Method, system, and device for processing natural gas energy measurement data based on the Internet of Things

Abstract

The present application discloses a method, system, and device for processing natural gas energy measurement data based on the Internet of Things, relating to the technical field of the Internet of Things. The method includes: obtaining natural gas energy measurement data, and obtaining the target natural gas energy measurement data of the target gas-using device according to the natural gas energy measurement data; obtaining the environmental data of the target gas-using device, and generating the current operation data of the target gas-using device according to the environmental data and the target natural gas energy measurement data; determining whether the current operation state of the target gas-using device is normal according to the current operation data. If not, obtaining the fault index data of the target gas-using device, and determining the fault information of the target gas-using device according to the fault index data; sending a corresponding early warning information to the monitoring center according to the device information and the fault information. The present application has the effect of improving the monitoring intensity of gas-using devices.

Description

Technical Field

[0001] This application relates to the technical field of the Internet of Things, and in particular to a method, system, and device for processing natural gas energy metering data based on the Internet of Things. Background Art

[0002] In the energy field, natural gas, as an important clean energy, its metering and management are directly related to the utilization efficiency and economic benefits of natural gas. Traditional natural gas energy metering is based on volume or mass, while natural gas energy metering is to further measure the calorific value of natural gas on the basis of volume or mass measurement. By multiplying the heat per unit volume or unit mass by the corresponding volume or mass, the total energy of natural gas is calculated, and metering is carried out based on the total energy of natural gas. Natural gas energy metering can avoid the calorific value deviation caused by different gas sources, ensure that natural gas from different origins and of different qualities can reflect its true energy value in transactions, and thus maintain the fairness and justice of the market.

[0003] Currently, in the process of using natural gas, the gas-using equipment is usually managed and monitored by manual inspection, but this method has relatively low monitoring intensity, resulting in low safety in the process of using natural gas. Summary of the Invention

[0004] In order to improve the monitoring intensity of gas-using equipment, this application provides a method, system, and device for processing natural gas energy metering data based on the Internet of Things.

[0005] In a first aspect, this application provides a method for processing natural gas energy metering data based on the Internet of Things, adopting the following technical solution:

[0006] A method for processing natural gas energy metering data based on the Internet of Things, for an Internet of Things system, the Internet of Things system includes an energy metering data application layer, an energy metering data transmission layer, and an energy metering data perception layer, the method is executed by the energy metering application layer, and the method includes:

[0007] Obtain natural gas energy metering data, and obtain the target natural gas energy metering data of the target gas-using equipment according to the natural gas energy metering data; the natural gas energy metering data includes flow data, pressure data, temperature data, composition data, calorific value data, and timestamp data of natural gas;

[0008] Obtain the environmental data of the target gas-using equipment, and generate the current operation data of the target gas-using equipment according to the environmental data and the target natural gas energy metering data;

[0009] Determine whether the current operating state of the target gas-using device is normal according to the current operating data. If not, obtain the fault index data of the target gas-using device, and determine the fault information of the target gas-using device according to the fault index data;

[0010] Obtain the device information of the target gas-using device, and send corresponding warning information to the monitoring center according to the device information and the fault information.

[0011] By adopting the above technical solution, first obtain the natural gas energy measurement data, and obtain the target natural gas energy measurement data of the target gas-using device according to the natural gas energy measurement data. The natural gas energy measurement data includes the flow data, pressure data, temperature data, composition data, calorific value data and timestamp data of natural gas. Then obtain the environmental data of the target gas-using device, and generate the current operating data of the target gas-using device according to the environmental data and the target natural gas energy measurement data. Then determine whether the current operating state of the target gas-using device is normal according to the current operating data. If the current operating state of the target gas-using device is abnormal, obtain the fault index data of the target gas-using device, and determine the fault information of the target gas-using device according to the fault index data. Finally, obtain the device information of the target gas-using device, and send corresponding warning information to the monitoring center according to the device information and the fault information; In the above method, the current operating state of the gas-using device is monitored through the natural gas energy measurement data, and a warning is issued when the current operating state of the gas-using device is abnormal, which improves the monitoring and management of the gas-using device, and thus improves the safety during the use of natural gas.

[0012] Optionally, before the step of obtaining the natural gas energy measurement data and obtaining the target natural gas energy measurement data of the target gas-using device according to the natural gas energy measurement data, it further includes:

[0013] For each gas-using device, obtain the sampling frequency index data of the gas-using device. The sampling frequency index data includes the historical fault frequency of the gas-using device and the historical consumption rate of natural gas in each working time period, and determine the sampling frequency of the gas-using device according to the sampling frequency index data;

[0014] Collect the natural gas energy measurement data of the gas-using device according to the sampling frequency.

[0015] By adopting the above technical solutions, in order to improve the accuracy and practicality of natural gas energy measurement data, for each gas-using device, sampling frequency index data of the gas-using device is obtained. The sampling frequency index data includes the historical failure frequency of the gas-using device and the historical consumption rate of natural gas during each working time period, and the sampling frequency of the gas-using device is determined according to the sampling frequency index data. Then, the natural gas energy measurement data of the gas-using device is collected according to the sampling frequency.

[0016] Optionally, the target natural gas energy measurement data includes target flow data, target pressure data, target temperature data, target composition data, target calorific value data, and target timestamp data of natural gas. The environmental data includes environmental temperature data and environmental pressure data. The step of generating the current operation data of the target gas-using device according to the environmental data and the target natural gas energy measurement data includes:

[0017] Determine the target gas consumption data, gas consumption volatility, and start-up frequency of the target gas-using device according to the target flow data and the target timestamp data;

[0018] Obtain the standard energy conversion efficiency of the target gas-using device, and determine the target energy conversion efficiency of the target gas-using device according to the standard energy conversion efficiency, the target pressure data, the target temperature data, the environmental pressure data, the environmental temperature data, and the target composition data;

[0019] Determine the target energy conversion value of the target gas-using device according to the target energy conversion efficiency, the target gas consumption data, and the target calorific value data;

[0020] Determine the working power of the target gas-using device according to the target energy conversion value and the timestamp data;

[0021] Generate the current operation data of the target gas-using device according to the gas consumption volatility, the start-up frequency, and the working power.

[0022] By adopting the above technical solution, in order to obtain the current operation data of the target gas-using equipment, the target gas consumption data, gas consumption volatility, and start-up frequency of the target gas-using equipment are determined according to the target flow data and target timestamp data. Then, the standard energy conversion efficiency of the target gas-using equipment is obtained, and the target energy conversion efficiency of the target gas-using equipment is determined according to the standard energy conversion efficiency, target pressure data, target temperature data, ambient pressure data, ambient temperature data, and target component data. Next, the target energy conversion value of the target gas-using equipment is determined according to the target energy conversion efficiency, target gas consumption data, and target calorific value data. Then, the working power of the target gas-using equipment is determined according to the target energy conversion value and timestamp data. Finally, the current operation data of the target gas-using equipment is generated according to the gas consumption volatility, start-up frequency, and working power.

[0023] Optionally, the step of determining whether the current operation state of the target gas-using equipment is normal according to the current operation data includes:

[0024] Perform normalization processing on the gas consumption volatility, start-up frequency, and working power to obtain corresponding first normalized value, second normalized value, and third normalized value;

[0025] Obtain the first weight, second weight, and third weight corresponding to the first normalized value, second normalized value, and third normalized value respectively, and calculate the state evaluation value of the target gas-using equipment according to the first normalized value, second normalized value, third normalized value, first weight, second weight, and third weight;

[0026] Judge whether the state evaluation value is within a preset range. If so, it indicates that the current operation state of the target gas-using equipment is normal; if not, it indicates that the current operation state of the target gas-using equipment is abnormal.

[0027] By adopting the above technical solution, in order to determine whether the current operation state of the target gas-using equipment is normal, perform normalization processing on the gas consumption volatility, start-up frequency, and working power to obtain corresponding first normalized value, second normalized value, and third normalized value. Then, obtain the first weight, second weight, and third weight corresponding to the first normalized value, second normalized value, and third normalized value respectively, and calculate the state evaluation value of the target gas-using equipment according to the first normalized value, second normalized value, third normalized value, first weight, second weight, and third weight. Furthermore, judge whether the state evaluation value is greater than within a preset range. If the state evaluation value is within the preset range, it indicates that the current operation state of the target gas-using equipment is normal; if the state evaluation value is not within the preset range, it indicates that the current operation state of the target gas-using equipment is abnormal.

[0028] Optionally, the step of determining the fault information of the target gas-using equipment according to the fault index data includes:

[0029] Obtain historical fault index data and divide the historical fault index data into k data sets;

[0030] Through k-fold cross-validation, train and validate a pre-constructed fault index model according to the data sets to obtain a trained and validated fault index model;

[0031] Input the fault index data into the trained and validated fault index model to obtain corresponding fault information.

[0032] By adopting the above technical solution, in order to determine the fault information of the target gas-using equipment, first obtain historical fault index data, divide the historical fault index data into k data sets, then through k-fold cross-validation, train and validate a pre-constructed fault index model according to the data sets to obtain a trained and validated fault index model, and finally input the fault index data into the trained and validated fault index model to obtain corresponding fault information.

[0033] Optionally, after the step of determining whether the current operating state of the target gas-using equipment is normal according to the current operating data, it further includes:

[0034] If so, obtain the performance index data of the target gas-using equipment, where the performance index data includes historical target gas consumption data, historical gas consumption volatility, historical start frequency, and historical working power, and determine the performance evaluation value of the target gas-using equipment according to the performance index data;

[0035] Match the performance evaluation value in a preset table to obtain the fault probability of the target gas-using equipment; the preset table includes the performance evaluation values and corresponding fault probabilities of each gas-using equipment, and the preset table is used to represent the mapping relationship between the performance evaluation value and the fault probability;

[0036] Judge whether the fault probability is higher than a preset threshold. If so, mark the target gas-using equipment as a to-be-inspected state. If not, mark the target gas-using equipment as a normal state.

[0037] By adopting the above technical solution, when it is determined that the current operating state of the target gas-using equipment is normal according to the current operating data, obtain the performance index data of the target gas-using equipment, determine the performance evaluation value of the target gas-using equipment according to the performance index data, then match the performance evaluation value in the preset table to obtain the fault probability of the target gas-using equipment, and then judge whether the fault probability is higher than the preset threshold. If the fault probability is higher than the preset threshold, mark the target gas-using equipment as a to-be-inspected state. If the fault probability is not higher than the preset threshold, mark the target gas-using equipment as a normal state.

[0038] Optionally, the device information includes the device type and the device location, and the fault information includes the fault type. The step of sending corresponding warning information to the monitoring center according to the device information and the fault information includes:

[0039] Determine the corresponding warning type according to the fault type;

[0040] Generate corresponding warning information according to the device type, the device location and the warning type, and send the warning information to the monitoring center.

[0041] By adopting the above technical solution, first determine the corresponding warning type according to the fault type, then generate corresponding warning information according to the device type, the device location and the warning type, and send the warning information to the monitoring center.

[0042] In a second aspect, the present application also provides a natural gas energy metering data processing system based on the Internet of Things, adopting the following technical solution:

[0043] A natural gas energy metering data processing system based on the Internet of Things, the system includes an energy metering data application layer, an energy metering data transmission layer and an energy metering data perception layer, and the energy metering application layer is configured with:

[0044] A target natural gas energy metering data generation module, configured to obtain natural gas energy metering data, and obtain the target natural gas energy metering data of the target gas-using equipment according to the natural gas energy metering data; the natural gas energy metering data includes flow data, pressure data, temperature data, composition data, calorific value data and timestamp data of natural gas;

[0045] A current operation data generation module, configured to obtain the environmental data of the target gas-using equipment, and generate the current operation data of the target gas-using equipment according to the environmental data and the target natural gas energy metering data;

[0046] A fault information generation module, configured to determine whether the current operation state of the target gas-using equipment is normal according to the current operation data, if not, obtain the fault index data of the target gas-using equipment, and determine the fault information of the target gas-using equipment according to the fault index data;

[0047] A warning information generation module, configured to obtain the device information of the target gas-using equipment, and send corresponding warning information to the monitoring center according to the device information and the fault information.

[0048] Optionally, the energy metering application layer is further configured with:

[0049] A sampling frequency calculation module, which is used to obtain, for each gas-using device, sampling frequency index data of the gas-using device, where the sampling frequency index data includes the historical failure frequency of the gas-using device and the historical consumption rate of natural gas during each working time period, and determine the sampling frequency of the gas-using device according to the sampling frequency index data;

[0050] The energy metering data perception layer is configured with:

[0051] A data acquisition module, which is used to acquire the natural gas energy metering data of the gas-using device according to the sampling frequency.

[0052] In a third aspect, the present application also provides a computer device, adopting the following technical solution:

[0053] A computer device includes a memory and a processor. A computer program that can run on the processor is stored on the memory. When the processor executes the computer program, the method described in the first aspect is implemented.

[0054] In summary, the present application at least includes the following beneficial technical effects: First, obtain the natural gas energy metering data, and obtain the target natural gas energy metering data of the target gas-using device according to the natural gas energy metering data. The natural gas energy metering data includes the flow data, pressure data, temperature data, composition data, calorific value data, and timestamp data of natural gas. Then, obtain the environmental data of the target gas-using device, and generate the current operation data of the target gas-using device according to the environmental data and the target natural gas energy metering data. Then, determine whether the current operation state of the target gas-using device is normal according to the current operation data. If the current operation state of the target gas-using device is abnormal, obtain the fault index data of the target gas-using device, and determine the fault information of the target gas-using device according to the fault index data. Finally, obtain the device information of the target gas-using device, and send a corresponding warning message to the monitoring center according to the device information and the fault information; In the above manner, the current operation state of the gas-using device is monitored through the natural gas energy metering data, and a warning is issued when the current operation state of the gas-using device is abnormal, improving the monitoring and management intensity of the gas-using device, and thus improving the safety during the use of natural gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 is the overall process schematic diagram of the embodiment of the present application.

[0056] Figure 2 is the structural schematic diagram of the system of the embodiment of the present application.

[0057] Figure 3 is the overall structural schematic diagram of the application scenario of the system of the embodiment of the present application.

[0058] Figure 4 It is a specific structural schematic diagram of the application scenario of the system according to an embodiment of the present application.

[0059] Figure 5 It is a block diagram of the structure of the computer device of the present application. Specific implementation manners

[0060] In order to make the objectives, technical solutions and advantages of the present application clearer, the following further describes the present application in detail with reference to the Figures 1-5 accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0061] An embodiment of the present application discloses a method for processing natural gas energy measurement data based on the Internet of Things.

[0062] Referring to Figure 1 , a method for processing natural gas energy measurement data based on the Internet of Things, which is used for an Internet of Things system. The Internet of Things system includes an energy measurement data application layer, an energy measurement data transmission layer, and an energy measurement data perception layer. The method is executed by the energy measurement application layer. The method includes:

[0063] Step S11: Obtain natural gas energy measurement data, and obtain the target natural gas energy measurement data of the target gas-using device according to the natural gas energy measurement data.

[0064] Among them, the natural gas energy measurement data includes flow data, pressure data, temperature data, composition data, calorific value data, and timestamp data of natural gas.

[0065] It should be noted that the energy measurement data perception layer collects natural gas energy measurement data through high-precision sensors and in combination with Internet of Things technology to ensure the accuracy and real-time nature of the natural gas energy measurement data.

[0066] Step S12: Obtain the environmental data of the target gas-using device, and generate the current operation data of the target gas-using device according to the environmental data and the target natural gas energy measurement data.

[0067] Step S13: Determine whether the current operation state of the target gas-using device is normal according to the current operation data. If not, obtain the fault index data of the target gas-using device, and determine the fault information of the target gas-using device according to the fault index data.

[0068] Specifically, determine whether the current operation state of the target gas-using device is normal according to the current operation data. If the current operation state of the target gas-using device is abnormal, obtain the fault index data of the target gas-using device, and determine the fault information of the target gas-using device according to the fault index data. If the current operation state of the target gas-using device is normal, execute step S61.

[0069] Step S14: Obtain the device information of the target gas-using device, and send corresponding warning information to the monitoring center according to the device information and the fault information.

[0070] In the above embodiment, first obtain the natural gas energy measurement data, and obtain the target natural gas energy measurement data of the target gas-using device according to the natural gas energy measurement data. The natural gas energy measurement data includes the flow rate data, pressure data, temperature data, composition data, calorific value data and timestamp data of natural gas. Then obtain the environmental data of the target gas-using device, and generate the current operation data of the target gas-using device according to the environmental data and the target natural gas energy measurement data. Then determine whether the current operation state of the target gas-using device is normal according to the current operation data. If the current operation state of the target gas-using device is abnormal, obtain the fault index data of the target gas-using device, and determine the fault information of the target gas-using device according to the fault index data. Finally, obtain the device information of the target gas-using device, and send corresponding warning information to the monitoring center according to the device information and the fault information. In the above method, the current operation state of the gas-using device is monitored through the natural gas energy measurement data, and a warning is given when the current operation state of the gas-using device is abnormal, which improves the monitoring and management of the gas-using device, and thus improves the safety in the process of using natural gas.

[0071] As a further embodiment of the processing method, before the step of obtaining the natural gas energy measurement data and obtaining the target natural gas energy measurement data of the target gas-using device according to the natural gas energy measurement data, it further includes:

[0072] Step S21: For each gas-using device, obtain the sampling frequency index data of the gas-using device, and determine the sampling frequency of the gas-using device according to the sampling frequency index data.

[0073] Among them, the sampling frequency index data includes the historical fault frequency of the gas-using device and the historical consumption rate of natural gas in each working time period.

[0074] Step S22: Collect the natural gas energy measurement data of the gas-using device according to the sampling frequency.

[0075] In the above embodiment, in order to improve the accuracy and practicability of the natural gas energy measurement data, for each gas-using device, obtain the sampling frequency index data of the gas-using device. The sampling frequency index data includes the historical fault frequency of the gas-using device and the historical consumption rate of natural gas in each working time period, and determine the sampling frequency of the gas-using device according to the sampling frequency index data. Then collect the natural gas energy measurement data of the gas-using device according to the sampling frequency.

[0076] As a further implementation of the processing method, the target natural gas energy measurement data includes target flow data, target pressure data, target temperature data, target composition data, target calorific value data, and target timestamp data of natural gas, and the environmental data includes environmental temperature data and environmental pressure data. The steps of generating the current operation data of the target gas-using equipment according to the environmental data and the target natural gas energy measurement data include:

[0077] Step S31: Determine the target gas consumption data, gas consumption volatility, and startup frequency of the target gas-using equipment according to the target flow data and the target timestamp data.

[0078] Step S32: Obtain the standard energy conversion efficiency of the target gas-using equipment, and determine the target energy conversion efficiency of the target gas-using equipment according to the standard energy conversion efficiency, target pressure data, target temperature data, environmental pressure data, environmental temperature data, and target composition data.

[0079] Step S33: Determine the target energy conversion value of the target gas-using equipment according to the target energy conversion efficiency, target gas consumption data, and target calorific value data.

[0080] Step S34: Determine the working power of the target gas-using equipment according to the target energy conversion value and the timestamp data.

[0081] Step S35: Generate the current operation data of the target gas-using equipment according to the gas consumption volatility, startup frequency, and working power.

[0082] In the above implementation, in order to obtain the current operation data of the target gas-using equipment, the target gas consumption data, gas consumption volatility, and startup frequency of the target gas-using equipment are determined according to the target flow data and the target timestamp data, then the standard energy conversion efficiency of the target gas-using equipment is obtained, and the target energy conversion efficiency of the target gas-using equipment is determined according to the standard energy conversion efficiency, target pressure data, target temperature data, environmental pressure data, environmental temperature data, and target composition data. Then, the target energy conversion value of the target gas-using equipment is determined according to the target energy conversion efficiency, target gas consumption data, and target calorific value data. Then, the working power of the target gas-using equipment is determined according to the target energy conversion value and the timestamp data. Finally, the current operation data of the target gas-using equipment is generated according to the gas consumption volatility, startup frequency, and working power.

[0083] As a further implementation of the processing method, the steps of determining whether the current operation state of the target gas-using equipment is normal according to the current operation data include:

[0084] Step S41: Perform normalization processing on the gas consumption volatility, startup frequency, and working power to obtain corresponding first normalized value, second normalized value, and third normalized value;

[0085] Step S42: Obtain the first weight, second weight, and third weight corresponding to the first normalization value, second normalization value, and third normalization value respectively, and calculate the state evaluation value of the target gas-using device according to the first normalization value, second normalization value, third normalization value, first weight, second weight, and third weight.

[0086] Step S43: Determine whether the state evaluation value is within the preset range. If so, it indicates that the current operating state of the target gas-using device is normal; if not, it indicates that the current operating state of the target gas-using device is abnormal.

[0087] Specifically, determine whether the state evaluation value is within the preset range. If the state evaluation value is within the preset range, it indicates that the current operating state of the target gas-using device is normal; if the state evaluation value is not within the preset range, it indicates that the current operating state of the target gas-using device is abnormal.

[0088] In the above embodiment, in order to determine whether the current operating state of the target gas-using device is normal, the gas consumption volatility, start-up frequency, and working power are normalized to obtain the corresponding first normalization value, second normalization value, and third normalization value. Then, obtain the first weight, second weight, and third weight corresponding to the first normalization value, second normalization value, and third normalization value respectively, and calculate the state evaluation value of the target gas-using device according to the first normalization value, second normalization value, third normalization value, first weight, second weight, and third weight. Furthermore, determine whether the state evaluation value is greater than the preset range. If the state evaluation value is within the preset range, it indicates that the current operating state of the target gas-using device is normal; if the state evaluation value is not within the preset range, it indicates that the current operating state of the target gas-using device is abnormal.

[0089] As a further embodiment of the processing method, the steps of determining the fault information of the target gas-using device according to the fault index data include:

[0090] Step S51: Obtain the historical fault index data and divide the historical fault index data into k data sets.

[0091] Step S52: Through the method of k-fold cross-validation, train and validate the pre-constructed fault index model according to the data sets to obtain the trained and validated fault index model.

[0092] Step S53: Input the fault index data into the trained and validated fault index model to obtain the corresponding fault information.

[0093] In the above embodiment, in order to determine the fault information of the target gas-using equipment, historical fault index data is first obtained and divided into k data sets, and then through k-fold cross-validation, the pre-constructed fault index model is trained and verified according to the data sets to obtain a trained and verified fault index model. Finally, the fault index data is input into the trained and verified fault index model to obtain the corresponding fault information.

[0094] As a further embodiment of the processing method, after the step of determining whether the current operating state of the target gas-using equipment is normal according to the current operating data, it further includes:

[0095] Step S61, if so, obtain the performance index data of the target gas-using equipment and determine the performance evaluation value of the target gas-using equipment according to the performance index data.

[0096] Among them, the performance index data includes historical target gas consumption data, historical gas consumption volatility, historical start frequency, and historical working power.

[0097] Specifically, if it is determined according to the current operating data that the current operating state of the target gas-using equipment is normal, obtain the performance index data of the target gas-using equipment. The performance index data includes historical target gas consumption data, historical gas consumption volatility, historical start frequency, and historical working power, and determine the performance evaluation value of the target gas-using equipment according to the performance index data.

[0098] Step S62, match the performance evaluation value in the preset table to obtain the fault probability of the target gas-using equipment.

[0099] Among them, the preset table includes the performance evaluation values and corresponding fault probabilities of each gas-using equipment, and the preset table is used to represent the mapping relationship between the performance evaluation value and the fault probability.

[0100] Step S63, determine whether the fault probability is higher than the preset threshold. If so, mark the target gas-using equipment as a state to be inspected. If not, mark the target gas-using equipment as a normal state.

[0101] Specifically, determine whether the fault probability is higher than the preset threshold. If the fault probability is higher than the preset threshold, mark the target gas-using equipment as a state to be inspected. If the fault probability is not higher than the preset threshold, mark the target gas-using equipment as a normal state.

[0102] It can be understood that when the target gas-using equipment is marked as a state to be inspected, the maintenance personnel will inspect and maintain the target gas-using equipment at an appropriate time.

[0103] In the above embodiment, when it is determined that the current operating state of the target gas-using device is normal according to the current operating data, the performance index data of the target gas-using device is obtained, and the performance evaluation value of the target gas-using device is determined according to the performance index data. Then, the performance evaluation value is matched in the preset table to obtain the failure probability of the target gas-using device. Then, it is determined whether the failure probability is higher than the preset threshold. If the failure probability is higher than the preset threshold, the target gas-using device is marked as a to-be-inspected state. If the failure probability is not higher than the preset threshold, the target gas-using device is marked as a normal state.

[0104] As a further embodiment of the processing method, the device information includes the device type and the device location, and the fault information includes the fault type. The step of sending the corresponding warning information to the monitoring center according to the device information and the fault information includes:

[0105] Step S61, determining the corresponding warning type according to the fault type.

[0106] Step S62, generating the corresponding warning information according to the device type, the device location, and the warning type, and sending the warning information to the monitoring center.

[0107] In the above embodiment, first determine the corresponding warning type according to the fault type, then generate the corresponding warning information according to the device type, the device location, and the warning type, and send the warning information to the monitoring center.

[0108] The embodiment of the present application also discloses a natural gas energy metering data processing system based on the Internet of Things.

[0109] Reference Figure 2 and Figure 3 , the natural gas energy metering data processing system based on the Internet of Things, the system includes an energy metering data application layer, an energy metering data transmission layer, and an energy metering data perception layer. The energy metering application layer is configured with:

[0110] A target natural gas energy metering data generation module, configured to obtain natural gas energy metering data, and obtain the target natural gas energy metering data of the target gas-using device according to the natural gas energy metering data; the natural gas energy metering data includes the flow data, pressure data, temperature data, composition data, calorific value data, and timestamp data of natural gas;

[0111] A current operating data generation module, configured to obtain the environmental data of the target gas-using device, and generate the current operating data of the target gas-using device according to the environmental data and the target natural gas energy metering data;

[0112] A fault information generation module, configured to determine whether the current operating status of the target gas-using equipment is normal according to the current operating data. If not, obtain the fault index data of the target gas-using equipment, and determine the fault information of the target gas-using equipment according to the fault index data;

[0113] An early warning information generation module, configured to obtain the equipment information of the target gas-using equipment, and send corresponding early warning information to the monitoring center according to the equipment information and the fault information.

[0114] The energy measurement application layer is further configured with:

[0115] A sampling frequency calculation module, configured to, for each gas-using equipment, obtain the sampling frequency index data of the gas-using equipment, where the sampling frequency index data includes the historical fault frequency of the gas-using equipment and the historical consumption rate of natural gas during each working time period, and determine the sampling frequency of the gas-using equipment according to the sampling frequency index data;

[0116] Reference Figure 4 , the energy measurement data perception layer is configured with:

[0117] A data acquisition module, configured to acquire the natural gas energy measurement data of the gas-using equipment according to the sampling frequency.

[0118] The overall framework of the application scenario of the natural gas energy measurement data processing system based on the Internet of Things in this application is as Figure 3 shown, and may include an energy measurement data application layer, an energy measurement data transmission layer, and an energy measurement data perception layer that interact in sequence, thereby forming a basic three-layer architecture of the energy measurement Internet of Things.

[0119] Reference Figure 4 , the energy measurement data application layer is configured with: a target natural gas energy measurement data generation module, a current operating data generation module, a fault information generation module, and an early warning information generation module. The target natural gas energy measurement data generation module, the current operating data generation module, the fault information generation module, and the early warning information generation module can respectively interact with the data storage module; the energy measurement data transmission layer includes an equipment management module and a data transmission management module, and the equipment management module can interact with the data transmission management module; the energy measurement data perception layer includes a flow sensor, a pressure sensor, and a temperature sensor. Through the above three-layer Internet of Things system, a perfect closed-loop information operation logic is established, ensuring the orderly operation of the perception information and the control information, and realizing the intelligent management of energy measurement.

[0120] Specifically, for the Internet of Things system in this embodiment, the energy measurement data application layer is configured to: obtain natural gas energy measurement data, and obtain the target natural gas energy measurement data of the target gas-using equipment according to the natural gas energy measurement data; the natural gas energy measurement data includes flow data, pressure data, temperature data, composition data, calorific value data, and timestamp data of natural gas; obtain the environmental data of the target gas-using equipment, and generate the current operation data of the target gas-using equipment according to the environmental data and the target natural gas energy measurement data; determine whether the current operation state of the target gas-using equipment is normal according to the current operation data, if not, obtain the fault index data of the target gas-using equipment, and determine the fault information of the target gas-using equipment according to the fault index data; obtain the equipment information of the target gas-using equipment, and send corresponding warning information to the monitoring center according to the equipment information and the fault information.

[0121] The natural gas energy measurement data processing system based on the Internet of Things of the present invention can implement any one of the methods in the natural gas energy measurement data processing method based on the Internet of Things, and the specific working process of the natural gas energy measurement data processing system based on the Internet of Things of the present invention can refer to the corresponding process in the above-mentioned natural gas energy measurement data processing method based on the Internet of Things.

[0122] The embodiment of the present application also discloses a computer device.

[0123] Refer to Figure 5 , a computer device, including a memory and a processor, where a computer program that can run on the processor is stored on the memory, and when the processor executes the computer program, it implements any one of the above-mentioned natural gas energy measurement data processing methods based on the Internet of Things.

[0124] The above are all the preferred embodiments of the present application. Without restricting the protection scope of the present application accordingly, any feature disclosed in this specification (including the abstract and drawings), unless specifically described, can be replaced by other equivalent or similar-purpose alternative features. That is, unless specifically described, each feature is only an example in a series of equivalent or similar features.

Claims

1. A natural gas energy metering data processing method based on the Internet of Things, characterized in that: Used in an Internet of Things system, the Internet of Things system includes an energy metering data application layer, an energy metering data transmission layer and an energy metering data perception layer, the method is performed by the energy metering data application layer, the method includes: Obtaining natural gas energy metering data, and obtaining target natural gas energy metering data of a target gas-consuming device based on the natural gas energy metering data; the natural gas energy metering data includes natural gas flow data, pressure data, temperature data, composition data, calorific value data and timestamp data; Acquire environmental data of a target gas-consuming device, and generate current operating data of the target gas-consuming device according to the environmental data and the target natural gas energy metering data; Determine whether the current operating state of the target gas-consuming device is normal according to the current operating data; if not, obtain fault indicator data of the target gas-consuming device, and determine fault information of the target gas-consuming device according to the fault indicator data; Acquire the equipment information of the target gas-consuming equipment, and send corresponding warning information to the monitoring center according to the equipment information and the fault information; The target natural gas energy metering data includes target flow data, target pressure data, target temperature data, target composition data, target calorific value data and target timestamp data of natural gas, the environmental data includes environmental temperature data and environmental pressure data, and the step of generating the current operation data of the target gas-using equipment according to the environmental data and the target natural gas energy metering data includes: Determine the target gas consumption data, gas consumption fluctuation rate and startup frequency of the target gas-consuming equipment according to the target flow data and the target timestamp data; Obtaining a standard energy conversion efficiency of the target gas-using equipment, and determining a target energy conversion efficiency of the target gas-using equipment according to the standard energy conversion efficiency, the target pressure data, the target temperature data, the ambient pressure data, the ambient temperature data and the target composition data; Determine the target energy conversion value of the target gas-consuming equipment according to the target energy conversion efficiency, the target gas consumption data and the target calorific value data; Determine the operating power of the target gas-consuming equipment according to the target energy conversion value and the timestamp data; Generate current operation data of the target gas-consuming equipment according to the gas consumption fluctuation rate, the startup frequency and the operating power; The step of determining whether the current operating state of the target gas-consuming equipment is normal according to the current operating data comprises: Normalizing the gas consumption fluctuation rate, the startup frequency, and the operating power to obtain corresponding first normalized value, second normalized value, and third normalized value; Obtaining the first weight, the second weight, and the third weight corresponding to the first normalized value, the second normalized value, and the third normalized value, respectively, and calculating the state assessment value of the target gas-consuming equipment according to the first normalized value, the second normalized value, the third normalized value, the first weight, the second weight, and the third weight; It is determined whether the state evaluation value is within a preset range. If so, it indicates that the current operating state of the target gas-using equipment is normal. If not, it indicates that the current operating state of the target gas-using equipment is abnormal.

2. The method for processing natural gas energy metering data based on the Internet of Things according to claim 1 is characterized in that: Before the step of obtaining the natural gas energy metering data and obtaining the target natural gas energy metering data of the target gas-consuming equipment according to the natural gas energy metering data, the method further includes: For each gas-consuming device, sampling frequency index data of the gas-consuming device is obtained, wherein the sampling frequency index data includes the historical failure frequency and the historical consumption rate of natural gas of the gas-consuming device in each working time period, and the sampling frequency of the gas-consuming device is determined according to the sampling frequency index data; The natural gas energy metering data of the gas-consuming equipment is collected according to the sampling frequency.

3. The method for processing natural gas energy metering data based on the Internet of Things according to claim 1 is characterized in that: The step of determining the fault information of the target gas-consuming equipment according to the fault indicator data comprises: Acquire historical fault indicator data, and divide the historical fault indicator data into k data sets; By means of k-fold cross validation, the pre-built fault indicator model is trained and verified according to the data set to obtain a trained and verified fault indicator model; The fault indicator data is input into a trained and verified fault indicator model to obtain corresponding fault information.

4. The method for processing natural gas energy metering data based on the Internet of Things according to claim 1 is characterized in that: After the step of determining whether the current operating state of the target gas-consuming equipment is normal according to the current operating data, the method further includes: If yes, then obtain the performance index data of the target gas-consuming equipment, the performance index data including historical target gas consumption data, historical gas consumption fluctuation rate, historical startup frequency and historical working power, and determine the performance evaluation value of the target gas-consuming equipment according to the performance index data; Matching the performance evaluation value in a preset table to obtain the failure probability of the target gas-consuming equipment; the preset table includes the performance evaluation value of each gas-consuming equipment and the corresponding failure probability, and the preset table is used to represent the mapping relationship between the performance evaluation value and the failure probability; It is determined whether the failure probability is higher than a preset threshold value. If so, the target gas-using equipment is marked as a pending inspection state; if not, the target gas-using equipment is marked as a normal state.

5. The method for processing natural gas energy metering data based on the Internet of Things according to claim 1 is characterized in that: The device information includes the device type and the device location, the fault information includes the fault type, and the step of sending corresponding warning information to the monitoring center according to the device information and the fault information includes: Determine a corresponding warning type according to the fault type; Corresponding warning information is generated according to the device type, the device location and the warning type, and the warning information is sent to a monitoring center.

6. The natural gas energy metering data processing system based on the Internet of Things is characterized by: The system comprises an energy metering data application layer, an energy metering data transmission layer and an energy metering data perception layer, wherein the energy metering data application layer is configured with: A target natural gas energy metering data generating module is used to obtain natural gas energy metering data, and obtain target natural gas energy metering data of a target gas-consuming device according to the natural gas energy metering data; The natural gas energy metering data includes natural gas flow data, pressure data, temperature data, composition data, calorific value data and timestamp data; A current operation data generation module, used to obtain environmental data of a target gas-consuming device, and generate current operation data of the target gas-consuming device according to the environmental data and the target natural gas energy metering data; a fault information generating module, used to determine whether the current operating state of the target gas-consuming device is normal according to the current operating data, and if not, to obtain fault indicator data of the target gas-consuming device, and to determine the fault information of the target gas-consuming device according to the fault indicator data; The warning information generation module is used to obtain the equipment information of the target gas-consuming equipment, and send corresponding warning information to the monitoring center according to the equipment information and the fault information.

7. The natural gas energy metering data processing system based on the Internet of Things according to claim 6 is characterized in that: The energy metering data application layer is also configured with: A sampling frequency calculation module is used to obtain sampling frequency index data of each gas-consuming device, wherein the sampling frequency index data includes the historical failure frequency and the historical consumption rate of natural gas of the gas-consuming device in each working time period, and determine the sampling frequency of the gas-consuming device according to the sampling frequency index data; The energy metering data perception layer is configured with: The data acquisition module is used to acquire the natural gas energy metering data of the gas-consuming equipment according to the sampling frequency.

8. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the method according to any one of claims 1 to 5 when executing the computer program.

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