Fire early warning system for paper machine and working method of fire early warning system
By installing a variety of sensors in the key parts of the papermaker and using intelligent analysis algorithms, a papermaking warning system is designed to solve the problem of slow and poor fire extinguishing effects in the existing technology in the existing technology, and achieve high and accurate fire extinguishing effect, and achieve high and accurate accuracy. The fire warning and emergency response of sexual and timeliness improve the safety performance of the papermaker.
Patent Information
- Application Number
- CN202411354593.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-27
- Publication Date
- 2025-01-24
AI Technical Summary
The existing paper machine drying workers lack special fire warning devices and rely on manual inspections and upper spray systems for fire prevention and control. The response speed is slow and the fire extinguishing effect is poor, which cannot effectively curb the spread of the fire in the early stages.
A papermaking warning system is designed, including information collection modules, information processing modules and emergency execution modules. By installing temperature sensors, smoke sensors, infrared thermal imageriors, and image recognition cameras in key parts, collect data in real time, and use machine learning or deep learning algorithms to extract fire feature information, combined with the preset fire warning model for comprehensive assessment. When the fire risk was detected, an early warning signal was issued by the sound light alarm, SMS, and mail, and an emergency plan was automatically initiated.
It improves the accuracy and timeliness of fire warning, reduces the false alarm rate and missed alarm rate, enhances emergency response capabilities, reduces fire losses, and improves the overall safety performance of the paper machine.
Smart Images
Figure CN119360524A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of fire early warning, and in particular to a fire early warning method and system for a papermaking machine. Background Art
[0002] A paper machine is a complete set of equipment that makes pulp form a paper web, including the main machine such as the headbox, wire section, press section, drying section, calender, paper reel and transmission section, and auxiliary systems such as steam, water, vacuum, lubrication and heat recovery. Among them, the drying section has become a high-incidence area for fire accidents due to high-temperature operation and the flammable nature of paper materials. Fires often bring huge economic losses to enterprises and even lead to the bankruptcy of enterprises. Fire early warning technology can effectively reduce the probability and loss of fire. Fire early warning technology can detect fires at the early stage of fire, buy precious time for timely fire extinguishing measures, and reduce fire losses. Through fire early warning technology, the operating status and surrounding environment of the paper machine can be monitored in real time, and fire hazards can be discovered and eliminated in time to improve production safety. However, the drying section of existing paper machines generally lacks special fire early warning devices, and mostly relies on manual inspections and upper sprinkler systems for fire prevention and control. There are problems such as slow response speed and poor fire extinguishing effect, which cannot effectively curb the spread of fires in the early stage. Summary of the invention
[0003] In view of the deficiencies in the prior art, the present invention provides a fire warning method and system for a paper machine, which solves the problems mentioned in the background technology.
[0004] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a fire warning system for a paper machine, the fire warning system comprising an information collection module, an information processing module and an emergency execution module.
[0005] As a preferred technical solution of the present invention, the function of the information collection module is to collect data. Through various sensors such as temperature sensors, smoke sensors, infrared thermal imagers and image recognition cameras installed in key parts of the papermaking machine such as the drying part, pressing part, and wire part, data on temperature, smoke concentration, thermal radiation intensity and image information are collected in real time.
[0006] As a preferred technical solution of the present invention, the information processing module includes data processing, feature extraction and comprehensive evaluation. The data processing is to transmit the collected data to the central processing unit by wired or wireless means, and perform preprocessing, filtering and denoising and other operations to improve data quality. The feature extraction is to use machine learning or deep learning algorithms to extract fire-related feature information from the processed data, such as temperature mutation, smoke diffusion rate, flame image characteristics. The comprehensive evaluation function is to conduct a comprehensive assessment of the fire risk of the papermaking machine based on the extracted feature information and combined with a preset fire warning model.
[0007] As a preferred technical solution of the present invention, the emergency execution module includes early warning release and emergency response. The early warning release is when the assessment result shows that there is a fire risk, an early warning signal is immediately sent to the operator and the fire control center through various means such as sound and light alarms, text messages, and emails, and the approximate location and risk level of the fire are displayed. The emergency response is to automatically start or prompt the operator to start the emergency plan after the early warning signal is issued, such as shutting down related equipment, starting the automatic fire extinguishing sensing device, and evacuating personnel.
[0008] As a preferred technical solution of the present invention, S1. Through temperature sensors, smoke sensors, infrared thermal imagers, image recognition cameras and other sensors at key parts of the paper machine such as the drying part, the pressing part, and the wire part, data on temperature, smoke concentration, thermal radiation intensity and image information are collected in real time;
[0009] S2. The collected data is transmitted to the central processing unit via wired or wireless means for preprocessing, filtering and denoising to improve the data quality;
[0010] S3. Use deep learning algorithms to extract fire-related feature information from the processed data, such as temperature mutation, smoke diffusion speed, and flame image features;
[0011] S4. Based on the extracted feature information and the preset fire warning model, a comprehensive assessment is performed on the fire risk of the paper machine. When the assessment result shows that the fire risk does not exceed the preset threshold, the above steps are repeated. When the assessment result shows that the fire risk exceeds the preset threshold, the signal is immediately passed to the next step.
[0012] S5. When receiving a fire risk exceeding the preset threshold, an early warning signal is immediately sent to the operator and the fire control center through various means such as sound and light alarms, text messages, and emails, and the approximate location and risk level of the fire are displayed;
[0013] S6. After the warning signal is issued, the emergency plan will be automatically started or the operator will be prompted to start, such as shutting down relevant equipment, starting automatic fire extinguishing devices, evacuating personnel, etc., to control the spread of fire and reduce losses.
[0014] As a preferred technical solution of the present invention, the model in S4 can be constructed and optimized based on multi-dimensional information such as historical fire data, equipment operating status and environmental factors.
[0015] Compared with the prior art, the present invention has the following beneficial effects:
[0016] (1) The accuracy and timeliness of fire warnings are improved. By integrating multiple sensors and intelligent analysis algorithms, comprehensive monitoring and integrated assessment of paper machine fire risks are achieved.
[0017] (2) The false alarm rate and missed alarm rate are reduced. By combining feature extraction with comprehensive evaluation, the false alarm phenomenon caused by single sensor failure or environmental interference is effectively reduced.
[0018] (3) The emergency response capability has been enhanced. After the early warning signal is issued, the emergency plan can be quickly activated to control the spread of fire and reduce losses.
[0019] (4) The overall safety performance of the papermaking machine has been improved, providing a strong guarantee for safe production in the papermaking industry. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] Figure 1 It is a schematic diagram of the process of the present invention;
[0021] Figure 2 Schematic diagram of the system of the present invention. DETAILED DESCRIPTION
[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0023] Example
[0024] See also Figure 1-2 The present invention provides the following technical solutions: a fire warning system for a paper machine, the fire warning system includes an information collection module, an information processing module and an emergency execution module.
[0025] Specifically, the function of the information collection module is to collect data. Through various sensors such as temperature sensors, smoke sensors, infrared thermal imagers, and image recognition cameras installed in key parts of the papermaking machine such as the drying section, pressing section, and wire section, data on temperature, smoke concentration, thermal radiation intensity, and image information can be collected in real time.
[0026] Specifically, the information processing module includes data processing, feature extraction and comprehensive evaluation. The data processing is to transmit the collected data to the central processing unit by wired or wireless means, and perform preprocessing, filtering and denoising and other operations to improve data quality. The feature extraction is to use machine learning or deep learning algorithms to extract fire-related feature information from the processed data, such as temperature mutation, smoke diffusion rate, flame image characteristics. The comprehensive evaluation function is to conduct a comprehensive assessment of the fire risk of the papermaking machine based on the extracted feature information and combined with a preset fire warning model.
[0027] Specifically, the emergency execution module includes early warning issuance and emergency response. The early warning issuance is when the assessment result shows that there is a fire risk, an early warning signal is immediately sent to the operator and the fire control center through various means such as sound and light alarms, text messages, and emails, and the approximate location and risk level of the fire are displayed. The emergency response is to automatically start or prompt the operator to start the emergency plan after the early warning signal is issued, such as shutting down related equipment, starting the automatic fire extinguishing sensor device, and evacuating personnel.
[0028] Specifically, a working method of a fire warning system for a paper machine, S1. Using a variety of sensors such as temperature sensors, smoke sensors, infrared thermal imagers, and image recognition cameras at key locations such as a drying section, a press section, and a wire section of the paper machine, data on temperature, smoke concentration, thermal radiation intensity, and image information are collected in real time;
[0029] S2. The collected data is transmitted to the central processing unit via wired or wireless means for preprocessing, filtering and denoising to improve the data quality;
[0030] S3. Use deep learning algorithms to extract fire-related feature information from the processed data, such as temperature mutation, smoke diffusion speed, and flame image features;
[0031] S4. Based on the extracted feature information and the preset fire warning model, a comprehensive assessment is performed on the fire risk of the paper machine. When the assessment result shows that the fire risk does not exceed the preset threshold, the above steps are repeated. When the assessment result shows that the fire risk exceeds the preset threshold, the signal is immediately passed to the next step.
[0032] S5. When receiving a fire risk exceeding the preset threshold, an early warning signal is immediately sent to the operator and the fire control center through various means such as sound and light alarms, text messages, and emails, and the approximate location and risk level of the fire are displayed;
[0033] S6. After the warning signal is issued, the emergency plan will be automatically started or the operator will be prompted to start, such as shutting down relevant equipment, starting automatic fire extinguishing devices, evacuating personnel, etc., to control the spread of fire and reduce losses.
[0034] Specifically, the model in S4 can be constructed and optimized based on multi-dimensional information such as historical fire data, equipment operating status, and environmental factors.
[0035] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
Claims
1. A fire warning system for a paper machine, characterized in that: The fire warning system includes an information collection module, an information processing module and an emergency execution module.
2. A fire warning system for a paper machine according to claim 1, characterized in that: The function of the information collection module is to collect data. Through various sensors such as temperature sensors, smoke sensors, infrared thermal imagers and image recognition cameras installed in key parts of the papermaking machine such as the drying part, pressing part, and wire part, the data of temperature, smoke concentration, thermal radiation intensity and image information are collected in real time.
3. A fire warning system for a paper machine according to claim 1, characterized in that: The information processing module includes data processing, feature extraction and comprehensive evaluation. The data processing is to transmit the collected data to the central processing unit by wired or wireless means, and perform preprocessing, filtering and denoising and other operations to improve data quality. The feature extraction is to use machine learning or deep learning algorithms to extract fire-related feature information from the processed data, such as temperature mutation, smoke diffusion speed, flame image characteristics. The comprehensive evaluation function is to conduct a comprehensive assessment of the fire risk of the papermaking machine based on the extracted feature information and combined with a preset fire warning model.
4. A fire warning system for a paper machine according to claim 1, characterized in that: The emergency execution module includes early warning release and emergency response. The early warning release is when the assessment result shows that there is a fire risk, an early warning signal is immediately sent to the operator and the fire control center through various means such as sound and light alarms, text messages, and emails, and the approximate location and risk level of the fire are displayed. The emergency response is to automatically start or prompt the operator to start the emergency plan after the early warning signal is released, such as shutting down related equipment, starting the automatic fire extinguishing sensor device, and evacuating personnel.
5. A working method of a fire warning system for a paper machine, characterized in that: S1. Through temperature sensors, smoke sensors, infrared thermal imagers, image recognition cameras and other sensors in key parts of the paper machine such as the drying part, press part, and wire part, data on temperature, smoke concentration, thermal radiation intensity and image information are collected in real time; S2. The collected data is transmitted to the central processing unit via wired or wireless means for preprocessing, filtering and denoising to improve the data quality; S3. Use deep learning algorithms to extract fire-related feature information from the processed data, such as temperature mutation, smoke diffusion speed, and flame image features; S4. Based on the extracted feature information and the preset fire warning model, a comprehensive assessment is performed on the fire risk of the paper machine. When the assessment result shows that the fire risk does not exceed the preset threshold, the above steps are repeated. When the assessment result shows that the fire risk exceeds the preset threshold, the signal is immediately passed to the next step. S5. When receiving a fire risk exceeding the preset threshold, an early warning signal is immediately sent to the operator and the fire control center through various means such as sound and light alarms, text messages, and emails, and the approximate location and risk level of the fire are displayed; S6. After the warning signal is issued, the emergency plan will be automatically started or the operator will be prompted to start, such as shutting down relevant equipment, starting automatic fire extinguishing devices, evacuating personnel, etc., to control the spread of fire and reduce losses.
6. The working method of a fire warning system for a paper machine according to claim 5, characterized in that: The model in S4 can be constructed and optimized based on multi-dimensional information such as historical fire data, equipment operating status and environmental factors.