Exploration of intelligent tunnel excavation has consistently attracted continuous research over the past decades to improve efficiency, reliability, and safety for urban tunnel construction projects (Pan et al. in Exp Syst Appl 225, 2023 [1]). Generally, the success of tunnel projects highly relies on the performance of tunnel boring machines (TBM). Due to complex geological conditions and knowledge gaps, the current industry practice for TBM operation mainly relies on human experience which may result in compromised TBM performance or safety hazards if there is a lack of experience or human errors (Zhou et al. in Autom Constr 107, 2019 [2]). Thanks to the continuous advancement in sensor technologies, sensors that are equipped around TBM can generate big data that records the working status in real time. Such data provides unprecedented research opportunities to upgrade TBM with a higher level of intelligence and better performance.