# Health State Assessment of Road Tunnel Based on Improved Extension Cloud Model
## 1 Introduction
[18] combined AHP with game theory to construct a fuzzy multi-criteria decision-making analysis method. [PERSON] et al. [19] used the AHP and the entropy weight method to construct a tunnel construction safety evaluation system. The transformation between qualitative and quantitative values is unavoidable in the process of health status evaluation. The fuzziness and randomness problems exist in the boundary of health levels [20]. Academician [PERSON] proposed a cloud model which reflects the uncertainty in the concept of natural language, namely fuzziness and randomness. The cloud model can realize the conversion of qualitative and quantitative indicators through the cloud generator, which can effectively express fuzzy and random concepts [21]. [PERSON] et al. [21] proposed an evaluation method based on the improved cloud model and the improved evidence theory to accurately evaluate the fire risk of urban public tunnels. [PERSON] et al. [22] combined the variable weight theory with the cloud model theory to accurately evaluate the risk level of water inrush during karst tunnel construction. This approach helps to reduce the impact of subjective factors on evaluation results and rationalize the allocation of index weights. [PERSON] et al. [23] used the cloud model to evaluate the emergency capability of subway shield construction. [PERSON] et al. [24] set a detailed evaluation system based on the cloud model and the AHP to realize the risk assessment of highway tunnel construction. The above method proves the applicability of the cloud model in the study of highway tunnel health evaluation and effectively solves the fuzziness and randomness of the health status evaluation at the boundary. The extension theory is introduced into the health status evaluation due to its unique advantages in qualitatively or quantitatively analyzing and dealing with contradictory problems [25]. Up to now, the cloud model has been combined with the extension theory by some research fields to construct the extension cloud model. Compared with the cloud model, the extension cloud model is very suitable for health status evaluation as can solve the multi-index decision making problem. [PERSON] et al. [26] set a safety evaluation model for collisions of marine ships based on the extension cloud theory. The fuzziness and uncertainty of evaluation indicators are taken into account and the results of multiple evaluation indicators are integrated effectively in this model. The problem is that the uncertainty or fuzziness of evaluation level boundaries is considered inadequate in traditional mooring safety assessment methods. To solve this problem, [PERSON] et al. [27] constructed a ship mooring safety assessment model based on the normal cloud extension theory. [PERSON] et al. [28] evaluated the collapse risk of a water diversion tunnel during construction based on the extension cloud model. However, the use of the extension cloud model is not well-researched in the study of health assessment for road tunnels. The feasibility of applying the extension cloud model in the health assessment of road tunnels and the evaluation process based on the extension cloud model still needs further research. Based on the above, the health assessment system for tunnels is set according to dynamic and static evaluation indicators. The weight of the evaluation indicators is determined through subjective and objective combination weighting. In addition, the road tunnel health status evaluation method is set based on the improved extension cloud model. Finally, the feasibility of the method is verified by the detection data of the Zhangzhuo Expressway Tunnel. Specifically, this paper mainly contributes to the following aspects:  
* The relationship between the trend of changes in road tunnel health status and its health status is considered based on selecting static evaluation indicators. The health status evaluation system for road tunnels that combines dynamic and static evaluation is set after further selecting dynamic indicators.