The insulated gate bipolar transistor (IGBT) module plays a pivotal role in the modular multilevel converter (MMC), making online monitoring essential for ensuring the MMC system’s safety, reliability, and cost-effectiveness. Addressing the challenge of real-time monitoring for multi-chip parallel IGBT modules in the MMC system, this paper presents a design method of condition monitoring system based on the relationship between the module’s case temperature distribution and its aging state, which enables adaptive evaluation and management of IGBT module under different operating conditions. Firstly, the impact of aging failure on the heat flow of IGBT modules in MMC sub-modules is analyzed, with case temperature selected as the characteristic parameter representing the module's state. Secondly, an aging state monitoring model for IGBT, based on neural network, is established. This model is adaptable to different working points, allowing for the characterization and identification of module states according to the demand preference of different application scenarios. Finally, the proposed condition monitoring system design method is verified on MMC test platform, demonstrating its feasibility and effectiveness. This paper provides an innovative solution for IGBT status monitoring in MMC sub-modules under high power operating conditions, offering a practical and effective approach to state maintenance.