Occupational risk evaluation is one of the most indispensable issues in the risk prevention and control process for the natural gas pipeline construction (NGPC) project. The Fine-Kinney model, recognized as an effective occupational risk evaluation technique, has limited capability to handle the occupational risk analysis problem under the complex spherical fuzzy (CSF) environment. Accordingly, a synthetical Fine-Kinney framework based on the compromise ranking of alternatives from distance to ideal solution (CRADIS) method is developed to overcome these downsides of occupation risk analysis in the NGPC project within the CSF context. A prioritized weighted average (PWA) operator for complex spherical fuzzy numbers (CSFNs) is incorporated into the group risk evaluation matrix generation process, which can take the priority degrees of experts into account. Then, the extended CRADIS method-based Fine-Kinney framework is generated, in which the Choquet integral for CSFNs is incorporated to reflect the impact of interactive risk factors. Next, the detailed solution procedures of the framework for handling the occupational risk evaluation problem are presented. Finally, the described framework is employed as an empirical example of occupational risk analysis for the NGPC project to demonstrate its feasibility in practice. After that, a sensitivity analysis of the parameter is investigated to testify to the stability and rationality of the reported synthetical Fine-Kinney framework. Subsequently, to further display the advantages of the developed Fine-Kinney framework, a comparative study is implemented to discuss the evaluation result of occupational risk derived from the proposed framework and those of the existing similar Fine-Kinney frameworks. The analysis results indicate that the occupational risk (attack by human or animal) with the maximum risk priority value (1.000) using the framework is identified as the most serious risk for the NGPC project.

职业风险评估是天然气管道建设（NGPC）项目风险防控过程中必不可少的问题之一。Fine-Kinney模型被认为是一种有效的职业风险评估技术，但在复杂球形模糊（CSF）环境下处理职业风险分析问题的能力有限。因此，开发了一种基于从距离到理想解决方案 (CRADIS) 方法的替代方案的折衷排名的综合 Fine-Kinney 框架，以克服 CSF 上下文中 NGPC 项目中职业风险分析的这些缺点。复杂球形模糊数（CSFN）的优先加权平均（PWA）算子被纳入组风险评估矩阵生成过程，可以考虑专家的优先度。然后，生成了基于扩展 CRADIS 方法的 Fine-Kinney 框架，其中结合了 CSFN 的 Choquet 积分以反映交互风险因素的影响。接下来，给出了处理职业风险评估问题的框架的详细解决过程。最后，所描述的框架被用作 NGPC 项目职业风险分析的经验示例，以证明其在实践中的可行性。之后，对该参数进行敏感性分析，以证明所报道的合成 Fine-Kinney 框架的稳定性和合理性。随后，为了进一步展示所开发的 Fine-Kinney 框架的优势，进行了一项比较研究，讨论了从提出的框架和现有的类似 Fine-Kinney 框架得出的职业风险评估结果。分析结果表明，使用该框架的风险优先级值最大（1.000）的职业风险（人或动物的攻击）被确定为NGPC项目最严重的风险。