Article: Study on fault diagnosis and recovery for digital distribution networks: ITOT fusion Journal: International Journal of Business Intelligence and Data Mining (IJBIDM) 2026 Vol.28 No.9 pp.43 - 62 Abstract: This study proposed a fault diagnosis and recovery method of digital distribution network based on ITOT fusion. Build a digital distribution network operation data acquisition architecture using ITOT fusion technology, and perform PCA dimensionality reduction on the collected data. Input the data into a genetic algorithm optimised wavelet neural network to obtain fault diagnosis results. Build a digital distribution network fault recovery model based on the fault diagnosis results, and solve the fault recovery model using the BPSOGWO algorithm to obtain the optimal fault recovery strategy. In diagnosing faults, the proposed method attains a remarkable average accuracy of up to 97.55%, the average fault recovery rate is 96.88%, and the fault recovery time varies between 0.8 s and 1.9 s. Inderscience Publishers - linking academia, business and industry through research

Title: Study on fault diagnosis and recovery for digital distribution networks: ITOT fusion

Authors: Chunmei Zhang; Xingque Xu; Yongjian Li; Silin Liu; Jianyi Li

Addresses: Zhongshan Power Supply Bureau, Guangdong Power Grid Co., Ltd. Zhongshan, 528400, China ' Zhongshan Power Supply Bureau, Guangdong Power Grid Co., Ltd. Zhongshan, 528400, China ' Zhongshan Power Supply Bureau, Guangdong Power Grid Co., Ltd. Zhongshan, 528400, China ' Zhongshan Power Supply Bureau, Guangdong Power Grid Co., Ltd. Zhongshan, 528400, China ' Zhongshan Power Supply Bureau, Guangdong Power Grid Co., Ltd. Zhongshan, 528400, China

Abstract: This study proposed a fault diagnosis and recovery method of digital distribution network based on ITOT fusion. Build a digital distribution network operation data acquisition architecture using ITOT fusion technology, and perform PCA dimensionality reduction on the collected data. Input the data into a genetic algorithm optimised wavelet neural network to obtain fault diagnosis results. Build a digital distribution network fault recovery model based on the fault diagnosis results, and solve the fault recovery model using the BPSOGWO algorithm to obtain the optimal fault recovery strategy. In diagnosing faults, the proposed method attains a remarkable average accuracy of up to 97.55%, the average fault recovery rate is 96.88%, and the fault recovery time varies between 0.8 s and 1.9 s.

Keywords: ITOT fusion; digital distribution network; fault diagnosis; fault recovery; optimised wavelet neural network; BPSOGWO algorithm.

DOI: 10.1504/IJBIDM.2026.154225

International Journal of Business Intelligence and Data Mining, 2026 Vol.28 No.9, pp.43 - 62

Received: 05 Nov 2025
Accepted: 02 Feb 2026
Published online: 17 Jun 2026 *

Title: Study on fault diagnosis and recovery for digital distribution networks: ITOT fusion

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