A smart gas pipe network device energy-saving monitoring method and an internet of things system

Abstract

The application provides a kind of wisdom gas pipe network device energy-saving monitoring method and internet of things system, it is related to gas pipe network operation field, by the gas company management platform of wisdom gas pipe network device energy-saving monitoring internet of things system is executed, it includes: based on the importance of multiple gas pipelines and the device information of multiple groups of monitoring devices, determine monitoring strategy;Based on sensing data and monitoring strategy, determine the target device in multiple groups of monitoring devices, and the energy-saving level and energy-saving control parameters corresponding to the target device;Energy-saving control parameters are sent to the wisdom gas government safety supervision management platform, in response to obtaining confirmation information, control instruction is generated based on energy-saving control parameters to control target device to execute target operation.By determining reasonable monitoring strategy, the data acquisition / transmission process of monitoring device is managed, the data acquisition / transmission process can be better planned, the overall available duration of monitoring device is increased while ensuring timely data acquisition.

Description

Technical Field

[0001] This manual relates to the field of gas pipeline network operation, and in particular to an energy-saving monitoring method and Internet of Things system for intelligent gas pipeline network devices. Background Technology

[0002] To ensure the safe operation of gas pipeline networks, various devices are often installed along the gas pipelines to monitor, collect, and transmit relevant data. These devices rely on battery power for operation. If the operation of these devices is not properly planned, the batteries may run out of power, requiring on-site maintenance and repair, which will disrupt normal data collection.

[0003] Therefore, it is desirable to provide a smart gas pipeline network device energy-saving monitoring method and Internet of Things system to better manage the energy-saving devices in the gas pipeline network. Summary of the Invention

[0004] To achieve rational planning of the operation of smart gas pipeline network devices and timely response to situations where device batteries are depleted, thereby better managing energy conservation in gas pipeline network devices, this invention provides a smart gas pipeline network device energy conservation monitoring method and Internet of Things system.

[0005] The invention includes a method for energy-saving monitoring of smart gas pipeline network devices, executed by the gas company management platform of a smart gas pipeline network device energy-saving monitoring IoT system. The method includes: obtaining the importance levels of multiple gas pipelines from the data center of a smart gas government safety supervision and management platform, and retrieving device information from multiple sets of monitoring devices corresponding to the multiple gas pipelines; determining a monitoring strategy based on the importance levels and the device information; each monitoring device includes a monitoring module and a communication module; and, based at least on the monitoring strategy, determining a target device among the multiple sets of monitoring devices and the corresponding energy-saving level of the target device, and determining energy-saving control parameters based on the energy-saving level; the energy-saving control parameters include the operating parameters of the target device. The system selects at least one of the following: operating mode, energy-saving data acquisition frequency, and data transmission volume; sends the energy-saving control parameters to the smart gas government safety supervision and management platform; in response to receiving confirmation information from the smart gas government safety supervision and management platform, generates a control command based on the energy-saving control parameters; the control command is configured to control the target device to perform at least one of the following operations: based on the operating mode in the energy-saving control parameters, controls the communication module of the target device to turn on or off; controls the target device to acquire data according to the energy-saving data acquisition frequency through the monitoring module; controls the target device to transmit data based on the data transmission volume through the communication module.

[0006] The invention also includes an IoT system for energy-saving monitoring of smart gas pipeline devices, comprising a smart gas government safety supervision and management platform, a smart gas government safety supervision sensor network platform, a smart gas government safety supervision object platform, a gas company sensor network platform, and a smart gas equipment object platform; the smart gas government safety supervision object platform includes a gas company management platform, which is configured to execute the aforementioned smart gas pipeline device energy-saving monitoring method.

[0007] By determining a reasonable monitoring strategy and managing the data acquisition / transmission process of the monitoring device, the data acquisition / transmission process can be better planned, ensuring timely data acquisition while increasing the overall availability of the monitoring device. Attached Figure Description

[0008] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0009] Figure 1 This is a schematic diagram of the platform structure of an intelligent gas pipeline network device energy-saving monitoring Internet of Things system according to some embodiments of this specification;

[0010] Figure 2 This is an exemplary flowchart of an energy-saving monitoring method for a smart gas pipeline network device according to some embodiments of this specification;

[0011] Figure 3 This is a schematic diagram illustrating the determination of the sampling frequency according to some embodiments of this specification;

[0012] Figure 4 This is a schematic diagram of an evaluation model shown according to some embodiments of this specification;

[0013] Figure 5 This is a schematic diagram illustrating the determination of energy-saving control parameters according to some embodiments of this specification.

[0014] Figure Label Explanation: 100-Smart Gas Pipeline Network Energy-Saving Monitoring IoT System; 110-Smart Gas Government Safety Supervision and Management Platform; 111-Government Safety Data Center; 120-Smart Gas Government Safety Supervision Sensor Network Platform; 130-Smart Gas Government Safety Supervision Object Platform; 131-Gas Company Management Platform; 132-Gas Company Data Center; 140-Gas Company Sensor Network Platform; 150-Gas Equipment Object Platform; 411-Time Node Sequence; 412-Importance Level; 413-Fault Information; 414-Device Information; 415-Sensor Data of Monitoring Devices; 416-Data Acquisition Requirements; 420-Evaluation Model; 421-First Sub-Model; 422-Second Sub-Model; 431-Energy Saving Demand Sequence; 432-Time Period of Interest; 511-Device Information of Target Device; 512-Sensor Data of Target Device; 520-Gas Pipeline Network Map; 521-Node; 522-Edge; 530-Determining Model; 540-Energy Saving Control Parameters. Detailed Implementation

[0015] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0016] It should be understood that the terms "system," "device," and / or "module" used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

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

[0018] Figure 1 This is a schematic diagram of the platform structure of an IoT system for energy-saving monitoring of smart gas pipeline devices, as shown in some embodiments of this specification.

[0019] In some embodiments, the smart gas pipeline device energy-saving monitoring Internet of Things system 100 may include a smart gas government safety supervision and management platform 110, a smart gas government safety supervision sensor network platform 120, a smart gas government safety supervision object platform 130, a gas company sensor network platform 140, and a gas equipment object platform 150.

[0020] The Smart Gas Government Safety Supervision and Management Platform 110 refers to a functional platform used by government safety departments to manage gas safety. In some embodiments, the Smart Gas Government Safety Supervision and Management Platform 110 also includes a government safety data center 111. The government safety data center 111 is a database used to store data from the smart gas pipeline network energy-saving monitoring IoT system 100. For example, the government safety data center 111 can store information such as the importance of multiple gas pipelines in the gas pipeline network. In some embodiments, the Smart Gas Government Safety Supervision and Management Platform 110 is implemented based on a processor or server.

[0021] In some embodiments, the smart gas government safety supervision and management platform 110 can interact with the smart gas government safety supervision sensor network platform 120. For example, the smart gas government safety supervision and management platform 110 can receive energy-saving control parameters uploaded by the smart gas government safety supervision sensor network platform 120 and send confirmation information of the energy-saving control parameters to the smart gas government safety supervision sensor network platform 120.

[0022] The Smart Gas Government Safety Supervision Sensor Network Platform 120 is a functional platform for managing government sensor communications. In some embodiments, the Smart Gas Government Safety Supervision Sensor Network Platform 120 can be implemented based on communication equipment or servers, etc. In some embodiments, the Smart Gas Government Safety Supervision Sensor Network Platform 120 can realize the functions of sensing and communication of perception information and control information.

[0023] In some embodiments, the smart gas government safety supervision sensor network platform 120 can interact with the smart gas government safety supervision object platform 130. For example, the smart gas government safety supervision sensor network platform 120 can receive energy-saving control parameters uploaded by the smart gas government safety supervision object platform 130, and send the confirmation information on the energy-saving control parameters issued by the smart gas government safety supervision management platform 110 to the smart gas government safety supervision object platform 130.

[0024] The Smart Gas Government Safety Supervision Platform 130 is a platform used by the government to generate regulatory information and implement control information. In some embodiments, the Smart Gas Government Safety Supervision Platform 130 may include a gas company management platform 131. In some embodiments, the gas company management platform 131 may include a gas company data center 132. In some embodiments, the gas company management platform 131 may be configured as a server or a processor.

[0025] In some embodiments, the gas company management platform 131 can interact with the gas company sensor network platform 140. For example, the gas company management platform can acquire sensor data collected by multiple monitoring devices of the gas equipment object platform 150 based on the gas company sensor network platform 140.

[0026] The gas company sensor network platform 140 is a platform for the comprehensive management of sensor information of the gas company. In some embodiments, the gas company sensor network platform 140 can realize the functions of sensing and communication of perception information and sensing and communication of control information. In some embodiments, the gas company sensor network platform 140 can be configured as at least one of a communication base station, a router, and a wireless WIFI device.

[0027] In some embodiments, the gas company's sensor network platform 140 can be connected to the smart gas government safety supervision object platform 130 and the gas equipment object platform 150.

[0028] In some embodiments of this specification, the information operation in the smart gas pipeline network device energy-saving monitoring IoT system 100 can form a closed loop between various functional platforms, and operate in a coordinated and regular manner under the unified management of the smart gas company management platform, thereby realizing the informatization and intelligence of smart gas pipeline network device energy-saving monitoring.

[0029] Figure 2 This is an exemplary flowchart of an energy-saving monitoring method for a smart gas pipeline network device, as shown in some embodiments of this specification. Figure 2 As shown, the energy-saving monitoring method for intelligent gas pipeline network devices includes the following steps. In some embodiments, the energy-saving monitoring method for intelligent gas pipeline network devices can be executed by the gas company management platform 131.

[0030] Step 210: Obtain the importance of multiple gas pipelines from the data center of the government safety management sub-platform, and call up the device information of multiple sets of monitoring devices corresponding to multiple gas pipelines. Based on the importance and device information, determine the monitoring strategy.

[0031] Importance level is data reflecting how important a gas pipeline is to the safe operation of the gas pipeline network. For example, the more gas users a gas pipeline supplies and the higher their demand for a stable gas supply, the higher the importance level of the gas pipeline.

[0032] In some embodiments, importance can be represented by a numerical value, with a larger value indicating greater importance.

[0033] In some embodiments, the gas company's management platform can obtain information about the importance of gas pipelines from the government's safety management sub-platform.

[0034] In some embodiments, importance may also include the data priority corresponding to the gas pipeline.

[0035] Data priority refers to the priority level of gas data collected by the monitoring device. In some embodiments, data priority can be represented by a numerical value.

[0036] For detailed information on data priority and its acquisition, please refer to this manual. Figure 3 The relevant description in the document.

[0037] The monitoring device is an intelligent monitoring device used to acquire and transmit data related to gas pipelines. In some embodiments, the smart gas equipment object platform can be equipped with multiple sets of monitoring devices.

[0038] In some embodiments, the monitoring device may include a monitoring module and a communication module. The monitoring module is used for sensing or data acquisition and may include, but is not limited to, a flow meter, a pressure sensor, and a temperature sensor. The communication module is used to enable data transmission with other platforms in the smart gas pipeline energy-saving monitoring IoT system or with other objects outside the smart gas pipeline energy-saving monitoring IoT system.

[0039] In some embodiments, the monitoring device can also perform data processing, early warning, and alarm functions. For example, the monitoring device can perform simple statistical analysis on the collected data to determine the highest and lowest values. As another example, the monitoring device can issue an alarm or early warning when the collected data is outside a reasonable range or when the data trend does not conform to normal conditions.

[0040] In some embodiments, the gas company management platform can retrieve device information from a memory for multiple sets of monitoring devices corresponding to multiple gas pipelines.

[0041] Device information is information used to characterize the features or attributes of a monitoring device. For example, device information may include the type of monitoring device, power consumption information, etc.

[0042] The type of monitoring device refers to whether the monitoring device is a flow meter, pressure sensor, temperature sensor, or other device.

[0043] Electricity consumption information is information related to the power consumption and usage status of the monitoring device, such as remaining power and power consumption rate. In some embodiments, electricity consumption information can be obtained by the gas company's management platform through real-time communication with the monitoring device, or by the gas company's management platform through estimation based on the monitoring device's operating time and power consumption.

[0044] A monitoring strategy refers to the strategy employed by a monitoring device when acquiring / transmitting data. For example, a monitoring strategy may include at least a set of non-target devices among multiple monitoring devices, and the acquisition frequency of each non-target device.

[0045] Non-target devices refer to monitoring devices that do not require energy-saving control.

[0046] Data acquisition frequency refers to the number of times a non-target device acquires data per unit of time.

[0047] When managing monitoring devices based on monitoring strategies, non-target devices can acquire / transmit data based on the acquisition frequency.

[0048] In some embodiments, the process of determining a monitoring strategy includes determining which monitoring devices are non-target devices and determining the sampling frequency of the non-target devices.

[0049] In some embodiments, the gas company management platform can determine the monitoring strategy for monitoring devices in the gas pipeline through various means based on the importance of the gas pipeline and device information.

[0050] In some embodiments, the gas company's management platform can identify monitoring devices whose importance level exceeds a certain threshold as non-target devices. The threshold is a critical value used to determine whether a monitoring device is a non-target device, and can be preset based on experience.

[0051] In some embodiments, the gas company's management platform can determine the sampling frequency of non-target devices by querying a frequency reference table based on the type of the non-target device. The frequency reference table includes reference types of monitoring devices and their corresponding reference sampling frequencies, and can be constructed based on prior experience.

[0052] In some embodiments, the gas company management platform can also determine the data priority of multiple gas pipelines within a preset time period based on pipeline information and status information; and determine non-target devices in the multiple gas pipelines and their data collection frequency based on data priority and device information. For more detailed specifications, please refer to this specification. Figure 2 And its related descriptions.

[0053] Step 220: Based at least on the monitoring strategy, determine the target device and the corresponding energy-saving level among multiple sets of monitoring devices, and determine the energy-saving control parameters based on the energy-saving level.

[0054] The target device refers to the monitoring device that requires energy-saving control.

[0055] Energy efficiency rating is data that characterizes the intensity of energy-saving control measures implemented on monitoring devices. The higher the energy efficiency rating, the stronger the energy efficiency control measures implemented on the monitoring devices. For example, the higher the energy efficiency rating, the lower the frequency of data acquisition / transmission by the monitoring device. Taking energy efficiency ratings from Level 1 to Level 10 as an example, when the energy efficiency rating of the monitoring device is Level 10, the gas company's management platform can control the monitoring device to shut down.

[0056] In some embodiments, the gas company management platform can identify target devices among the monitoring devices, at least based on a monitoring strategy. For example, the gas company management platform can identify a set of non-target devices based on the monitoring strategy, and identify the monitoring devices that do not belong to the set of non-target devices as target devices.

[0057] In some embodiments, the energy efficiency rating of the monitoring device can be determined based on device information. For example, the power consumption of the monitoring device can be determined based on the device information, and its importance can also be determined. For instance, the higher the power consumption and the lower the importance of the monitoring device, the higher its energy efficiency rating.

[0058] In some embodiments, the gas company's management platform can also determine temperature thresholds and sensing change characteristics based on sensor data from the target device; and determine the energy-saving level of the target device based on the temperature thresholds and sensing change characteristics. For more detailed specifications, please refer to this specification. Figure 5 The relevant description in the document.

[0059] In some embodiments, the gas company's management platform can determine the energy-saving control parameters of the target device based on its energy-saving level.

[0060] Energy-saving control parameters refer to the parameters used when controlling the energy efficiency of a monitoring device. For example, energy-saving control parameters include, but are not limited to, at least one of the following: time point, operating mode of the monitoring device, energy-saving data acquisition frequency, and data transmission volume.

[0061] Time nodes are key points in time related to the implementation of energy-saving control. For example, time nodes may include the time when energy-saving control begins, the time when energy-saving control ends, and the time when monitoring devices start / stop different operating modes during the energy-saving control process.

[0062] The operating modes of the monitoring device can include off, low power mode, and active mode.

[0063] Low-power mode means that only the monitoring module is enabled, while the communication module is disabled. Through a dynamic power management module, the communication module is activated when an event of interest occurs, and the sensor data collected during the communication module's shutdown period is transmitted. The event of interest refers to anomalies in the gas pipeline monitoring data, such as any one of temperature, humidity, or pressure exceeding the safe range. The safe range can be determined based on prior experience.

[0064] Active mode means that both the monitoring module and the communication module are turned on, and sensor data is continuously collected at an energy-saving collection frequency, and the collected sensor data is uploaded at a certain transmission frequency.

[0065] Energy-saving data acquisition frequency refers to the number of times the target device acquires data per unit of time.

[0066] Data transmission volume refers to the amount of data transmitted by the monitoring device in a single data transmission, which can be expressed in bytes.

[0067] In some embodiments, the gas company's management platform can determine the energy-saving control parameters of the monitoring device by querying a reference control parameter table, based on the device's energy-saving classification. The reference control table can include the correspondence between reference energy-saving classifications and reference control parameters, and can be constructed based on prior experience.

[0068] Step 230: Send the energy-saving control parameters to the smart gas government safety supervision and management platform. In response to receiving confirmation information from the smart gas government safety supervision and management platform, generate control commands based on the energy-saving control parameters.

[0069] In some cases, controlling the data acquisition / transmission process of monitoring devices based on energy-saving control parameters can affect the efficiency of data acquisition / transmission. In such situations, to avoid impacting the safe operation of the gas pipeline network, the gas company's management platform can send the energy-saving control parameters to the smart gas government safety supervision and management platform. The smart gas government safety supervision and management platform and its corresponding regulatory users will then determine whether the energy-saving control parameters are available. If the energy-saving control parameters are available, the smart gas government safety supervision and management platform can send a confirmation message to the gas company's management platform.

[0070] In some embodiments, in response to receiving confirmation information from the smart gas government safety supervision and management platform, the gas company management platform can generate control instructions based on energy-saving control parameters. The control instructions may include the energy-saving control parameters and the target device that needs to be controlled according to the energy-saving control parameters.

[0071] Step 240: Control the target device to perform the target operation based on the control command.

[0072] In some embodiments, the control command is configured to control the target device to perform a target operation.

[0073] A target operation is an operation related to the operation of a target device. In some embodiments, a target operation includes at least one of adjusting an operating mode, acquiring data, and transmitting data.

[0074] In some embodiments, the gas company's management platform can control the communication module of the target device to be turned on or off based on the operating mode in the energy-saving control parameters. When the communication module of the target device is turned on, the gas company's management platform can control the target device to transmit data through the communication module based on the data transmission volume.

[0075] In some embodiments, the gas company's management platform can control the target device and obtain sensor data by collecting data at an energy-saving collection frequency through a monitoring module.

[0076] When the gas pipeline monitoring device is powered by an independent power source (such as a battery), if it is not managed properly, the power may run out and data collection may fail. In this case, staff will need to be arranged for maintenance, which will affect the timeliness of data acquisition and increase the workload.

[0077] In some embodiments of this specification, by determining a reasonable monitoring strategy and managing the data acquisition / transmission process of the monitoring device, the data acquisition / transmission process can be better planned, ensuring timely data acquisition while increasing the overall availability of the monitoring device.

[0078] Figure 3 This is a schematic diagram illustrating the determination of the sampling frequency according to some embodiments of this specification. For example... Figure 3 As shown, the process of determining the sampling frequency may include the following. In some embodiments, the process of determining the sampling frequency may be performed by the gas company's management platform.

[0079] Step 310: Based on the pipeline information and status information of multiple gas pipelines, determine the data priority of the multiple gas pipelines within a preset time period.

[0080] Pipeline information refers to information related to the transmission of gas through gas pipelines. This includes, for example, the medium being transmitted, the set transmission temperature, and the set transmission pressure. The medium being transmitted can include the components of the gas being transmitted, such as methane, hydrogen, carbon monoxide, and liquefied petroleum gas.

[0081] In some embodiments, the gas company's management platform can obtain pipeline information for multiple gas pipelines from the gas company's data center.

[0082] Status information refers to information about the status of gas transported by gas pipelines. In some embodiments, status information may include peak periods, off-peak periods, etc.

[0083] In some embodiments, the gas company's management platform can obtain gas transport volume data for multiple gas pipelines at different times from the gas company's data center, and divide the gas transport volume into peak and off-peak periods based on the volume. For example, the gas company's management platform can calculate the average gas transport volume, designating periods with gas transport volumes above the average as peak periods and periods with volumes below the average as off-peak periods.

[0084] A preset time period refers to the period during which a monitoring strategy needs to be determined. In some embodiments, the preset time period can be determined in various ways. For example, the preset time period can be a time period pre-set by technicians (such as the period from 01:00 to 04:00 every day). Another example is that the preset time period can also be a time period obtained by dividing a 24-hour day into segments (such as dividing every three hours starting from 0:00). Yet another example is that the preset time period can also be the time period of interest output by the second sub-model of the evaluation model. For more information on the evaluation model, see [link to relevant documentation]. Figure 4 And related explanations.

[0085] In some embodiments, the gas company management platform can determine the reference priority of different monitoring devices on the gas pipeline by querying a priority table based on the pipeline information of the gas pipeline; and adjust the reference priority by adjusting rules based on the status information to determine the data priority of different monitoring devices.

[0086] The priority table includes the data priorities of monitoring devices corresponding to different pipeline information. For example, it includes the data priorities of temperature sensors, pressure sensors, and flow meters for pipeline information where the medium is hydrogen, the temperature is normal, and the pressure is high. In some embodiments, the priority table can be preset by technicians based on experience.

[0087] Adjustment rules refer to rules for adjusting the data priority of various gas data. In some embodiments, adjustment rules may include: when the status information of a preset time period is a peak period, increasing the reference priority to obtain the data priority; when the status information of a preset time period is a low period, decreasing the reference priority to obtain the data priority. The methods of increasing or decreasing may include increasing or decreasing by a certain level (e.g., increasing by 1 level or decreasing by 1 level), amplifying or reducing by a certain factor (e.g., amplifying to 1.2 times or reducing to 0.8 times), etc.

[0088] Step 320: Based on data priority and device information, determine the non-target devices in the multiple monitoring devices and the acquisition frequency of the non-target devices.

[0089] Non-target devices refer to monitoring devices that do not require energy-saving control.

[0090] In some embodiments, for monitoring devices on different gas pipelines, the estimated acquisition frequency of the monitoring devices is determined according to the data priority and power consumption rate of the monitoring devices; monitoring devices with an estimated acquisition frequency greater than a preset frequency threshold are designated as non-target devices. The preset frequency threshold can be set by technicians based on prior experience; the estimated acquisition frequency can be determined using the following formula (1):

[0091] (1)

[0092] Where F refers to the estimated acquisition frequency. Refers to the speed of electricity consumption. Data priority is defined as k, where k is a conversion coefficient (k > 0). Power consumption rate is the amount of electricity consumed by the data acquisition device per unit time. In some embodiments, power consumption rate can be calculated based on the changes in the battery level of the data acquisition device over a historical period.

[0093] It is understandable that the faster the power consumption rate and the lower the data priority, the more energy needs to be saved, i.e., the lower the estimated collection frequency.

[0094] In some embodiments, the gas company's management platform can use a standard sampling frequency as the sampling frequency for non-target devices. The standard sampling frequency is the sampling frequency that meets monitoring requirements without considering power consumption. In some embodiments, the standard sampling frequency can be set based on historical experience.

[0095] In some embodiments, the gas company management platform can send the collection frequency of non-target devices to the corresponding non-target devices through the smart gas sensor network platform, so as to control the non-target devices to collect data within a preset time period according to the collection frequency.

[0096] In some embodiments of this specification, data priority is determined by pipeline information and status information, and used to identify non-target devices that do not require energy saving and their acquisition frequency. This can ensure the sufficiency of collected data while saving energy, thereby ensuring the normal operation of the gas pipeline.

[0097] In some embodiments, the gas company management platform can also determine the estimated power consumption rate and estimated remaining power of the monitoring device at at least one time point in a preset period based on the historical power consumption information of the monitoring device; in response to the existence of a warning time point where the estimated remaining power is not higher than the warning power, generate warning information based on the warning time point and send it to the associated user terminal; in response to the estimated remaining power of a non-target device not higher than the warning power, adjust the collection frequency based on preset rules, and control the non-target device to collect data based on the adjusted collection frequency.

[0098] Electricity usage information refers to the electricity consumption information of the monitoring device. For example, the electricity consumed each time the monitoring device collects electricity data, and the remaining electricity.

[0099] Estimated power consumption rate refers to the estimated rate at which the monitoring device will consume electricity in the future. Estimated remaining power refers to the estimated remaining power of the monitoring device at a future time.

[0100] In some embodiments, the gas company's management platform can perform time series analysis on historical electricity consumption information arranged in chronological order to determine the estimated electricity consumption rate and the estimated remaining electricity.

[0101] Warning battery level refers to the battery level threshold that indicates the battery is about to run out.

[0102] In some embodiments, the warning power level can be obtained in a variety of ways. For example, the warning power level can be preset by technicians based on historical experience.

[0103] In some embodiments, the warning power consumption is related to at least one of the historical energy-saving control parameters of the monitoring device and the sensor change characteristics.

[0104] Historical energy-saving control parameters refer to the energy-saving control parameters that the monitoring device has executed during historical periods. For more information on energy-saving control parameters, please refer to [link to relevant documentation]. Figure 1 And its related descriptions.

[0105] In some embodiments, the gas company's management platform can directly read historical energy-saving control parameters of the monitoring devices from the gas company's data center.

[0106] In some embodiments, the warning energy consumption is positively correlated with the frequency of change of operating modes in historical energy-saving control parameters. For example, the gas company's management platform can adjust the warning energy consumption based on the frequency of change of operating modes; the higher the frequency of change, the higher the warning energy consumption. The frequency of change of operating modes refers to the number of times the operating mode switches per unit of time.

[0107] In some embodiments, the gas company's management platform can statistically analyze historical energy-saving control parameters of the monitoring device to determine the frequency of changes in the operating mode. It is understood that the higher the frequency of changes in the operating mode, the more inconsistent the electricity consumption rate, and the less accurate the prediction of remaining electricity. Therefore, it is necessary to increase the warning power level to prevent the power from running out.

[0108] In some embodiments, the warning power consumption is positively correlated with the sensor change characteristics. It can be understood that the smaller the sensor change characteristics, the smaller the data changes monitored by the monitoring device, and the more stable the power consumption rate, thus allowing for a more appropriate reduction in the warning power consumption. For further explanation regarding sensor change characteristics, please refer to [link to relevant documentation]. Figure 5 And its related descriptions.

[0109] In some embodiments, when the frequency of being in the active mode in the historical energy-saving control parameter's working mode is greater than the mode threshold, the gas company's management platform can adjust the warning power consumption based solely on the sensor change characteristics, without considering the impact of changes in historical energy-saving control parameters on the warning power consumption.

[0110] In some embodiments of this specification, adjusting the warning power consumption by using historical energy-saving control parameters and sensor change characteristics can reduce the impact of errors in estimating power consumption rate and estimated remaining power on the monitoring device, thereby preventing the power from being depleted prematurely.

[0111] The warning time point refers to the point in time when an alert is needed regarding the battery level. In some embodiments, the warning time point may include the point in time when the estimated remaining battery level is no higher than the warning battery level.

[0112] Warning information refers to information related to providing early warnings about battery status. In some embodiments, warning information may include the estimated remaining battery power of the monitoring device requiring the warning and the warning time.

[0113] In some embodiments, when there is an early warning time, the gas company's management platform can send the estimated remaining power and the early warning time to the user's terminal to remind maintenance personnel or managers to replace the battery of the monitoring device, etc.

[0114] A preset rule refers to a rule for adjusting the operating frequency. In some embodiments, the preset rule may be to determine the adjustment range of the operating frequency by estimating the percentage difference between the remaining battery power and a battery threshold.

[0115] In some embodiments, the gas company management platform can send the adjusted acquisition frequency to the corresponding non-target device in the gas equipment object platform to replace its original acquisition frequency, so that it can acquire data according to the adjusted acquisition frequency.

[0116] In some embodiments of this specification, the warning time point is determined by estimating the remaining power, which allows for timely battery replacement of monitoring devices with insufficient power. At the same time, the acquisition frequency is adjusted for non-target devices with estimated insufficient remaining power to ensure that they maintain a certain data acquisition capability before battery replacement, thereby ensuring effective monitoring of gas pipelines.

[0117] Figure 4 This is a schematic diagram of an evaluation model shown according to some embodiments of this specification.

[0118] In some embodiments, the gas company management platform determines the energy-saving management needs of the gas pipeline in the future period through evaluation model 420; in response to the energy-saving management needs being required, a monitoring strategy is determined based on the importance of the gas pipeline and device information.

[0119] For more information on importance, device details, and monitoring strategies, please refer to [link / reference]. Figure 2 And related explanations; for more information about preset time periods, please see [link / reference]. Figure 3 And related explanations.

[0120] An evaluation model is a model used to determine the energy-saving management needs of gas pipelines in future periods. In some embodiments, the evaluation model is a machine learning model, such as a recurrent neural network (RNN) model or other trained machine learning models.

[0121] The inputs to the evaluation model include a time sequence, the importance of the gas pipeline, fault information, and device information of the monitoring devices corresponding to the gas pipeline. The output includes an energy-saving demand sequence corresponding to the time sequence.

[0122] Energy management requirements refer to the overall energy management needs of monitoring devices in gas pipelines. These requirements include both the need for and the absence of energy management.

[0123] A time node sequence refers to a sequence of multiple time nodes within a future period arranged in chronological order. In some embodiments, the gas company's management platform divides the future period into multiple time nodes according to a second time interval, resulting in a time node sequence. The future period can be set based on historical experience. The second time interval is shorter than the first time interval; for more information on the first time interval, please refer to [link to relevant documentation]. Figure 2 And related explanations.

[0124] In some embodiments, the time node sequence may also include the current time node.

[0125] Fault information refers to information related to faults occurring in gas pipelines. Fault information includes the time of the fault, the monitoring device involved, etc. In some embodiments, the gas company's management platform obtains fault information reported by gas users through their user terminals via the gas company's sensor network platform.

[0126] An energy conservation demand sequence refers to a sequence of energy conservation management needs at multiple time points. Each element in the energy conservation demand sequence corresponds to an energy conservation management need at a specific time point. The elements are arranged in chronological order according to their time points, and the time points of each element correspond to the elements in the time point sequence.

[0127] In some embodiments, the gas company management platform trains an evaluation model based on multiple first training samples with first labels. The platform can input these first training samples into the initial evaluation model, construct a loss function based on the model's output and the first labels, iteratively update the model's parameters using this loss function, and terminate the iteration when the iteration completion condition is met, thus obtaining the trained evaluation model. The iterative update method includes, but is not limited to, gradient descent. The iteration completion condition includes loss function convergence or the number of iterations reaching a threshold.

[0128] The first training sample includes the time sequence of the sample, the importance of the sample gas pipeline, sample fault information, and sample device information. The first training sample can be obtained based on historical data.

[0129] In some embodiments, the gas company management platform determines the energy-saving management requirements of all sample monitoring devices in the sample gas pipeline at each sample time point based on the importance of the sample gas pipeline and sample fault information. For example, if at a certain sample time point all sample monitoring devices have an importance level greater than a threshold and none of the sample monitoring devices have failed at that sample time point, then the energy-saving management requirement for the sample gas pipeline at that sample time point is no energy-saving management required. Otherwise, the energy-saving management requirement for the sample gas pipeline at that sample time point is energy-saving management required. The gas company management platform combines the energy-saving management requirements of the sample gas pipeline at all sample time points to obtain the first label corresponding to the first training sample.

[0130] In some embodiments, such as Figure 4 As shown, the evaluation model 420 includes a first sub-model 421 and a second sub-model 422.

[0131] The inputs of the first sub-model 421 include time node sequence 411, importance of gas pipeline 412, fault information 413, and device information 414 of the monitoring device corresponding to the gas pipeline. The output includes energy-saving demand sequence 431 corresponding to time node sequence 411.

[0132] The inputs of the second sub-model 422 include time node sequence 411, importance of gas pipeline 412, fault information 413, device information 414, sensor data of monitoring device 415, and data acquisition requirements 416. The outputs include energy saving demand sequence 431 and time period of interest 432.

[0133] In some embodiments, the gas company management platform assesses the energy-saving management needs of the gas pipeline based on a first sub-model in response to data priority meeting preset conditions; and assesses the energy-saving management needs of the gas pipeline based on a second sub-model in response to data priority not meeting preset conditions.

[0134] For more information on the sensor data from the monitoring device, please refer to [link / reference]. Figure 2 And related explanations.

[0135] The first sub-model is the same as the evaluation model described above; see above for more details.

[0136] The second sub-model is also used to determine the energy-saving management needs of gas pipelines in the future. Compared with the first sub-model, the second sub-model is more complex.

[0137] Data acquisition requirements refer to the needs of the gas company's management platform for collecting sensor data. For example, data acquisition requirements include the type of sensor data to be collected and the corresponding time period. In some embodiments, data acquisition requirements are system preset values ​​or manually set by administrators.

[0138] The period of interest (POI) refers to the period during which energy-saving management is recommended. POI includes one or more future time points.

[0139] In some embodiments, the gas company management platform trains a second sub-model based on multiple second training samples with second labels. The training process of the second sub-model is similar to that of the first sub-model; see above for more details.

[0140] The second training sample includes the time sequence of the sample, the importance of the sample gas pipeline, sample fault information, sample device information, sensor data of the sample monitoring device, and sample data acquisition requirements. The second training sample can be obtained based on historical data.

[0141] In some embodiments, the gas company's management platform acquires sensor data from the sample monitoring device, including time periods when flow rate data is greater than a preset flow rate threshold, time periods when temperature data is less than a preset temperature threshold, and time periods corresponding to sample data collection requirements. These time periods are combined to obtain labeled time periods, and the first label and the labeled time periods are determined as the second label corresponding to the second training sample. The preset flow rate threshold and preset temperature threshold can be set based on historical experience.

[0142] In some embodiments, in response to data priority meeting preset conditions, the gas company management platform can assess the energy-saving management needs of the gas pipeline based on a first sub-model; in response to the gas pipeline data priority not meeting preset conditions, the gas company management platform can assess the energy-saving management needs of the gas pipeline based on a second sub-model. The preset conditions can be that the gas pipeline data priority is not greater than a preset priority threshold. The preset priority threshold can be a system preset value.

[0143] In some embodiments of this specification, when the data priority of the gas pipeline meets preset conditions, a first sub-model is used to determine energy-saving management needs, which can improve evaluation efficiency and save time. When the data priority of the gas pipeline does not meet preset conditions, a second sub-model is used to determine energy-saving management needs, which not only yields a more accurate sequence of energy-saving needs but also identifies the time periods of interest, thus facilitating better energy-saving management of the gas pipeline.

[0144] In some embodiments, in response to the need for energy-saving management of gas pipelines during a preset period, the gas company's management platform determines a monitoring strategy based on the importance of the gas pipeline and device information. For more detailed specifications, please refer to this specification. Figure 2 Related descriptions.

[0145] Some embodiments in this specification determine the energy-saving management needs of gas pipelines at each time point. By classifying monitoring devices and performing subsequent operations only at the time points where energy-saving management is required, the amount of data processing can be effectively reduced, and computing power and energy consumption can be saved.

[0146] Figure 5 This is a schematic diagram illustrating the determination of energy-saving control parameters according to some embodiments of this specification.

[0147] In some embodiments, the gas company's management platform identifies target devices based on monitoring strategies; it retrieves sensor data collected from the target device from the gas equipment object platform via the gas company's sensor network platform; based on the sensor data of the target device, it determines the minimum temperature and sensor change characteristics; based on the minimum temperature and sensor change characteristics, it determines the energy-saving level of the target device; and based on the energy-saving level, it determines energy-saving control parameters.

[0148] For more information on monitoring strategies, sensor data, energy efficiency ratings, and energy-saving control parameters, please refer to [link / reference]. Figure 2 And related explanations.

[0149] For detailed information on determining target devices based on monitoring strategies, please refer to this instruction manual. Figure 2 The relevant description in the document.

[0150] The temperature threshold is the lowest temperature in the environment where the monitoring device is located.

[0151] In some embodiments, the gas company management platform can determine the minimum temperature data based on the sensor data of the target device and set the minimum temperature data as the temperature threshold.

[0152] Sensor data is data that reflects the characteristics of a gas pipeline. For example, sensor data may include, but is not limited to, at least one of flow rate data, pressure data, and temperature data, which can reflect the gas flow rate, pressure, and temperature in the gas pipeline.

[0153] In some embodiments, the gas company's management platform can retrieve sensor data collected by the target device from the gas equipment object platform through the gas company's sensor network platform.

[0154] Sensing change characteristics refer to features related to changes in the sensing data of the target device. For example, sensing change characteristics include the frequency of temperature changes, the frequency of pressure changes, and the frequency of flow rate changes. In some embodiments, the gas company's management platform calculates the sensing change characteristics based on historical or real-time temperature, pressure, and flow data from the target device.

[0155] In some embodiments, the gas company management platform calculates the energy-saving level of the target device based on the lowest temperature, sensor change characteristics, and acquisition frequency. For example, the energy-saving level is positively correlated with the lowest temperature, temperature change frequency, pressure change frequency, and flow change frequency, and negatively correlated with the acquisition frequency. In some embodiments, the gas company management platform calculates the energy-saving level of the target device using the following formula (2).

[0156] (2)

[0157] in, For the energy efficiency level of the target device, The lowest temperature, The frequency of temperature change The frequency of pressure change. For the frequency of flow change, For the sampling frequency, , , , These are the weighting coefficients. The conversion coefficients corresponding to the sampling frequency. , , , , It can be set based on experience.

[0158] In some embodiments, , Negative correlation is related to the consistency between the target device's historical sensing data and historical status information.

[0159] The consistency between historical sensor data and historical state information reflects the degree of agreement between the two. Higher consistency indicates a better match between the historical sensor data and historical state information, leading to more accurate monitoring strategies based on pressure and flow data. In this case, it is necessary to reduce the weighting of the pressure and flow change frequencies, i.e., reduce... , , , A value of 0 indicates that the effects of pressure change frequency and flow rate change frequency are not considered.

[0160] In some embodiments, the gas company's management platform compares the curves of historical status information with the curves of historical sensor data, and determines the consistency between the historical sensor data and historical status information based on the comparison results. For example, if the historical status information changes at a certain historical time point, the historical sensor data should change synchronously. The gas company's management platform determines the consistency between the historical sensor data and historical status information based on the interval between the historical time points corresponding to the same change in the historical status information and historical sensor data. The shorter the interval, the higher the consistency.

[0161] In some embodiments, such as Figure 5 As shown, the gas company management platform constructs a gas pipeline network map 520 based on the device information 511 and the sensor data 512 of the target device; based on the gas pipeline network map 520, it determines the energy-saving control parameters 540 through the determination model 530.

[0162] For more information about the device, please see [link / details]. Figure 2 And related explanations.

[0163] A gas pipeline network map refers to a graph structure that reflects the sensor data acquisition situation in a gas pipeline network. In some embodiments, a gas pipeline network map includes multiple nodes 521 and multiple edges 522 connecting the nodes.

[0164] Each node in the gas pipeline network map corresponds to a target device.

[0165] In some embodiments, the node features in the gas pipeline network map include device information and sensor data of the target device corresponding to the node.

[0166] In a gas pipeline network map, an edge connecting two nodes indicates that the two nodes are connected by a gas pipeline, and the direction of the edge represents the gas flow direction between the two nodes. In some embodiments, the gas company's management platform determines the gas flow direction based on the connection relationship of the gas pipelines.

[0167] In some embodiments, the edge features in the gas pipeline network map include pipeline information and the importance of the gas pipelines.

[0168] For more information on the importance of gas pipelines, please see [link to relevant information]. Figure 2 And related explanations; for more information on pipelines, please refer to [link / reference]. Figure 3 And related explanations.

[0169] The determined model is the model used to determine energy-saving control parameters. In some embodiments, the determined model is a machine learning model, such as a graph neural network (GNN) model, or other trained machine learning models.

[0170] The input to the model includes a gas pipeline network map, and the output includes energy-saving control parameters corresponding to each node in the gas pipeline network map.

[0171] In some embodiments, the gas company management platform trains a deterministic model based on multiple third training samples with third labels. The training process for the deterministic model is similar to that of the first sub-model; for more details, please refer to [link to documentation]. Figure 4 And related explanations.

[0172] In some embodiments, the gas company management platform determines the energy-saving score of historical target devices based on historical device information at a specific historical time point, and determines the safety score of historical target devices based on historical fault information at that historical time point. The total score of the historical target devices is then calculated through a weighted summation. If the average of the total scores of multiple historical target devices exceeds a preset score threshold, the gas company management platform constructs a sample gas pipeline network map based on the historical device information and historical sensor data at that historical time point, serving as a third training sample. The weights of the weighted summation and the preset score threshold can be set empirically. For more information on fault information, see [link to relevant documentation]. Figure 4 And related explanations.

[0173] In some embodiments, the energy-saving score of the historical target device is negatively correlated with the historical power consumption information in the historical device information, and the safety score of the historical target device is negatively correlated with the number of failures in the historical fault information.

[0174] In some embodiments, the gas company management platform determines the energy-saving control parameters actually used by each node in the sample gas pipeline network map as the third label.

[0175] Some embodiments in this specification, based on gas pipeline network maps, determine energy-saving control parameters through a model, enabling the simultaneous determination of energy-saving control parameters for multiple target devices, thereby achieving unified management of multiple target devices. Using machine learning models to determine energy-saving control parameters can improve the efficiency and accuracy of parameter determination.

[0176] In some embodiments, during the operation of the target device based on energy-saving control parameters, in response to the target device's current remaining power not exceeding the power threshold, the target device adjusts the energy-saving control parameters, the gas company's management platform adjusts the initial flow rate of the target pipeline where the target device is located, and determines the flow rate update value; based on the adjusted flow rate update value, the opening degree of the flow valve in the target pipeline is determined, and the flow valve is controlled to adjust based on the opening degree; in response to the target device's current remaining power exceeding the power threshold, the target pipeline is controlled to deliver gas according to the initial flow rate, and the energy-saving control parameters are re-determined.

[0177] For more information on remaining battery power and battery power thresholds, please see [link to relevant information]. Figure 3 And related explanations.

[0178] In some embodiments, in response to the target device's historical energy-saving control parameters meeting the power upload conditions, the target device uploads the current remaining power to the remote control terminal.

[0179] The battery level upload condition is used to determine whether the target device should upload its current remaining battery level. In some embodiments, the battery level upload condition is that the target device's cumulative operating time exceeds a preset duration threshold or the cumulative data transmission volume exceeds a preset data volume threshold. The preset duration threshold and preset data volume threshold can be set based on historical experience.

[0180] In some embodiments, in response to the target device's current remaining power not exceeding a power threshold, the target device automatically adjusts its energy-saving control parameters, and the gas company's management platform adjusts the initial flow rate of the target pipeline where the target device is located, determining the updated flow rate value. The adjustment of energy-saving control parameters includes, but is not limited to, one or more of the following: selecting lower power consumption operating modes based on priority, reducing the sampling frequency, and reducing data transmission volume.

[0181] The target pipeline refers to the gas pipeline where the target device is located, and the current remaining power is not higher than the power threshold.

[0182] The traffic update value refers to the traffic after adjusting the initial traffic.

[0183] In some embodiments, the flow rate update value is positively correlated with the current remaining power percentage of the target device. The gas company management platform can calculate the flow rate update value using the following formula (3).

[0184] (3)

[0185] in, For traffic update value, For initial traffic, Minimum flow rate This represents the current remaining battery percentage. It can be the system default value.

[0186] In some embodiments, flow control is achieved by changing the opening of a flow valve in the target pipeline. The larger the opening of the flow valve, the greater the flow rate.

[0187] In some embodiments, the gas company's management platform determines the opening degree of the flow valve by querying an opening degree-flow ratio table based on the flow update value.

[0188] The valve opening-flow rate conversion table shows the correspondence between the valve opening and the flow rate. The valve opening-flow rate conversion table can be determined experimentally.

[0189] In some embodiments, if the target device's current remaining power is higher than a power threshold, it indicates that the target device has completed charging or battery replacement. In this case, the gas company's management platform controls the target pipeline to deliver gas according to the initial flow rate and re-determines the energy-saving control parameters by querying a control parameter reference table or by using a determination model. For more information on determining energy-saving control parameters by querying a control parameter reference table, see [link to relevant documentation]. Figure 2 And related explanations.

[0190] In some embodiments described in this specification, when the remaining power of the target device is low, it operates with lower power consumption and reduces the gas flow rate, sacrificing some gas usage efficiency to ensure the stability of the gas supply. Once the target device has finished charging or the battery has been replaced, the flow rate is restored to the initial flow rate and the energy-saving control parameters are redefined, thereby improving gas usage efficiency and effectively achieving energy-saving management.

[0191] Some embodiments in this specification determine the energy-saving level of the target device based on the lowest temperature and sensor change characteristics. This allows for the determination of a more reasonable energy-saving level based on more influencing factors. Energy management based on the energy-saving level can further reduce energy consumption and save costs.

[0192] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, 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 and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0193] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "some embodiments" refers to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that "some embodiments" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0194] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A method for energy-saving monitoring of a smart gas pipeline network device, characterized in that, The gas company's management platform, which is responsible for the energy-saving monitoring of smart gas pipeline network devices via IoT, includes: The importance of multiple gas pipelines is obtained from the data center of the government safety management sub-platform. The importance includes data priority. The device information of multiple monitoring devices corresponding to the multiple gas pipelines is called. The monitoring devices include monitoring modules and communication modules. The energy-saving management needs of the gas pipeline in the future period are determined by an evaluation model, which is a machine learning model. In response to the energy-saving management requirement, an energy-saving management strategy is determined based on the importance level and the device information. The monitoring strategy includes: determining the data priority of multiple gas pipelines within a preset time period based on pipeline information and status information of multiple gas pipelines; determining non-target devices among multiple sets of monitoring devices and the acquisition frequency of the non-target devices based on the data priority and the device information; and controlling the non-target devices to acquire data during the preset time period based on the acquisition frequency. Based at least on the monitoring strategy, target devices and corresponding energy-saving levels of multiple sets of monitoring devices are determined, and energy-saving control parameters are determined based on the energy-saving levels; the energy-saving control parameters include at least one of the target device's operating mode, energy-saving acquisition frequency, and data transmission volume; The energy-saving control parameters are sent to the smart gas government safety supervision and management platform. In response to receiving confirmation information from the smart gas government safety supervision and management platform, a control command is generated based on the energy-saving control parameters.

2. The method as described in claim 1, characterized in that, Also includes: Based on the monitoring strategy, the target device is determined; The gas company’s sensor network platform retrieves the sensor data collected by the target device from the gas equipment object platform, and the temperature threshold and sensor change characteristics are determined based on the sensor data of the target device. Based on the temperature threshold and the sensing change characteristics, the energy-saving level of the target device is determined; Based on the energy-saving level, the energy-saving control parameters are determined.

3. The method as described in claim 2, characterized in that, Also includes: During the operation of the target device based on the energy-saving control parameters, in response to the fact that the current remaining power of the target device is not higher than the power threshold, the energy-saving control parameters are adjusted, the initial flow rate of the target pipeline where the target device is located is adjusted, and the flow rate update value is determined. Based on the updated flow rate value, the opening degree of the flow valve in the target pipeline is determined, and the flow valve is controlled to adjust based on the opening degree. In response to the target device having a current remaining power level higher than the power threshold, the target pipeline is controlled to deliver gas according to the initial flow rate, and the energy-saving control parameters are redefined.

4. A smart gas pipeline network energy-saving monitoring Internet of Things system, characterized in that, This includes a smart gas government safety supervision and management platform, a smart gas government safety supervision sensor network platform, a smart gas government safety supervision object platform, a gas company sensor network platform, and a gas equipment object platform. The intelligent gas government safety supervision platform includes a gas company management platform, which is configured as follows: The importance of multiple gas pipelines is obtained from the data center of the government safety management sub-platform. The importance includes data priority. The device information of multiple monitoring devices corresponding to the multiple gas pipelines is called. The monitoring devices include monitoring modules and communication modules. The energy-saving management needs of the gas pipeline in the future period are determined by an evaluation model, which is a machine learning model. In response to the energy-saving management requirement, an energy-saving management strategy is determined based on the importance level and the device information. The monitoring strategy includes: determining the data priority of multiple gas pipelines within a preset time period based on pipeline information and status information of multiple gas pipelines; determining non-target devices among multiple sets of monitoring devices and the acquisition frequency of the non-target devices based on the data priority and the device information; and controlling the non-target devices to acquire data during the preset time period based on the acquisition frequency. Based at least on the monitoring strategy, target devices and corresponding energy-saving levels of multiple sets of monitoring devices are determined, and energy-saving control parameters are determined based on the energy-saving levels; the energy-saving control parameters include at least one of the target device's operating mode, energy-saving acquisition frequency, and data transmission volume; The energy-saving control parameters are sent to the smart gas government safety supervision and management platform. In response to receiving confirmation information from the smart gas government safety supervision and management platform, a control command is generated based on the energy-saving control parameters.

5. The Internet of Things system as described in claim 4, characterized in that, The gas company management platform is further configured as follows: Based on the monitoring strategy, the target device is determined; The gas company’s sensor network platform retrieves the sensor data collected by the target device from the gas equipment object platform, and the temperature threshold and sensor change characteristics are determined based on the sensor data of the target device. Based on the temperature threshold and the sensing change characteristics, the energy-saving level of the target device is determined; Based on the energy-saving level, the energy-saving control parameters are determined.

6. The Internet of Things system as described in claim 5, characterized in that, The gas company management platform is also configured as follows: During the operation of the target device based on the energy-saving control parameters, in response to the fact that the current remaining power of the target device is not higher than the power threshold, the energy-saving control parameters are adjusted, the initial flow rate of the target pipeline where the target device is located is adjusted, and the flow rate update value is determined. Based on the updated flow rate value, the opening degree of the flow valve in the target pipeline is determined, and the flow valve is controlled to adjust based on the opening degree. In response to the target device having a current remaining power level higher than the power threshold, the target pipeline is controlled to deliver gas according to the initial flow rate, and the energy-saving control parameters are redefined.

Images