Heat tracing system temperature monitoring and early warning method and system

Abstract

The invention provides a heat tracing system temperature monitoring and early warning method and system, and belongs to the technical field of temperature monitoring and early warning, and the method comprises the steps: 1, obtaining a plurality of field nodes of a heat tracing system, deploying a preset collection device on each field node, and carrying out the real-time collection of the heat tracing temperature of each field node; 2, packaging the collected real-time temperature data, and sending the packaged real-time temperature data to a corresponding team receiving device; 3, the received real-time temperature data are processed and transmitted to a cloud platform; 4, acquiring historical temperature data of each field node in the heat tracing system, determining a plurality of temperature judgment threshold values, and then sending out an alarm signal; and 5, constructing a multi-level management view based on the real-time temperature data of all the field nodes and the alarm state, and then obtaining a temperature monitoring result, thereby effectively improving the temperature monitoring efficiency and early warning timeliness of the heat tracing system, and remarkably enhancing the stability and safety of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature monitoring and early warning, and in particular to a method and system for temperature monitoring and early warning of a heating system. Background Art

[0002] At present, heat tracing systems are widely used in industrial and civil fields, usually to keep equipment and pipelines running normally in cold conditions. However, existing temperature monitoring solutions for heat tracing systems mostly rely on single data node monitoring or regular testing, resulting in the inability to detect and handle temperature anomalies in a timely manner, affecting the overall safety and stability of the system.

[0003] The closest existing technical solution is a system based on single-layer node temperature monitoring, which realizes a simple alarm function by transmitting temperature anomalies layer by layer. However, its detection accuracy is limited, the monitoring area is difficult to cover the entire system, and real-time dynamic warning is impossible. Based on the defects of the above-mentioned existing technical solutions, this solution is difficult to adapt to the multi-level and full-coverage heating system temperature monitoring needs, and has problems such as poor real-time performance and delayed response.

[0004] Therefore, the present invention provides a method and system for monitoring and warning the temperature of a heating system. Summary of the invention

[0005] The present invention provides a method and system for temperature monitoring and early warning of a heating system, which is used to build a multi-level temperature monitoring and early warning system through multi-node real-time temperature collection, historical data threshold analysis and cloud management, and realizes full node coverage, real-time early warning and management visualization, effectively improving the temperature monitoring efficiency and early warning timeliness of the heating system, and significantly enhancing the stability and safety of the system.

[0006] The present invention provides a method for monitoring and warning the temperature of a heating system, comprising:

[0007] Step 1: Acquire several field nodes of the heating system, and deploy a preset acquisition device on each field node to collect the heating temperature of each field node in real time;

[0008] Step 2: Pack the collected real-time temperature data and send it to the corresponding team receiving device;

[0009] Step 3: Process the received real-time temperature data and transmit it to the cloud platform;

[0010] Step 4: Obtain the historical temperature data of each field node in the heating system, and determine several temperature judgment thresholds in combination with the processed real-time temperature data, and then issue an alarm signal;

[0011] Step 5: Build a multi-level management view based on the real-time temperature data and alarm status of all field nodes to obtain temperature monitoring results.

[0012] The present invention provides a method for monitoring and early warning the temperature of a heating system, which obtains a plurality of field nodes of the heating system and deploys a preset acquisition device on each field node to collect the heating temperature of each field node in real time, including:

[0013] Conduct structural analysis on the heating system and obtain several parts of the heating system;

[0014] Based on the preset model, heat loss analysis is performed on all parts of the heating system, thereby determining a plurality of first parts and second parts of the heating system;

[0015] Determine a first location of the heat tracing system as a first field node, and determine a second location of the heat tracing system as a second field node;

[0016] Installing a temporary temperature sensor on each first field node and the second field node, acquiring corresponding temperature change data, and verifying the temperature data based on a preset method;

[0017] Determine the first on-site node that passes the verification as the third on-site node, and at the same time, determine the second on-site node that passes the verification as the fourth on-site node;

[0018] Deploy the first acquisition device on each third field node, and deploy the second acquisition device on each fourth field node;

[0019] The heating temperatures of the third field node and the fourth field node are collected in real time based on the first collection device and the second collection device.

[0020] The present invention provides a method for monitoring and warning the temperature of a heating system, which packages the collected real-time temperature data and sends the packaged data to a corresponding team receiving device, including:

[0021] Pack the collected real-time temperature data and obtain relevant key information of the data packet;

[0022] Generate a first matching code for each data packet based on key information of the data packet and a preset identification rule;

[0023] Determine a first matching coefficient of the data packet based on key information related to the data packet;

[0024] Preliminarily matching the data packet with the receiving team device based on the first matching code and the first matching coefficient of the data packet, thereby obtaining a plurality of first data packets corresponding to each receiving team;

[0025] Encoding each first data packet based on a preset encoding rule, thereby generating a second matching code for each data packet;

[0026] Perform a preliminary match based on the second matching code of the first data packet with the receiving team device to verify the match;

[0027] The first data packet after verification and matching is sent to the corresponding team receiving device.

[0028] The present invention provides a method for monitoring and warning the temperature of a heating system, which determines a first matching coefficient of a data packet based on key information related to the data packet, and includes:

[0029] Determine the first matching coefficient of the data packet based on the relevant key information of the data packet:

[0030]

[0031] Among them, Q i is the first matching coefficient of the ith data packet, α1 i is the weight coefficient of the size of the i-th data packet, X i is the size of the ith data packet, α2 i is the weight coefficient of the timestamp coefficient of the ith data packet, T i is the timestamp coefficient of the ith data packet, α3 i is the weight coefficient of the temperature node factor of the ith data packet, N i is the temperature node factor of the ith data packet, α4 i is the weight coefficient of the device characteristic factor of the ith data packet, D i is the device characteristic factor of the ith data packet, Q1 i is the basic matching coefficient of the ith data packet.

[0032] The present invention provides a method for monitoring and warning the temperature of a heating system, which processes the received real-time temperature data and transmits it to a cloud platform, including:

[0033] Obtain and analyze the historical operating data of the heating system to determine the overall normal operating temperature range of the heating system and determine the preliminary temperature threshold of the heating system;

[0034] When the received temperature data of the field node is greater than the preliminary temperature threshold, the corresponding field node is marked as abnormal;

[0035] The real-time temperature and marking status of each field node are transmitted to the cloud platform.

[0036] The present invention provides a method for monitoring and warning the temperature of a heating system, which obtains the historical temperature data of each field node in the heating system, and determines several temperature judgment thresholds in combination with the processed real-time temperature data, and then issues an alarm signal, including:

[0037] Retrieve the historical temperature data of each field node from the preset local storage;

[0038] Analyze the historical temperature data of all field nodes to determine the normal temperature range of each field node;

[0039] determining a historical temperature threshold for each field node based on a normal temperature range for each field node;

[0040] Determine a number of temperature judgment thresholds corresponding to each field node based on the historical temperature threshold, real-time temperature and a preset method of each field node;

[0041] Determine the real-time temperature state of each field node based on the real-time temperature of each field node and the corresponding temperature judgment threshold;

[0042] Generate alarm signals based on the real-time temperature status and abnormal mark status of each field node.

[0043] The present invention provides a temperature monitoring and early warning method for a heating system.

[0044] Abnormal marking status, including: high temperature or low temperature exceeding limit marking, abnormal temperature fluctuation marking;

[0045] Real-time temperature status, including: normal status, temperature exceeding limit status, abnormal high temperature status, abnormal low temperature status, abnormal temperature fluctuation status and abnormal temperature stagnation status.

[0046] The present invention provides a temperature monitoring and early warning system for a heating system, comprising:

[0047] Temperature acquisition module: obtains several field nodes of the heating system, and deploys a preset acquisition device on each field node to collect the heating temperature of each node in real time;

[0048] Data receiving module: packages the collected real-time temperature data and sends it to the corresponding team receiving device;

[0049] Data transmission module: processes the received real-time temperature data and transmits it to the cloud platform;

[0050] Temperature alarm module: obtains the historical temperature data of each field node in the heating system, and determines several temperature judgment thresholds based on the processed real-time temperature data, and then issues an alarm signal;

[0051] Result acquisition module: Build a multi-level management view based on the real-time temperature data and alarm status of all on-site nodes to obtain temperature monitoring results.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] Through multi-node real-time temperature collection, historical data threshold analysis and cloud management, a multi-level temperature monitoring and early warning system has been built, achieving full node coverage, real-time early warning and management visualization, effectively improving the temperature monitoring efficiency and early warning timeliness of the heating system, and significantly enhancing the stability and safety of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 The present invention is a flow chart of a method for monitoring and warning the temperature of a heating system provided by an embodiment of the present invention.

[0056] Figure 2 It is a structural schematic diagram of a temperature monitoring and early warning system for a heating system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are 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 creative work are within the scope of protection of the present invention.

[0058] Example 1

[0059] The embodiment of the present invention provides a method for monitoring and warning the temperature of a heating system. Figure 1 As shown, including:

[0060] Step 1: Acquire several field nodes of the heating system, and deploy a preset acquisition device on each field node to collect the heating temperature of each field node in real time;

[0061] Step 2: Pack the collected real-time temperature data and send it to the corresponding team receiving device;

[0062] Step 3: Process the received real-time temperature data and transmit it to the cloud platform;

[0063] Step 4: Obtain the historical temperature data of each field node in the heating system, and determine several temperature judgment thresholds in combination with the processed real-time temperature data, and then issue an alarm signal;

[0064] Step 5: Build a multi-level management view based on the real-time temperature data and alarm status of all field nodes to obtain temperature monitoring results.

[0065] In this embodiment, field nodes are multiple location points set in the heat tracing system, each of which requires real-time temperature monitoring. These nodes are usually pipelines, valves or other key device parts, which are easily affected by temperature changes. For example, a chemical plant pipeline is equipped with multiple field nodes to monitor the temperature during the transportation of raw materials to ensure that the pipeline does not freeze or overheat;

[0066] In this embodiment, the preset acquisition device is a temperature sensing device installed at each field node, which is used to collect heating temperature data in real time. These devices usually have built-in sensors, data collection modules, etc., and support data packaging and transmission. For example, a thermocouple sensor installed at each node sends temperature data to a receiving system at a regular interval;

[0067] In this embodiment, the heating temperature refers to the temperature value of the nodes such as pipelines and valves in the heating system during actual operation, which is usually maintained within a specific range with the help of heating equipment. For example, the pipeline transporting crude oil in winter needs to maintain the heating temperature between 10-15 degrees Celsius to prevent the oil from waxing.

[0068] In this embodiment, the team receiving device is a terminal device for team operators to view temperature data in real time. These devices can be handheld terminals, workstation computers or other information receiving tools, which are convenient for operators to find temperature anomalies in time. For example, the receiving display in the control room can display the temperature information of each node in real time and warn the team members of temperature anomalies.

[0069] In this embodiment, the temperature judgment threshold is a reference range obtained by comparing historical data with real-time data, which is used to determine whether the temperature is abnormal. When the temperature exceeds or falls below the threshold, the system triggers an alarm signal so that timely measures can be taken. For example, when the pipeline temperature is lower than 5 degrees Celsius or higher than 20 degrees Celsius, the system triggers an alarm signal to prompt the team to immediately repair the heating device.

[0070] In this embodiment, the alarm status shows whether there is a temperature abnormality point in the current system;

[0071] In this embodiment, the multi-level management view is a display interface constructed based on all node data, which visualizes the on-site situation by level such as team, workshop, and factory area;

[0072] In this embodiment, the temperature monitoring result is an analysis conclusion based on the temperature data and alarm status of each node to assist management personnel in making decisions. For example, the multi-level management view displayed on the factory's main control panel can clearly see the temperature conditions of each workshop and the alarm status of each field node.

[0073] The beneficial effects of the above technical solution are: through multi-node real-time temperature collection, historical data threshold analysis and cloud management, a multi-level temperature monitoring and early warning system is built, achieving full node coverage, real-time early warning and management visualization, effectively improving the temperature monitoring efficiency and early warning timeliness of the heating system, and significantly enhancing the stability and safety of the system.

[0074] Example 2

[0075] The embodiment of the present invention provides a temperature monitoring and early warning method for a heating system, which obtains a plurality of field nodes of the heating system and deploys a preset acquisition device on each field node to collect the heating temperature of each field node in real time, including:

[0076] Conduct structural analysis on the heating system and obtain several parts of the heating system;

[0077] Based on the preset model, heat loss analysis is performed on all parts of the heating system, thereby determining a plurality of first parts and second parts of the heating system;

[0078] Determine a first location of the heat tracing system as a first field node, and determine a second location of the heat tracing system as a second field node;

[0079] Installing a temporary temperature sensor on each first field node and the second field node, acquiring corresponding temperature change data, and verifying the temperature data based on a preset method;

[0080] Determine the first on-site node that passes the verification as the third on-site node, and at the same time, determine the second on-site node that passes the verification as the fourth on-site node;

[0081] Deploy the first acquisition device on each third field node, and deploy the second acquisition device on each fourth field node;

[0082] The heating temperatures of the third field node and the fourth field node are collected in real time based on the first collection device and the second collection device.

[0083] In this embodiment, the heat loss analysis is heat conduction loss: calculate the heat loss from the heating pipe and components (such as joints, valves, etc.) to the surrounding environment through heat conduction, especially in areas with poor insulation effect; convection loss: analyze the convection heat exchange between the outer surface of the heating system and the environment, especially in outdoor pipes with high wind speed, the convection loss increases significantly; radiation loss: usually the radiation heat loss of the heating system is small, but it may be reflected in high temperature or long distance pipes;

[0084] In this embodiment, the first location is a location with large heat loss. These locations are usually located in long straight pipe sections, areas where insulation materials are aged, or relatively exposed pipe sections;

[0085] In this embodiment, the second location is a "cold spot" in the heating system, that is, a location where the temperature is most likely to drop, and it is ensured that the temperature at this location does not fall below a safe temperature.

[0086] In this embodiment, the first field node and the second field node refer to important parts determined through heat loss analysis in the heating system. These parts will experience different heat loss conditions during the heating process. Therefore, they are divided into first and second type nodes according to different needs to perform more accurate temperature monitoring. For example, in a long-distance pipeline heating system, the area close to the valve is designated as the first field node because the metal material is easy to conduct heat, while the low heat loss part in the middle section of the pipeline is designated as the second field node, which is convenient for selecting different monitoring schemes.

[0087] In this embodiment, the preset method refers to a standardized step for verifying the collected temperature data to confirm the accuracy of temperature collection and the validity of the data, including data screening, smoothing, etc., to ensure that the data can reflect the actual temperature changes;

[0088] In this embodiment, temperature data is temperature information acquired in real time by the acquisition device, which serves as the basis for system early warning and analysis. For example, a preset method is used to verify the temperature data, such as comparing the average temperature with the historical normal value, screening out abnormal data fluctuations caused by equipment interference, and ensuring that the temperature data fed back by the sensor is true and reliable.

[0089] In this embodiment, the third field node and the fourth field node are the first and second nodes that have been temperature verified, that is, nodes that have been verified by a preset method and have stable temperature data. These nodes are more representative and can be further used for actual heating temperature monitoring and early warning. For example, after verification, the original first node in the heating pipeline of a factory is located at the valve. After verification, the data is confirmed to be stable, so this point is determined as the third field node, and the middle pipeline position is determined as the fourth field node for subsequent temperature monitoring.

[0090] In this embodiment, the first acquisition device and the second acquisition device refer to temperature sensing devices used for the third and fourth field nodes, respectively. According to the heat loss characteristics of different nodes, these devices may have different sensitivities or data processing functions to meet the monitoring requirements of their respective areas. For example, the first acquisition device is equipped with a high-precision temperature sensor, which is specially used for the third field node with high heat loss to capture small temperature differences in time, while the second acquisition device uses equipment suitable for long-term and stable monitoring, and is mainly deployed in the fourth field node with lower heat loss.

[0091] The beneficial effects of the above technical solution are: by conducting structural analysis and heat loss analysis on the heating system, innovatively determining the on-site nodes, and deploying temperature sensors to achieve real-time monitoring. This method ensures the accuracy and reliability of temperature data, screens valid nodes through a verification mechanism, optimizes the data acquisition process, and through the first and second acquisition devices, the system can obtain the heating temperature of key nodes in real time, improves the comprehensiveness and responsiveness of monitoring, and enhances the safety and efficiency of the heating system.

[0092] Example 3

[0093] The embodiment of the present invention provides a temperature monitoring and early warning method for a heat tracing system, which packages the collected real-time temperature data and sends the packaged data to a corresponding team receiving device, including:

[0094] Pack the collected real-time temperature data and obtain relevant key information of the data packet;

[0095] Generate a first matching code for each data packet based on key information of the data packet and a preset identification rule;

[0096] Determine a first matching coefficient of the data packet based on key information related to the data packet;

[0097] Preliminarily matching the data packet with the receiving team device based on the first matching code and the first matching coefficient of the data packet, thereby obtaining a plurality of first data packets corresponding to each receiving team;

[0098] Encoding each first data packet based on a preset encoding rule, thereby generating a second matching code for each data packet;

[0099] Perform a preliminary match based on the second matching code of the first data packet with the receiving team device to verify the match;

[0100] The first data packet after verification and matching is sent to the corresponding team receiving device.

[0101] In this embodiment, key information refers to the core content extracted from each data packet when packaging temperature data, which is used to distinguish and identify the attributes of different data packets. This information usually includes the collection time, node location, temperature range, etc., so as to provide a basic identification basis for data transmission and matching. For example, the key information of a data packet includes the collection time of "2024-10-30 12:00", the temperature of 15°C, and the node location of "Pipeline Section A Valve 1".

[0102] In this embodiment, the preset identification rule is used to generate a unique identification for each data packet, and a corresponding matching code is generated according to the key information in a set format or rule;

[0103] In this embodiment, the first matching code is a preliminary code generated by a preset identification rule, which is used to identify the attribution or priority of the data packet. For example, the preset identification rule may require "date-node number-temperature range" as the encoding format, and the generated first matching code of the data packet may be "20241030-A1-15".

[0104] In this embodiment, the first matching coefficient is a weight or priority coefficient related to the data packet generated based on key information, which is used to help the team receiving device determine the importance of the data packet or the accuracy of the match. The matching coefficient is generated in combination with temperature fluctuations or node importance. For example, when the node temperature fluctuates greatly, the matching coefficient is set to a higher value (such as 0.9), while a lower matching coefficient (such as 0.3) is set for a more stable node, so that the receiving device gives priority to receiving high-priority data packets.

[0105] In this embodiment, the preliminary matching refers to preliminary matching and screening of the first matching code and the first matching coefficient of the data packet with the requirements or preference conditions of the receiving team equipment to find the data packet that best meets the requirements;

[0106] In this embodiment, the first data packet is a data packet that meets the conditions of the team receiving device after preliminary matching. For example, a team receiving device only receives data packets from a specific area. The system will perform preliminary matching based on the matching code and matching coefficient, and finally filter out the first data packet that meets the conditions.

[0107] In this embodiment, the preset encoding rule is a further rule for encoding according to the data packet attributes, generating a second matching code to improve matching accuracy;

[0108] In this embodiment, the second matching code provides more detailed information to facilitate accurate comparison during the verification and matching process. For example, the preset encoding rule requires that the matching code be further added with a timestamp and data version information to generate a second matching code, such as "20241030-A1-15-v2".

[0109] In this embodiment, verification matching refers to the final comparison of the second matching code of the first data packet after preliminary matching with the team receiving device to ensure that the data packet can be sent only after it is accurate. This process helps filter out incorrectly matched packets and improves the accuracy of data transmission. For example, in the verification matching stage, the system compares the second matching code again, and after confirming that the matching accuracy with the team receiving device meets the requirements, the data packet is sent to the team terminal.

[0110] The beneficial effects of the above technical solution are: by packaging and matching the real-time temperature data, the first matching code and the first matching coefficient are innovatively introduced, and combined with the preset identification rules and coding rules, efficient classification and accurate transmission of data are achieved, and the matching accuracy between the data packet and the team receiving equipment is improved, ensuring the timely and accurate delivery of temperature monitoring information, enhancing the monitoring capability and early warning effect of the heating system, and improving the overall operation efficiency of the system.

[0111] Example 4

[0112] An embodiment of the present invention provides a temperature monitoring and early warning method for a heating system, which determines a first matching coefficient of a data packet based on key information related to the data packet, including:

[0113] Determine the first matching coefficient of the data packet based on the relevant key information of the data packet:

[0114]

[0115] Among them, Q i is the first matching coefficient of the ith data packet, α1 i is the weight coefficient of the size of the i-th data packet, X i is the size of the ith data packet, α2 i is the weight coefficient of the timestamp coefficient of the ith data packet, T i is the timestamp coefficient of the ith data packet, α3 i is the weight coefficient of the temperature node factor of the ith data packet, N i is the temperature node factor of the ith data packet, α4 i is the weight coefficient of the device characteristic factor of the ith data packet, D i is the device characteristic factor of the ith data packet, Q1 i is the basic matching coefficient of the ith data packet.

[0116] In this embodiment, the timestamp coefficient refers to a value related to the data packet collection time, which is used to reflect the real-time and validity of the data packet. Generally, the closer the data packet is to the current time, the higher its timestamp coefficient is, so as to ensure that the latest data is processed first. Assuming that the current time is "2024-10-30 12:00", if the collection time of a data packet is "2024-10-3011:59", its timestamp coefficient may be 0.9; and if the collection time is "2024-10-3010:00", the timestamp coefficient may be reduced to 0.5;

[0117] In this embodiment, the temperature node factor refers to a value related to the characteristics of a specific temperature monitoring node, which usually reflects the importance of the node, historical temperature fluctuations or stability, etc. This factor is used to evaluate the impact of different nodes on temperature monitoring during the matching process. For example, in a heat tracing system, the temperature node factor of a key valve may be set to 1.2 because it plays a key role in the system, while the temperature node factor of another non-key node may be set to 0.8;

[0118] In this embodiment, the device characteristic factor refers to a value related to the performance, sensitivity, and adaptability of the data acquisition device itself, reflecting the reliability and stability of the device. This factor is used to evaluate the role of the device in temperature monitoring. If a temperature sensor has high sensitivity and good stability, its device characteristic factor can be set to 1.3; while an old device may be set to 0.7 because it is susceptible to interference;

[0119] In this embodiment, the basic matching coefficient refers to the value obtained after a preliminary evaluation of the data packet based on the preset criteria without considering other factors. It provides a basic matching benchmark for the data packet, usually a fixed value or a simple calculation result. If the basic matching coefficient of all data packets is set to 0.5, it means that the matching degree of the data packet is considered to be at a medium level when there are no other influencing factors. If other factors are combined for weighting later, a higher or lower final matching coefficient may be obtained.

[0120] The beneficial effects of the above technical solution are: by calculating the first matching coefficient based on the key information of the data packet, and comprehensively considering the weights of multiple factors such as data packet size, timestamp, temperature node and equipment characteristics, it is possible to achieve refined identification of data packet characteristics, improve the accuracy of data packet monitoring and the reliability of temperature monitoring, and effectively improve the accuracy and response efficiency of temperature monitoring and early warning of the heating system.

[0121] Example 5

[0122] The embodiment of the present invention provides a temperature monitoring and early warning method for a heating system, which processes received real-time temperature data and transmits it to a cloud platform, including:

[0123] Obtain and analyze the historical operating data of the heating system to determine the overall normal operating temperature range of the heating system and determine the preliminary temperature threshold of the heating system;

[0124] When the received temperature data of the field node is greater than the preliminary temperature threshold, the corresponding field node is marked as abnormal;

[0125] The real-time temperature and marking status of each field node are transmitted to the cloud platform.

[0126] In this embodiment, the historical operation data of the heating system refers to the temperature changes, environmental conditions, node status and other information recorded in the past operation of the heating system. These data are used to analyze the temperature fluctuation pattern of the heating system and the stability of the equipment operation, and provide a basis for determining the normal temperature range and setting the temperature threshold. For example, the historical operation data of a heating system shows that when operating in winter, the temperature of section A of the pipeline is usually maintained at 10-15°C, and in summer it is maintained at 15-20°C. These data can help analyze the impact of seasons on the system operating temperature;

[0127] In this embodiment, the normal operating temperature range is a reasonable temperature interval obtained based on historical data analysis, indicating the temperature range in which the heating system maintains a normal state under different conditions. Any temperature outside this range may indicate a system abnormality. For example, after analyzing the historical data of the heating system, it is determined that the normal operating temperature range is 10-20°C, of ​​which the normal range in winter is 10-15°C and in summer is 15-20°C. This range can be used as a standard for preliminary judgment of temperature abnormality;

[0128] In this embodiment, the preliminary temperature threshold is one or more key temperature values ​​set based on the normal operating temperature range, which is used to detect whether the real-time temperature exceeds the safe range and help identify potential temperature anomalies. The preliminary temperature threshold may include multiple different temperature points for different seasons or different equipment areas. For example, for the heating system of pipeline section A, the preliminary temperature threshold is set to 15°C in winter and 20°C in summer. When the real-time temperature data exceeds these values, the system will perform further abnormality checks.

[0129] In this embodiment, the abnormal mark is a special mark for the node whose temperature exceeds the preliminary temperature threshold, which is usually used to remind the system or operator that the node may be abnormal. This mark will be transmitted to the cloud platform along with the temperature data for centralized monitoring and processing on the platform. For example, if the temperature data of a node reaches 25°C, exceeding its summer threshold of 20°C, the system will mark the node as abnormal and display its status as "abnormal" so that the operator can pay attention and take measures in time.

[0130] The beneficial effects of the above technical solution are: by obtaining the historical operating data of the heating system, the overall normal temperature range is determined, and a preliminary temperature threshold is set, abnormal temperature data is marked, and the real-time temperature and marking status are transmitted to the cloud platform, thereby realizing remote monitoring and data integration, effectively improving the accuracy of system abnormality detection and the response speed of early warning, and ensuring the safe operation and efficient management of the heating system.

[0131] Example 6

[0132] The embodiment of the present invention provides a temperature monitoring and early warning method for a heating system, which obtains historical temperature data of each field node in the heating system, and determines a plurality of temperature judgment thresholds in combination with the processed real-time temperature data, and then issues an alarm signal, including:

[0133] Retrieve the historical temperature data of each field node from the preset local storage;

[0134] Analyze the historical temperature data of all field nodes to determine the normal temperature range of each field node;

[0135] determining a historical temperature threshold for each field node based on a normal temperature range for each field node;

[0136] Determine a number of temperature judgment thresholds corresponding to each field node based on the historical temperature threshold, real-time temperature and a preset method of each field node;

[0137] Determine the real-time temperature state of each field node based on the real-time temperature of each field node and the corresponding temperature judgment threshold;

[0138] Generate alarm signals based on the real-time temperature status and abnormal mark status of each field node.

[0139] In this embodiment, the historical temperature threshold is a critical value determined based on the historical temperature data of the field node and the normal temperature range, which is used to identify the situation where the temperature exceeds the reasonable range. This threshold provides a benchmark for real-time temperature monitoring and helps to determine whether the temperature fluctuation is normal. For example, by analyzing the historical data of node A, it is found that its temperature is usually between 10-15°C, so its historical temperature threshold is set to 15°C. If the real-time temperature is higher than 15°C, the system considers that there may be an abnormality.

[0140] In this embodiment, the temperature judgment threshold is a dynamic threshold determined based on the historical temperature threshold and real-time temperature data in combination with a preset judgment method, which is used to accurately judge the temperature status of the node. The temperature judgment threshold will be adjusted according to the real-time temperature conditions and usage environment of the node to ensure the accuracy of the warning. For example, if the historical temperature threshold of node A is 15°C and the real-time temperature is close to this value, the judgment threshold can be further divided: a high temperature alarm threshold of 17°C and a low temperature alarm threshold of 12°C can be set to monitor the temperature more finely.

[0141] In this embodiment, the real-time temperature status is the health status of the current temperature of the node determined based on the real-time temperature data and the temperature judgment threshold. This status indicates whether the temperature is within the normal range, close to abnormality, or has exceeded the threshold and is marked as abnormal. If the real-time temperature of node A is 16°C, it exceeds the historical temperature threshold of 15°C and may be defined as a "high temperature alarm"; if it is lower than 12°C, it is defined as a "low temperature alarm"; and within the range of 12-15°C, it is "normal".

[0142] In this embodiment, the generation of an alarm signal based on the real-time temperature status and abnormal mark status of each field node is a comprehensive judgment of the real-time temperature status of the field node and whether there is an abnormal mark. If the real-time status of the node is abnormal, the system will generate an alarm signal and remind the operator to pay attention to the node through the alarm system. Assume that the real-time temperature of node A is 16.5°C and the temperature judgment threshold is set to 15°C. After node A is marked as abnormal, the system will generate an alarm signal and transmit it to the console or cloud platform to promptly notify the operation and maintenance personnel to check and handle the abnormal situation of the node.

[0143] The beneficial effects of the above technical solution are: by analyzing the historical temperature data of each field node, the personalized temperature judgment threshold is dynamically determined, the ability to identify temperature anomalies is effectively improved, accurate early warning is achieved, the risk of system failure is reduced, and the safe and stable operation of the heating system is ensured. At the same time, alarm signals are generated based on real-time status, which enhances operation and maintenance efficiency and response speed.

[0144] Example 7

[0145] The embodiment of the present invention provides a method for monitoring and warning the temperature of a heating system.

[0146] Abnormal marking status, including: high temperature or low temperature exceeding limit marking, abnormal temperature fluctuation marking;

[0147] Real-time temperature status, including: normal status, temperature exceeding limit status, abnormal high temperature status, abnormal low temperature status, abnormal temperature fluctuation status and abnormal temperature stagnation status.

[0148] In this embodiment, the high temperature or low temperature over-limit mark means that when the temperature of the field node exceeds the preset high temperature or low temperature judgment threshold, the system will mark the node so as to promptly remind the operation and maintenance personnel to pay attention to abnormal situations. This mark is mainly used to identify the risk of overheating or overcooling that may occur in the heating system. For example, in the pipeline heating system, the high temperature judgment threshold of node A is 70°C, and the low temperature judgment threshold is 5°C. If the real-time temperature detection finds that the temperature of node A reaches 75°C, the system will automatically generate a "high temperature over-limit mark" for the node; if the temperature drops to 4°C, a "low temperature over-limit mark" is generated to remind the node that it is in an abnormal temperature state.

[0149] In this embodiment, the abnormal temperature fluctuation state refers to the drastic fluctuation of the node temperature in a short period of time, that is, the amplitude and frequency of the temperature change exceed the normal operating range. Abnormal temperature fluctuations usually indicate that there may be unstable factors in the system, such as failure of the heating equipment, rapid changes in ambient temperature, or sensor abnormalities. For example, the normal temperature range of node B is 10-20°C, and the temperature fluctuation generally does not exceed 2°C / minute. However, the system detected that the temperature of node B first rose rapidly from 12°C to 18°C ​​within 1 minute, and then dropped to 8°C. This was identified as an "abnormal temperature fluctuation state", indicating that there may be instability in the heating system, which requires further inspection and maintenance;

[0150] In this embodiment, the abnormal temperature stagnation state means that the node temperature stays at a certain temperature for a long time, and does not fluctuate reasonably with the normal operation of the system or changes in the external environment. Temperature stagnation usually indicates that there may be problems with the heating system or temperature monitoring equipment, such as failure of the heating element, failure of the temperature sensor, or abnormally stable external temperature. For example, under normal circumstances, the temperature of node C should fluctuate between 5-20°C with changes in ambient temperature. However, the system continuously monitors that the temperature of node C has remained at 15°C for several hours without obvious changes. The system will mark this node as "abnormal temperature stagnation state" and remind the operation and maintenance personnel to check and check whether there is a possibility of sensor failure or failure of the heating equipment.

[0151] The beneficial effects of the above technical solution are: by combining historical and real-time temperature data, setting multi-level abnormal marking status and real-time temperature status, realizing accurate temperature monitoring and intelligent early warning of the heating system, and having the ability to efficiently identify high temperature, low temperature, abnormal fluctuations and temperature stagnation, and being able to quickly detect and mark various temperature anomalies, providing a decision-making basis for timely maintenance, thereby improving the safety and operational stability of the system.

[0152] Example 8

[0153] An embodiment of the present invention provides a temperature monitoring and early warning system for a heating system, comprising:

[0154] Temperature acquisition module: obtains several field nodes of the heating system, and deploys a preset acquisition device on each field node to collect the heating temperature of each node in real time;

[0155] Data receiving module: packages the collected real-time temperature data and sends it to the corresponding team receiving device;

[0156] Data transmission module: processes the received real-time temperature data and transmits it to the cloud platform;

[0157] Temperature alarm module: obtains the historical temperature data of each field node in the heating system, and determines several temperature judgment thresholds based on the processed real-time temperature data, and then issues an alarm signal;

[0158] Result acquisition module: Build a multi-level management view based on the real-time temperature data and alarm status of all on-site nodes to obtain temperature monitoring results.

[0159] The beneficial effects of the above technical solution are: through multi-node real-time temperature collection, historical data threshold analysis and cloud management, a multi-level temperature monitoring and early warning system is built, achieving full node coverage, real-time early warning and management visualization, effectively improving the temperature monitoring efficiency and early warning timeliness of the heating system, and significantly enhancing the stability and safety of the system.

[0160] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0161] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0162] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A temperature monitoring and early warning method for a heating system, characterized in that: include: Step 1: Acquire several field nodes of the heating system, and deploy a preset acquisition device on each field node to collect the heating temperature of each field node in real time; Step 2: Pack the collected real-time temperature data and send it to the corresponding team receiving device; Step 3: Process the received real-time temperature data and transmit it to the cloud platform; Step 4: Obtain the historical temperature data of each field node in the heating system, and determine several temperature judgment thresholds in combination with the processed real-time temperature data, and then issue an alarm signal; Step 5: Build a multi-level management view based on the real-time temperature data and alarm status of all field nodes to obtain temperature monitoring results.

2. A method for monitoring and warning temperature of a heating system according to claim 1, characterized in that: Acquire several field nodes of the heating system, and deploy a preset acquisition device on each field node to collect the heating temperature of each field node in real time, including: Conduct structural analysis on the heating system and obtain several parts of the heating system; Based on the preset model, heat loss analysis is performed on all parts of the heating system, thereby determining a plurality of first parts and second parts of the heating system; Determine a first location of the heat tracing system as a first field node, and determine a second location of the heat tracing system as a second field node; Installing a temporary temperature sensor on each first field node and the second field node, acquiring corresponding temperature change data, and verifying the temperature data based on a preset method; Determine the first on-site node that passes the verification as the third on-site node, and at the same time, determine the second on-site node that passes the verification as the fourth on-site node; Deploy the first acquisition device on each third field node, and deploy the second acquisition device on each fourth field node; The heating temperatures of the third field node and the fourth field node are collected in real time based on the first collection device and the second collection device.

3. A method for temperature monitoring and early warning of a heating system according to claim 1, characterized in that: The collected real-time temperature data is packaged and sent to the corresponding team receiving device, including: Pack the collected real-time temperature data and obtain relevant key information of the data packet; Generate a first matching code for each data packet based on key information of the data packet and a preset identification rule; Determine a first matching coefficient of the data packet based on key information related to the data packet; Preliminarily matching the data packet with the receiving team device based on the first matching code and the first matching coefficient of the data packet, thereby obtaining a plurality of first data packets corresponding to each receiving team; Encoding each first data packet based on a preset encoding rule, thereby generating a second matching code for each data packet; Perform a preliminary match based on the second matching code of the first data packet with the receiving team device to verify the match; The first data packet after verification and matching is sent to the corresponding team receiving device.

4. A method for temperature monitoring and early warning of a heating system according to claim 1, characterized in that: Determining a first matching coefficient of the data packet based on relevant key information of the data packet includes: Determine the first matching coefficient of the data packet based on the relevant key information of the data packet: Among them, Q i is the first matching coefficient of the ith data packet, α1 i is the weight coefficient of the size of the i-th data packet, X i is the size of the ith data packet, α2 i is the weight coefficient of the timestamp coefficient of the ith data packet, T i is the timestamp coefficient of the ith data packet, α3 i is the weight coefficient of the temperature node factor of the ith data packet, N i is the temperature node factor of the ith data packet, α4 i is the weight coefficient of the device characteristic factor of the ith data packet, D i is the device characteristic factor of the ith data packet, Q1 i is the basic matching coefficient of the ith data packet.

5. A method for temperature monitoring and early warning of a heating system according to claim 1, characterized in that: The received real-time temperature data is processed and transmitted to the cloud platform, including: Obtain and analyze the historical operating data of the heating system to determine the overall normal operating temperature range of the heating system and determine the preliminary temperature threshold of the heating system; When the received temperature data of the field node is greater than the preliminary temperature threshold, the corresponding field node is marked as abnormal; The real-time temperature and marking status of each field node are transmitted to the cloud platform.

6. A method for monitoring and warning the temperature of a heating system according to claim 5, characterized in that: Obtain the historical temperature data of each field node in the heating system, and determine several temperature judgment thresholds based on the processed real-time temperature data, and then issue an alarm signal, including: Retrieve the historical temperature data of each field node from the preset local storage; Analyze the historical temperature data of all field nodes to determine the normal temperature range of each field node; determining a historical temperature threshold for each field node based on a normal temperature range for each field node; Determine a number of temperature judgment thresholds corresponding to each field node based on the historical temperature threshold, real-time temperature and a preset method of each field node; Determine the real-time temperature state of each field node based on the real-time temperature of each field node and the corresponding temperature judgment threshold; Generate alarm signals based on the real-time temperature status and abnormal mark status of each field node.

7. A method for monitoring and warning the temperature of a heating system according to claim 6, characterized in that: Abnormal marking status, including: high temperature or low temperature exceeding limit marking, abnormal temperature fluctuation marking; Real-time temperature status, including: normal status, temperature exceeding limit status, abnormal high temperature status, abnormal low temperature status, abnormal temperature fluctuation status and abnormal temperature stagnation status.

8. A temperature monitoring and early warning system for a heating system, characterized in that: include: Temperature acquisition module: obtains several field nodes of the heating system, and deploys a preset acquisition device on each field node to collect the heating temperature of each node in real time; Data receiving module: packages the collected real-time temperature data and sends it to the corresponding team receiving device; Data transmission module: processes the received real-time temperature data and transmits it to the cloud platform; Temperature alarm module: obtains the historical temperature data of each field node in the heating system, and determines several temperature judgment thresholds based on the processed real-time temperature data, and then issues an alarm signal; Result acquisition module: Build a multi-level management view based on the real-time temperature data and alarm status of all on-site nodes to obtain temperature monitoring results.

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