Transient Current Ratio Dendrite Net for High-Resistance Connection Diagnosis in BLDCM

Luo, Chong; Wang, Jianyu; Miao, Qiang

doi:10.1109/tpel.2024.3356069

Cited by 1 publication

(1 citation statement)

References 28 publications

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“…The data-driven approach utilizes monitoring signals to extract fault information, which can be categorized into two types: feature-based and end-to-end approaches [7]. Electrical current and vibration signals are two common monitoring signals in an induction motor [8,9]. Feature-based approach processes raw signals to directly extract fault features that are derived from statistical characteristics, frequency domain attributes, and time-frequency domain attributes.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis of induction motor in the cooling water supply system using a multi-channel data fusion transformer with limited sample conditions^*

Niu,

Wang,

Miao

2024

Meas. Sci. Technol.

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Induction motors play a vital role in the cooling water supply system of hydropower facilities. However, it is unrealistic to collect suffi-cient fault samples in hydropower station. The scarcity of labeled samples poses a challenge in developing a powerful diagnostic model with high classification accuracy. To address this challenge, this paper proposes a multi-channel data fusion strategy based on Trans-former for feature enhancement. Initially, original signals are transferred into non-overlapping single-channel data patches to preserve correlation features across different channels. Then, temporal and spatial attention modules are applied to process the data patches, which can learn and fuse temporal and spatial information, respectively. Subsequently, the data patches are embedded to retain posi-tion information and represent fault-related features through class embedding, which are further processed by a Transformer encoder with self-attention mechanisms. Finally, the classification task is achieved by utilizing a multilayer perceptron layer connected to the class embedding. In facing up with limited training samples, the proposed method could learn robust features that are beneficial to improve the fault diagnosis ability of induction motor. The proposed method is compared with three basic models and two improved methods, demonstrating the superiority of the proposed method in accuracy and feature clustering performance with limited sample conditions. Additionally, the ablation experiment demonstrates the necessity of each module in the proposed method.

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Section: Introductionmentioning

confidence: 99%

Fault diagnosis of induction motor in the cooling water supply system using a multi-channel data fusion transformer with limited sample conditions^*

Niu,

Wang,

Miao

2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

Transient Current Ratio Dendrite Net for High-Resistance Connection Diagnosis in BLDCM

Cited by 1 publication

References 28 publications

Fault diagnosis of induction motor in the cooling water supply system using a multi-channel data fusion transformer with limited sample conditions^*

Fault diagnosis of induction motor in the cooling water supply system using a multi-channel data fusion transformer with limited sample conditions^*

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Transient Current Ratio Dendrite Net for High-Resistance Connection Diagnosis in BLDCM

Cited by 1 publication

References 28 publications

Fault diagnosis of induction motor in the cooling water supply system using a multi-channel data fusion transformer with limited sample conditions*

Fault diagnosis of induction motor in the cooling water supply system using a multi-channel data fusion transformer with limited sample conditions*

Contact Info

Product

Resources

About

Fault diagnosis of induction motor in the cooling water supply system using a multi-channel data fusion transformer with limited sample conditions^*

Fault diagnosis of induction motor in the cooling water supply system using a multi-channel data fusion transformer with limited sample conditions^*