[1]CUI Tiejun,WANG Chongxin,LI Shasha.System fault evolution direction based on topological safety entropy and an entropy gradient field[J].CAAI Transactions on Intelligent Systems,2026,21(3):776-782.[doi:10.11992/tis.202510010]
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System fault evolution direction based on topological safety entropy and an entropy gradient field

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 21 Number of periods: 2026 3 Page number: 776-782 Column: 学术论文—人工智能基础 Public date: 2026-05-05
Title:
System fault evolution direction based on topological safety entropy and an entropy gradient field
Author(s):
CUI Tiejun1; 2;  WANG Chongxin1;  LI Shasha1; 2
1. School of Environmental and Chemical Engineering, Shenyang Ligong University, Shenyang 110159, China;
2. Liaoning Safety Engineering Industry School, Shenyang Ligong University, Shenyang 110159, China
Keywords:
complex system; system fault; evolution; topological safety entropy; entropy gradient field; critical point identification; evolution direction; space fault network; fault prediction
CLC:
TP181；X913
DOI:
10.11992/tis.202510010
Abstract:
To quantify the disorder of fault evolution paths and determine the dominant fault types in complex systems, a system fault evolution direction analysis model based on topological safety entropy and an entropy gradient field is proposed. The system is abstracted as a node–link topological structure, and the topological safety entropy is calculated through node failure rate weights and topological proportions to quantify the degree of disorder. The topological entropy space gradient and evolutionary parameter entropy gradient are solved, and the dominant type of fault evolution is determined based on the gradient angle. By combining this solution with the Hessian matrix, the critical point of system topology instability is identified, and the threshold for fault type jump is clarified. The basic idea of the algorithm and the derivation process of the mathematical model are given. A wind turbine is taken as an example for verification. The results show that the system’s topological safety entropy (2.2577 bit) is near the theoretical upper limit, reflecting that the system is in a high-risk disordered state; the evolution direction angle (30.9°) tends to electrical component failure, which is consistent with the conclusions of the controller’s high weight (0.6133) and high topological proportion (0.2224); the critical parameters are a vibration frequency of 55.4 Hz and a temperature of 174.2 °C, which serve as the threshold for fault type jump. Finally, the physical meaning of the results is discussed. This research provides methods for fault prediction and safety management of complex systems.
References:
[1] 崔铁军. 空间故障网络理论与系统故障演化过程研究[J]. 安全与环境学报, 2020(4): 1255-1262 CUI Tiejun. Profound trace and exploration into the space fault network theory and the system fault evolution process[J]. Journal of safety and environment, 2020(4): 1255-1262
[2] 金智新, 王延生, 邓存宝, 等. 广义安全结构理论研究[J]. 中国安全科学学报, 2017, 27(5): 41-46 JIN Zhixin, WANG Yansheng, DENG Cunbao, et al. Research on generalized safety structure theory[J]. China safety science journal, 2017, 27(5): 41-46
[3] 崔铁军, 李莎莎. 系统故障演化过程熵及其受逻辑关系的影响研究[J]. 智能系统学报, 2024, 19(3): 749-756 CUI Tiejun, LI Shasha. Study on entropy of system fault evolution process and its influence on logical relationships[J]. CAAI transactions on intelligent systems, 2024, 19(3): 749-756
[4] 郭力萌, 金智新, 王延生, 等. 基于安全结构理论的系统外部扰动演化规律研究[J]. 中国安全生产科学技术, 2022, 18(5): 60-65 GUO Limeng, JIN Zhixin, WANG Yansheng, et al. Study on evolution law of system external disturbance based on safety structure theory[J]. Journal of safety science and technology, 2022, 18(5): 60-65
[5] 朱峻永, 杨东赞, 王昕, 等. 面向智能变电站运维的连锁故障态势感知研究[J]. 电力系统保护与控制, 2025, 53(16): 136-146 ZHU Junyong, YANG Dongzan, WANG Xin, et al. Research on cascading failure situation awareness for smart substation operation and maintenance[J]. Power system protection and control, 2025, 53(16): 136-146
[6] 刘万, 尹纯亚, 李凤婷, 等. 交流故障下光储弱电网电压波动传导路径及对频率变化影响分析[J]. 电网与清洁能源, 2025, 41(7): 107-115, 121 LIU Wan, YIN Chunya, LI Fengting, et al. An analysis of voltage fluctuation conduction paths and impacts on frequency change of photovoltaic-energy storage-weak grids under AC faults[J]. Power system and clean energy, 2025, 41(7): 107-115, 121
[7] 王坤, 陈良银, 胥林, 等. 软件定义广域网中多控制器故障下的路径可编程性恢复方法[J]. 四川大学学报(自然科学版), 2025, 62(4): 838-846 WANG Kun, CHEN Liangyin, XU Lin, et al. Path programmability recovery under multiple controller failures in software-defined WAN[J]. Journal of Sichuan University (natural science edition), 2025, 62(4): 838-846
[8] 程志鹏, 张斌, 陈郑淦哲, 等. 基于长元路径异构图神经网络的故障诊断方法 [J/OL]. 控制理论与应用: 1-9[2025-09-10]. https://link.cnki.net/urlid/44.1240.TP.20250424.1615.062. CHENG Zhipeng, ZHANG Bin, CHEN Zhengganzhe, et al. Fault diagnosis method based on long meta-path heterogeneous graph neural network [J/OL]. Control theory & applications: 1-9[2025-09-10]. https://link.cnki.net/urlid/44.1240.TP.20250424.1615.062.
[9] 张煜佳, 袁野, 周苏洋, 等. 基于动态图投影的大规模复杂配电网故障快速溯源方法[J]. 电力系统自动化, 2025, 49(13): 177-186 ZHANG Yujia, YUAN Ye, ZHOU Suyang, et al. Fast fault back-tracing method for large-scale complex distribution networks based on dynamic graph projection[J]. Automation of electric power systems, 2025, 49(13): 177-186
[10] 钱小毅, 王利鑫, 姜兴宇, 等. 基于交互监测与连通性模型的化工过程故障传播分析 [J/OL]. 化工学报: 1-14[2025-09-10]. https://link.cnki.net/urlid/11.1946.TQ.20250313.1152.002. QIAN Xiaoyi, WANG Lixin, JIANG Xingyu, et al. Fault propagation analysis of chemical process based on interactive monitoring and connectivity model [J/OL]. CIESC journal: 1-14[2025-09-10]. https://link.cnki.net/urlid/11.1946.TQ.20250313.1152.002.
[11] 谭帅, 王一帆, 姜庆超, 等. 基于不同故障传播路径差异化的故障诊断方法[J]. 自动化学报, 2025(1): 161-173 TAN Shuai, WANG Yifan, JIANG Qingchao, et al. Fault propagation path-aware network: a fault diagnosis method[J]. Acta automatica sinica, 2025(1): 161-173
[12] 金智新, 王延生, 邓存宝. 基于安全结构理论的安全事件内涵数学表达[J]. 中国安全科学学报, 2017, 27(10): 38-43 JIN Zhixin, WANG Yansheng, DENG Cunbao. Intension expressing of safety events based on safety structure theory[J]. China safety science journal, 2017, 27(10): 38-43
[13] 崔铁军, 李莎莎. 空间故障网络的柔性逻辑描述[J]. 智能系统学报, 2021, 16(3): 552-559 CUI Tiejun, LI Shasha. Flexible logic description of space fault network[J]. CAAI transactions on intelligent systems, 2021, 16(3): 552-559
[14] 李洪兴, 汪培庄. 概念在因素空间中的落影表现[J]. 烟台大学学报(自然科学与工程版), 1994(2): 15-22 LI Hongxing, WANG Peizhuang. Falling shadow representation of fuzzy concepts on factor spaccs[J]. Journal of Yantai University (natural science and engineering edition), 1994(2): 15-22
[15] ZHU Bin, WANG Xian. A cover-based framework for topological complexity in hyperspace dynamical systems[J]. Communications in nonlinear science and numerical simulation, 2026, 159: 109887
[16] FLORENTINO M. Relation between Filippov systems with zero topological entropy and Li–Yorke chaos[J]. Chaos, solitons & fractals, 2026, 207: 118067
[17] LUPATINI P, CARVALHO SILVA F, VAR?O R. Entropy for compact operators and results on entropy and specification[J]. Monatshefte für mathematik, 2026, 209(3): 497-511
[18] HALDER S, KIM C M, PERIWAL V. Topological entropy correlates with the predictive power of multiplexed ensemble reservoir computing[EB/OL]. (2026-02-07)[2026-03-01]. https://10.64898/2026.02.04.703839.
[19] TIAN Ruoyao, SUN Haorui, MEI Biao, et al. A heterogeneous graph neural network with spatial–temporal and operating condition-aware message passing mechanism for RUL prediction of aero-engines[J]. Advanced engineering informatics, 2026, 73: 104507
[20] LIANG Xiucheng, YAP W, BILJECKI F. Heterogeneous graph neural networks for building attribute prediction from hierarchical urban features and cross-view imagery[J]. ISPRS journal of photogrammetry and remote sensing, 2026, 234: 185-204
[21] PENG Jiangliang, LI Zhiyi, YANG Lianmei, et al. Dynamic diagnosis of an extreme precipitation event over the southern slope of Tianshan Mountains using multi-source observations[J]. Remote sensing, 2025, 17(9): 1521
[22] 李智. 智能变电站二次设备的GRU故障定位与连锁故障态势感知方法[D]. 成都: 西南交通大学, 2023. LI Zhi. Method on fault location of secondary equipment in smart substation based on GRU and situation awareness of cascading failure[D]. Chengdu: Southwest Jiaotong University, 2023.
[23] ERPYLEVA V, BALASHOV Y. Use of automated tools for analyzing the propagation of failures in aircraft system[J]. E3S web of conferences, 2023, 402: 02005
[24] AMIN M T. An integrated methodology for fault detection, root cause diagnosis, and propagation pathway analysis in chemical process systems[J]. Cleaner engineering and technology, 2021, 4: 100187
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