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Study of scintillation detector fault diagnosis based on ELM method

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成果类型:
期刊论文
作者:
Ding, Tiansong;Yan, Yongjun;Li, Xiang;Liu, Linfei
通讯作者:
Yongjun Yan
作者机构:
[Ding, Tiansong; Liu, Linfei; Li, Xiang; Yan, Yongjun] Univ South China, Coll Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.
通讯机构:
[Yongjun Yan] C
College of Nuclear Science and Technology, University of South China, Hengyang, Hunan Province 421001, China
语种:
英文
关键词:
ELM;Fault diagnosis;Machine learning;Scintillation detector
期刊:
NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT
ISSN:
0168-9002
年:
2022
卷:
1032
页码:
166637
基金类别:
National Natural Science Foundation of China [11575081]; Natural Science Foundation of Hunan Province, China [2018JJ2317]
机构署名:
本校为第一机构
院系归属:
核科学技术学院
摘要:
This paper proposes a method for scintillation detector fault diagnosis based on the Extreme Learning Machine (ELM) algorithm. A related characteristics database is established including the falling edge time, signal amplitude of nuclear pulse signals, and energy spectrum peak channel, low channel address count of energy spectrum signal under various operating conditions. Then a diagnosis model for scintillation detector is created by improved ELM algorithm which have changed the activation function of the hidden layers and modified the number of hidden layers. An experiment system is also con...

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