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Predictive control method and system for boiler fuel based on machine learning

A boiler fuel and predictive control technology, applied in general control systems, control/regulation systems, adaptive control, etc., can solve the dynamic characteristics of steam temperature adjustment objects and the influence of model parameters, it is difficult to establish accurate mathematical models, and it is difficult to obtain Control performance and other issues to achieve the effect of reducing the range of motion and the number of motions, being easy to use and increasing the lifespan

Active Publication Date: 2019-03-29
苏州恩基热能科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, the above-mentioned existing technical solutions have the following defects: the temperature target after water spraying is set according to the mathematical model of the steam temperature adjustment object, and the time-varying, uncertain and nonlinear nature of the steam temperature adjustment object makes it difficult to Establishing an accurate mathematical model and only relying on PID control, no matter how the PID parameters are matched, it is difficult to adapt the steam temperature to changes in various disturbances (such as changes in combustion conditions, dust accumulation in superheaters, large load fluctuations, soot blowing, etc.)
Moreover, once the operating conditions change greatly, the dynamic characteristics and model parameters of the steam temperature regulation object will be greatly affected, resulting in large temperature fluctuations
Therefore, it is difficult to obtain satisfactory control performance by using the traditional PID control method

Method used

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  • Predictive control method and system for boiler fuel based on machine learning
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  • Predictive control method and system for boiler fuel based on machine learning

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Embodiment 1

[0058] refer to figure 1 and figure 2 , is a machine learning-based boiler fuel predictive control method disclosed in the present invention, comprising the following steps:

[0059] S1. Obtain a temperature signal after water spraying. Wherein, the temperature signal after water spraying is obtained once every preset time, and step S2 is entered after each time the temperature signal after water spraying is obtained.

[0060] S2. Judging whether the currently obtained temperature signal after water spraying is normal; if it is judged that the temperature signal after water spraying is normal, go to step S3; if it is judged that the temperature signal after water spraying is abnormal, go back to step S1.

[0061] Specifically, by comparing the detected temperature parameter with the preset upper limit parameter and lower limit parameter, it is judged whether the temperature signal is normal after water spraying, when the temperature parameter is between the preset upper lim...

Embodiment 2

[0072] refer to Figure 4 , is a machine learning-based boiler fuel predictive control system disclosed in the present invention, comprising a main superheated main steam temperature adjustment module (10), a secondary temperature adjustment module (20) after superheated water spraying, an accumulative learning module (30) and a temperature Deviation calculation module (40). The input pin SP of the temperature sub-adjustment module (20) is connected with the output pin AV of the superheated main steam temperature main adjustment module (10) after superheated water spraying, and the output pin OT of the cumulative learning module (30) is connected with the superheated main steam temperature. The input pin OT of the main adjustment module (10) is connected, the output pin OB of the cumulative learning module (30) is connected with the input pin OB of the superheated main steam temperature main adjustment module (10), and the temperature deviation calculation module (40) The out...

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Abstract

The invention discloses a predictive control method and a system for boiler fuel based on machine learning, relates to the technical field of machine learning, and aims to solve the problem of poor control performance of the predictive control method for boiler fuel by using a conventional temperature cascade PID. The technical scheme is that the method comprises the following steps of: obtaininga temperature signal after water spray; determining whether the temperature signal after water spray is normal; obtaining a corrected temperature target upper limit assignment OT after water spray anda temperature target lower limit assignment OB after water spray according to a real-time temperature value after water spray and a preset cumulative learning algorithm; and limiting the temperaturetarget value range after water spray, which is output to the superheated temperature sub control after water spray by the temperature main control of superheated main steam, by leaning the obtained the temperature target upper limit assignment OT after water spray and the temperature target lower limit assignment OB after water spray. According to the predictive control method and the system for boiler fuel based on machine learning, the stability of the main steam temperature can be maintained without manual intervention, and the effect of effectively improving the control performance can berealized.

Description

technical field [0001] The invention relates to the technical field of machine self-learning, in particular to a machine learning-based boiler fuel predictive control method and system. Background technique [0002] Both thermal power and thermal power use boilers for energy conversion, turning water into high-temperature and high-pressure steam. The quality of steam is measured by temperature and pressure indicators. Among them, the steam temperature is an important indicator. The temperature should not be too low, otherwise the superheat of the steam will be insufficient, and the water vapor will impact the final stage blade of the turbine, which will bring equipment orders and safety hazards; the temperature should not be too high, otherwise, the boiler overheating will easily cause the steam pipeline Metal fatigue and creep occur under high temperature and pressure, resulting in reduced pipe life. Therefore, in industrial sites with boiler containers, temperature contro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 邹大勇钱华
Owner 苏州恩基热能科技有限公司