An Internet-based smart gas cloud platform

Abstract

The present invention relates to the technical field of gas supply monitoring and management, and specifically to an Internet-based smart gas cloud platform, comprising a server, wherein the server is communicatively connected to a data acquisition unit, a gas pipeline monitoring unit, a gas meter operation analysis unit, a gas flow monitoring unit, a gas quality monitoring unit, an early warning feedback analysis unit, a user terminal, a control terminal, and a cloud storage library. The present invention implements a determination and analysis of the user's gas pipeline status and user's gas flow through symbolic calibration, coordinate model establishment, statistical analysis of change curves, formulaic calculation, and threshold comparison, and performs corresponding early warning feedback and control operations based on abnormal conditions, thereby improving the timeliness and effectiveness of user gas pipeline leak detection, minimizing the impact range of pipeline leaks to the greatest extent, effectively protecting the lives and property of users, avoiding resource waste and potential safety risks caused by abnormal gas usage behavior of users, and improving gas usage stability.

Description

Technical Field

[0001] The present invention relates to the technical field of gas supply monitoring and management, and specifically to an Internet-based smart gas cloud platform. Background Art

[0002] With the rapid development of Internet technology and people's increasing demand for convenient, safe and intelligent energy use, the gas supply system is also moving towards intelligence.

[0003] Traditional gas supply and management models have many problems. For example, the detection of gas pipeline leaks is not timely and accurate enough, and is often not discovered until the leakage problem becomes serious, posing a huge threat to the safety of users' lives and property; the operating status of gas meters is difficult to monitor in real time, and a rapid response cannot be made when a fault occurs, affecting users' normal gas use and the management efficiency of gas companies; fluctuations in gas flow are difficult to effectively control, which may lead to unstable gas use or waste of resources; the means of monitoring gas quality are limited, making it impossible to detect quality problems in a timely manner and take targeted measures to improve them.

[0004] In order to solve the above-mentioned defects, a technical solution is now provided. Summary of the Invention

[0005] The purpose of the present invention is to provide an Internet-based smart gas cloud platform to solve the problems raised in the above background.

[0006] The object of the present invention can be achieved by the following technical solutions: an Internet-based smart gas cloud platform, comprising a server, the server being communicatively connected to a data acquisition unit, a gas pipeline monitoring unit, a gas meter operation analysis unit, a gas flow monitoring unit, a gas quality monitoring unit, an early warning feedback analysis unit, a user terminal, a control terminal, and a cloud storage library;

[0007] The data acquisition unit is used to collect the external parameter information of the gas pipeline corresponding to each user, the operating status parameter information of the smart gas meter of each user, the gas flow parameter information of the smart gas meter of each user, and the gas quality status parameter information, and send them to the gas pipeline monitoring unit, the gas meter operation analysis unit, the gas flow monitoring unit, and the gas quality monitoring unit respectively; the gas pipeline monitoring unit is used to receive the external parameter information of the gas pipeline corresponding to each user, and perform gas pipeline determination and analysis processing, thereby generating a gas pipeline sealing signal and a gas pipeline leakage signal, and sending the gas pipeline leakage signal to the early warning feedback analysis unit;

[0008] The gas meter operation analysis unit is used to receive the operating status parameter information of each user's smart gas meter, and perform gas meter operating status determination and analysis processing, thereby generating a gas meter normal operation signal and a gas meter abnormal operation signal, and sending the gas meter abnormal operation signal to the early warning feedback analysis unit;

[0009] The gas flow analysis unit is used to receive the gas flow parameter information of each user's smart gas meter, and perform gas flow determination and analysis processing, thereby generating a normal gas flow fluctuation signal and an abnormal gas flow fluctuation signal, and sending the abnormal gas flow fluctuation signal to the early warning feedback analysis unit;

[0010] The gas quality monitoring unit is used to receive gas quality status parameter information from each user and perform gas quality determination and analysis processing, thereby generating gas quality deterioration signals due to insufficient methane content, excessive hydrogen sulfide content, abnormal calorific value, abnormal density, excessive humidity, and irrelevant signals, and sends various types of gas quality deterioration feedback signals to the early warning feedback analysis unit, wherein the various types of gas quality deterioration feedback signals include gas quality deterioration signals due to insufficient methane content, excessive hydrogen sulfide content, abnormal calorific value, abnormal density, and excessive humidity;

[0011] The early warning feedback analysis unit is used to receive different types of abnormal feedback signals for early warning analysis and processing, and to issue early warning information reminders through the user terminal and to perform abnormal fault type relief operations through the control terminal;

[0012] The cloud storage library is used to store the reference sound spectrograms corresponding to the detection points in the external area of the gas pipeline, and to store the reference operating current, operating voltage, and operating temperature of the smart gas meter.

[0013] Furthermore, the specific execution steps for gas pipeline determination and analysis are as follows:

[0014] Obtain the external area of the gas pipeline corresponding to all users, and arrange detection points in the external area of the gas pipeline corresponding to each user to obtain the detection points in the external area of the gas pipeline corresponding to each user;

[0015] Obtain the temperature of each detection point in the external area of the gas pipeline corresponding to each user in real time at each monitoring time point in unit time, and take its value, which is recorded as i represents the number of each user, i = 1, 2, ...., m, m represents the total number of user numbers, j represents the number of each detection point in the external area of the gas pipeline, j = 1, 2, ...., n, n represents the total number of detection point numbers in the external area of the gas pipeline, f represents the number of each monitoring time point in unit time, f = 1, 2, ...., g, g represents the total number of monitoring time point numbers in unit time, and the temperature of each detection point in the external area of the gas pipeline corresponding to each user at each monitoring time point in unit time is averaged to obtain the average temperature of each detection point in the external area of the gas pipeline corresponding to each user in unit time, and take its value, recorded as At the same time, obtain the detection temperature of the gas inside the gas pipeline corresponding to each user in unit time, and take its value, recorded as NW i According to the formula Calculate the temperature impact index WY of the external area of the gas pipeline corresponding to each user i , a1 and a2 represent the set impact factors respectively;

[0016] Acquire the sound signals of each detection point in the external area of the gas pipeline corresponding to each user in real time per unit time, and generate the sound spectrum diagram of each detection point in the external area of the gas pipeline corresponding to each user per unit time based on the sound spectrum analysis software;

[0017] The sound spectrum graphs of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are compared and analyzed with the reference sound spectrum graphs of the detection points in the external area of the gas pipeline corresponding to each user in the cloud storage library, and the overlapping segments of the sound spectrums of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are obtained. Based on the overlapping segments of the sound spectrums, the abnormal segments of the sound spectrums of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are obtained, and thus the abnormal sounds of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are taken as the abnormal sounds of each detection point in the external area of the gas pipeline corresponding to each user within a unit time. The number of abnormal sounds of each detection point in the external area of the gas pipeline corresponding to each user within a unit time is counted and marked as The duration of each abnormal sound per unit time at each detection point in the external area of the gas pipeline corresponding to each user is extracted from the sound spectrum of each detection point in the external area of the gas pipeline corresponding to each user in unit time, and the sum of the durations is calculated to obtain the total duration of abnormal sound per unit time at each detection point in the external area of the gas pipeline corresponding to each user, and it is marked as

[0018] According to the formula Calculate the sound impact index SY of the external area of the gas pipeline corresponding to each user i , e represents a natural constant, a3 and a4 represent the set impact factors respectively;

[0019] The regional images of the outside of the gas pipeline corresponding to each user at each monitoring time point in unit time are obtained in real time, and the corrosion area, shedding area, and damage area of the outside of the gas pipeline corresponding to each user at each monitoring time point in unit time are extracted from them. The maximum corrosion area, maximum shedding area, and maximum damage area are screened out as the corrosion area, shedding area, and damage area of the outside of the gas pipeline corresponding to each user in unit time, and they are marked as FS respectively. i TS i 、PS i ;

[0020] According to the formula PY i =FS i ×a5+TS i ×a6+PS i ×a7 Calculate the damage impact index PY of the external area of the gas pipeline corresponding to each user i , a5, a6, and a7 represent the set impact factors respectively;

[0021] According to the formula Calculate the leakage assessment coefficient XL of the external area of the gas pipeline corresponding to each user i , b1, b2, b3 represent the set weight factors respectively;

[0022] A leakage degree assessment coefficient threshold is set, and the leakage degree assessment coefficient of the external area of the gas pipeline corresponding to each user is compared and analyzed with the leakage degree assessment coefficient threshold. When the leakage degree assessment coefficient of the external area of the gas pipeline corresponding to a user is greater than or equal to the leakage degree assessment coefficient threshold, a gas pipeline leakage signal is generated; when the leakage degree assessment coefficient of the external area of the gas pipeline corresponding to a user is less than the leakage degree assessment coefficient threshold, a gas pipeline sealing signal is generated.

[0023] Furthermore, the specific execution steps for determining and analyzing the working status of the gas meter are as follows:

[0024] Real-time monitoring obtains the operating current of each monitoring time point in the working status parameter information of each user's smart gas meter, which is recorded as And calculate the mean value to get the average operating current of each user's smart gas meter in unit time, which is recorded as And extract the reference operating current of the smart gas meter from the cloud storage, recorded as I0, according to the formula Calculate the operating flow steady value LW of each user's smart gas meter i , c1 and c2 represent the set weight factors respectively;

[0025] Real-time monitoring obtains the operating voltage of each monitoring time point in the unit time from the working status parameter information of each user's smart gas meter, which is recorded as And calculate the mean value to get the average operating voltage of each user's smart gas meter in unit time, which is recorded as And extract the reference operating voltage of the smart gas meter from the cloud storage, denoted as U0, according to the formula Calculate the operating pressure stability value UW of each user's smart gas meter i , c3 and c4 represent the set weight factors respectively;

[0026] Real-time monitoring obtains the operating temperature of each monitoring time point in the unit time from the working status parameter information of each user's smart gas meter, which is recorded as And calculate the mean value to get the average operating temperature of each user's smart gas meter in unit time, which is recorded as The reference operating temperature of the smart gas meter is extracted from the cloud repository, denoted as wd0, according to the formula Calculate the operating temperature stability value WW of each user's smart gas meter i , c5 and c6 represent the set weight factors respectively;

[0027] According to the formula YX i =LW i ×d1+UW i ×d2+WW i ×d3 calculates the operating coefficient YX of each user's smart gas meter i , d1, d2, d3 are respectively represented as the set coefficient factors;

[0028] Setting multiple control intervals for the working operation coefficient, and the multiple control intervals include a first working control interval and a second working control interval, and substituting the working operation coefficient of each user's smart gas meter into the pre-set multiple control intervals for comparative analysis, wherein the interval data values of the first working control interval and the second working control interval increase in a gradient;

[0029] When the operating coefficient of a user's smart gas meter is within a pre-set first operating control interval, an abnormal operating signal of the smart gas meter is generated. When the operating coefficient of a user's smart gas meter is within a pre-set second operating control interval, a normal operating signal of the smart gas meter is generated.

[0030] Furthermore, the specific execution steps for gas flow determination and analysis are as follows:

[0031] Real-time monitoring is used to obtain the cumulative gas flow of each user's smart gas meter per unit time. A two-dimensional dynamic coordinate system is established with time as the horizontal axis and the cumulative gas flow as the vertical axis. The cumulative gas flow per unit time is plotted on the two-dimensional dynamic coordinate system by connecting points, thereby obtaining the cumulative gas flow change curve of each user's smart gas meter;

[0032] An upper reference line for cumulative flow and a lower reference line for cumulative flow are set in the cumulative gas flow change curve of each user's smart gas meter. The positions of the cumulative flow values at the upper reference line and the lower reference line in the two-dimensional dynamic coordinate system are recorded as abnormal points. At the same time, the collection time points corresponding to the two adjacent abnormal points are taken, and the collection time points corresponding to the two adjacent abnormal points are analyzed by difference to obtain the abnormal interval length. The number of abnormal points is thus counted and marked as N. i , calculate the average value of all abnormal intervals to get the average abnormal interval time, and mark it as T i At the same time, the cumulative flow corresponding to all abnormal points is averaged to obtain the average of abnormal flow and marked as YL i ;

[0033] According to the formula Calculate the gas flow fluctuation assessment coefficient LP for each user i , e1, e2, and e3 are respectively represented as the set weight factors;

[0034] A gas flow fluctuation assessment coefficient threshold is set, and the gas flow fluctuation assessment coefficient of each user is compared and analyzed with the preset gas flow fluctuation assessment coefficient threshold. When the gas flow fluctuation assessment coefficient of a user is less than or equal to the preset gas flow fluctuation assessment coefficient threshold, a gas flow small fluctuation signal is generated; when the gas flow fluctuation assessment coefficient of a user is greater than the preset gas flow fluctuation assessment coefficient threshold, a gas flow large fluctuation signal is generated.

[0035] Furthermore, the specific execution steps for gas quality determination and analysis are as follows:

[0036] Real-time monitoring obtains the methane content, hydrogen sulfide content, calorific value, density and humidity of each user's gas quality status parameter information per unit time, and marks them as Q i , ρ i 、sd i , according to the set formula Get the gas quality evaluation coefficient ZL of each user i , f1, f2, f3, f4, and f5 are the set correction factors respectively;

[0037] Set a gas quality assessment coefficient threshold, and compare and analyze the gas quality assessment coefficient of each user with the preset gas quality assessment coefficient threshold. When the gas quality assessment coefficient of a user is greater than or equal to the preset gas quality assessment coefficient threshold, a gas quality normal signal is generated. When the gas quality assessment coefficient of a user is less than the preset gas quality assessment coefficient threshold, a gas quality abnormal signal is generated.

[0038] Based on the generated gas quality abnormality signal, the cause of the gas quality abnormality is analyzed and processed, thereby obtaining the gas quality deterioration signal caused by insufficient methane content, the gas quality deterioration signal caused by high hydrogen sulfide content, the gas quality deterioration signal caused by abnormal calorific value, the gas quality deterioration signal caused by abnormal density, the gas quality deterioration signal caused by excessive humidity, and irrelevant signals.

[0039] Furthermore, the specific steps for analyzing and handling the causes of abnormal gas quality are as follows:

[0040] Obtain each gas quality status parameter and the preset threshold value corresponding to each gas quality status parameter in real time, and compare and analyze each gas quality status parameter with the corresponding preset threshold value;

[0041] The methane content is compared with the preset methane content threshold. When the methane content is greater than or equal to the preset methane content threshold, an irrelevant signal is generated. When the methane content is less than the preset methane content threshold, a signal indicating insufficient methane content leading to poor air quality is generated.

[0042] The hydrogen sulfide content is compared and analyzed with the preset hydrogen sulfide content threshold. When the hydrogen sulfide content is less than the preset hydrogen sulfide content threshold, an irrelevant signal is generated. When the hydrogen sulfide content is greater than or equal to the preset hydrogen sulfide content threshold, a signal indicating that the hydrogen sulfide content is too high and the air quality has deteriorated is generated.

[0043] Compare and analyze the calorific value with the preset calorific value reference range. When the calorific value is within the preset calorific value reference range, an irrelevant signal is generated. When the calorific value is not within the preset calorific value reference range, a calorific value abnormality signal resulting in poor quality is generated.

[0044] The density is compared and analyzed with the preset density reference interval. When the density is within the preset density reference interval, an irrelevant signal is generated. When the density is not within the preset density reference interval, a density abnormality leading to quality deterioration signal is generated.

[0045] The humidity is compared and analyzed with the preset humidity threshold. When the humidity is less than or equal to the preset humidity threshold, an irrelevant signal is generated. When the humidity is greater than the preset humidity threshold, a signal indicating that the humidity is too high and the air quality has deteriorated is generated.

[0046] Beneficial effects of the present invention:

[0047] The present invention realizes the determination and analysis of the user's gas pipeline status through symbolic calibration, formulaic calculation and threshold comparison, and provides corresponding early warning feedback based on the abnormal status of the gas pipeline. It can improve the timeliness and effectiveness of the user's gas pipeline leakage detection, minimize the impact range of pipeline leakage to the greatest extent, improve the safety of the gas pipeline and effectively protect the life and property of users.

[0048] The present invention realizes the determination and analysis of the operating status of the user's smart gas meter through symbolic calibration, formulaic calculation and comparison of control intervals, and provides corresponding early warning feedback based on the abnormal operating status of the gas meter. To a certain extent, it effectively avoids the further expansion of abnormal operating conditions of the smart gas meter, reduces inaccurate measurement and user complaints caused by gas meter abnormalities, and improves management efficiency.

[0049] The present invention realizes the judgment and analysis of user gas flow through the establishment of a coordinate model, statistical analysis of the change curve, formula calculation and threshold comparison. It further conducts a comprehensive analysis of the user gas flow fluctuation based on the historical judgment signal, and performs corresponding early warning feedback and control operations based on the abnormal state of gas flow fluctuation, avoiding resource waste and potential safety risks caused by abnormal gas usage behavior of users, and improving the stability of user gas usage.

[0050] The present invention monitors the user's gas quality parameters and analyzes and determines the gas quality status based on them, thereby realizing timely detection of gas quality problems of users, and providing early warning and improvement measures for users and gas supply source control ends, helping users and gas supply sources to better manage and utilize gas resources, and effectively improving users' gas usage experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The present invention will be further described below with reference to the accompanying drawings.

[0052] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0054] See also Figure 1As shown, the present invention is an Internet-based smart gas cloud platform, including a server, which is communicatively connected to a data acquisition unit, a gas pipeline monitoring unit, a gas meter operation analysis unit, a gas flow monitoring unit, a gas quality monitoring unit, an early warning feedback analysis unit, a user terminal, a control terminal and a cloud storage library;

[0055] The data acquisition unit is used to collect the external parameter information of the gas pipeline corresponding to each user, the operating status parameter information of the smart gas meter of each user, the gas flow parameter information of the smart gas meter of each user, and the gas quality status parameter information, and send them to the gas pipeline monitoring unit, the gas meter operation analysis unit, the gas flow monitoring unit, and the gas quality monitoring unit respectively; when the gas pipeline monitoring unit receives the external parameter information of the gas pipeline corresponding to each user, it performs gas pipeline judgment and analysis based on it. The specific execution steps are as follows:

[0056] Obtain the external area of the gas pipeline corresponding to each user, and arrange detection points in the external area of the gas pipeline corresponding to each user to obtain the detection points in the external area of the gas pipeline corresponding to each user;

[0057] Obtain the temperature of each detection point in the external area of the gas pipeline corresponding to each user in real time at each monitoring time point in unit time, and take its value, which is recorded as i represents the number of each user, i = 1, 2, ...., m, m represents the total number of user numbers, j represents the number of each detection point in the external area of the gas pipeline, j = 1, 2, ...., n, n represents the total number of detection point numbers in the external area of the gas pipeline, f represents the number of each monitoring time point in unit time, f = 1, 2, ...., g, g represents the total number of monitoring time point numbers in unit time, and the temperature of each detection point in the external area of the gas pipeline corresponding to each user at each monitoring time point in unit time is averaged to obtain the average temperature of each detection point in the external area of the gas pipeline corresponding to each user in unit time, and take its value, recorded as At the same time, obtain the detection temperature of the gas inside the gas pipeline corresponding to each user in unit time, and take its value, recorded as NW i According to the formula Calculate the temperature impact index WY of the external area of the gas pipeline corresponding to each user i , a1 and a2 represent the set impact factors respectively;

[0058] Acquire the sound signals of each detection point in the external area of the gas pipeline corresponding to each user in real time per unit time, and generate the sound spectrum diagram of each detection point in the external area of the gas pipeline corresponding to each user per unit time based on the sound spectrum analysis software;

[0059] The sound spectrum graphs of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are compared and analyzed with the reference sound spectrum graphs of the detection points in the external area of the gas pipeline corresponding to each user in the cloud storage library, and the overlapping segments of the sound spectrums of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are obtained. Based on the overlapping segments of the sound spectrums, the abnormal segments of the sound spectrums of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are obtained, and thus the abnormal sounds of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are taken as the abnormal sounds of each detection point in the external area of the gas pipeline corresponding to each user within a unit time. The number of abnormal sounds of each detection point in the external area of the gas pipeline corresponding to each user within a unit time is counted and marked as The duration of each abnormal sound per unit time at each detection point in the external area of the gas pipeline corresponding to each user is extracted from the sound spectrum of each detection point in the external area of the gas pipeline corresponding to each user in unit time, and the sum of the durations is calculated to obtain the total duration of abnormal sound per unit time at each detection point in the external area of the gas pipeline corresponding to each user, and it is marked as

[0060] According to the formula Calculate the sound impact index SY of the external area of the gas pipeline corresponding to each user i , e represents a natural constant, a3 and a4 represent the set impact factors respectively;

[0061] The regional images of the outside of the gas pipeline corresponding to each user at each monitoring time point in unit time are obtained in real time, and the corrosion area, shedding area, and damage area of the outside of the gas pipeline corresponding to each user at each monitoring time point in unit time are extracted from them. The maximum corrosion area, maximum shedding area, and maximum damage area are screened out as the corrosion area, shedding area, and damage area of the outside of the gas pipeline corresponding to each user in unit time, and they are marked as FS respectively. i TS i 、PS i ;

[0062] According to the formula PY i =FS i ×a5+TS i ×a6+PS i ×a7 Calculate the damage impact index PY of the external area of the gas pipeline corresponding to each user i , a5, a6, and a7 represent the set impact factors respectively;

[0063] According to the formula Calculate the leakage assessment coefficient XL of the external area of the gas pipeline corresponding to each user i , b1, b2, b3 represent the set weight factors respectively;

[0064] Set a leakage degree assessment coefficient threshold, and compare and analyze the leakage degree assessment coefficient of the external area of the gas pipeline corresponding to each user with the leakage degree assessment coefficient threshold. When the leakage degree assessment coefficient of the external area of the gas pipeline corresponding to a user is greater than or equal to the leakage degree assessment coefficient threshold, a gas pipeline leakage signal is generated. When the leakage degree assessment coefficient of the external area of the gas pipeline corresponding to a user is less than the leakage degree assessment coefficient threshold, a gas pipeline sealing signal is generated.

[0065] The generated gas pipeline leakage signal is sent to the early warning feedback analysis unit for early warning analysis and processing. Specifically:

[0066] Based on the generated gas pipeline leak signal, a gas pipeline leak alarm is triggered, and a text message "Pipeline Leakage" is generated and sent to the user's terminal. Simultaneously, the user's gas supply is interrupted through the control terminal, and a maintenance technician is assigned to inspect the gas pipeline. Once the inspection is complete, the gas pipeline leak alarm is immediately deactivated and gas supply is restored to the user. In a specific embodiment, the present invention uses symbolic calibration, formulaic calculations, and threshold comparisons to determine and analyze the status of a user's gas pipeline. It also provides corresponding early warning feedback based on abnormal gas pipeline conditions, thereby improving the timeliness and effectiveness of gas pipeline leak detection, minimizing the impact of pipeline leaks, and enhancing gas pipeline safety, effectively protecting the lives and property of users.

[0067] When the gas meter operation analysis unit receives the operating status parameter information of each user's smart gas meter, it performs gas meter operating status determination and analysis based on the information. The specific execution steps are as follows:

[0068] Real-time monitoring obtains the operating current of each monitoring time point in the working status parameter information of each user's smart gas meter, which is recorded as And calculate the mean value to get the average operating current of each user's smart gas meter in unit time, which is recorded as And extract the reference operating current of the smart gas meter from the cloud storage, recorded as I0, according to the formula Calculate the operating flow steady value LW of each user's smart gas meter i , c1 and c2 represent the set weight factors respectively;

[0069] Real-time monitoring obtains the operating voltage of each monitoring time point in the unit time from the working status parameter information of each user's smart gas meter, which is recorded as And calculate the mean value to get the average operating voltage of each user's smart gas meter in unit time, which is recorded as And extract the reference operating voltage of the smart gas meter from the cloud storage, denoted as U0, according to the formula Calculate the operating pressure stability value UW of each user's smart gas meter i , c3 and c4 represent the set weight factors respectively;

[0070] Real-time monitoring obtains the operating temperature of each monitoring time point in the unit time from the working status parameter information of each user's smart gas meter, which is recorded as And calculate the mean value to get the average operating temperature of each user's smart gas meter in unit time, which is recorded as The reference operating temperature of the smart gas meter is extracted from the cloud repository, denoted as wd0, according to the formula Calculate the operating temperature stability value WW of each user's smart gas meter i , c5 and c6 represent the set weight factors respectively;

[0071] According to the formula YX i =LW i ×d1+UW i ×d2+WW i ×d3 calculates the operating coefficient YX of each user's smart gas meter i , d1, d2, d3 are respectively represented as the set coefficient factors;

[0072] Setting multiple control intervals for the working operation coefficient, and the multiple control intervals include a first working control interval and a second working control interval, and substituting the working operation coefficient of each user's smart gas meter into the pre-set multiple control intervals for comparative analysis, wherein the interval data values of the first working control interval and the second working control interval increase in a gradient;

[0073] When the operating coefficient of a user's smart gas meter is within a pre-set first operating control interval, a smart gas meter abnormal operation signal is generated; when the operating coefficient of a user's smart gas meter is within a pre-set second operating control interval, a smart gas meter normal operation signal is generated;

[0074] The generated smart gas meter operation abnormality signal is sent to the early warning feedback analysis unit for early warning analysis and processing. Specifically: according to the generated smart gas meter operation abnormality signal, the smart gas meter operation abnormality alarm is triggered, and the text content of "smart gas meter operation abnormality" is generated and sent to the user terminal. At the same time, a maintenance technician is assigned through the control terminal to perform maintenance operations on the smart gas meter, and the smart gas meter operation abnormality alarm is lifted as soon as the maintenance operation is completed.

[0075] In a specific embodiment, the present invention realizes the determination and analysis of the operating status of the user's smart gas meter through symbolic calibration, formulaic calculation and comparison of control intervals, and provides corresponding early warning feedback based on the abnormal operating status of the gas meter. To a certain extent, it effectively avoids the further expansion of abnormal operating conditions of the smart gas meter, reduces inaccurate measurement and user complaints caused by gas meter abnormalities, and improves management efficiency.

[0076] When the gas flow analysis unit receives the gas flow parameter information from each user's smart gas meter, it performs gas flow determination and analysis based on the information. The specific execution steps are as follows:

[0077] Real-time monitoring is used to obtain the cumulative gas flow of each user's smart gas meter per unit time. A two-dimensional dynamic coordinate system is established with time as the horizontal axis and the cumulative gas flow as the vertical axis. The cumulative gas flow per unit time is plotted on the two-dimensional dynamic coordinate system by connecting points, thereby obtaining the cumulative gas flow change curve of each user's smart gas meter;

[0078] An upper reference line for cumulative flow and a lower reference line for cumulative flow are set in the cumulative gas flow change curve of each user's smart gas meter. The positions of the cumulative flow values at the upper reference line and the lower reference line in the two-dimensional dynamic coordinate system are recorded as abnormal points. At the same time, the collection time points corresponding to the two adjacent abnormal points are taken, and the collection time points corresponding to the two adjacent abnormal points are analyzed by difference to obtain the abnormal interval length. The number of abnormal points is thus counted and marked as N. i , calculate the average value of all abnormal intervals to get the average abnormal interval time, and mark it as T i At the same time, the cumulative flow corresponding to all abnormal points is averaged to obtain the average of abnormal flow and marked as YL i ;

[0079] According to the formula Calculate the gas flow fluctuation assessment coefficient LP for each user i , e1, e2, and e3 are respectively represented as the set weight factors;

[0080] A gas flow fluctuation assessment coefficient threshold is set, and the gas flow fluctuation assessment coefficient of each user is compared and analyzed with the preset gas flow fluctuation assessment coefficient threshold. When the gas flow fluctuation assessment coefficient of a user is less than or equal to the preset gas flow fluctuation assessment coefficient threshold, a gas flow small fluctuation signal is generated. When the gas flow fluctuation assessment coefficient of a user is greater than the preset gas flow fluctuation assessment coefficient threshold, a gas flow large fluctuation signal is generated.

[0081] The generated large gas flow fluctuation signal is sent to the early warning feedback analysis unit for early warning analysis and processing. Specifically: based on the generated large gas flow fluctuation signal, a gas flow fluctuation determination signal corresponding to the historical unit time of the same time period within the unit time is obtained. When the gas flow fluctuation determination signal corresponding to the historical unit time is also a large gas flow fluctuation signal, a normal gas flow fluctuation signal is generated. When the gas flow fluctuation determination signal corresponding to the historical unit time is not a large gas flow fluctuation signal, a gas flow fluctuation abnormality signal is generated.

[0082] Based on the generated gas flow fluctuation abnormality signal, the gas flow fluctuation abnormality alarm is triggered, and a text content of "Is there a large amount of gas consumption behavior" is generated and sent to the user terminal for inquiry. When the answer from the user terminal is "yes", the gas flow fluctuation abnormality alarm is lifted. When the answer from the user terminal is "no", the gas flow fluctuation abnormality alarm continues to be triggered, and the gas supply to the user is interrupted through the control terminal at the same time, and the gas supply to the user is restored after the gas flow fluctuation abnormality alarm is lifted.

[0083] In a specific embodiment, the present invention implements a determination and analysis of user gas flow through the establishment of a coordinate model, statistical analysis of change curves, and formulaic calculations and threshold comparisons. Furthermore, based on historical determination signals, a comprehensive analysis of user gas flow fluctuations is performed, and corresponding early warning feedback and control operations are performed based on abnormal gas flow fluctuations. This avoids resource waste and potential safety risks caused by abnormal gas usage behavior by users, and improves the stability of user gas usage. When the gas quality monitoring unit receives the gas quality status parameter information of each user and performs gas quality determination and analysis based on it, the specific execution steps are as follows:

[0084] Real-time monitoring obtains the methane content, hydrogen sulfide content, calorific value, density and humidity of each user's gas quality status parameter information per unit time, and marks them as Q i , ρ i 、sd i , according to the set formula Get the gas quality evaluation coefficient ZL of each user i , f1, f2, f3, f4, and f5 are the set correction factors respectively;

[0085] It should be noted that the methane content is used to indicate the proportion of methane gas in the gas. The greater the proportion of methane gas in the gas, the more complete the combustion, the more stable the flame, the higher the combustion efficiency, and the higher the cooking efficiency, which indicates better gas quality.

[0086] The hydrogen sulfide content is used to indicate the proportion of hydrogen sulfide gas in the fuel gas. The higher the proportion of hydrogen sulfide gas in the fuel gas, the more harmful the gas may be to human health, cause pipeline corrosion, or lead to incomplete combustion, indicating that the fuel gas quality is worse.

[0087] Calorific value is used to indicate the amount of heat released by the complete combustion of a unit volume of gas. A higher calorific value means that the gas can provide more energy when burned, and can more efficiently meet the user's cooking, heating, and hot water supply needs, indicating that the gas quality is better.

[0088] Humidity is a data value used to indicate the moisture content in the gas. When the moisture content in the gas is higher, it means that during the combustion process, the moisture will absorb heat and turn into water vapor, which will lower the flame temperature and prevent the combustion reaction from proceeding fully, thereby reducing the combustion efficiency, indicating that the gas quality is worse.

[0089] Set a gas quality assessment coefficient threshold, and compare and analyze the gas quality assessment coefficient of each user with the preset gas quality assessment coefficient threshold. When the gas quality assessment coefficient of a user is greater than or equal to the preset gas quality assessment coefficient threshold, a gas quality normal signal is generated. When the gas quality assessment coefficient of a user is less than the preset gas quality assessment coefficient threshold, a gas quality abnormal signal is generated.

[0090] Based on the generated gas quality abnormality signal, the cause of the gas quality abnormality is analyzed and processed, specifically:

[0091] Obtain each gas quality status parameter and the preset threshold value corresponding to each gas quality status parameter in real time, and compare and analyze each gas quality status parameter with the corresponding preset threshold value;

[0092] The methane content is compared with the preset methane content threshold. When the methane content is greater than or equal to the preset methane content threshold, an irrelevant signal is generated. When the methane content is less than the preset methane content threshold, a signal indicating insufficient methane content leading to poor air quality is generated.

[0093] The hydrogen sulfide content is compared and analyzed with the preset hydrogen sulfide content threshold. When the hydrogen sulfide content is less than the preset hydrogen sulfide content threshold, an irrelevant signal is generated. When the hydrogen sulfide content is greater than or equal to the preset hydrogen sulfide content threshold, a signal indicating that the hydrogen sulfide content is too high and the air quality has deteriorated is generated.

[0094] Compare and analyze the calorific value with the preset calorific value reference range. When the calorific value is within the preset calorific value reference range, an irrelevant signal is generated. When the calorific value is not within the preset calorific value reference range, a calorific value abnormality signal resulting in poor quality is generated.

[0095] The density is compared and analyzed with the preset density reference interval. When the density is within the preset density reference interval, an irrelevant signal is generated. When the density is not within the preset density reference interval, a density abnormality leading to quality deterioration signal is generated.

[0096] The humidity is compared with the preset humidity threshold. When the humidity is less than or equal to the preset humidity threshold, an irrelevant signal is generated. When the humidity is greater than the preset humidity threshold, a signal indicating that the humidity is too high and the air quality is deteriorating is generated.

[0097] The generated gas quality deterioration signals due to insufficient methane content, high hydrogen sulfide content, abnormal calorific value, abnormal density, and excessive humidity are sent to the early warning feedback analysis unit for early warning analysis and processing. Specifically:

[0098] The generated methane content is insufficient, resulting in a gas quality deterioration signal, which triggers a methane content abnormality alarm and generates a "gas quality abnormality" text message that is sent to the user terminal to remind the user to pay attention to gas quality issues. At the same time, the methane content of the gas is increased by controlling the terminal to improve the gas quality abnormality.

[0099] The generated high hydrogen sulfide content leads to a gas quality deterioration signal, triggering an abnormal hydrogen sulfide content alarm and generating a "gas quality abnormality" text content to send to the user terminal to remind the user to pay attention to the gas quality problem. At the same time, the gas quality abnormality is improved by controlling the terminal to reduce the hydrogen sulfide content;

[0100] Based on the generated calorific value abnormality leading to gas quality deterioration signal or density abnormality leading to gas quality deterioration signal, a gas quality abnormality alarm is triggered, and a "gas quality abnormality" text content is generated and sent to the user terminal to remind the user to pay attention to gas quality issues. At the same time, the gas component ratio is adjusted by the control terminal to improve the gas quality abnormality;

[0101] Based on the generated signal that the humidity is too high and the gas quality deteriorates, a humidity abnormality alarm is triggered, and a "gas quality abnormality" text content is generated and sent to the user terminal to remind the user to pay attention to the gas quality problem. At the same time, the humidity is adjusted by the control terminal to improve the abnormal gas quality.

[0102] In a specific embodiment, the present invention monitors the gas quality parameters of the user and analyzes and determines the gas quality status based on the parameters, thereby realizing timely detection of gas quality problems of the user, and providing early warning and improvement measures for the user and the gas supply source control end, thereby helping the user and the gas supply source to better manage and utilize gas resources, and effectively improving the user's gas experience. The above content is merely an example and explanation of the structure of the present invention. Technicians in this technical field can make various modifications or supplements to the specific embodiments described, or replace them with similar methods. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the scope of protection of the present invention.

Claims

1. An Internet-based smart gas cloud platform, characterized by: The server includes a data acquisition unit, a gas pipeline monitoring unit, a gas meter operation analysis unit, a gas flow monitoring unit, a gas quality monitoring unit, an early warning feedback analysis unit, a user terminal, a control terminal and a cloud storage library; The gas pipeline monitoring unit is used to receive the external parameter information of the gas pipeline corresponding to each user, and perform gas pipeline determination and analysis processing, thereby generating a gas pipeline sealing signal and a gas pipeline leakage signal, and sending the gas pipeline leakage signal to the early warning feedback analysis unit; The specific execution steps of the gas pipeline determination and analysis process are as follows: Obtain the external area of the gas pipeline corresponding to all users, and arrange detection points in the external area of the gas pipeline corresponding to each user to obtain the detection points in the external area of the gas pipeline corresponding to each user; Obtain the temperature of each detection point in the external area of the gas pipeline corresponding to each user in real time at each monitoring time point in unit time, and take its value, which is recorded as , i represents the number of each user, i=1,2,....,m, m represents the total number of user numbers, j represents the number of each detection point in the external area of the gas pipeline, j=1,2,....,n, n represents the total number of detection point numbers in the external area of the gas pipeline, f represents the number of each monitoring time point in unit time, f=1,2,....,g, g represents the total number of monitoring time point numbers in unit time, and the temperature of each detection point in the external area of the gas pipeline corresponding to each user at each monitoring time point in unit time is averaged to obtain the average temperature of each detection point in the external area of the gas pipeline corresponding to each user in unit time, and take its value, recorded as ; At the same time, the detected temperature of the gas inside the gas pipeline corresponding to each user in unit time is obtained, and its value is taken and recorded as ; According to the formula Calculate the temperature impact index of the external area of the gas pipeline corresponding to each user , a1 and a2 represent the set impact factors respectively; Acquire the sound signals of each detection point in the external area of the gas pipeline corresponding to each user in real time per unit time, and generate the sound spectrum diagram of each detection point in the external area of the gas pipeline corresponding to each user per unit time based on the sound spectrum analysis software; The sound spectrum graphs of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are compared and analyzed with the reference sound spectrum graphs of the detection points in the external area of the gas pipeline corresponding to each user in the cloud storage library, and the overlapping segments of the sound spectrums of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are obtained. Based on the overlapping segments of the sound spectrums, the abnormal segments of the sound spectrums of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are obtained, and thus the abnormal sounds of each detection point in the external area of the gas pipeline corresponding to each user within a unit time are taken as the abnormal sounds of each detection point in the external area of the gas pipeline corresponding to each user within a unit time. The number of abnormal sounds of each detection point in the external area of the gas pipeline corresponding to each user within a unit time is counted and marked as ; The duration of each abnormal sound per unit time at each detection point in the external area of the gas pipeline corresponding to each user is extracted from the sound spectrum of each detection point in the external area of the gas pipeline corresponding to each user in unit time, and the sum of the durations is calculated to obtain the total duration of abnormal sound per unit time at each detection point in the external area of the gas pipeline corresponding to each user, and it is marked as ; According to the formula Calculate the sound impact index of each user's corresponding gas pipeline external area , e represents a natural constant, a3 and a4 represent the set impact factors respectively; The regional images of the outside of the gas pipeline corresponding to each user at each monitoring time point in unit time are obtained in real time, and the corrosion area, shedding area, and damage area of the outside of the gas pipeline corresponding to each user at each monitoring time point in unit time are extracted from them. The maximum corrosion area, maximum shedding area, and maximum damage area are screened out as the corrosion area, shedding area, and damage area of the outside of the gas pipeline corresponding to each user in unit time, and they are marked as ; According to the formula Calculate the damage impact index of the external area of the gas pipeline corresponding to each user , a5, a6, and a7 represent the set impact factors respectively; According to the formula Calculate the leakage assessment coefficient of the external area of the gas pipeline corresponding to each user , b1, b2, b3 represent the set weight factors respectively; A leakage degree assessment coefficient threshold is set, and the leakage degree assessment coefficient of the external area of the gas pipeline corresponding to each user is compared and analyzed with the leakage degree assessment coefficient threshold. When the leakage degree assessment coefficient of the external area of the gas pipeline corresponding to a user is greater than or equal to the leakage degree assessment coefficient threshold, a gas pipeline leakage signal is generated; when the leakage degree assessment coefficient of the external area of the gas pipeline corresponding to a user is less than the leakage degree assessment coefficient threshold, a gas pipeline sealing signal is generated.

2. The Internet-based smart gas cloud platform according to claim 1, characterized in that: The data acquisition unit is used to collect the external parameter information of the gas pipeline corresponding to each user, the working status parameter information of the smart gas meter of each user, the gas flow parameter information of the smart gas meter of each user, and the gas quality status parameter information, and send them to the gas pipeline monitoring unit, the gas meter operation analysis unit, the gas flow monitoring unit and the gas quality monitoring unit respectively; The gas meter operation analysis unit is used to receive the operating status parameter information of each user's smart gas meter, and perform gas meter operating status determination and analysis processing, thereby generating a gas meter normal operation signal and a gas meter abnormal operation signal, and sending the gas meter abnormal operation signal to the early warning feedback analysis unit; The gas flow analysis unit is used to receive gas flow parameter information from each user's smart gas meter, perform gas flow determination and analysis, generate a normal gas flow fluctuation signal and an abnormal gas flow fluctuation signal based on the information, and send the abnormal gas flow fluctuation signal to the early warning feedback analysis unit; The gas quality monitoring unit is used to receive gas quality status parameter information of each user, and perform gas quality determination and analysis processing, thereby generating various types of gas quality abnormality feedback signals, and sending various types of gas quality abnormality feedback signals to the early warning feedback analysis unit.

3. The Internet-based smart gas cloud platform according to claim 2, characterized in that: Various types of gas quality abnormality feedback signals include gas quality deterioration signals caused by insufficient methane content, gas quality deterioration signals caused by high hydrogen sulfide content, gas quality deterioration signals caused by abnormal calorific value, gas quality deterioration signals caused by abnormal density, and gas quality deterioration signals caused by excessive humidity.

4. The Internet-based smart gas cloud platform according to claim 2, characterized in that: The specific execution steps of the gas meter working status determination and analysis process are as follows: Real-time monitoring is used to obtain the operating current of each monitoring time point per unit time from the working status parameter information of each user's smart gas meter, and the average value is calculated to obtain the average operating current of each user's smart gas meter per unit time. The reference operating current of the smart gas meter is extracted from the cloud storage library, and the operating current steady value of each user's smart gas meter is obtained through comprehensive analysis. ; Real-time monitoring is used to obtain the operating voltage of each monitoring time point per unit time from the working status parameter information of each user's smart gas meter, and the average value is calculated to obtain the average operating voltage of each user's smart gas meter per unit time. The reference operating voltage of the smart gas meter is extracted from the cloud storage library, and the operating voltage stability value of each user's smart gas meter is obtained through comprehensive analysis. ; Real-time monitoring is used to obtain the operating temperature of each monitoring time point per unit time from the working status parameter information of each user's smart gas meter, and the average value is calculated to obtain the average operating temperature of each user's smart gas meter per unit time. The reference operating temperature of the smart gas meter is extracted from the cloud storage library, and the operating temperature stability value of each user's smart gas meter is obtained through comprehensive analysis. ; According to the formula Calculate the operating coefficient of each user's smart gas meter , d1, d2, d3 are respectively represented as the set coefficient factors; Setting multiple control intervals for the working operation coefficient, and the multiple control intervals include a first working control interval and a second working control interval, and substituting the working operation coefficient of each user's smart gas meter into the pre-set multiple control intervals for comparative analysis, wherein the interval data values of the first working control interval and the second working control interval increase in a gradient; When the operating coefficient of a user's smart gas meter is within a pre-set first operating control interval, an abnormal operating signal of the smart gas meter is generated. When the operating coefficient of a user's smart gas meter is within a pre-set second operating control interval, a normal operating signal of the smart gas meter is generated.

5. The Internet-based smart gas cloud platform according to claim 2, characterized in that: The specific execution steps of the gas flow determination and analysis process are as follows: Real-time monitoring is used to obtain the cumulative gas flow of each user's smart gas meter per unit time. A two-dimensional dynamic coordinate system is established with time as the horizontal axis and the cumulative gas flow as the vertical axis. The cumulative gas flow per unit time is plotted on the two-dimensional dynamic coordinate system by connecting points, thereby obtaining the cumulative gas flow change curve of each user's smart gas meter; An upper reference line for cumulative flow and a lower reference line for cumulative flow are set in the cumulative gas flow change curve of each user's smart gas meter. The positions of the cumulative flow values at the upper reference line and the lower reference line in the two-dimensional dynamic coordinate system are recorded as abnormal points. At the same time, the collection time points corresponding to the two adjacent abnormal points are taken, and the collection time points corresponding to the two adjacent abnormal points are analyzed by difference to obtain the abnormal interval length. The number of abnormal points is thus counted and marked as , calculate the average value of all abnormal intervals to get the average abnormal interval time, and mark it as At the same time, the cumulative flow corresponding to all abnormal points is averaged to obtain the abnormal flow mean and marked as ; According to the formula Calculate the gas flow fluctuation assessment coefficient for each user , e1, e2, and e3 are respectively represented as the set weight factors; A gas flow fluctuation assessment coefficient threshold is set, and the gas flow fluctuation assessment coefficient of each user is compared and analyzed with the preset gas flow fluctuation assessment coefficient threshold. When the gas flow fluctuation assessment coefficient of a user is less than or equal to the preset gas flow fluctuation assessment coefficient threshold, a gas flow small fluctuation signal is generated; when the gas flow fluctuation assessment coefficient of a user is greater than the preset gas flow fluctuation assessment coefficient threshold, a gas flow large fluctuation signal is generated.

6. The Internet-based smart gas cloud platform according to claim 2, characterized in that: The specific execution steps of the gas quality determination and analysis process are as follows: Real-time monitoring obtains the methane content, hydrogen sulfide content, calorific value, density and humidity of each user's gas quality status parameter information per unit time, and marks them as , according to the set formula , get the gas quality assessment coefficient of each user , f1, f2, f3, f4, and f5 are the set correction factors respectively; Set a gas quality assessment coefficient threshold, and compare and analyze the gas quality assessment coefficient of each user with the preset gas quality assessment coefficient threshold. When the gas quality assessment coefficient of a user is greater than or equal to the preset gas quality assessment coefficient threshold, a gas quality normal signal is generated. When the gas quality assessment coefficient of a user is less than the preset gas quality assessment coefficient threshold, a gas quality abnormal signal is generated. Based on the generated gas quality abnormality signal, the cause of the gas quality abnormality is analyzed and processed, thereby obtaining the gas quality deterioration signal caused by insufficient methane content, the gas quality deterioration signal caused by high hydrogen sulfide content, the gas quality deterioration signal caused by abnormal calorific value, the gas quality deterioration signal caused by abnormal density, the gas quality deterioration signal caused by excessive humidity and irrelevant signals.

7. The Internet-based smart gas cloud platform according to claim 6, characterized in that: The specific steps for analyzing and processing the causes of abnormal gas quality are as follows: Obtain each gas quality status parameter and the preset threshold value corresponding to each gas quality status parameter in real time, and compare and analyze each gas quality status parameter with the corresponding preset threshold value; The methane content is compared with the preset methane content threshold. When the methane content is greater than or equal to the preset methane content threshold, an irrelevant signal is generated. When the methane content is less than the preset methane content threshold, a signal indicating insufficient methane content leading to poor air quality is generated. The hydrogen sulfide content is compared and analyzed with the preset hydrogen sulfide content threshold. When the hydrogen sulfide content is less than the preset hydrogen sulfide content threshold, an irrelevant signal is generated. When the hydrogen sulfide content is greater than or equal to the preset hydrogen sulfide content threshold, a signal indicating that the hydrogen sulfide content is too high and the air quality has deteriorated is generated. Compare and analyze the calorific value with the preset calorific value reference range. When the calorific value is within the preset calorific value reference range, an irrelevant signal is generated. When the calorific value is not within the preset calorific value reference range, a calorific value abnormality signal resulting in poor quality is generated. The density is compared and analyzed with the preset density reference interval. When the density is within the preset density reference interval, an irrelevant signal is generated. When the density is not within the preset density reference interval, a density abnormality leading to quality deterioration signal is generated. The humidity is compared and analyzed with the preset humidity threshold. When the humidity is less than or equal to the preset humidity threshold, an irrelevant signal is generated. When the humidity is greater than the preset humidity threshold, a signal indicating that the humidity is too high and the air quality has deteriorated is generated.

8. The Internet-based smart gas cloud platform according to claim 1, characterized in that: The early warning feedback analysis unit is used to receive different types of abnormal feedback signals for early warning analysis and processing, and to issue early warning information reminders through the user terminal and to perform abnormal fault type resolution operations through the control terminal.

9. The Internet-based smart gas cloud platform according to claim 1, characterized in that: The cloud storage library is used to store reference sound spectrograms corresponding to detection points in the external area of the gas pipeline, and to store reference operating current, operating voltage, and operating temperature of the smart gas meter.

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