Optimization method of waste heat valve control based on fusion drive

LIU Jing; LI Chaoran; ZHANG Jiannan; ZHAO Jia

doi:10.19666/j.rlfd.202306390

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Optimization method of waste heat valve control based on fusion drive

更新时间：2025-09-28

- Optimization method of waste heat valve control based on fusion drive
- Thermal Power Generation Vol. 52, Issue 10, Pages: 176-186(2023)
- 作者机构：
  
  1. 河北工业大学人工智能与数据科学学院
  2. 河北省数据驱动工业智能工程研究中心
  3. 天津开发区精诺瀚海数据科技有限公司
  4. 河北工业大学理学院
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202306390
  CLC： TH134;TK115
- Published：2023
- 稿件说明：
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LIU Jing, LI Chaoran, ZHANG Jiannan, et al. Optimization method of waste heat valve control based on fusion drive[J]. Thermal power generation, 2023, 52(10): 176-186.
DOI：

LIU Jing, LI Chaoran, ZHANG Jiannan, et al. Optimization method of waste heat valve control based on fusion drive[J]. Thermal power generation, 2023, 52(10): 176-186. DOI： 10.19666/j.rlfd.202306390.

摘要

传统余热阀门控制技术主要分为机理建模和数据驱动2种方法，但在实际的应用中前者因机理复杂，难以准确描述，后者要求数据质量高、工况样本全，难以短时间满足。针对上述问题，提出一种基于融合驱动的余热阀门控制优化方法，该方法首先融合机理知识与数据知识构建基于模糊集合的知识图谱模型，将阀门开度知识实体化；其次，建立基于时间保护机制的长短时记忆（long short-term memory

LSTM）神经网络阀门开度优化模型，并提出时间保护机制算法，确定阀门最优调节频率；最后，通过知识推理得到推荐阀门开度。经实验分析验证，该方法通过融合余热回收机理等定性知识和设备运行数据等定量知识，在提升设备安全性的同时，产生的高温饱和蒸汽焓值提升概率为94%，平均每天可提升8 640 k J，实现了余热回收阀门开度的智慧决策。

Abstract

The traditional waste heat valve control technology is mainly divided into two methods

mechanism modeling and data-driven. However

in practical applications

the former is difficult to accurately describe due to the complex mechanism. The latter requires high data quality and full working condition samples

which is difficult to meet in a short time. Aiming at the above problems

a fusion-driven optimization method for waste heat valve control is proposed. Firstly

the mechanism knowledge and data knowledge are fused to construct a knowledge graph model based on fuzzy sets

and the valve opening knowledge is materialized. Secondly

the LSTM valve opening optimization model based on time protection mechanism is established

and the time protection mechanism algorithm is proposed to determine the optimal adjustment frequency of the valve. Finally

the recommended valve opening is obtained by knowledge reasoning. Through experimental analysis and verification

this method integrates qualitative knowledge such as waste heat recovery mechanism and quantitative knowledge such as equipment operation data. While improving the safety of equipment

the probability of generating high-temperature saturated steam enthalpy is increased by 94%

and the average daily increase is 8 640 kJ

which realizes the intelligent decision of waste heat recovery valve opening.

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