Coal milling system fault diagnosis based on improved NSET

REN Mengyi; JIAO Songming

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Coal milling system fault diagnosis based on improved NSET

更新时间：2025-09-28

- Coal milling system fault diagnosis based on improved NSET
- Thermal Power Generation Vol. 44, Issue 12, Pages: 87-92(2015)
- 作者机构：
  
  华北电力大学自动化系
- 作者简介：
- 基金信息：
- DOI：
  CLC： TD94;TD453
- Published：2015
- 稿件说明：
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REN Mengyi, JIAO Songming. Coal milling system fault diagnosis based on improved NSET[J]. Thermal power generation, 2015, 44(12): 87-92.
DOI：

REN Mengyi, JIAO Songming. Coal milling system fault diagnosis based on improved NSET[J]. Thermal power generation, 2015, 44(12): 87-92. DOI：

摘要

为能够快速、准确地对制粉系统故障进行诊断

根据制粉系统的运行特性和故障特征

对基于非线性状态估计的制粉系统故障诊断方法

提出了新的构造过程记忆矩阵的方法

依据马氏距离对故障数据样本进行预处理

并使用预处理后的数据构造过程记忆矩阵

从而有效地减少了冗余数据

提高了诊断效率和诊断的实用性和稳定性。

Abstract

To diagnose the faults occurred in pulverizing system accurately and rapidly

this paper proposed a novel method for constructing the process memory matrix

against the pulverizing system fault diagnosis method based on nonlinear state estimation

according to the operation characteristics and fault features of the coal milling system.This new method is used to pretreat fault data based on Mahalanobis distance.In addition

it establishes process memory matrix based on the pretreated fault data to reduce redundancy data.By this way

the new method improves the fault diagnosis efficiency and plays a more active role in ensuring practicability and stability of the coal milling system fault diagnosis.

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