Research on a risk assessment model for dense urban cable channels based on fuzzy mathematics

With the acceleration of urbanization, the safe and stable operation of dense urban cable channels is of great importance to the guarantee of urban power and communication systems. Cable channels face many sources of risk that bring great challenges to urban power supplies. Most existing risk assessment methods are based on accurate mathematical models, which require clear and deterministic boundaries of assessment indicators. These methods have difficulty in dealing with the fuzziness and uncertainty of cable channel risk factors, such as the challenge of determining the degree of aging of cable insulation or the degree of influence of external environmental factors that cannot be simply quantified. This paper presents a risk assessment model of a dense urban cable passage based on fuzzy mathematics. The model combines a membership function with a fuzzy comprehensive evaluation method to analyze and classify the risk factors of a dense urban cable passage. Eight risk factors were identified, including external damage, facility defects, and non-standard cable laying, and the importance of each factor was evaluated by constructing a membership matrix based on historical data and expert scoring methods. A typical dense cable trench and cable tunnel in actual operation in a region of China Southern Power Grid are analyzed, and the risk level is calculated by MATLAB 2021a programming. The results show that the model can effectively assess the level of risk and clearly show the impact of individual risk factors on the overall risk. For example, in the cable trench risk assessment, the model accurately identifies that external damage and cable overheating risk factors lead to moderate risk, and the remaining six factors are low risk. In the cable tunnel assessment, the corresponding risk level of each risk factor is also accurately determined. This indicates that the evaluation method based on fuzzy mathematics can not only quantify the uncertainty of risk factors but also improve the rationality of the evaluation results and provide a scientific decision basis for the safety management and maintenance of cable channels. The model has significant advantages over traditional evaluation methods.