Temperature Sensor Fault Detection in Chiller Based on One-class Support Vector Machine Algorithm

Mao Qianjun; Liang Zhiyuan; Liu Donghua; Hu Yunpeng; Li Guannan; Fang Xi

doi:10.3969/j.issn.0253-4339.2019.05.130

您当前的位置：

首页 >

文章列表页 >

Temperature Sensor Fault Detection in Chiller Based on One-class Support Vector Machine Algorithm

更新时间：2024-07-18

- Temperature Sensor Fault Detection in Chiller Based on One-class Support Vector Machine Algorithm
- Journal of Refrigeration Vol. 40, Issue 5, (2019)
- 作者机构：
  
  1. 武汉科技大学城市建设学院
  2. 武汉商学院
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0253-4339.2019.05.130
  CLC：
- Published：2019
- 稿件说明：
移动端阅览
Mao Qianjun, Liang Zhiyuan, Liu Donghua, et al. Temperature Sensor Fault Detection in Chiller Based on One-class Support Vector Machine Algorithm[J]. Journal of refrigeration, 2019, 40(5).
DOI：

Mao Qianjun, Liang Zhiyuan, Liu Donghua, et al. Temperature Sensor Fault Detection in Chiller Based on One-class Support Vector Machine Algorithm[J]. Journal of refrigeration, 2019, 40(5). DOI： 10.3969/j.issn.0253-4339.2019.05.130.

摘要

冷水机组系统中，温度传感器出现故障会严重影响机组工作效率及使用寿命。针对冷水机组温度传感器偏差故障，本文提出一种基于单类支持向量机(one-class support vector machine

OC-SVM)的故障检测方法，采用冷水机组正常数据建立OC-SVM模型，通过十折交叉验证法获得模型优化参数。分别采用工程实测数据、实验数据(共4组)对该方法进行了验证，结果表明：基于OC-SVM的方法能有效检测出4组冷水机组的温度传感器偏差故障。其中对于螺杆式冷水机组（数据集Ⅰ)的故障检测效果明显，当冷冻水侧温度传感器偏差故障幅值绝对值大于1 ℃时，检测效率达到100%。

Abstract

Temperature sensor faults may lead to abnormal system operations that can damage the chiller system and reduce its life span. Herein

a fault detection method based on the one-class support vector machine (OC-SVM) algorithm has been proposed. Fault-free data were used to train the OC-SVM model for detection of temperature sensor biases. The optimized model parameters were obtained by the 10-fold cross validation method. Four chiller datasets

including in-site and laboratory data

were used to validate the proposed method. Results showed that the OC-SVM showed good fault detection performance on the four chiller datasets

with the effect of fault detection being especially obvious for the screw chiller (dataset I). The detection efficiency reached 100%

when the absolute value of temperature sensor fault biases at chilled-water side was greater than 1 ℃.

关键词

Keywords

references

Views

6694

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Fault Detection for Chiller Based on DR-BN

Experimental Investigation on Water Fouling Risk in Small Diameter Tubes of Chillers

Theoretical Limit of Chiller Efficiency

Research on Fault Diagnosis of Chillers Based on Improved BP Network

Related Author

Zhou Xiwen

Tan Yingying

Yuan Junfei

Wang Lin

Wang Zhanwei

Zhang Huan

Li Yuhan

Zhan Feilong

Related Institution

Institute of Refrigeration, Heat Pump, and Air Conditioning, Henan University of Science and Technology

GD Midea Refrigeration Equipment Co., Ltd.

GD Midea HVAC Equipment Co., Ltd.

Institute of Refrigeration and Cryogenic Engineering, Shanghai Jiao Tong University

浙江大学电气工程学院

Address：10/F, Yindu Mansion, 67 Fucheng Road, Haidian Dist, Beijing, China Postal code：100142
Tel：010-68711412 Email：editor@car.org.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09064830号-19 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰