platform 110, a government regulatory service platform 120, a government regulatory management platform 130, a government regulatory sensor network platform 140, a government regulatory object platform 150, a gas company sensor network platform 160 and a gas equipment object platform 170.

[0013] The citizen user platform 110 refers to a platform for interacting with citizen users.

[0014] In some embodiments, the citizen user platform 110 is configured to interact with the citizen cloud service sub-platform 120-1 and the government security supervision service sub-platform 120-2. For example, the citizen user platform 110 can be configured to obtain feedback information from citizen users and send it to the citizen cloud service sub-platform 120-1 of the government supervision service platform 120.

[0015] The government regulatory service platform 120 refers to a platform that provides regulatory services to the government.

[0016] In some embodiments, the government regulatory service platform 120 may include a citizen cloud service sub-platform 120 - 1 and a government security regulatory service sub-platform 120 - 2 .

[0017] The citizen cloud service sub-platform 120-1 is a sub-platform that can provide gas business services to citizen users.

[0018] The government security supervision service sub-platform 120-2 is a sub-platform that can provide security supervision services to citizen users.

[0019] The government supervision management platform 130 is a platform for the government to conduct supervision and management. For example, the government supervision management platform 130 can be configured to perform Figure 2 Pipeline repair method based on smart gas.

[0020] In some embodiments, the government regulatory management platform 130 may include a government gas management sub-platform 130 - 1 and a government safety management sub-platform 130 - 2 .

[0021] The government gas management sub-platform 130-1 may be a sub-platform for the government to supervise and manage gas business. In some embodiments, the government gas management sub-platform 130-1 is configured to interact with the citizen cloud service sub-platform 120-1 and the government gas management sensor network sub-platform 140-1 for data exchange.

[0022] The government security management sub-platform 130-2 may be a sub-platform for the government to perform security supervision and management. In some embodiments, the government security management sub-platform 130-2 is configured to perform data interaction with the government supervision service platform 120 and the government security management sensor network sub-platform 140-2.

[0023] The government supervision sensor network platform 140 refers to a connection platform for realizing interaction between the government supervision management platform 130 and the government supervision object platform 150, and is configured as a communication network and a gateway.

[0024] In some embodiments, the government regulatory sensor network platform 140 may include a government gas management sensor network sub-platform 140 - 1 and a government security management sensor network sub-platform 140 - 2 .

[0025] The government gas management sensor network sub-platform 140 - 1 can be a connection platform for realizing interaction between the government gas management sub-platform 130 - 1 and the gas company management platform 150 - 1 .

[0026] The government security management sensor network sub-platform 140 - 2 can be a connection platform for realizing interaction between the government security management sub-platform 130 - 2 and the gas company management platform 150 - 1 .

[0027] The government regulatory object platform 150 may be a functional platform used by the government to perceive information generation and control information execution.

[0028] In some embodiments, the government regulatory object platform 150 may include a gas company management platform 150 - 1 .

[0029] The gas company management platform 150 - 1 may be a platform used by the gas company to sense information generation and control information execution.

[0030] In some embodiments, the gas company management platform 150 - 1 may be configured to perform data exchange with the government gas management sensor network sub-platform 140 - 1 and the government security management sensor network sub-platform 140 - 2 .

[0031] The gas company sensor network platform 160 may be a connection platform for realizing interaction between the gas company management platform 150 - 1 and the gas equipment object platform 170 , and is configured as a communication network and a gateway.

[0032] In some embodiments, the gas company sensor network platform 160 may be configured to interact with the gas equipment object platform 170 and the gas company management platform 150-1. For example, the gas company sensor network platform 160 may obtain pipeline repair equipment information from the gas equipment object platform 170 and send it to the gas company management platform 150-1.

[0033] The gas equipment object platform 170 is a functional platform that can sense information related to gas equipment and execute control information.

[0034] In some embodiments, the gas equipment object platform 170 may include pipeline repair equipment and the like.

[0035] For more information about the citizen user platform 110, government supervision service platform 120, government supervision management platform 130, government supervision sensor network platform 140, government supervision object platform 150, gas company sensor network platform 160 and gas equipment object platform 170, please refer to Figure 2-Figure 4 Instructions in .

[0036] Figure 2 is an exemplary flow chart of a pipeline repair method based on smart gas according to some embodiments of this specification. In some embodiments, process 200 can be executed by a government regulatory management platform based on the smart gas pipeline repair IoT system 100. Figure 2 As shown, the process 200 includes the following steps 210 to 260.

[0037] Step 210, obtaining pipeline repair equipment information and pipeline data to be repaired from the gas company management platform.

[0038] For instructions on the gas company management platform, see Figure 1 See the relevant instructions in .

[0039] Pipeline repair equipment information refers to information related to pipeline repair equipment.

[0040] Pipeline repair equipment refers to equipment used to repair holes, cracks, blockages, etc. in gas pipelines or gas pipelines. For example, pipeline repair equipment may include pipe filling machines, pipe internal coating equipment, non-dig pipe repair equipment, pipe rapid repair kits, endoscope inspection equipment, etc.

[0041] Pipeline repair equipment can be used to repair gas pipelines or gas pipelines to keep them in normal operation and extend their service life. During the actual maintenance of gas pipelines, one or more types of pipeline repair equipment can be matched according to the fault type of the gas pipeline.

[0042] In some embodiments, pipeline repair equipment information may include equipment usage and / or equipment detection data.

[0043] The equipment usage status refers to whether each pipeline repair device among the multiple pipeline repair devices is in use.

[0044] Equipment monitoring data refers to the most recent monitoring data of the pipeline repair equipment at the current moment.

[0045] In some embodiments, the equipment monitoring data may include various indicator data related to the performance of various types of pipeline repair equipment, such as temperature, vibration amplitude, current size, etc. of various types of pipeline repair equipment. Different types of pipeline repair equipment may have different types of indicator data.

[0046] In some embodiments, the gas company management platform can obtain pipeline repair equipment information from the gas equipment object platform through the gas company sensor network platform, and the government supervision management platform can obtain pipeline repair equipment information from the gas company management platform through the government supervision sensor network platform.

[0047] The pipeline data to be repaired refers to the data related to the pipeline to be repaired. The pipeline to be repaired refers to the gas pipeline where a gas failure occurs.

[0048] In some embodiments, the repair urgency may be different depending on the failure type of the pipeline to be repaired.

[0049] The repair urgency refers to the degree of impact that the pipeline to be repaired has on the safety of the public users. For example, some types of pipelines to be repaired need to be repaired urgently, while some types of pipelines to be repaired can be put aside for repair.

[0050] In some embodiments, the pipeline data to be repaired includes at least one of the fault type, location, length, and pipeline operation parameters collected in a preset time period of at least one pipeline to be repaired.

[0051] The fault type refers to the type of the fault of the gas pipeline. For example, the fault type may include at least one of a leak fault, a crack fault, a blockage fault, and the like.

[0052] The preset time period may be a time period between the current moment and a preset historical moment. The preset historical moment may be preset by those skilled in the art based on experience.

[0053] The pipeline operation parameters may include at least one of the pressure, flow rate, temperature, etc. of the pipeline to be repaired.

[0054] In some embodiments, the gas company management platform can obtain the pipeline data to be repaired from the call center or other departments, and the government supervision management platform can obtain the pipeline data to be repaired from the gas company management platform through the government supervision sensor network platform.

[0055] Step 220: Determine the pipeline repair sequence based on the pipeline repair equipment information and the pipeline data to be repaired.

[0056] In some embodiments, the pipeline repair sequence may include multiple repair instructions, each repair instruction is executed by at least one target pipeline repair device, and each repair instruction includes a target repair pipeline and its corresponding repair parameters.

[0057] The target repair pipeline refers to the pipeline to be repaired that needs urgent repair.

[0058] Target pipeline repair equipment refers to pipeline repair equipment that repairs the target repair pipeline.

[0059] Repair parameters refer to parameters related to the target repair pipeline.

[0060] In some embodiments, the repair parameters may include a repair sequence for the target repair pipeline and / or a type of target pipeline repair equipment used to repair the target repair pipeline.

[0061] In some embodiments, the government regulatory management platform may use all pipelines to be repaired involved in the pipeline to be repaired data as target repair pipelines in multiple repair instructions.

[0062] In some embodiments, the government regulatory management platform may determine the repair order of the target repair pipeline in the repair parameters through a first preset comparison table based on the fault type in the pipeline data to be repaired.

[0063] The first preset comparison table includes a correspondence between reference fault types and repair sequences of reference target repair pipelines. The first preset comparison table can be constructed based on prior knowledge or historical data.

[0064] In some embodiments, in response to the existence of multiple target repair pipelines of the same fault type, the government regulatory management platform may randomly determine the repair order of the target repair pipelines.

[0065] In some embodiments, the government regulatory management platform may determine the type of target pipeline repair equipment used for the target repair pipeline in the repair parameters through a second preset comparison table based on the fault type of the target repair pipeline in the pipeline data to be repaired.

[0066] The second preset comparison table includes a correspondence between reference fault types and types of target pipeline repair equipment used for reference target repair pipelines. The second preset comparison table can be constructed based on prior knowledge or historical data.

[0067] In some embodiments, the government regulatory management platform may allocate target pipeline repair equipment that matches the fault type of the target repair pipeline in order of repair sequence based on the repair sequence of the target repair pipeline and pipeline repair equipment information.

[0068] In some embodiments, the government regulatory management platform can also use Figure 3 The method shown in the figure determines the pipeline repair sequence. For details, see Figure 3 Instructions in .

[0069] Step 230: Based on the repair instruction, perform at least one of the following operations.

[0070] In some embodiments, the government supervision management platform may perform at least one of the following operations based on the repair instruction, and each of the following operations may include the following steps 231 to 235: Step 231, receiving feedback information collected by the citizen user platform through the government supervision service platform.

[0071] For instructions on the government regulatory service platform and the citizen user platform, please see Figure 1 See the relevant instructions in .

[0072] Feedback information refers to the information fed back by citizen users during the repair period of the target repair pipeline.

[0073] In some embodiments, the feedback information may include fault feedback information, repair feedback information, gas usage feedback information, etc. received from citizen users during the repair of the target repair pipeline.

[0074] Fault feedback information refers to feedback information related to gas equipment during the use of gas by gas users. For example, fault feedback information may include feedback information such as whether the gas equipment has failed or whether the gas pipeline is damaged.

[0075] The repair feedback information refers to feedback information on the repair effect of the gas equipment or gas pipeline that needs repair after repair. For example, the repair feedback information may include feedback information that the gas output of the gas equipment or gas pipeline that needs repair is still too small after repair.

[0076] Gas usage feedback information refers to feedback information from gas users on gas usage. For example, the gas usage feedback information may include feedback information that a gas user uses gas in the same way at the same time period every day, but the current gas usage is larger than the previous gas usage.

[0077] In some embodiments, the government regulatory management platform may receive feedback information collected by the citizen user platform through the government regulatory service platform.

[0078] Step 232, based on the feedback information, determine the update collection frequency of the pressure regulating equipment and the gas metering device deployed on the target gas pipeline, and send it to the pressure regulating equipment and the gas metering device for execution.

[0079] The target gas pipeline refers to the gas pipeline branch where the target repair pipeline is located.

[0080] Pressure regulating equipment refers to equipment used to control the pressure in the gas pipeline and keep the pressure within a preset range, such as a gas pressure regulator, etc. The preset range can be preset by those skilled in the art based on experience.

[0081] A gas metering device refers to a device used to measure the gas flow in a gas pipeline, such as a differential pressure flow meter.

[0082] The acquisition frequency refers to the frequency at which the pressure regulating device adjusts the pressure in the gas pipeline or the frequency at which the gas metering device measures the gas flow in the gas pipeline.

[0083] Update collection frequency refers to the collection frequency after update.

[0084] In some embodiments, the government regulatory management platform can determine the number of negative feedbacks received during the repair of the target repair pipeline based on the feedback information; determine the acquisition frequency adjustment amount based on the number of negative feedbacks; and determine the updated acquisition frequency based on the acquisition frequency adjustment amount and the initial acquisition frequency.

[0085] Negative feedback may include negative fault feedback information, repair feedback information, gas usage feedback information, etc. Negative fault feedback information may include gas equipment failure, etc. Negative repair feedback information may include that the gas output is still too small after the repair of gas equipment or gas pipelines that need to be repaired. Negative gas usage feedback information may include that the gas user uses gas in the same way at the same time of day, but the gas usage at the current moment is larger than the previous gas usage, etc.

[0086] In some embodiments, the government regulatory management platform may count the number of negative feedback messages received during the repair of the target repair pipeline as the number of negative feedbacks.

[0087] In some embodiments, the government regulatory management platform may determine the collection frequency adjustment amount based on the number of negative feedbacks through a third preset comparison table.

[0088] The third preset comparison table includes the correspondence between the number of reference negative feedbacks and the reference acquisition frequency adjustment amount. The third preset comparison table can be constructed based on prior knowledge or historical data.

[0089] The initial acquisition frequency can be preset by those skilled in the art based on experience.

[0090] As an example only, the government supervision management platform may use the following first formula to determine the updated collection frequency: The updated acquisition frequency = initial acquisition frequency + acquisition frequency adjustment amount.

[0091] Step 233, obtaining the pressure regulation parameters during the repair process collected by the pressure regulation equipment and the gas supply parameters during the repair process collected by the gas metering device.

[0092] The pressure regulation parameters refer to the parameters of the pressure regulation equipment. For example, the pressure regulation parameters may include the target pressure and pressure regulation speed of the pressure regulation equipment.

[0093] The gas supply parameters refer to parameters related to the gas supply in the target gas pipeline, such as the gas supply volume in the target gas pipeline.

[0094] In some embodiments, the gas company management platform can obtain the pressure regulating parameters during the repair process collected by the pressure regulating device and the gas supply parameters during the repair process collected by the gas metering device from the gas equipment object platform through the gas company sensor network platform. Then the government supervision management platform can obtain the pressure regulating parameters during the repair process and the gas supply parameters during the repair process from the gas company management platform through the government supervision sensor network platform.

[0095] Step 234, obtaining the monitoring data collected by the monitoring components deployed on the remaining target repair pipelines from the gas company management platform.

[0096] The remaining target repair pipeline refers to the target repair pipeline for which the repair instruction has not yet been executed.

[0097] Monitoring components refer to components that monitor pipeline operating parameters. Monitoring components may include pressure sensors, temperature sensors, flow rate sensors, etc.

[0098] Monitoring data refers to the data collected by monitoring components.

[0099] In some embodiments, the monitoring data may include pipeline operating parameters.

[0100] In some embodiments, the gas company management platform may obtain monitoring data from the gas equipment object platform via the gas company sensor network platform.

[0101] Step 235, generating a repair update instruction based on the pipeline data to be repaired, the pressure regulation parameters during the repair process, the gas supply parameters during the repair process, and the monitoring data.

[0102] The repair update instruction is an instruction used to update the repair instruction in the pipeline repair sequence. The repair update instruction can be used to control the update of the pipeline repair sequence.

[0103] In some embodiments, the update pipeline repair sequence may represent the order in which multiple target repair pipelines of the same fault type are repaired.

[0104] In some embodiments, the government regulatory management platform can determine the repair urgency of multiple target repair pipelines of the same fault type based on the pipeline data to be repaired, the pressure regulation parameters during the repair process, the gas supply parameters during the repair process, and the monitoring data; sort the repair urgency of multiple target repair pipelines of the same fault type from high to low to obtain the sorting result of the repair urgency; and re-determine the repair order of the target repair pipelines based on the sorting result of the repair urgency.

[0105] In some embodiments, the government regulatory management platform can determine the repair urgency of the target repair pipeline through a fourth preset comparison table based on the pipeline data to be repaired, the pressure regulation parameters during the repair process, the gas supply parameters during the repair process, and the monitoring data.

[0106] The fourth preset comparison table includes reference repair pipeline data, reference pressure adjustment parameters during the repair process, reference gas supply parameters during the repair process, and a corresponding relationship between reference monitoring data and the maintenance urgency of the reference target repair pipeline. The fourth preset comparison table can be constructed based on prior knowledge or historical data.

[0107] In some embodiments, the government supervision and management platform may use the ranking results of the repair urgency and the corresponding ranking results of the target repair pipelines as the re-determined repair order of the target repair pipelines.

[0108] In some embodiments, the government regulatory management platform can also use Figure 4 The method shown generates repair update instructions. For details, see Figure 4 Instructions in .

[0109] In some embodiments, the pipeline repair method based on smart gas may further include the following steps 240 to 260.

[0110] Step 240 , for the ongoing repair instructions, in response to the existence of pipeline repair equipment that meets the preset conditions, the total repair time of each ongoing repair instruction is estimated.

[0111] The preset condition may include newly assignable pipeline repair equipment. The newly assignable pipeline repair equipment may include pipeline repair equipment that was previously occupied and used to repair the target repair pipeline and has now been terminated, newly purchased pipeline repair equipment, and pipeline repair equipment that previously had poor performance but can be put into use again after maintenance.

[0112] The total repair time refers to the total time it takes to complete a target repair pipeline.

[0113] In some embodiments, the government supervision management platform can determine a first target feature vector based on the target repair pipeline data and its corresponding repair parameters; determine multiple first associated feature vectors based on the first target feature vector through a first vector database; and determine the final total repair time obtained by weighted summing the reference total repair time corresponding to the multiple first associated feature vectors as the total repair time of the target repair pipeline corresponding to the repair instruction. The weight can be preset by those skilled in the art based on experience.

[0114] The first vector database includes a plurality of first reference feature vectors, wherein each first reference feature vector has a corresponding reference total repair time. The reference feature vector is a feature vector constructed based on historical repair pipeline data and its corresponding repair parameters.

[0115] In some embodiments, the government regulatory management platform may determine the weight corresponding to each first associated feature vector based on the total historical repair duration corresponding to the first associated feature vector.

[0116] The total historical repair time refers to the total time it takes to complete a historical target repair pipeline.

[0117] In some embodiments, the government supervision and management platform may determine the weight corresponding to the first associated feature vector based on the total historical repair time corresponding to the first associated feature vector through a fifth preset comparison table.

[0118] The fifth preset comparison table includes a correspondence between the total historical repair time corresponding to the reference first associated feature vector and the weight corresponding to the reference first associated feature vector. The fifth preset comparison table can be constructed based on prior knowledge or historical data.

[0119] In some embodiments of the present specification, by determining the weight corresponding to the target reference vector based on the total historical restoration time corresponding to the target reference vector, the accuracy of the determined weight can be improved.

[0120] In some embodiments, the government supervision management platform may determine, based on the first target feature vector, a first reference feature vector that meets a preset condition in a first vector database, and determine multiple first reference feature vectors that meet the preset condition as associated feature vectors. In some embodiments, the preset condition may include that the vector distance from the first target feature vector satisfies a preset condition, etc. The preset condition may be preset by a person skilled in the art based on experience, such as a distance less than a distance threshold.

[0121] Step 250: Determine at least one target repair instruction based on the total repair time.

[0122] In some embodiments, the target repair instructions may include repair instructions whose total repair time is greater than a repair threshold.

[0123] The repair threshold refers to the critical value of the total repair time, and can be preset by those skilled in the art based on experience.

[0124] In some embodiments, the government regulatory management platform may determine a repair threshold based on the repair urgency of the target repair pipeline. For example, the higher the repair urgency of the target repair pipeline, the lower the repair threshold may be preset.

[0125] In some embodiments of the present specification, a repair threshold is determined based on the repair urgency of the target repair pipeline. When the repair urgency of the target repair pipeline is higher, the risk of a gas accident is higher. At this time, the repair threshold can be appropriately lowered to shorten the total repair time and reduce the risk.

[0126] In some embodiments, the government regulatory management platform may determine a repair instruction whose total repair time is greater than a repair threshold as a target repair instruction.

[0127] Step 260: Update the repair parameters of the target repair instruction.

[0128] In some embodiments, in response to the existence of multiple pipeline repair equipment that meet preset conditions and the existence of multiple target repair instructions, the government regulatory management platform may sort the repair urgency of the target repair pipelines corresponding to the target repair instructions in order from high to low, so as to re-determine the repair order of each target repair pipeline and / or the type of target pipeline repair equipment used to repair the target repair pipeline, thereby updating the repair parameters of each target repair instruction.

[0129] In some embodiments of the present specification, a pipeline repair sequence is determined based on pipeline repair equipment information and pipeline data to be repaired, and in the process of executing the repair instructions of the pipeline repair sequence, feedback information, pressure regulation parameters, gas supply parameters and monitoring data of residential users are obtained to generate repair update instructions, and the repair instructions that have not yet been executed in the pipeline repair sequence are timely controlled and updated to determine a reasonable pipeline repair sequence as a means of repairing the gas pipeline, to repair the faulty gas pipeline and ensure the gas supply needs of citizen users.

[0130] In addition, for ongoing repair instructions, if there is new pipeline repair equipment that can be allocated, the total repair time of multiple ongoing repair instructions is estimated, and then priority is given to target repair instructions whose total repair time is greater than the repair threshold, and the repair parameters are adjusted to ensure that urgent target repair pipelines are repaired first, so as to further guarantee the gas supply needs of gas users.

[0131] Figure 3is an exemplary flow chart for determining a pipeline repair sequence according to some embodiments of this specification. In some embodiments, process 300 may be executed by a government regulatory management platform based on the smart gas pipeline repair IoT system 100. Figure 3 As shown, the process 300 includes the following steps 310 to 350.

[0132] Step 310: Determine the performance level of the pipeline repair equipment based on the pipeline repair equipment information.

[0133] For information on pipeline repair equipment, see Figure 2 Relevant instructions in step 210.

[0134] The performance level can reflect the performance of the pipeline repair equipment. For example, the better the performance of the pipeline repair equipment, the higher the performance level.

[0135] In some embodiments, the performance level may be represented by a numerical value, where the higher the numerical value, the better the performance level.

[0136] In some embodiments, the government regulatory management platform can determine a second target feature vector based on pipeline repair equipment information; determine multiple second associated feature vectors through a second vector database based on the second target feature vector; and use the average of the fault degrees in the reference performance conditions corresponding to the multiple second associated feature vectors as the performance level of the pipeline repair equipment.

[0137] The second vector database includes a plurality of second reference feature vectors, wherein each second reference feature vector has a corresponding reference performance condition. The reference feature vector is a feature vector constructed based on historical pipeline repair equipment information.

[0138] The reference performance situation can reflect whether the pipeline repair equipment fails and the extent of the failure during the actual historical repair process.

[0139] The degree of failure refers to the degree of failure of pipeline repair equipment in the actual historical repair process. The degree of failure can be in the form of a score and can be determined by those skilled in the art based on experience.

[0140] In some embodiments, the government regulatory management platform can construct a reference performance situation based on whether the pipeline repair equipment fails and the extent of the failure during the actual historical repair process.

[0141] In some embodiments, the government supervision management platform can determine a second reference feature vector that meets the preset conditions in the second vector database based on the second target feature vector, and determine multiple second reference feature vectors that meet the preset conditions as second associated feature vectors. In some embodiments, the preset conditions may include that the vector distance from the second target feature vector meets the preset conditions, etc. The preset conditions may be preset by those skilled in the art based on experience, such as the distance being less than a distance threshold.

[0142] Step 320, determining a target pipeline repair device based on the performance level.

[0143] In some embodiments, the target pipeline repair device may include a pipeline repair device that is in an idle state and has a performance level higher than a performance threshold. For more information about the target pipeline repair device, see Figure 2 Description of step 220. The performance threshold refers to a critical value of a performance level.

[0144] The performance threshold can be preset by those skilled in the art based on experience.

[0145] In some embodiments, the government supervision management platform may determine the performance thresholds of different types of pipeline repair equipment based on the usage level of the corresponding pipeline repair equipment during the repair process. For example, the higher the usage level of the pipeline repair equipment during the repair process, the higher the performance threshold may be preset.

[0146] In some embodiments, the government supervision management platform may use the following steps 321-322 to determine the degree of use of any pipeline repair equipment during the repair process: Step 321, obtaining preset multiple groups (eg, preset m groups, where m is a positive integer greater than or equal to 1) of historical usage data of pipeline repair equipment of a certain type (eg, type A) that has been used.

[0147] Each set of historical usage data may include the usage time of different types of pipeline repair equipment used in the process of repairing a historical target repair pipeline and the total historical repair time, and each set of historical usage data uses a certain type (e.g., type A) of pipeline repair equipment.

[0148] The usage time refers to the time it takes to repair a pipeline using a certain type of pipeline repair equipment in the process of completing a historical target repair pipeline.

[0149] For a description of the total time of historical repairs, see Figure 2 Description of step 240.

[0150] In some embodiments, the government regulatory management platform can obtain the usage time and the total historical repair time through monitoring equipment (such as time sensors) installed on the pipeline repair equipment.

[0151] Step 322, based on the sum of the usage time of a certain type (e.g., type A) of pipeline repair equipment corresponding to multiple preset groups (e.g., preset m groups) of historical usage data and the sum of the total historical repair time corresponding to multiple groups of historical usage data, determine the usage degree of the corresponding type (e.g., type A) of pipeline repair equipment.

[0152] As an example only, the government regulatory management platform may use the following second formula to determine the degree of use of pipeline repair equipment of type A, where type A may be any type: The utilization degree of Type A pipeline repair equipment = the sum of the usage time of Type A pipeline repair equipment corresponding to the preset m groups of historical usage data ÷ the sum of the total historical repair time corresponding to the m groups of historical usage data × 100%.

[0153] In some embodiments of the present specification, the performance thresholds of different types of pipeline repair equipment are determined based on the usage level of the corresponding pipeline repair equipment during the repair process. When the usage level of the pipeline repair equipment during the repair process is higher, it means that the pipeline repair equipment has a greater impact on the repair effect during the repair process of the target repair pipeline. At this time, the performance threshold of the pipeline repair equipment with a high usage level can be set higher, so that the selected pipeline repair equipment is more reliable, thereby ensuring the repair effect of the target repair pipeline, thereby avoiding damage to the pipeline repair equipment during the repair process, affecting the repair progress.

[0154] In some embodiments, the government regulatory management platform may determine, based on the performance level of the pipeline repair equipment, a pipeline repair equipment that is in an idle state and has a performance level higher than a performance threshold as a target pipeline repair equipment.

[0155] Step 330: Determine the repair urgency of each pipeline to be repaired based on the pipeline data to be repaired.

[0156] For information on pipeline data to be repaired and repair urgency, see Figure 2 Description of step 210.

[0157] In some embodiments, the government supervision and management platform can determine the repair urgency of each pipeline to be repaired based on the pipeline data to be repaired through a sixth preset comparison table.

[0158] The sixth preset comparison table includes the corresponding relationship between the reference repair pipeline data and the maintenance urgency of the reference repair pipeline. The sixth preset comparison table can be constructed based on prior knowledge or historical data.

[0159] In some embodiments, the government regulatory management platform can also construct a pipeline map to be repaired based on the pipeline data to be repaired; and based on the pipeline map to be repaired, determine the repair urgency of each pipeline to be repaired through a repair prediction model.

[0160] The pipeline map to be repaired refers to a connection map between pipelines to be repaired that is constructed based on the pipelines to be repaired.

[0161] In some embodiments, the pipeline graph to be repaired may include nodes and edges, the edges connect the nodes, and the nodes and edges may have attributes.

[0162] In some embodiments, the nodes of the pipeline map to be repaired may correspond to the pipeline to be repaired. The attributes of the nodes may reflect the relevant characteristics of the pipeline to be repaired corresponding to the node. For example, the node attributes may include: the fault type, location, length of the pipeline to be repaired, and the pipeline operation parameters collected during a preset time period. For a description of the fault type, preset time period, and pipeline operation parameters, see Figure 2 Description of step 210.

[0163] In some embodiments, the node attributes of the pipeline map to be repaired may also include: the total number of gas-using residents in the surrounding area and downstream of the pipeline to be repaired and the historical gas usage of the gas-using residents downstream.

[0164] The peripheral area refers to an area within a preset radius area with the pipeline to be repaired as the center. The preset radius can be preset by those skilled in the art based on experience.

[0165] The historical gas usage refers to the total amount of gas used by all gas-using residents downstream of the pipeline to be repaired within a preset time period. The preset time period can be preset by those skilled in the art based on experience.

[0166] In some embodiments of the present specification, the node attributes of the map of pipelines to be repaired may also include the total number of gas-using residents in the surrounding area and downstream of the pipelines to be repaired and the historical gas usage of the downstream gas-using residents, which can further improve the accuracy of the repair urgency of each pipeline to be repaired that is ultimately determined.

[0167] In some embodiments, an edge of the pipeline map to be repaired represents the connection between two pipelines to be repaired. The attributes of the edge can reflect the relevant characteristics of the path connecting the two pipelines to be repaired. For example, the attributes of the edge can include: the connection area of ​​the two connected pipelines to be repaired corresponding to the edge.

[0168] In some embodiments, the repair prediction model may be a machine learning model. In some embodiments, the type of the repair prediction model may include a graph neural network model (GNN). The output of the repair prediction model may be the maintenance urgency corresponding to each node.

[0169] In some embodiments, the repair prediction model can be obtained through training based on a plurality of first training samples with first training labels.

[0170] In some embodiments, each group of first training samples in the first training samples may include a historical sample repair pipeline map. The historical sample repair pipeline map refers to a pipeline map to be repaired constructed based on the historical sample pipelines to be repaired. In some embodiments, since there may be multiple historical sample pipelines to be repaired on the historical sample repair pipeline map, the first training label may include multiple first sub-training labels, each of which corresponds to a historical sample pipeline to be repaired.

[0171] In some embodiments, the government regulatory management platform can construct a historical sample repair pipeline graph through historical sample pipelines to be repaired, wherein the attributes of the nodes and edges of the historical sample repair pipeline graph can be determined based on historical data.

[0172] In some embodiments, the first training label may be the repair urgency corresponding to the pipeline to be repaired of each node in the historical sample repair pipeline graph.

[0173] The first training labels can be determined by manual annotation.

[0174] In some embodiments, the government regulatory management platform may construct a first training label based on a first gas safety situation and a first user feedback in a first historical preset period corresponding to a first training sample.

[0175] In some embodiments, the first gas safety situation may include a plurality of first sub-gas safety situations, and each first sub-safety gas situation corresponds to a first sub-training label.

[0176] The first sub-first gas safety situation refers to whether an explosion or other accidents occur in a pipeline to be repaired from the historical moment t1 corresponding to the first training sample to the start of repair and its corresponding first sub-hazard score. The first sub-hazard score can be a score in the range of 0 to a, where a is any number greater than 0. The first historical preset period can be the period from the historical moment t1 to the start of repair.

[0177] The historical moment t1 can be determined by those skilled in the art based on experience.

[0178] In some embodiments, the government regulatory management platform can determine the first sub-hazard score corresponding to the pipeline to be repaired based on the casualties, property losses, etc. of accidents related to the pipeline to be repaired within a first historical preset time period. For example, the greater the casualties and the more serious the property losses in the accidents related to the pipeline to be repaired, the higher the first sub-hazard score corresponding to the pipeline to be repaired.

[0179] In some embodiments, the first user feedback may include multiple first sub-user feedbacks, and each first sub-user feedback corresponds to a first sub-training label.

[0180] The first sub-user feedback refers to the number of negative feedbacks from gas residents in the surrounding area and downstream of a pipeline to be repaired in the first historical preset period regarding the pipeline to be repaired. For the method of determining the number of negative feedbacks, please refer to the previous description.

[0181] As an example only, the government regulatory management platform may use the following third formula to determine each first sub-training label in the first training label: The first sub-training label = the first sub-risk score + the first sub-user feedback.

[0182] In some embodiments, the government regulatory management platform can input the historical sample repair pipeline diagram in the first training sample with the first training label into the initial repair prediction model, and then construct a loss function through the first training label and the prediction result of the initial repair prediction model, and iteratively update the parameters of the initial repair prediction model based on the loss function until the loss function converges, the number of iterations reaches a threshold, etc., the training is completed, and a trained repair prediction model is obtained.

[0183] In some embodiments, the government regulatory management platform may input the map of pipelines to be repaired into a repair prediction model, and the repair prediction model outputs the repair urgency of each pipeline to be repaired.

[0184] In some embodiments of the present specification, by constructing a pipeline map to be repaired, inputting a repair prediction model, and determining the repair urgency of each pipeline to be repaired, it is possible to quickly and accurately predict the repair urgency of each pipeline to be repaired.

[0185] Step 340: Determine at least one target repair pipeline based on the repair urgency.

[0186] In some embodiments, the target repair pipeline may include a pipeline to be repaired that is in an idle state and whose repair urgency is higher than an emergency threshold. For more information about the target repair pipeline, see Figure 2 Relevant instructions in step 220.

[0187] The emergency threshold refers to the critical value of the maintenance urgency, and can be preset by those skilled in the art based on experience.

[0188] In some embodiments, the government regulatory management platform may determine an emergency threshold based on a difference between the ambient temperature and a preset temperature range. For example, the greater the difference, the lower the emergency threshold may be preset.

[0189] The ambient temperature refers to the temperature of the environment where the target repair pipeline is located. The government supervision and management platform can obtain the ambient temperature through a monitoring device (such as a temperature sensor, etc.) installed on the target repair pipeline.

[0190] The preset temperature range refers to a preset ambient temperature range under normal conditions. The preset temperature range can be preset by those skilled in the art based on experience.

[0191] In some embodiments of the present specification, an emergency threshold is determined based on the difference between the ambient temperature and a preset temperature range. When the ambient temperature of the target repair pipeline is higher or lower than the preset temperature range, the risk of the failed target repair pipeline directly or indirectly causing a gas accident will be higher than when it is within the preset temperature range. At this time, the emergency threshold can be lowered to allow more pipelines to be repaired to come under supervision and reduce the risk of gas accidents.

[0192] In some embodiments, the government supervision management platform may determine, based on the repair urgency of each pipeline to be repaired, a pipeline to be repaired that is in an idle state and has a repair urgency higher than an urgency threshold as a target repair pipeline.

[0193] Step 350: Determine a pipeline repair sequence based on the repair urgency of the target pipeline repair equipment and the target repair pipeline.

[0194] For a description of the pipeline repair sequence, see Figure 2 Description in step 220.

[0195] In some embodiments, the government regulatory management platform can determine the target pipeline repair equipment corresponding to the target repair pipeline based on the fault type of the target repair pipeline; sort the repair urgency of the target repair pipeline from high to low to determine the sorting result of the repair urgency; and use the sorting result of the repair urgency and the corresponding sorting result of the target repair pipeline as the repair order of the target repair pipeline, thereby determining the pipeline repair sequence.

[0196] For instructions on how to determine the target pipeline repair equipment corresponding to the target repair pipeline based on the fault type of the target repair pipeline, see Figure 2 Description in step 210.

[0197] In some embodiments of the present specification, the pipeline repair sequence is determined by determining the target pipeline repair equipment based on the performance level of the pipeline repair equipment and the maintenance urgency of the target repair pipeline, thereby ensuring that the pipeline repair equipment that is in an idle state and has a high performance level gives priority to the target repair pipeline with a high maintenance urgency, which can further improve the rationality of the determined pipeline repair sequence, thereby better meeting the gas supply needs of citizen users.

[0198] Figure 4 is an exemplary flow chart of generating a repair update instruction according to some embodiments of this specification. In some embodiments, process 400 can be executed by a government regulatory management platform based on the smart gas pipeline repair IoT system 100. Figure 4 As shown, process 400 includes the following steps 410 to 420.

[0199] Step 410, determining a pipeline map to be repaired based on the pipeline data to be repaired.

[0200] For a description of the pipeline data to be repaired, see Figure 2 Relevant instructions in step 210.

[0201] For a definition of the pipeline map to be repaired and instructions on how to construct the pipeline map to be repaired, see Figure 3 Relevant instructions in step 330.

[0202] Step 420, based on the pipeline map to be repaired, the pressure regulation parameters during the repair process, the gas supply parameters during the repair process and the monitoring data, the repair update model is used to determine the updated maintenance urgency of the remaining target repair pipelines.

[0203] For a description of the pressure regulation parameters, gas supply parameters, remaining target repair pipelines, and repair urgency, see Figure 2 See the relevant instructions in .

[0204] In some embodiments, the monitoring data may also include at least one of audio data, traffic information around the target repair pipeline, and human flow information. For more information about monitoring data, see Figure 2 Instructions in step 234.

[0205] Audio data refers to sound data related to the operation of the target repair pipeline. The audio data can reflect whether the sound of the pipeline operation is normal.

[0206] In some embodiments, the gas company management platform can obtain audio data from a sound sensor installed on the target repair pipeline from the gas equipment object platform through the gas company sensor network platform. The government supervision management platform can obtain audio data from a sound sensor installed on the target repair pipeline from the gas company management platform through the government supervision sensor network platform.

[0207] Traffic information refers to information related to traffic around the target repair pipeline, such as the traffic volume and driving speed around the target repair pipeline.

[0208] The human flow information refers to information related to the human flow around the target repair pipeline, such as the human flow around the target repair pipeline.

[0209] Traffic information and human flow information around the target pipeline for repair are potential hazards that can affect the degree of harm caused by the gas accident caused by the target pipeline for repair. For example, in a gas accident caused by the same target pipeline for repair, the more people there are around the target pipeline for repair, the greater the casualties caused.

[0210] In some embodiments, the government supervision and management platform can obtain traffic information and pedestrian flow information through a camera device (eg, a camera).

[0211] In some embodiments of the present specification, in the process of determining the updated maintenance urgency of the remaining target repair pipelines, the monitoring data used not only takes into account the pipeline operation parameters, but also takes into account the audio data, traffic information and pedestrian flow information around the target repair pipeline, thereby further improving the accuracy of the finally determined updated maintenance urgency of the remaining target repair pipelines.

[0212] In some embodiments, the repair update model 413 may be a machine learning model. In some embodiments, the type of the repair update model 413 may include a graph neural network model (GNN). The output of the repair update model 413 may be an updated maintenance urgency corresponding to a specific node, and the specific node may be a node corresponding to a remaining target repair pipeline.

[0213] In some embodiments, the input of the repair update model 413 may include a pipeline map 411-1 to be repaired, pressure regulation parameters 411-2 during the repair process, gas supply parameters 411-3 during the repair process, and monitoring data 411-4, and the output may include an updated maintenance urgency 414 of the remaining target repair pipelines.

[0214] In some embodiments, the input of the repair update model may also include the repair urgency 412 of each pipeline to be repaired output by the repair prediction model.

[0215] For an explanation of the repair urgency of each pipeline to be repaired output by the repair prediction model, see Figure 3 Description of step 330.

[0216] In some embodiments of the present specification, the input of the repair update model also considers the repair urgency of each pipeline to be repaired output by the repair prediction model, which can further improve the accuracy of the updated repair urgency of the remaining target repair pipelines.

[0217] In some embodiments, the repair update model can be obtained through training based on a plurality of second training samples with second training labels.

[0218] In some embodiments, each group of second training samples in the second training samples may include a historical sample repair pipeline diagram, historical sample pressure regulation parameters during the repair process, historical sample gas supply parameters during the repair process, and historical sample monitoring data, and the second training label may be the updated actual repair urgency of the remaining historical sample repair pipelines. In some embodiments, there may be multiple remaining historical sample target repair pipelines on the historical sample repair pipeline diagram, and the second training label may include multiple second sub-training labels, each second sub-training label corresponding to a remaining historical sample target repair pipeline.

[0219] In some embodiments, the second training sample may be obtained based on historical data, and the second training label may be obtained based on manual annotation.

[0220] In some embodiments, the government regulatory management platform may construct a second training label based on a second gas safety situation in a second historical preset period corresponding to the second training sample and a second user feedback.

[0221] In some embodiments, the second gas safety situation may include a plurality of second sub-gas safety situations, and each second sub-safety gas situation corresponds to a second sub-training label.

[0222] The second sub-gas safety situation refers to whether an accident such as explosion occurs in a target repair pipeline of a remaining historical sample from the historical moment t2 corresponding to the second training sample to the start of repair and its corresponding second sub-hazard score. The second sub-hazard score can be a score in the interval of 0 to a, where a is any number greater than 0. The historical moment t1 can be earlier than the historical moment t2. The second historical preset period can be the period between the historical moment t2 and the start of repair.

[0223] The historical moment t2 can be determined by those skilled in the art based on experience.

[0224] In some embodiments, the government regulatory management platform can determine the second sub-risk score corresponding to a remaining historical sample target repair pipeline based on the casualties, property losses, etc. of accidents related to a remaining historical sample target repair pipeline within a second historical preset time period. For example, the greater the casualties and property losses of accidents related to a remaining historical sample target repair pipeline, the higher the second sub-risk score corresponding to the remaining historical sample target repair pipeline.

[0225] In some embodiments, the second user feedback may include multiple second sub-user feedbacks, and each second sub-user feedback corresponds to a second sub-training label.

[0226] The second sub-user feedback refers to the number of negative feedbacks from gas residents in the surrounding area and downstream of a remaining historical sample target repair pipeline within the second historical preset period for the remaining historical sample target repair pipeline. For the method of determining the number of negative feedbacks, please refer to Figure 3 See the relevant instructions in .

[0227] As an example only, the government supervision management platform may use the following fourth formula to determine each second sub-training label in the second training label: Second sub-training label = second sub-risk score + second sub-user feedback.

[0228] In some embodiments, the government supervision management platform can obtain multiple sets of second training samples with second training labels; input the multiple sets of second training samples with second training labels into the initial repair update model, perform multiple rounds of iterations; and when the iteration end condition is met, end the iteration to obtain a trained repair update model. The end condition can be the convergence of the loss function, the number of iterations reaching a threshold, etc.

[0229] In some embodiments, for each iteration, the government regulatory management platform may perform the following steps 421 to 423: Step 421, input the historical sample repair pipeline diagram, the historical sample pressure regulation parameters during the repair process, the historical sample gas supply parameters during the repair process, and the historical sample monitoring data in multiple groups of second training samples with second training labels into the initial repair update model to obtain the output of the initial repair update model corresponding to one or more second training samples.

[0230] Step 422, according to the output of the initial repair update model corresponding to one or more second training samples and the second training labels of the one or more second training samples, substitute them into the formula of the predefined loss function to calculate the value of the loss function.

[0231] Step 423, reversely update the model parameters in the initial repair update model according to the value of the loss function.

[0232] The government supervision management platform can use various methods to perform reverse update. For example, the government supervision management platform can perform reverse update based on the gradient descent method. In some embodiments, the second training sample can also include the repair urgency of each historical sample repair pipeline output by the repair prediction model.

[0233] In some embodiments, the repair prediction model and the repair update model can be obtained through joint training. Each iteration needs to update the parameters of the repair prediction model and the repair update model at the same time. The training sample corresponding to the repair prediction model is recorded as the first training sample, and the corresponding training label is recorded as the first training label. The first training sample includes a historical sample repair pipeline diagram, and there are multiple historical sample pipelines to be repaired on the historical sample repair pipeline diagram. The first training label may include multiple first sub-training labels, and each first sub-training label corresponds to a historical sample pipeline to be repaired. The training sample corresponding to the repair update model is recorded as the second training sample, and the corresponding training label is recorded as the second training label. The second training sample includes a historical sample repair pipeline diagram, and there are multiple remaining historical sample target repair pipelines on the historical sample repair pipeline diagram. The second training label may include multiple second sub-training labels, and each second sub-training label corresponds to a remaining historical sample target repair pipeline.

[0234] For an explanation of the first training sample and the first training label, see Figure 3 Description of step 330.

[0235] The difference between the result predicted by the repair prediction model and the first training label is recorded as a first loss item, and the first loss item includes multiple first sub-loss items, each of which corresponds to the difference between the predicted value of the repair urgency of the pipeline to be repaired and the corresponding first sub-training label.

[0236] The difference between the result predicted by the repair update model and the second training label is recorded as a second loss term, and the second loss term includes multiple second sub-loss terms, each second sub-loss term corresponds to the difference between an updated predicted value of the repair urgency and the corresponding second sub-training label, and the updated predicted value of the repair urgency corresponds to the remaining target repair pipeline.

[0237] The loss function value of the joint training is obtained by weighted summing the first loss term and the second loss term, wherein the first loss term corresponds to the first weight, the first weight includes multiple first sub-weights, and each first sub-weight corresponds to a first sub-loss term. The second loss term corresponds to the second weight, the second weight includes multiple second sub-weights, and each second sub-weight corresponds to a second sub-loss term.

[0238] In some embodiments, the government regulatory management platform may determine a first sub-weight based on the fault type corresponding to the historical sample pipeline to be repaired and determine a second sub-weight based on the fault type of the remaining historical sample target repair pipeline.

[0239] In some embodiments, the more serious the fault type corresponding to the historical sample pipeline to be repaired, the larger the first sub-weight corresponding to the historical sample pipeline to be repaired can be preset by the government supervision management platform. The severity of the pipeline to be repaired corresponding to different fault types can be different.

[0240] Those skilled in the art can preset the severity of the pipeline to be repaired corresponding to different fault types based on experience. For example, if the fault type of the pipeline to be repaired is a leak fault or a crack fault of gas leakage, because it is easy to explode, the severity of the pipeline to be repaired corresponding to this fault type can be preset as very serious. For another example, if the fault type of the pipeline to be repaired is a blockage fault, which at most causes inconvenience to gas users but will not cause safety hazards for a while, the severity of the pipeline to be repaired corresponding to this fault type can be preset as slight.

[0241] In some embodiments, the more serious the fault type corresponding to the remaining historical sample target repair pipeline is, the larger the second sub-weight corresponding to the remaining historical sample target repair pipeline can be preset by the government supervision management platform. The method for determining the severity of the pipeline to be repaired corresponding to different fault types is similar to the method for determining the severity of the pipeline to be repaired, and please refer to the above description for details.

[0242] In the joint training process of the repair prediction model and the repair update model, the historical sample repair pipeline map in the first training sample with the first training label can be input into the initial repair prediction model, and then the maintenance urgency corresponding to each historical sample pipeline to be repaired output by the initial repair prediction model, as well as the historical sample repair pipeline map in the second training sample, the historical sample pressure regulation parameters during the repair process, the historical sample gas supply parameters during the repair process and the historical sample monitoring data are input into the initial repair update model, and then the loss function value obtained by weighted summation of the first loss term and the second loss term is used to iteratively update the parameters of the initial repair prediction model and the initial repair update model until the loss function converges, the number of iterations reaches a threshold, etc., the training is completed, and the trained repair prediction model and repair update model are obtained. The government supervision and management platform can record the difference between the result predicted by the initial repair prediction model and the first training label as the first loss term, and the difference between the result predicted by the initial repair update model and the second training label as the second loss term.

[0243] In some embodiments of the present specification, the repair prediction model and the repair update model are obtained through joint training, which can improve the efficiency of training. At the same time, during the joint training process, the loss function value of the joint training is obtained based on the weighted sum of the first loss term and the second loss term, which can further improve the accuracy of the final prediction results of the repair prediction model and the repair update model obtained by the joint training.

[0244] Step 430: Generate repair update instructions for the remaining target repair pipelines based on the updated repair urgency.

[0245] In some embodiments, the government regulatory management platform can sort the updated maintenance urgency from high to low to obtain a sorting result of the maintenance urgency; and use the sorting result of the maintenance urgency and the corresponding sorting result of the remaining target repair pipelines as the re-determined repair order of the remaining target repair pipelines to generate a repair update instruction for the remaining target repair pipelines.

[0246] When actually repairing the target repair pipeline, multiple target repair pipelines will be repaired at the same time. In addition to affecting the operation of the current target repair pipeline, the repair will also affect the remaining target repair pipelines waiting to be repaired due to the influence of pressure regulation parameters, audio data, traffic information and pedestrian flow information around the target repair pipeline during repair, thereby increasing the possibility of gas accidents occurring in the remaining target repair pipelines waiting to be repaired before maintenance, affecting the maintenance urgency of the remaining target repair pipelines waiting to be repaired.

[0247] By re-evaluating the repair urgency of the remaining target repair pipelines waiting to be repaired based on the pipeline repair equipment information and pipeline data to be repaired obtained in real time during the maintenance process, and then redetermining the pipeline repair sequence in the original manner based on the re-evaluated repair urgency, the rationality of the determined pipeline repair sequence can be further improved, thereby better meeting the gas supply needs of citizen users.

[0248] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0249] It should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, the alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A pipeline repair method based on smart gas, characterized in that: The method is executed by a government supervision and management platform based on a smart gas pipeline repair Internet of Things system, the smart gas pipeline repair Internet of Things system includes a citizen user platform, a government supervision service platform, the government supervision and management platform, a gas company management platform and a gas equipment object platform, and the method includes: Obtain pipeline repair equipment information and pipeline data to be repaired from the gas company management platform; Based on the pipeline repair equipment information and the pipeline data to be repaired, a pipeline repair sequence is determined; the pipeline repair sequence includes a plurality of repair instructions, each of which is executed by at least one target pipeline repair equipment, and each of which includes a target repair pipeline and its corresponding repair parameters; Based on the repair instruction, perform at least one of the following operations: receiving feedback information collected by the citizen user platform through the government supervision service platform; Based on the feedback information, determine the update collection frequency of the pressure regulating equipment and the gas metering device deployed on the target gas pipeline, and send it to the pressure regulating equipment and the gas metering device for execution; Acquire the pressure regulating parameters collected by the pressure regulating device during the repair process and the gas supply parameters collected by the gas metering device during the repair process; Acquire monitoring data collected by monitoring components deployed on the remaining target repair pipelines from the gas company management platform; And based on the pipeline data to be repaired, the pressure regulation parameters during the repair process, the gas supply parameters during the repair process and the monitoring data, a repair update instruction is generated, and the repair update instruction is used to control the update of the pipeline repair sequence.

2. The method according to claim 1, characterized in that The smart gas-based pipeline repair IoT system also includes a government supervision sensor network platform, a government supervision object platform, and a gas company sensor network platform; The government supervision service platform includes a citizen cloud service sub-platform and a government safety supervision service sub-platform, the government supervision management platform includes a government gas management sub-platform and a government safety management sub-platform, the government supervision sensor network platform includes a government gas management sensor network sub-platform and a government safety management sensor network sub-platform, and the government supervision object platform includes the gas company management platform; The citizen user platform is configured to interact with the citizen cloud service sub-platform and the government security supervision service sub-platform for data exchange; The government gas management sub-platform is configured to perform data interaction with the citizen cloud service sub-platform and the government gas management sensor network sub-platform; The government security management sub-platform is configured to perform data interaction with the government supervision service platform and the government security management sensor network sub-platform; The gas company management platform is configured to perform data interaction with the government gas management sensor network sub-platform and the government safety management sensor network sub-platform; The gas company sensor network platform is configured to perform data interaction with the gas equipment object platform.

3. The method according to claim 1, characterized in that The determining of the pipeline repair sequence based on the pipeline repair equipment information and the pipeline data to be repaired comprises: Determining a performance level of the pipeline repair equipment based on the pipeline repair equipment information; Based on the performance level, determining the target pipeline repair equipment; Based on the pipeline data to be repaired, determining the repair urgency of each pipeline to be repaired; Based on the maintenance urgency, determining at least one of the target repair pipelines; And based on the maintenance urgency of the target pipeline repair equipment and the target repair pipeline, the pipeline repair sequence is determined.

4. The method according to claim 1, characterized in that: The generating of the repair update instruction based on the pipeline data to be repaired, the pressure regulating parameters during the repair process, the gas supply parameters during the repair process and the monitoring data includes: Based on the pipeline data to be repaired, determining a pipeline map to be repaired; Based on the pipeline map to be repaired, the pressure regulation parameters during the repair process, the gas supply parameters during the repair process, and the monitoring data, the updated maintenance urgency of the remaining target repair pipelines is determined through a repair update model, wherein the repair update model is a machine learning model; And based on the updated repair urgency, generating a repair update instruction for the remaining target repair pipeline.

5. The method according to claim 1, characterized in that The method further comprises: For the ongoing repair instructions, in response to the presence of pipeline repair equipment that meets the preset conditions, estimating the total repair time of each ongoing repair instruction; Based on the total repair time, determining at least one target repair instruction; and updating the repair parameters of the target repair instruction.

6. A smart gas-based pipeline repair IoT system, characterized in that: Including citizen user platform, government supervision service platform, government supervision management platform, government supervision sensor network platform, government supervision object platform, gas company sensor network platform and gas equipment object platform; The government supervision service platform includes a citizen cloud service sub-platform and a government safety supervision service sub-platform, the government supervision management platform includes a government gas management sub-platform and a government safety management sub-platform, the government supervision sensor network platform includes a government gas management sensor network sub-platform and a government safety management sensor network sub-platform, and the government supervision object platform includes a gas company management platform; The citizen user platform is configured to interact with the citizen cloud service sub-platform and the government security supervision service sub-platform for data exchange; The government gas management sub-platform is configured to perform data interaction with the citizen cloud service sub-platform and the government gas management sensor network sub-platform; The government security management sub-platform is configured to perform data interaction with the government security supervision service sub-platform and the government security management sensor network sub-platform; The gas company management platform is configured to perform data interaction with the government gas management sensor network sub-platform and the government safety management sensor network sub-platform; The gas company sensor network platform is configured to perform data interaction with the gas equipment object platform and the gas company management platform; The government regulatory management platform is configured to execute the smart gas-based pipeline repair method described in claim 1.

7. The system according to claim 6, characterized in that The government supervision management platform is further configured as follows: Determining a performance level of the pipeline repair equipment based on the pipeline repair equipment information; Based on the performance level, determining the target pipeline repair equipment; Based on the pipeline data to be repaired, determining the repair urgency of each pipeline to be repaired; Based on the maintenance urgency, determining at least one of the target repair pipelines; And based on the maintenance urgency of the target pipeline repair equipment and the target repair pipeline, the pipeline repair sequence is determined.

8. The system according to claim 6, characterized in that The government supervision management platform is further configured as follows: Based on the pipeline data to be repaired, construct a pipeline map to be repaired; Based on the pipeline map to be repaired, the pressure regulation parameters during the repair process, the gas supply parameters during the repair process, and the monitoring data, the updated maintenance urgency of the remaining target repair pipelines is determined through a repair update model, where the repair update model is a machine learning model; And based on the updated repair urgency, a repair update instruction for the remaining target repair pipeline is generated.

9. The system according to claim 6, characterized in that The government supervision management platform is also configured to: For the ongoing repair instructions, in response to the presence of pipeline repair equipment that meets the preset conditions, estimating the total repair time of each ongoing repair instruction; Based on the total repair time, determining at least one target repair instruction; and updating the repair parameters of the target repair instruction.

10. A computer-readable storage medium, characterized in that: The storage medium stores computer instructions. When the computer reads the computer instructions in the storage medium, the computer executes the smart gas-based pipeline repair method as described in any one of claims 1 to 4.

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