Management system and method for improving steam yield of sintering waste heat boiler

Abstract

The invention discloses a management system for improving the steam yield of a sintering waste heat boiler. The management system comprises a data acquisition module, a prediction model construction module, a real-time monitoring module, a remote control module, an intelligent diagnosis module and a user interaction interface. The data acquisition module is used for collecting operation parameters, maintenance records and operation habit data of the sintering waste heat boiler. By integrating an intelligent system, automatic control over the sintering waste heat boiler is achieved, and the operation efficiency is improved. By optimizing the combustion process and operation management, the fuel utilization rate is increased, and the energy consumption is reduced. Remote monitoring and diagnosis functions are realized, faults can be found and solved in time, and shutdown loss caused by equipment faults is avoided. The application of the intelligent system also reduces environmental pollution, and meets the requirements of sustainable development. And the usability of the system and the user experience are improved through the design of a user interaction interface.

Description

Technical Field

[0001] The present invention relates to the technical field of waste heat recovery, and in particular to a management system and method for improving the steam output of a sintering waste heat boiler. Background Art

[0002] In the steel production process, the sintering process will produce a large amount of high-temperature flue gas, which contains rich thermal energy. In order to effectively utilize this part of thermal energy, sintering waste heat boilers are widely used in steel enterprises to generate steam by recovering the heat energy in the flue gas, which is then used for power generation or other process. However, there are some problems in the operation of traditional sintering waste heat boilers, such as unstable steam production, high energy consumption, frequent failures, etc. These problems seriously affect the efficiency and economic benefits of waste heat recovery.

[0003] In order to increase the steam production and reduce energy consumption of sintering waste heat boilers, researchers have conducted a lot of exploration and practice. Traditional improvement methods mainly focus on optimizing the boiler structure, adjusting the combustion process, and improving the heat exchanger. However, these methods often have problems such as high cost, long cycle, and limited effect, which are difficult to meet the urgent needs of modern steel companies for high efficiency, energy saving, and environmental protection.

[0004] In recent years, with the rapid development of intelligent technology, applying intelligent technology to the management and control of sintering waste heat boilers to increase steam production and reduce energy consumption has become a new research direction. However, the existing intelligent management systems and methods still have deficiencies in prediction accuracy, real-time performance, adaptability, and user interactivity, making it difficult to achieve comprehensive, accurate, and real-time monitoring and management of the operating status of sintering waste heat boilers. Summary of the invention

[0005] The purpose of the present invention is to solve the above-mentioned problems of the background technology and to propose a management system and method for improving the steam production of a sintering waste heat boiler.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A management system for improving the steam output of a sintering waste heat boiler, comprising a data acquisition module, a prediction model building module, a real-time monitoring module, a remote control module, an intelligent diagnosis module and a user interaction interface;

[0008] The data acquisition module is used to collect the operating parameters, maintenance records and operating habit data of the sintering waste heat boiler;

[0009] The prediction model building module uses machine learning algorithms to build a prediction model based on the data collected by the data acquisition module;

[0010] The real-time monitoring module is used to monitor the changes of various parameters of the sintering waste heat boiler in real time and issue an alarm when the parameters exceed the normal range;

[0011] The remote control module is used to remotely control the operation of the sintering waste heat boiler through an intelligent system to minimize energy consumption and maximize steam production;

[0012] Intelligent diagnostic module is used to analyze abnormal situations and find out the root cause of the problem and provide solutions;

[0013] The user interaction interface is used to display real-time data, prediction results, alarm information and diagnostic reports, and also provides a user input interface;

[0014] Among them, the prediction model building module uses the following formula to predict steam production:

[0015] P=f(T,P in ,P out ,F,C)

[0016] Where P represents steam production, T represents boiler operation time, P in Indicates boiler inlet pressure, P out represents boiler outlet pressure, F represents fuel flow rate, and C represents flue gas composition.

[0017] As a further solution of the present invention: the prediction model can predict the steam production change trend, energy consumption and potential failure points in the future.

[0018] As a further solution of the present invention: the real-time monitoring module also includes an abnormal data recording function for recording and analyzing abnormal data to assist the intelligent diagnosis module in fault diagnosis and provide fault warning;

[0019] The fault diagnosis module uses the following formula to calculate the fault probability:

[0020]

[0021] Where D dev Denotes the data deviation rate, D actual Indicates the actual measured value, D expected represents the expected value, when D dev When the preset threshold is exceeded, it is judged as abnormal data.

[0022] As a further solution of the present invention: the remote control module can automatically adjust the operating parameters of the sintering waste heat boiler, such as fuel type, air intake, and combustion process, according to the prediction model and real-time monitoring data to minimize energy consumption and maximize steam production, and can also receive user instructions for manual adjustment.

[0023] As a further solution of the present invention: the intelligent diagnosis module includes a fault warning module, a fault diagnosis module and a maintenance suggestion module, the fault warning module is used to issue a warning before a potential fault occurs, the fault diagnosis module is used to analyze abnormal conditions and determine the type and location of the fault, and the maintenance suggestion module is used to provide targeted maintenance suggestions and repair plans;

[0024] The fault diagnosis module uses the following formula to calculate the fault probability:

[0025]

[0026] Where P fault represents the failure probability, N fault Indicates the number of times the same fault occurs, N total Indicates the total number of runs.

[0027] As a further solution of the present invention: the user interaction interface includes a visual interface and a voice interaction interface, the visual interface is used to display real-time data, prediction results, alarm information and diagnostic reports, and the voice interaction interface is used to receive user voice commands and provide voice feedback.

[0028] A management method for improving the steam production of a sintering waste heat boiler, characterized in that it includes the following steps: collecting data through a data acquisition module, building and training a prediction model using a prediction model building module, monitoring parameter changes in real time and recording abnormal data through a real-time monitoring module, remotely controlling the operation of the sintering waste heat boiler using a remote control module based on the prediction model and real-time monitoring data, analyzing abnormal situations and providing solutions through an intelligent diagnosis module, displaying real-time data, prediction results, alarm information and diagnostic reports through a user interaction interface, receiving user instructions or feedback at the same time, and continuously optimizing the prediction model and control strategy based on system operation data and user feedback.

[0029] As a further solution of the present invention: it also includes the steps of: after the intelligent diagnosis module determines the fault type and location, automatically triggering the maintenance suggestion module to provide targeted maintenance suggestions and repair plans, and notifying the user through the user interaction interface.

[0030] Beneficial effects of the present invention: By integrating the intelligent system, the automatic control of the sintering waste heat boiler is realized, and the operation efficiency is improved. By optimizing the combustion process and operation management, the fuel utilization rate is improved and the energy consumption is reduced. The remote monitoring and diagnosis functions are realized, and the faults can be discovered and solved in time, avoiding the downtime losses caused by equipment failure. The application of the intelligent system also reduces environmental pollution and meets the requirements of sustainable development. The design of the user interaction interface improves the ease of use and user experience of the system. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. 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.

[0032] Embodiment 1, the present invention is a management system for improving the steam production of a sintering waste heat boiler, comprising a data acquisition module, a prediction model building module, a real-time monitoring module, a remote control module, an intelligent diagnosis module and a user interaction interface;

[0033] The data acquisition module is used to collect the operating parameters, maintenance records and operating habit data of the sintering waste heat boiler;

[0034] The prediction model building module uses machine learning algorithms to build a prediction model based on the data collected by the data acquisition module;

[0035] The real-time monitoring module is used to monitor the changes of various parameters of the sintering waste heat boiler in real time and issue an alarm when the parameters exceed the normal range;

[0036] The remote control module is used to remotely control the operation of the sintering waste heat boiler through an intelligent system to minimize energy consumption and maximize steam production;

[0037] Intelligent diagnostic module is used to analyze abnormal situations and find out the root cause of the problem and provide solutions;

[0038] The user interaction interface is used to display real-time data, prediction results, alarm information and diagnostic reports, and also provides a user input interface;

[0039] Among them, the prediction model building module uses the following formula to predict steam production:

[0040] P=f(T,P in ,P out ,F,C)

[0041] Where P represents steam production, T represents boiler operation time, P in Indicates boiler inlet pressure, P out represents boiler outlet pressure, F represents fuel flow rate, and C represents flue gas composition.

[0042] Embodiment 2, the present invention is a management system for improving the steam production of sintering waste heat boiler, including a data acquisition module, a prediction model building module, a real-time monitoring module, a remote control module, an intelligent diagnosis module and a user interaction interface;

[0043] The data acquisition module is used to collect the operating parameters, maintenance records and operating habit data of the sintering waste heat boiler;

[0044] The prediction model building module uses machine learning algorithms to build a prediction model based on the data collected by the data acquisition module;

[0045] The real-time monitoring module is used to monitor the changes of various parameters of the sintering waste heat boiler in real time and issue an alarm when the parameters exceed the normal range;

[0046] The remote control module is used to remotely control the operation of the sintering waste heat boiler through an intelligent system to minimize energy consumption and maximize steam production;

[0047] Intelligent diagnostic module is used to analyze abnormal situations and find out the root cause of the problem and provide solutions;

[0048] The user interaction interface is used to display real-time data, prediction results, alarm information and diagnostic reports, and also provides a user input interface;

[0049] Among them, the prediction model building module uses the following formula to predict steam production:

[0050] P=f(T,P in ,P out ,F,C)

[0051] Where P represents steam production, T represents boiler operation time, P in Indicates boiler inlet pressure, P out represents boiler outlet pressure, F represents fuel flow rate, and C represents flue gas composition.

[0052] The prediction model can predict the steam production trend, energy consumption and potential failure points in the future.

[0053] The real-time monitoring module also includes an abnormal data recording function, which is used to record and analyze abnormal data to assist the intelligent diagnosis module in fault diagnosis and provide fault warning;

[0054] The fault diagnosis module uses the following formula to calculate the fault probability:

[0055]

[0056] Where D dev Denotes the data deviation rate, D actual Indicates the actual measured value, D expected represents the expected value, when D dev When the preset threshold is exceeded, it is judged as abnormal data.

[0057] The remote control module can automatically adjust the operating parameters of the sintering waste heat boiler, such as fuel type, air intake, and combustion process, based on the prediction model and real-time monitoring data to minimize energy consumption and maximize steam production. It can also receive user instructions for manual adjustments.

[0058] The intelligent diagnosis module includes a fault warning module, a fault diagnosis module and a maintenance suggestion module. The fault warning module is used to issue a warning before a potential fault occurs. The fault diagnosis module is used to analyze abnormal conditions and determine the type and location of the fault. The maintenance suggestion module is used to provide targeted maintenance suggestions and repair plans.

[0059] The fault diagnosis module uses the following formula to calculate the fault probability:

[0060]

[0061] Where P fault represents the failure probability, N fault Indicates the number of times the same fault occurs, N total Indicates the total number of runs.

[0062] The user interaction interface includes a visual interface and a voice interaction interface. The visual interface is used to display real-time data, prediction results, alarm information and diagnostic reports, and the voice interaction interface is used to receive user voice commands and provide voice feedback.

[0063] In another embodiment, a management method for improving the steam production of a sintering waste heat boiler includes the following steps: collecting data through a data acquisition module, building and training a prediction model using a prediction model building module, monitoring parameter changes in real time and recording abnormal data through a real-time monitoring module, remotely controlling the operation of the sintering waste heat boiler using a remote control module based on the prediction model and real-time monitoring data, analyzing abnormal situations and providing solutions through an intelligent diagnosis module, displaying real-time data, prediction results, alarm information and diagnostic reports through a user interaction interface, receiving user instructions or feedback at the same time, and continuously optimizing the prediction model and control strategy based on system operation data and user feedback.

[0064] In another embodiment, the step is further included: after the intelligent diagnosis module determines the fault type and location, the maintenance suggestion module is automatically triggered to provide targeted maintenance suggestions and repair plans, and the user is notified through the user interaction interface.

[0065] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the claims of the present invention.

Claims

1. A management system for improving the steam output of a sintering waste heat boiler, characterized in that: It includes data acquisition module, prediction model building module, real-time monitoring module, remote control module, intelligent diagnosis module and user interaction interface; The data acquisition module is used to collect the operating parameters, maintenance records and operating habit data of the sintering waste heat boiler; The prediction model building module uses a machine learning algorithm to build a prediction model based on the data collected by the data acquisition module; The real-time monitoring module is used to monitor the changes of various parameters of the sintering waste heat boiler in real time and issue an alarm when the parameters exceed the normal range; The remote control module is used to remotely control the operation of the sintering waste heat boiler through an intelligent system to minimize energy consumption and maximize steam production; The intelligent diagnosis module is used to analyze abnormal conditions and find out the root cause of the problem and provide solutions; The user interaction interface is used to display real-time data, prediction results, alarm information and diagnostic reports, and also provides a user input interface; The prediction model building module uses the following formula to predict steam production: P=f(T,P in ,P out ,F,C) Where P represents steam production, T represents boiler operation time, P in Indicates boiler inlet pressure, P out represents boiler outlet pressure, F represents fuel flow rate, and C represents flue gas composition.

2. A management system for improving steam production of sintering waste heat boiler according to claim 1, characterized in that: The prediction model can predict the steam production change trend, energy consumption and potential failure points in the future.

3. A management system for improving steam production of sintering waste heat boiler according to claim 1, characterized in that: The real-time monitoring module also includes an abnormal data recording function for recording and analyzing abnormal data to assist the intelligent diagnosis module in fault diagnosis and provide fault warning; The fault diagnosis module uses the following formula to calculate the fault probability: Where D dev Denotes the data deviation rate, D actual Indicates the actual measured value, D expected represents the expected value, when D dev When the preset threshold is exceeded, it is judged as abnormal data.

4. A management system for improving steam production of sintering waste heat boiler according to claim 1, characterized in that: The remote control module can automatically adjust the operating parameters of the sintering waste heat boiler, such as fuel type, air intake, and combustion process, according to the prediction model and real-time monitoring data to minimize energy consumption and maximize steam production, and can also receive user instructions for manual adjustment.

5. A management system for improving steam production of sintering waste heat boiler according to claim 1, characterized in that: The intelligent diagnosis module includes a fault warning module, a fault diagnosis module and a maintenance suggestion module. The fault warning module is used to issue a warning before a potential fault occurs. The fault diagnosis module is used to analyze abnormal conditions and determine the type and location of the fault. The maintenance suggestion module is used to provide targeted maintenance suggestions and repair plans. The fault diagnosis module uses the following formula to calculate the fault probability: Where P fault represents the failure probability, N fault Indicates the number of times the same fault occurs, N total Indicates the total number of runs.

6. A management system for improving steam production of sintering waste heat boiler according to claim 1, characterized in that: The user interaction interface includes a visualization interface and a voice interaction interface. The visualization interface is used to display real-time data, prediction results, alarm information and diagnostic reports, and the voice interaction interface is used to receive user voice commands and provide voice feedback.

7. A management method for improving the steam output of a sintering waste heat boiler, characterized in that: The following steps are involved: Collect data through the data acquisition module, build and train the prediction model using the prediction model building module, monitor parameter changes in real time and record abnormal data through the real-time monitoring module, remotely control the operation of the sintering waste heat boiler using the remote control module based on the prediction model and real-time monitoring data, analyze abnormal situations and provide solutions through the intelligent diagnosis module, display real-time data, prediction results, alarm information and diagnostic reports through the user interaction interface, receive user instructions or feedback at the same time, and continuously optimize the prediction model and control strategy based on system operation data and user feedback.

8. A management system and method for improving steam production of sintering waste heat boiler according to claim 7, characterized in that: The method also includes the following steps: after the intelligent diagnosis module determines the fault type and location, the maintenance suggestion module is automatically triggered to provide targeted maintenance suggestions and repair plans, and the user is notified through the user interaction interface.

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