{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T00:49:41Z","timestamp":1760057381782,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,2,6]],"date-time":"2025-02-06T00:00:00Z","timestamp":1738800000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Project of State Grid Hubei Electric Power Co., Ltd., Xiaogan Power Supply Company (Research on proactive warning method of abnormal operation of substation equipment based on deep learning)","award":["SGHBXG00JXJS2310925"],"award-info":[{"award-number":["SGHBXG00JXJS2310925"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computation"],"abstract":"<jats:p>The paper proposes a method for circuit breaker state judgment based on ant colony algorithm-optimized Dempster-Shafer evidence theory.It can improve the accuracy and robustness of state judgment. As a key device in the power system, the state judgment of circuit breakers is crucial for the safety and stability of the power grid. Existing methods have limitations in handling conflicts and uncertainties of multi-source data, and a single model is difficult to meet the needs of complex data fusion. Therefore, the paper applies the ant colony algorithm to optimize the basic probability assignment in Dempster-Shafer evidence theory to improve the fusion effect of multi-source data. The ant colony algorithm, through its global search and adaptive characteristics, can effectively optimize evidence combination and enhance the accuracy of the fusion results. The experiment used a support vector machine model based on current signals and a decision tree model based on vibration signals for data fusion and discrimination. The results showed that the Dempster-Shafer evidence theory model optimized by the ant colony algorithm achieved a discrimination accuracy of 75% under various circuit breaker conditions. Compared to the Dempster-Shafer evidence theory fusion model, it improved by approximately 8.3%, and compared to the current research\u2019s Dempster-Shafer evidence theory and neural network methods, it improved by 5%.. This method has broad application prospects in enhancing the operational stability of power grid equipment and improving fault detection efficiency.<\/jats:p>","DOI":"10.3390\/computation13020043","type":"journal-article","created":{"date-parts":[[2025,2,6]],"date-time":"2025-02-06T08:53:41Z","timestamp":1738832021000},"page":"43","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Research on the Circuit Breaker State Judgment Method Based on Ant Colony Optimization Dempster-Shafer Evidence Theory"],"prefix":"10.3390","volume":"13","author":[{"given":"Qian","family":"Zhang","sequence":"first","affiliation":[{"name":"State Grid Hubei Electric Power Co., Ltd., Xiaogan Power Supply Company, Xiaogan 432000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhi","family":"Liu","sequence":"additional","affiliation":[{"name":"State Grid Hubei Electric Power Co., Ltd., Xiaogan Power Supply Company, Xiaogan 432000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhilan","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Grid Hubei Electric Power Co., Ltd., Xiaogan Power Supply Company, Xiaogan 432000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Guo","sequence":"additional","affiliation":[{"name":"State Grid Hubei Electric Power Co., Ltd., Xiaogan Power Supply Company, Xiaogan 432000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Wang","sequence":"additional","affiliation":[{"name":"State Grid Hubei Electric Power Co., Ltd., Xiaogan Power Supply Company, Xiaogan 432000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3368-9215","authenticated-orcid":false,"given":"Runze","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaqi","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1109\/TPEL.2020.3003358","article-title":"A review of solid-state circuit breakers","volume":"36","author":"Rodrigues","year":"2020","journal-title":"IEEE Trans. Power Electron."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1186\/s41601-023-00304-y","article-title":"Circuit breakers in HVDC systems: State-of-the-art review and future trends","volume":"8","author":"Taherzadeh","year":"2023","journal-title":"Prot. Control Mod. Power Syst."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Qian, Z., Qi, X., Wang, S., Cao, W., Han, S., and Zhu, F. (2021, January 8\u20139). The Research and Application on the Intelligent Control System of the GIS Circuit Breaker. Proceedings of the 2021 International Conference on Power System Technology (POWERCON), Haikou, China.","DOI":"10.1109\/POWERCON53785.2021.9697797"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"022013","DOI":"10.1088\/1742-6596\/1748\/2\/022013","article-title":"State evaluation of circuit breakers based on improved fuzzy comprehensive evaluation method","volume":"1748","author":"Wu","year":"2021","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1109\/OJIES.2023.3320900","article-title":"A review on Hybrid Circuit Breakers for DC applications","volume":"4","author":"Bento","year":"2023","journal-title":"IEEE Open J. Ind. Electron. Soc."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"107990","DOI":"10.1016\/j.epsr.2022.107990","article-title":"Fault detection and diagnosis in power transformers: A comprehensive review and classification of publications and methods","volume":"209","author":"Abbasi","year":"2022","journal-title":"Electr. Power Syst. Res."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Moreno Escobar, J.J., Morales Matamoros, O., Tejeida Padilla, R., Lina Reyes, I., and Quintana Espinosa, H. (2021). A comprehensive review on smart grids: Challenges and opportunities. Sensors, 21.","DOI":"10.3390\/s21216978"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Zhao, X., Lv, S., Guan, X., Liu, W., Wang, H., Li, X., Ma, C., and Lu, Y. (2024, January 26\u201328). Research on Mechanical Fault Diagnosis Method of Circuit Breakers Based on Fusion of Multi-Source Signal Data. Proceedings of the 2024 7th International Conference on Energy, Electrical and Power Engineering (CEEPE), Yangzhou, China.","DOI":"10.1109\/CEEPE62022.2024.10586454"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"5269","DOI":"10.1109\/TCE.2024.3424280","article-title":"Hybrid Model of Multiple Echo State Network Integrated by Evidence Fusion for Fault Diagnosis of a High-Voltage Circuit Breaker","volume":"70","author":"Li","year":"2024","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"102088","DOI":"10.1016\/j.aei.2023.102088","article-title":"Trusted multi-source information fusion for fault diagnosis of electromechanical system with modified graph convolution network","volume":"57","author":"Zhang","year":"2023","journal-title":"Adv. Eng. Inform."},{"key":"ref_11","unstructured":"Qi, H. (2022). Research on Fault Diagnosis of High Voltage Circuit Breaker Based on Compressed Sensing Theory. [Master\u2019s Thesis, Lanzhou Jiaotong University]."},{"key":"ref_12","unstructured":"Li, Q. (2020). Research on Mechanical Fault Diagnosis Method for Universal Circuit Breakers Based on Convolutional Neural Networks. [Master\u2019s Thesis, Hebei University of Technology]."},{"key":"ref_13","unstructured":"Sun, Y. (2023). Research on Mechanical Fault Diagnosis Method of High Voltage Circuit Breaker Based on Electric-Vibration Signal Combination. [Master\u2019s Thesis, School of Electrical and Electronic Engineering]."},{"key":"ref_14","unstructured":"Lin, J. (2019). Research on Mechanical Fault Diagnosis Method for Circuit Breakers Based on Vibration Signals. [Master\u2019s Thesis, Shandong University]."},{"key":"ref_15","first-page":"4883","article-title":"Online Monitoring Method for Electrical Life of High-Voltage SF6 Circuit Breakers Based on Contact Vibration Characteristics of Arc Contacts","volume":"39","author":"Li","year":"2024","journal-title":"Trans. China Electrotech. Soc."},{"key":"ref_16","unstructured":"Chen, C. (2024). Research on Mechanical Fault Diagnosis Method of Air Circuit Breakers Based on Machine. [Master\u2019s Thesis, Chongqing Jiaotong University]."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Chen, Z. (2022). Research on Fault Diagnosis Method for Mechanical Components of Circuit Breakers Based on ANFIS. [Master\u2019s Thesis, Hebei University of Science and Technology].","DOI":"10.1109\/IAECST57965.2022.10062208"},{"key":"ref_18","first-page":"159","article-title":"Mechanical Fault Diagnosis of Circuit Breaker Based on Wavelet Packet Energy Spectrum and Support Vector Machine","volume":"52","author":"Peng","year":"2023","journal-title":"Mech. Electr. Eng. Technol."},{"key":"ref_19","first-page":"267","article-title":"Mechanical Status Identification of High Voltage Circuit Breakers Based on Principal Component Analysis and Support Vector Machines","volume":"56","author":"Liu","year":"2020","journal-title":"High Volt. Appar."},{"key":"ref_20","first-page":"99","article-title":"Design of On-Line Fault Monitoring System for Circuit Breaker Electric Operating Mechanism","volume":"09","author":"Liu","year":"2022","journal-title":"Lamps Light."},{"key":"ref_21","first-page":"152","article-title":"Fault diagnosis of high-voltage circuit breaker based on SO-PAA-GAF and AdaBoost ensemble learning","volume":"52","author":"Si","year":"2024","journal-title":"Power Syst. Prot. Control"},{"key":"ref_22","first-page":"112","article-title":"Application of Improved Random Forest Method in Mechanical Fault Diagnosis of Circuit Breakers","volume":"43","author":"Xu","year":"2021","journal-title":"Meas. Detect. Tech."},{"key":"ref_23","first-page":"250","article-title":"Research on Whale Optimization Algorithm-bidirectional Long-short-term Memory Neural Network for Prediction of Machinery Remaining Useful Life of Circuit Breaker","volume":"50","author":"Li","year":"2024","journal-title":"High Volt. Eng."},{"key":"ref_24","first-page":"77","article-title":"Partial Discharge Detection Technology of Open Circuit Breakers Based on D-S Evidence Theory","volume":"36","author":"Wang","year":"2023","journal-title":"Guangdong Electr. Power"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"110894","DOI":"10.1016\/j.measurement.2022.110894","article-title":"Fault diagnosis of high voltage circuit breaker based on multi-sensor information fusion with training weights","volume":"192","author":"Zhang","year":"2022","journal-title":"Measurement"}],"container-title":["Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-3197\/13\/2\/43\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:28:08Z","timestamp":1760027288000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-3197\/13\/2\/43"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,6]]},"references-count":25,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2025,2]]}},"alternative-id":["computation13020043"],"URL":"https:\/\/doi.org\/10.3390\/computation13020043","relation":{},"ISSN":["2079-3197"],"issn-type":[{"type":"electronic","value":"2079-3197"}],"subject":[],"published":{"date-parts":[[2025,2,6]]}}}