A data-driven health indicator extraction method for aircraft air conditioning system health monitoring |
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Authors: | Jianzhong SUN Chaoyi LI Cui LIU Ziwei GONG Ronghui WANG |
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Institution: | 1. Department of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;2. Maintenance Engineering Department, Xiamen Airlines, Xiamen 361000, China |
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Abstract: | Prognostics and Health Management (PHM) has become a very important tool in modern commercial aircraft. Considering limited built-in sensing devices on the legacy aircraft model, one of the challenges for airborne system health monitoring is to find an appropriate health indicator that is highly related to the actual degradation state of the system. This paper proposed a novel health indicator extraction method based on the available sensor parameters for the health monitoring of Air Conditioning System (ACS) of a legacy commercial aircraft model. Firstly, a specific Airplane Condition Monitoring System (ACMS) report for ACS health monitoring is defined. Then a non-parametric modeling technique is adopted to calculate the health indicator based on the raw ACMS report data. The proposed method is validated on a single-aisle commercial aircraft widely used for short and medium-haul routes, using more than 6000 ACMS reports collected from a fleet of aircraft during one year. The case study result shows that the proposed health indicator can effectively characterize the degradation state of the ACS, which can provide valuable information for proactive maintenance plan in advance. |
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Keywords: | Air conditioning system Aircraft health monitoring Airplane condition monitoring system Health indicator Prognostics and health management |
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