Research on fault prediction and maintenance strategy optimization of thermal power generation boilers
火力发电锅炉故障预测与检修策略优化研究

摘要

火力发电锅炉作为电力生产的关键设备，其运行状态直接影响到电力系统的稳定性和效率。本研究旨在探讨基于现代数据分析技术的故障预测方法以及优化检修策略，以提高锅炉运行的安全性与经济性。当前火力发电锅炉在故障预测方面面临的挑战，包括数据处理复杂、预测模型不精确等问题。提出了一种集成多种算法的智能故障预测系统，并通过案例验证了该系统的有效性和可靠性。基于故障预测结果提出了针对性的检修策略优化方案，强调预防性维护的重要性。通过科学合理的检修策略和精准的故障预测，能够显著降低锅炉故障率，提升发电效率。

Abstract

As a key equipment in power generation, the operation status of the thermal power generation boiler directly affects the stability and efficiency of the power system. This study aims to explore the fault prediction method based on modern data analysis technology and the optimized maintenance strategy, so as to improve the safety and economy of boiler operation. Currently, thermal power generation boilers face challenges in fault prediction, including complex data processing, inaccurate prediction models and other issues. An intelligent fault prediction system integrating multiple algorithms is proposed, and the effectiveness and reliability of the system are verified through a case study. Based on the fault prediction results, a targeted optimization scheme for the maintenance strategy is proposed, emphasizing the importance of preventive maintenance. Through scientific and reasonable maintenance strategies and accurate fault prediction, the failure rate of the boiler can be significantly reduced, and the power generation efficiency can be improved.