Simulation model construction method applied to district heating efficiency evaluation

Abstract

The application discloses a simulation model construction method applied to regional heating efficiency evaluation, relates to the technical field of heating management, and improves heating energy utilization efficiency.The application establishes multiple heating evaluation models through heating thermal parameters and user energy consumption data, divides a current heating quarter period into a plurality of heating detection time points, collects real-time heating thermal parameters and real-time user energy consumption data and inputs the real-time heating thermal parameters and the real-time user energy consumption data into the multiple heating evaluation models whenever a heating detection time point starts, then obtains required fuel quantity under the corresponding heating detection time point according to the energy consumption relationship among a heat source evaluation model, a pipe network evaluation model and a user energy efficiency evaluation model, and detects whether the transmission and distribution pipe network is abnormal.

Description

Technical Field

[0001] The present invention relates to the technical field of heating management, and in particular to a method for constructing a simulation model applied to district heating efficiency evaluation. Background Art

[0002] As a vital component of urban infrastructure, district heating systems play a key role in ensuring residents stay warm during the winter and ensuring the smooth operation of industrial production. Traditional district heating management models often rely on experience and extensive regulation, lacking precise monitoring and scientific evaluation of all aspects of the heating system.

[0003] In terms of heat source supply, the lack of real-time and accurate understanding of the actual thermal parameters of heat source output often leads to a mismatch between energy supply and actual demand, resulting in energy waste or insufficient supply. For example, in some cases, the heat source oversupplies heat, resulting in a large amount of heat energy being wasted during transmission and use; in other cases, insufficient supply may cause some users' indoor temperatures to fail to meet standards.

[0004] As the conduit for heat transfer, the operational status of the distribution network directly impacts heating effectiveness. However, due to the widespread distribution and complex structure of the network, traditional methods struggle to detect anomalies such as leaks and blockages. This not only causes heat loss but can also impact the stability and reliability of the entire heating system.

[0005] On the user side, different users have different energy consumption demands, but the traditional heating management model makes it difficult to accurately analyze and regulate the actual energy consumption of users, unable to achieve personalized heating services, and is not conducive to improving energy utilization efficiency. Therefore, a simulation model construction method for regional heating efficiency evaluation is provided. Summary of the Invention

[0006] In order to solve the above technical problems, the purpose of the present invention is to provide a simulation model construction method for district heating efficiency evaluation.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] The simulation model construction method for district heating efficiency evaluation includes the following steps:

[0009] Step S1: deploying multiple data collection devices at the heat source supply station, transmission and distribution network, and user terminals in the district heating system, setting a heating quarterly cycle, and then collecting heating thermal parameters and user energy consumption data of the district heating system in each heating quarterly cycle;

[0010] Step S2: establishing a multiple heating evaluation model based on heating thermal parameters and user energy consumption data, wherein the multiple heating evaluation model includes a heat source evaluation model, a pipe network evaluation model, a user energy efficiency evaluation model, and a regional visualization model;

[0011] Step S3: Divide the current heating season cycle into several heating detection time points. Whenever a heating detection time point begins, collect real-time heating thermal parameters and real-time user energy consumption data and input them into the multiple heating evaluation model. Then, according to the energy consumption relationship between the heat source evaluation model, the pipeline network evaluation model and the user energy efficiency evaluation model, obtain the required amount of fuel at the corresponding heating detection time point, and detect whether there is any abnormality in the transmission and distribution pipeline network.

[0012] Furthermore, the heat source supply station is used to produce heating heat source and input the heating heat source into the transmission and distribution network;

[0013] The transmission and distribution network is directly connected to each user area and is used to transmit the heating heat source to each user area according to the heating demand of each user area, and the user area refers to the residential area;

[0014] Temperature sensors, pressure sensors, flow meters and user heat meters are deployed at heat source supply stations, distribution pipelines and user areas, and the same data upload frequency is set for each collection device.

[0015] Furthermore, the process of collecting heating thermal parameters and user energy consumption data includes:

[0016] A heating quarterly cycle is set, and each time a heating quarterly cycle begins, each collection device collects various heating parameter data or user energy consumption data at the location;

[0017] The heating parameter data includes the supply water temperature change curve, the return water temperature change curve, the pipeline pressure change value and the flow curve; the user energy consumption data includes the cumulative heat consumption, the indoor temperature value, the user's target heating temperature and the supply and return water temperature difference;

[0018] Whenever a data upload cycle ends, each collection device uploads the data it has collected, and at the same time obtains the fuel usage of the source supply station during the data upload cycle, and then obtains the heating thermal parameters and user energy consumption data of each heating quarter cycle.

[0019] Furthermore, the process of establishing the regional visualization model includes:

[0020] Obtaining a district heating system structure diagram, the district heating system structure diagram including the spatial location distribution of heat source supply stations, transmission and distribution pipelines, and user areas;

[0021] Then, a regional visualization model is established according to the district heating system structure diagram. The regional visualization model includes a heat source supply station model part, a transmission and distribution network model part, and a user area model. The transmission and distribution network model part is connected to the heat source supply station model part and the user area model, and each user area model is numbered a1, a2, a3, ..., a n , n is a natural number greater than 0;

[0022] The transfer points of the distribution pipelines in each distribution network model are recorded as temperature sensitive points and pressure fluctuation points.

[0023] Furthermore, the process of establishing the heat source assessment model includes:

[0024] According to the historical supply water temperature change curve, historical return water temperature change curve and historical fuel usage of the heat source supply station in the most recent heating quarter cycle, the dynamic equation of the heat source output power under different fuel usage in the heating quarter cycle is obtained.

[0025] Furthermore, the process of establishing the pipeline network assessment model includes:

[0026] According to the location distribution of each acquisition device in the distribution network and the distribution of temperature-sensitive points and pressure fluctuation points, the distribution network model is divided into several pipe section units. Then, based on the three most recent supply water temperature change curves, return water temperature change curves, pipeline pressure change values ​​and flow curves, the standard pressure-flow velocity equation of each pipe section unit is obtained.

[0027] Furthermore, the process of establishing the user energy efficiency evaluation model includes:

[0028] The historical user energy consumption data of each user area over m heating seasons is retrieved. Based on the principles of thermodynamics, the user area is set to a uniform thermal environment. At the same time, since the heating season for indoor heating is generally winter, the heating efficiency fluctuates as the temperature difference between indoor and outdoor continues to increase. Here, m is a natural number greater than 20.

[0029] Then, multiple indoor temperature intervals are set. Based on the indoor temperature values ​​contained in the historical user energy consumption data, the historical user energy consumption data of each heating quarter is grouped. Then, based on the historical cumulative heat consumption and the supply and return water temperature difference in the same group of historical user energy consumption data, the heating efficiency under different indoor temperature intervals is obtained.

[0030] The heat source assessment model, user energy efficiency assessment model and pipe network assessment model are marked in the corresponding positions of the multiple heating assessment model.

[0031] Furthermore, the process of obtaining the required fuel quantity at the heating detection time point includes:

[0032] Each data upload period within the heating quarterly cycle is recorded as a heating detection time point. Then, at the beginning of the most recent heating quarterly cycle, each collection device collects various real-time heating parameter data and real-time user energy consumption data at its location, and annotates the real-time heating parameter data and real-time user energy consumption data in the multiple heating evaluation model;

[0033] The district heating system detects the heating demand uploaded by each user area and marks the heating demand on the corresponding user area model in the multiple heating assessment model. The heating demand includes the demand time period and the required heating temperature.

[0034] Whenever a heating detection time point begins, the user area model with heating demand is traversed from the multiple heating evaluation models, and the heating life cycle is set for the corresponding user area model according to the demand period in the heating demand;

[0035] In the multiple heating evaluation model, the pipe segment units associated between the user area model and the heat source supply station model are traversed and the corresponding heating pipe chain is generated. The required heating temperature and the real-time indoor temperature are then input into the user energy efficiency evaluation model and the corresponding pipe network evaluation model in sequence.

[0036] The heating pipe chains between the same pair of heating detection time points are overlapped and merged according to the same pipe section units;

[0037] Based on the user area model and the pipe network assessment model, the required heat between each pair of heating detection time points is hierarchically summarized and the summary results are input into the heat source supply station model. The heat source supply station model then outputs the required fuel quantity based on the summary results.

[0038] Furthermore, the process of detecting whether there is an abnormality in the transmission and distribution network includes:

[0039] According to the real-time flow curve of each pipe section unit, the expected pipeline pressure value of each pipe section unit is obtained, the pipe pressure change detection interval is set, and the expected pipeline pressure value is compared with the corresponding real-time pipeline pressure change value. If the difference between the real-time pipeline pressure change value and the pressure exceeding the threshold value is within the pipe pressure change detection interval, no operation is performed. Otherwise, it is judged that the corresponding pipe section unit has an abnormality, and then an abnormal maintenance prompt is sent to the staff according to the number of the corresponding pipe section unit.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. This invention establishes multiple heating assessment models based on collected heating thermal parameters and user energy consumption data. These models include a heat source assessment model, a pipe network assessment model, a user energy efficiency assessment model, and a regional visualization model. These models comprehensively evaluate the district heating system from different perspectives, enabling in-depth analysis of energy consumption and operational efficiency across the heat source, pipe network, and user end points, providing a scientific basis for optimizing the heating system.

[0042] 2. By dividing the current heating season into several heating test points, real-time heating thermal parameters and user energy consumption data are collected at the beginning of each heating test point and input into the multi-heating assessment model. This enables real-time assessment and dynamic regulation of the heating system. Based on the actual conditions at different heating test points, the required fuel quantity is accurately calculated, avoiding energy waste or insufficient supply and improving energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention.

[0044] Figure 1 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0045] To make the objectives, technical solutions, and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other implementations obtained by those of ordinary skill in the art without inventive effort are within the scope of protection of the present invention.

[0046] like Figure 1 As shown in FIG, the simulation model construction method for district heating efficiency evaluation includes the following steps:

[0047] Step S1: deploying multiple data collection devices at the heat source supply station, transmission and distribution network, and user terminals in the district heating system, setting a heating quarterly cycle, and then collecting heating thermal parameters and user energy consumption data of the district heating system in each heating quarterly cycle;

[0048] Step S2: establishing a multiple heating evaluation model based on heating thermal parameters and user energy consumption data, wherein the multiple heating evaluation model includes a heat source evaluation model, a pipe network evaluation model, a user energy efficiency evaluation model, and a regional visualization model;

[0049] Step S3: Divide the current heating season cycle into several heating detection time points. Whenever a heating detection time point begins, collect real-time heating thermal parameters and real-time user energy consumption data and input them into the multiple heating evaluation model. Then, according to the energy consumption relationship between the heat source evaluation model, the pipeline network evaluation model and the user energy efficiency evaluation model, obtain the required amount of fuel at the corresponding heating detection time point, and detect whether there is any abnormality in the transmission and distribution pipeline network.

[0050] Furthermore, step S1 is implemented by the following process:

[0051] The district heating system consists of a heat source supply station, a transmission and distribution network, and user areas, wherein the heat source supply station is used to produce heating heat and input the heating heat into the transmission and distribution network;

[0052] The transmission and distribution network is directly connected to each user area and is used to transmit the heating heat source to each user area according to the heating demand of each user area, and the user area refers to the residential area;

[0053] Deploy temperature sensors, pressure sensors, flow meters, and user heat meters at heat source supply stations, distribution pipelines, and user areas, and set the same data upload frequency for each collection device, which is generally 10 to 20 seconds.

[0054] It should be noted that due to the structure and spatial distribution of the transmission and distribution network, the temperature sensors, pressure sensors, and flow meters in each user area are used to collect various heating parameter data of the transmission and distribution network connected to it. At the same time, the various collection devices located in the transmission and distribution network are installed at the corners and middle positions of the transmission and distribution pipelines;

[0055] A heating quarterly cycle is set, and each time a heating quarterly cycle begins, each collection device collects various heating parameter data or user energy consumption data at the location;

[0056] The heating parameter data includes the supply water temperature change curve, the return water temperature change curve, the pipeline pressure change value and the flow curve; the user energy consumption data includes the cumulative heat consumption, the indoor temperature value, the user's target heating temperature and the supply and return water temperature difference;

[0057] Whenever a data upload cycle ends, each collection device uploads the data it has collected, and at the same time obtains the fuel usage of the source supply station during the data upload cycle, and then obtains the heating thermal parameters and user energy consumption data of each heating quarter cycle.

[0058] Furthermore, step S2 is implemented by the following process:

[0059] The multiple heating evaluation model consists of a heat source evaluation model, a pipe network evaluation model, a user energy efficiency evaluation model, and a regional visualization model;

[0060] The process of establishing the regional visualization model includes:

[0061] Obtaining a district heating system structure diagram, the district heating system structure diagram including the spatial location distribution of heat source supply stations, transmission and distribution pipelines, and user areas;

[0062] Then, a regional visualization model is established according to the district heating system structure diagram. The regional visualization model includes a heat source supply station model part, a transmission and distribution network model part, and a user area model. The transmission and distribution network model part is connected to the heat source supply station model part and the user area model, and each user area model is numbered a1, a2, a3, ..., a n , n is a natural number greater than 0;

[0063] The transfer points of the distribution pipelines in each distribution network model are recorded as temperature sensitive points and pressure fluctuation points.

[0064] The heat source assessment model includes:

[0065] Based on the historical supply water temperature change curve, historical return water temperature change curve, and historical fuel usage of the heat source supply station during the most recent heating season, the dynamic equation of the heat source output power under different fuel usage during the heating season is obtained:

[0066] ;

[0067] Where ŋ is the thermal efficiency, are water densities, and They represent the supply and return water temperatures, x represents the fuel usage, and represents the specific heat capacity at constant pressure and the heat of combustion of the fuel, and t represent the flow rate per unit time and the length of time.

[0068] The pipeline network assessment model includes:

[0069] Based on the location distribution of each data acquisition device in the distribution network and the distribution of temperature-sensitive points and pressure fluctuation points, the distribution network model is divided into several pipe section units. Then, based on the three most recent supply water temperature change curves, return water temperature change curves, pipeline pressure change values, and flow curves, the standard pressure-flow velocity equation for each pipe section unit is obtained.

[0070] The standard pressure-velocity equation is: ;

[0071] Indicates the pipeline pressure value of the pipe section unit at time t corresponding to the data upload period, f is the pipeline friction coefficient, L is the pipe section unit length, and D is the pipe section unit radius;

[0072] The user energy efficiency evaluation model includes:

[0073] The historical user energy consumption data of each user area over m heating seasons is retrieved. Based on the principles of thermodynamics, the user area is set to a uniform thermal environment. At the same time, since the heating season for indoor heating is generally winter, the heating efficiency fluctuates as the temperature difference between indoor and outdoor continues to increase. Here, m is a natural number greater than 20.

[0074] Then, multiple indoor temperature intervals are set. Based on the indoor temperature values ​​contained in the historical user energy consumption data, the historical user energy consumption data of each heating quarter is grouped. Then, based on the historical cumulative heat consumption and the supply and return water temperature difference in the same group of historical user energy consumption data, the heating efficiency μ under different indoor temperature intervals is obtained;

[0075] The formula for obtaining the heating efficiency is:

[0076] ;

[0077] Where k and α are proportional coefficients, t is the number of data upload cycles that have passed, Indicates the supply and return water temperature difference. Indicates the historical cumulative heat consumption during the numth data upload cycle, where num is a natural number greater than 0;

[0078] The heating efficiency formula for different heating seasons but the same indoor temperature range is iterated, and k and α are modified according to the iterative results.

[0079] The heat source assessment model, user energy efficiency assessment model and pipe network assessment model are marked in the corresponding positions of the multiple heating assessment model.

[0080] Furthermore, step S3 is implemented by the following process:

[0081] Each data upload period within the heating quarterly cycle is recorded as a heating detection time point. Then, at the beginning of the most recent heating quarterly cycle, each collection device collects various real-time heating parameter data and real-time user energy consumption data at its location, and annotates the real-time heating parameter data and real-time user energy consumption data in the multiple heating evaluation model;

[0082] It should be noted that the real-time water supply temperature change curve, real-time return water temperature change curve and real-time pipeline pressure change value of the transmission and distribution network are marked on the temperature sensitive points and pressure fluctuation points, and the real-time flow curve is marked on the pipe section unit;

[0083] The district heating system detects the heating demand uploaded by each user area and marks the heating demand on the corresponding user area model in the multiple heating assessment model. The heating demand includes the demand time period and the required heating temperature.

[0084] Whenever a heating detection time point begins, the user area model with heating demand is traversed from the multiple heating evaluation models, and the heating life cycle is set for the corresponding user area model according to the demand period in the heating demand;

[0085] In the multiple heating evaluation model, the pipe segment units associated between the user area model and the heat source supply station model are traversed and the corresponding heating pipe chain is generated. The required heating temperature and the real-time indoor temperature are then input into the user energy efficiency evaluation model and the corresponding pipe network evaluation model in sequence.

[0086] Since the same pipe segment unit manages multiple user area models at the same time, the heating pipe chains between the same pair of heating detection time points are overlapped and merged according to the same pipe segment unit;

[0087] Based on the user area model and the pipe network assessment model, the required heat between each pair of heating detection time points is hierarchically summarized and the summary results are input into the heat source supply station model. The heat source supply station model then outputs the required fuel quantity based on the summary results.

[0088] At the same time, based on the real-time flow curve of each pipe section unit, the estimated pipeline pressure value of each pipe section unit is obtained, and the pipe pressure change detection interval is set. The estimated pipeline pressure value is compared with the corresponding real-time pipeline pressure change value. If the difference between the real-time pipeline pressure change value and the pressure exceeding the threshold value is within the pipe pressure change detection interval, no operation is performed. Otherwise, it is judged that the corresponding pipe section unit has an abnormality, and then an abnormal maintenance prompt is sent to the staff according to the number of the corresponding pipe section unit;

[0089] Whenever a heating detection time point ends, it is determined whether the heating life cycle of the user area model has ended. If not, it will directly proceed to the next heating detection time point;

[0090] If it exists, the corresponding user area model will be ignored at the beginning of the next heating detection time point, and the above required fuel quantity determination will be repeated until all heating needs are met.

[0091] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A simulation model construction method for district heating efficiency evaluation, characterized in that: The following steps are involved: Step S1: deploying multiple data collection devices at the heat source supply station, transmission and distribution network, and user terminals in the district heating system, setting a heating quarterly cycle, and then collecting heating thermal parameters and user energy consumption data of the district heating system in each heating quarterly cycle; Step S2: establishing a multiple heating evaluation model based on heating thermal parameters and user energy consumption data, wherein the multiple heating evaluation model includes a heat source evaluation model, a pipe network evaluation model, a user energy efficiency evaluation model, and a regional visualization model; Step S3: Divide the current heating season cycle into several heating detection time points. Whenever a heating detection time point begins, collect real-time heating thermal parameters and real-time user energy consumption data and input them into the multiple heating evaluation model. Then, according to the energy consumption relationship between the heat source evaluation model, the pipeline network evaluation model and the user energy efficiency evaluation model, obtain the required amount of fuel at the corresponding heating detection time point, and detect whether there is any abnormality in the transmission and distribution pipeline network.

2. The method for constructing a simulation model for district heating efficiency evaluation according to claim 1, characterized in that: The heat source supply station is used to produce heating heat source and input the heating heat source into the transmission and distribution network; The transmission and distribution pipe network is directly connected to each user area and is used to transport the heating heat source to each user area according to the heating demand of each user area; Temperature sensors, pressure sensors, flow meters and user heat meters are deployed at heat source supply stations, transmission and distribution pipelines and user areas, and the same data upload frequency is set for each collection device.

3. The method for constructing a simulation model for district heating efficiency evaluation according to claim 2, characterized in that: The process of collecting heating thermal parameters and user energy consumption data includes: A heating quarterly cycle is set, and each time a heating quarterly cycle begins, each collection device collects various heating parameter data or user energy consumption data at the location; The heating parameter data includes the supply water temperature change curve, the return water temperature change curve, the pipeline pressure change value and the flow curve; the user energy consumption data includes the cumulative heat consumption, the indoor temperature value, the user's target heating temperature and the supply and return water temperature difference; Whenever a data upload cycle ends, each collection device uploads the data it has collected, and at the same time obtains the fuel usage of the source supply station during the data upload cycle, and then obtains the heating thermal parameters and user energy consumption data of each heating quarter cycle.

4. The method for constructing a simulation model for district heating efficiency evaluation according to claim 3, wherein: The process of establishing the regional visualization model includes: Obtaining a district heating system structure diagram, and establishing a regional visualization model based on the district heating system structure diagram, wherein the regional visualization model includes a heat source supply station model portion, a transmission and distribution pipeline network model portion, and a user area model; The transfer points of the distribution pipelines in each distribution network model are recorded as temperature sensitive points and pressure fluctuation points.

5. The method for constructing a simulation model for district heating efficiency evaluation according to claim 3, wherein: The process of establishing the heat source assessment model includes: According to the historical supply water temperature change curve, historical return water temperature change curve and historical fuel usage of the heat source supply station in the most recent heating quarter cycle, the dynamic equation of the heat source output power under different fuel usage in the heating quarter cycle is obtained.

6. The method for constructing a simulation model for district heating efficiency evaluation according to claim 3, characterized in that: The process of establishing the pipeline network assessment model includes: According to the location distribution of each acquisition device in the distribution network and the distribution of temperature-sensitive points and pressure fluctuation points, the distribution network model is divided into several pipe section units. Then, based on the three most recent supply water temperature change curves, return water temperature change curves, pipeline pressure change values ​​and flow curves, the standard pressure-flow velocity equation of each pipe section unit is obtained.

7. The method for constructing a simulation model for district heating efficiency evaluation according to claim 3, wherein: The process of establishing the user energy efficiency evaluation model includes: Set multiple indoor temperature ranges, group historical user energy consumption data for each heating quarter based on the indoor temperature values ​​contained in historical user energy consumption data, and obtain heating efficiency under different indoor temperature ranges based on the historical cumulative heat consumption and supply and return water temperature difference in the same group of historical user energy consumption data; The heat source assessment model, user energy efficiency assessment model and pipe network assessment model are marked in the corresponding positions of the multiple heating assessment model.

8. The method for constructing a simulation model for district heating efficiency evaluation according to claim 7, characterized in that: The process of obtaining the required fuel quantity at the heating detection time point includes: Each data upload period within the heating quarterly cycle is recorded as a heating detection time point. Then, at the beginning of the most recent heating quarterly cycle, each collection device collects various real-time heating parameter data and real-time user energy consumption data at its location, and annotates the real-time heating parameter data and real-time user energy consumption data in the multiple heating evaluation model; The district heating system detects the heating demand uploaded by each user area and marks the heating demand on the corresponding user area model in the multiple heating assessment model. The heating demand includes the demand time period and the required heating temperature. Whenever a heating detection time point begins, the user area model with heating demand is traversed from the multiple heating evaluation models, and the heating life cycle is set for the corresponding user area model according to the demand period in the heating demand; In the multiple heating evaluation model, the pipe segment units associated between the user area model and the heat source supply station model are traversed and the corresponding heating pipe chain is generated. The required heating temperature and the real-time indoor temperature are then input into the user energy efficiency evaluation model and the corresponding pipe network evaluation model in sequence. Based on the user area model and the pipeline network assessment model, the required heat between each pair of heating detection time points is hierarchically summarized, and the summary results are input into the heat source supply station model. The heat source supply station model then outputs the required fuel quantity based on the summary results.

9. The method for constructing a simulation model for district heating efficiency evaluation according to claim 8, characterized in that: The process of detecting whether there are any abnormalities in the transmission and distribution network includes: According to the real-time flow curve of each pipe section unit, the expected pipeline pressure value of each pipe section unit is obtained, the pipe pressure change detection interval is set, and the expected pipeline pressure value is compared with the corresponding real-time pipeline pressure change value. If the difference between the real-time pipeline pressure change value and the pressure exceeding the threshold value is within the pipe pressure change detection interval, no operation is performed; otherwise, it is judged that the corresponding pipe section unit has an abnormality.

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