Boiler four-tube online overtemperature early warning method

Abstract

The invention discloses a boiler four-tube online overtemperature early warning method. At present, conventional operation monitoring and adjustment are mainly carried out according to regulations and personnel experience, early warning and guidance adjustment methods are few, and newly added operation data and accumulated mass data mostly stay in manual analysis. The method comprises the following steps that the internal structure and the arrangement condition of the boiler are comprehensively and visually checked through a three-dimensional model; according to the established three-dimensional model, automatic detection of the wall thickness and the creep expansion deterioration trend of each heating surface pipe and risk early warning are realized, and the deterioration rule of the boiler is grasped in time; a comprehensive design data information base and a conventional detection and inspection information base are provided; machine learning and analysis are carried out on overtemperature historical data to obtain a historical data change curve and a change rule of each temperature measurement point, a current real-time temperature and an overtemperature condition are combined with the historical data rule to make a judgment and early warning, an operator is supervised and urged to actively adjust, and overtemperature is avoided; the method is used for boiler four-tube online overtemperature early warning.

Description

Technical Field

[0001] This invention relates to an online over-temperature early warning method for four tubes of a boiler. Background Technology

[0002] As boiler operating time increases, and boilers are often blended with large quantities of low-calorific-value, high-sulfur, high-ash, and low-melting-point coal, the heating surfaces operate in harsh environments for extended periods, leading to a high probability of ash accumulation, coking, corrosion, wear, and overheating-induced tube rupture. This results in significant challenges for safe boiler operation and effective maintenance. Leaks in the four tubes (heating tube, pipe, and pipe) are increasingly common during non-shutdown periods. Effectively analyzing the extent of damage caused by creep, wear, and overheating to boiler metal pipes is crucial for reducing these leaks. Currently, routine operation monitoring and adjustments rely primarily on procedures and personnel experience, with limited methods for early warning and adjustment guidance. New operational data and the vast amounts of accumulated data are largely analyzed manually, with little application of new information technologies for early warning, analysis, diagnosis, and guidance. Routine boiler inspections and maintenance are mostly limited to periodic shutdown inspections and emergency repairs after accidents. Data records are predominantly paper-based or simply electronic, resulting in low data management and utilization efficiency. There is a large amount of basic data on the four tubes of the boiler, including manual paper documents, simple electronic documents, and images. Although there is a lot of data, the classification, analysis, and effective mining of the data still need to be improved. A large amount of data has not been effectively utilized or mined. Summary of the Invention

[0003] The purpose of this invention is to provide an online over-temperature early warning method for four-tube boilers to solve the aforementioned technical problems.

[0004] The above objectives are achieved through the following technical solutions: A method for online over-temperature early warning of a four-tube boiler, comprising the following steps: Step 1: Use the 3D model to get a comprehensive and intuitive view of the boiler's internal structure and layout; Step 2: Based on the established three-dimensional model, automatically detect and warn of the wall thickness and creep deterioration trend of each heated surface tube, and promptly grasp the deterioration pattern of the boiler; Step 3: Provide a comprehensive database of design data and routine testing and inspection information; Step 4: By performing machine learning and analysis on historical over-temperature data, we obtain the historical data change curves and patterns for each temperature measurement point. By combining the current real-time temperature and over-temperature situation with the historical data patterns, we can make judgments, issue early warnings, and urge operators to make proactive adjustments to avoid over-temperature.

[0005] The specific process of step two in the above-mentioned online over-temperature early warning method for four-tube boilers is as follows: (1) Display the number of times the boiler is started and stopped, the running time, and the best reliability data in the history of continuous operation; (2) Monitor all wall temperature measuring points and important related parameters, mark the location of all wall temperature measuring points, display the real-time status of all wall temperatures, and display green for normal conditions and color-changing alarm for abnormal conditions; (3) Monitor the temperature and pressure change rate of each important measuring point, mine, organize, analyze, and deeply learn the historical data of all wall temperature measuring points, and display the historical data change curves and change patterns of each temperature measuring point. (4) The current temperature and the over-temperature situation are combined with the number of over-temperature events, duration and amplitude to make a risk judgment. The judgment results are divided into three levels of risk warning and prompts to intuitively assess the risk level.

[0006] The specific process of step three in the above-mentioned online over-temperature early warning method for four-tube boilers is as follows: (1) Provide a comprehensive design data database and routine inspection and testing data database, detailing the specifications, materials, wall thickness, creep, scale, oxide scale, and inspection and testing time of each pipe; (2) Set up permission management for data entry, search, and review to realize an innovative ledger management mode that is easy to search, convenient to enter, editable, and associated with a three-dimensional model. That is, the three-dimensional model is associated with the ledger data, and the ledger data information can be directly displayed through the three-dimensional model, making the three-dimensional ledger clear at a glance.

[0007] The above-mentioned online over-temperature early warning method for four-tube boilers, the specific process of step four is as follows: (1) Provide a rendered, labeled boiler wall temperature measurement point information, labeled heating surface name and structural layout, and associated real-time and historical over-temperature data of the boiler three-dimensional simulation model to comprehensively display the internal structure, tube arrangement and material size information of each heating surface of the boiler. (2) The information is accurate to the material, wall thickness, wear and other information of each metal pipe, down to the specification boundary line of the pipe or pipe section, and describes and reflects the physical relationship, position and hierarchy of each component of the boiler heating surface in the most natural, panoramic, physical and truthful way. (3) Provides accurate panoramic images and three-dimensional display of data information. After clicking on the measuring point, the daily, weekly and monthly historical curves will be displayed. The measuring point will change color and alarm after the pipe wall overheats. Beneficial effects

[0008] 1. This invention provides a simple and clear wall temperature monitoring system with a three-dimensional model display and color-changing warnings. It not only meets the basic needs of operators for over-temperature monitoring, but also allows for quick location of over-temperature measurement points. Combined with the rate of change of wall temperature measurement points and important related parameters, temperature deviation, alarm warnings, and risk alerts, it assists operation and management personnel in understanding the characteristics of wall temperature changes and accurately controlling wall temperature.

[0009] 2. This invention provides a comprehensive design data database and a routine inspection and testing database, detailing the specifications, materials, wall thickness, creep, scale, oxide scale, and inspection and testing time of each pipe. It sets up permission management for data entry, search, and approval, realizing an innovative ledger management mode that makes searching easy, data entry convenient, data editable, and linked to a 3D model. That is, the 3D model is linked to the ledger data, and the ledger data information can be directly displayed through the 3D model, making the three-dimensional ledger clear at a glance. Detailed Implementation

[0010] A method for online over-temperature early warning of a four-tube boiler, comprising the following steps: Step 1: Use the 3D model to get a comprehensive and intuitive view of the boiler's internal structure and layout; Step 2: Based on the established three-dimensional model, automatically detect and warn of the wall thickness and creep deterioration trend of each heated surface tube, and promptly grasp the deterioration pattern of the boiler; Step 3: Provide a comprehensive database of design data and routine testing and inspection information; Step 4: By performing machine learning and analysis on historical over-temperature data, we obtain the historical data change curves and patterns for each temperature measurement point. By combining the current real-time temperature and over-temperature situation with the historical data patterns, we can make judgments, issue early warnings, and urge operators to make proactive adjustments to avoid over-temperature.

[0011] The specific process of step two in the above-mentioned online over-temperature early warning method for four-tube boilers is as follows: (1) Display the number of times the boiler is started and stopped, the running time, and the best reliability data in the history of continuous operation; (2) Monitor all wall temperature measuring points and important related parameters, mark the location of all wall temperature measuring points, display the real-time status of all wall temperatures, and display green for normal conditions and color-changing alarm for abnormal conditions; (3) Monitor the temperature and pressure change rate of each important measuring point, mine, organize, analyze, and deeply learn the historical data of all wall temperature measuring points, and display the historical data change curves and change patterns of each temperature measuring point. (4) The current temperature and the over-temperature situation are combined with the number of over-temperature events, duration and amplitude to make a risk judgment. The judgment results are divided into three levels of risk warning and prompts to intuitively assess the risk level.

[0012] The specific process of step three in the above-mentioned online over-temperature early warning method for four-tube boilers is as follows: (1) Provide a comprehensive design data database and routine inspection and testing data database, detailing the specifications, materials, wall thickness, creep, scale, oxide scale, and inspection and testing time of each pipe; (2) Set up permission management for data entry, search, and review to realize an innovative ledger management mode that is easy to search, convenient to enter, editable, and associated with a three-dimensional model. That is, the three-dimensional model is associated with the ledger data, and the ledger data information can be directly displayed through the three-dimensional model, making the three-dimensional ledger clear at a glance.

[0013] The above-mentioned online over-temperature early warning method for four-tube boilers, the specific process of step four is as follows: (1) Provide a rendered, labeled boiler wall temperature measurement point information, labeled heating surface name and structural layout, and associated real-time and historical over-temperature data of the boiler three-dimensional simulation model to comprehensively display the internal structure, tube arrangement and material size information of each heating surface of the boiler. (2) The information is accurate to the material, wall thickness, wear and other information of each metal pipe, down to the specification boundary line of the pipe or pipe section, and describes and reflects the physical relationship, position and hierarchy of each component of the boiler heating surface in the most natural, panoramic, physical and truthful way. (3) Provides accurate panoramic images and three-dimensional display of data information. After clicking on the measuring point, the daily, weekly and monthly historical curves will be displayed. The measuring point will change color and alarm after the pipe wall overheats.

Claims

1. A method for online over-temperature early warning of a four-tube boiler, characterized in that: The method includes the following steps: Step 1: Use the 3D model to get a comprehensive and intuitive view of the boiler's internal structure and layout; Step 2: Based on the established three-dimensional model, automatically detect and warn of the wall thickness and creep deterioration trend of each heated surface tube, and promptly grasp the deterioration pattern of the boiler; Step 3: Provide a comprehensive database of design data and routine testing and inspection information; Step 4: By performing machine learning and analysis on historical over-temperature data, we obtain the historical data change curves and patterns for each temperature measurement point. By combining the current real-time temperature and over-temperature situation with the historical data patterns, we can make judgments, issue early warnings, and urge operators to make proactive adjustments to avoid over-temperature.

2. The boiler four-tube online over-temperature early warning method according to claim 1, characterized in that: The specific process of step two is as follows: (1) Display the number of times the boiler is started and stopped, the running time, and the best reliability data in the history of continuous operation; (2) Monitor all wall temperature measuring points and important related parameters, mark the location of all wall temperature measuring points, display the real-time status of all wall temperatures, and display green for normal conditions and color-changing alarm for abnormal conditions; (3) Monitor the temperature and pressure change rate of each important measuring point, mine, organize, analyze, and deeply learn the historical data of all wall temperature measuring points, and display the historical data change curves and change patterns of each temperature measuring point. (4) The current temperature and the over-temperature situation are combined with the number of over-temperature events, duration and amplitude to make a risk judgment. The judgment results are divided into three levels of risk warning and prompts to intuitively assess the risk level.

3. The boiler four-tube online over-temperature early warning method according to claim 2, characterized in that: The specific process of step three is as follows: (1) Provide a comprehensive design data database and routine inspection and testing data database, detailing the specifications, materials, wall thickness, creep, scale, oxide scale, and inspection and testing time of each pipe; (2) Set up permission management for data entry, search, and review to realize an innovative ledger management mode that is easy to search, convenient to enter, editable, and associated with a three-dimensional model. That is, the three-dimensional model is associated with the ledger data, and the ledger data information can be directly displayed through the three-dimensional model, making the three-dimensional ledger clear at a glance.

4. The boiler four-tube online over-temperature early warning method according to claim 3, characterized in that: The specific process of step four is as follows: (1) Provide a rendered, labeled boiler wall temperature measurement point information, labeled heating surface name and structural layout, and associated real-time and historical over-temperature data of the boiler three-dimensional simulation model to comprehensively display the internal structure, tube arrangement and material size information of each heating surface of the boiler. (2) The information is accurate to the material, wall thickness, wear and other information of each metal pipe, down to the specification boundary line of the pipe or pipe section, and describes and reflects the physical relationship, position and hierarchy of each component of the boiler heating surface in the most natural, panoramic, physical and truthful way. (3) Provides accurate panoramic images and three-dimensional display of data information. After clicking on the measuring point, the daily, weekly and monthly historical curves will be displayed. The measuring point will change color and alarm after the pipe wall overheats.