A novel method for evaluating the operating status of complex intelligent equipment

Haitian Zeng; Zhaoguo Wang; Yibo Xue; Jie Zhang

doi:10.1109/ICEI.2019.00053

A novel method for evaluating the operating status of complex intelligent equipment

Haitian Zeng
, Zhaoguo Wang
, Yibo Xue
, Jie Zhang

Tsinghua University
Tianjin Electric Power Corporation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

At present, there is no good analytical method for determining the operating status of the complex intelligent equipment. Decision methods based on thresholds have limitations, often get false positives and false negatives, and there are problems with wasted energy, high maintenance costs and low efficiency. Therefore, in order to reflect the overall operating status of the complex intelligent equipment effectively, we proposed a comprehensive operating status evaluation method based on the data-driven method, and gave the health degree is used to quantify its operating status. First, we analyzed the relationship and differences between feature parameters, and used GBDT regression algorithm to build the fitted model. Then we gave the definition and calculation method of health degree. Finally, we combined the regression model with the health degree to evaluate the operating status of the complex intelligent equipment. Our experimental results demonstrate the feasibility and effectiveness of the proposed analytical method in evaluation of the operating status of complex intelligent equipment.

Original language	English
Title of host publication	Proceedings - IEEE International Conference on Energy Internet, ICEI 2019
Editors	Guokai Wu, Jiye Wang, Qinliang Tan
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	261-266
Number of pages	6
ISBN (Electronic)	9781728114934
DOIs	https://doi.org/10.1109/ICEI.2019.00053
State	Published - May 2019
Externally published	Yes
Event	3rd IEEE International Conference on Energy Internet, ICEI 2019 - Nanjing, China Duration: 27 May 2019 → 31 May 2019

Publication series

Name	Proceedings - IEEE International Conference on Energy Internet, ICEI 2019

Conference

Conference	3rd IEEE International Conference on Energy Internet, ICEI 2019
Country/Territory	China
City	Nanjing
Period	27/05/19 → 31/05/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Complex intelligent equipment
Energy consumption
Evaluation
Health degree
Machine learning

Access to Document

10.1109/ICEI.2019.00053

Cite this

Zeng, H., Wang, Z., Xue, Y., & Zhang, J. (2019). A novel method for evaluating the operating status of complex intelligent equipment. In G. Wu, J. Wang, & Q. Tan (Eds.), Proceedings - IEEE International Conference on Energy Internet, ICEI 2019 (pp. 261-266). Article 8791407 (Proceedings - IEEE International Conference on Energy Internet, ICEI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICEI.2019.00053

Zeng, Haitian ; Wang, Zhaoguo ; Xue, Yibo et al. / A novel method for evaluating the operating status of complex intelligent equipment. Proceedings - IEEE International Conference on Energy Internet, ICEI 2019. editor / Guokai Wu ; Jiye Wang ; Qinliang Tan. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 261-266 (Proceedings - IEEE International Conference on Energy Internet, ICEI 2019).

@inproceedings{206e2c33ec2d4eebb68d75fbe61bcb64,

title = "A novel method for evaluating the operating status of complex intelligent equipment",

abstract = "At present, there is no good analytical method for determining the operating status of the complex intelligent equipment. Decision methods based on thresholds have limitations, often get false positives and false negatives, and there are problems with wasted energy, high maintenance costs and low efficiency. Therefore, in order to reflect the overall operating status of the complex intelligent equipment effectively, we proposed a comprehensive operating status evaluation method based on the data-driven method, and gave the health degree is used to quantify its operating status. First, we analyzed the relationship and differences between feature parameters, and used GBDT regression algorithm to build the fitted model. Then we gave the definition and calculation method of health degree. Finally, we combined the regression model with the health degree to evaluate the operating status of the complex intelligent equipment. Our experimental results demonstrate the feasibility and effectiveness of the proposed analytical method in evaluation of the operating status of complex intelligent equipment.",

keywords = "Complex intelligent equipment, Energy consumption, Evaluation, Health degree, Machine learning",

author = "Haitian Zeng and Zhaoguo Wang and Yibo Xue and Jie Zhang",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 3rd IEEE International Conference on Energy Internet, ICEI 2019 ; Conference date: 27-05-2019 Through 31-05-2019",

year = "2019",

month = may,

doi = "10.1109/ICEI.2019.00053",

language = "英语",

series = "Proceedings - IEEE International Conference on Energy Internet, ICEI 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "261--266",

editor = "Guokai Wu and Jiye Wang and Qinliang Tan",

booktitle = "Proceedings - IEEE International Conference on Energy Internet, ICEI 2019",

address = "美国",

}

Zeng, H, Wang, Z, Xue, Y & Zhang, J 2019, A novel method for evaluating the operating status of complex intelligent equipment. in G Wu, J Wang & Q Tan (eds), Proceedings - IEEE International Conference on Energy Internet, ICEI 2019., 8791407, Proceedings - IEEE International Conference on Energy Internet, ICEI 2019, Institute of Electrical and Electronics Engineers Inc., pp. 261-266, 3rd IEEE International Conference on Energy Internet, ICEI 2019, Nanjing, China, 27/05/19. https://doi.org/10.1109/ICEI.2019.00053

A novel method for evaluating the operating status of complex intelligent equipment. / Zeng, Haitian; Wang, Zhaoguo; Xue, Yibo et al.
Proceedings - IEEE International Conference on Energy Internet, ICEI 2019. ed. / Guokai Wu; Jiye Wang; Qinliang Tan. Institute of Electrical and Electronics Engineers Inc., 2019. p. 261-266 8791407 (Proceedings - IEEE International Conference on Energy Internet, ICEI 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A novel method for evaluating the operating status of complex intelligent equipment

AU - Zeng, Haitian

AU - Wang, Zhaoguo

AU - Xue, Yibo

AU - Zhang, Jie

PY - 2019/5

Y1 - 2019/5

N2 - At present, there is no good analytical method for determining the operating status of the complex intelligent equipment. Decision methods based on thresholds have limitations, often get false positives and false negatives, and there are problems with wasted energy, high maintenance costs and low efficiency. Therefore, in order to reflect the overall operating status of the complex intelligent equipment effectively, we proposed a comprehensive operating status evaluation method based on the data-driven method, and gave the health degree is used to quantify its operating status. First, we analyzed the relationship and differences between feature parameters, and used GBDT regression algorithm to build the fitted model. Then we gave the definition and calculation method of health degree. Finally, we combined the regression model with the health degree to evaluate the operating status of the complex intelligent equipment. Our experimental results demonstrate the feasibility and effectiveness of the proposed analytical method in evaluation of the operating status of complex intelligent equipment.

AB - At present, there is no good analytical method for determining the operating status of the complex intelligent equipment. Decision methods based on thresholds have limitations, often get false positives and false negatives, and there are problems with wasted energy, high maintenance costs and low efficiency. Therefore, in order to reflect the overall operating status of the complex intelligent equipment effectively, we proposed a comprehensive operating status evaluation method based on the data-driven method, and gave the health degree is used to quantify its operating status. First, we analyzed the relationship and differences between feature parameters, and used GBDT regression algorithm to build the fitted model. Then we gave the definition and calculation method of health degree. Finally, we combined the regression model with the health degree to evaluate the operating status of the complex intelligent equipment. Our experimental results demonstrate the feasibility and effectiveness of the proposed analytical method in evaluation of the operating status of complex intelligent equipment.

KW - Complex intelligent equipment

KW - Energy consumption

KW - Evaluation

KW - Health degree

KW - Machine learning

UR - https://www.scopus.com/pages/publications/85071589316

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DO - 10.1109/ICEI.2019.00053

M3 - 会议稿件

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T3 - Proceedings - IEEE International Conference on Energy Internet, ICEI 2019

SP - 261

EP - 266

BT - Proceedings - IEEE International Conference on Energy Internet, ICEI 2019

A2 - Wu, Guokai

A2 - Wang, Jiye

A2 - Tan, Qinliang

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd IEEE International Conference on Energy Internet, ICEI 2019

Y2 - 27 May 2019 through 31 May 2019

ER -

Zeng H, Wang Z, Xue Y, Zhang J. A novel method for evaluating the operating status of complex intelligent equipment. In Wu G, Wang J, Tan Q, editors, Proceedings - IEEE International Conference on Energy Internet, ICEI 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 261-266. 8791407. (Proceedings - IEEE International Conference on Energy Internet, ICEI 2019). doi: 10.1109/ICEI.2019.00053

A novel method for evaluating the operating status of complex intelligent equipment

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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