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This paper addresses the issues of Fault Detection and Isolation (FDI) in complex networked systems such as the Environmental Control System (ECS) of an aircraft. The ECS controls and supplies pressurized air to the aircraft and consists of multiple subsystems that in turn consist of interconnected components, heterogeneous sensing devices, and feedback controllers. These complex interconnections and feedback control loops make fault detection and isolation a very challenging task in the ECS. For example, a faulty component yields off-nominal outputs which are inputs to the other coupled components. This coupling leads to off-nominal outputs from otherwise healthy components, thus causing unwanted false-alarms. Secondly, due to off-nominal inputs, the healthy components are driven beyond their normal operating conditions, leading to cascading failures.

This paper addresses the issue of fault diagnosis in the heat exchanger of an aircraft Air Conditioning System (ACS). The heat exchanger cools the air by transferring the heat to the ram-air. Due to a variety of biological, mechanical and chemical reasons, the heat exchanger may experience fouling conditions that reduces the efficiency and could considerably affect the functionality of the ACS. Since, the access to the heat exchanger is limited and time consuming, it is preferable to implement an early fault diagnosis technique that would facilitate Condition Based Maintenance (CBM). The main contribution of the paper is pre-flight fault assessment of the heat exchanger using a combined model-based and data-driven approach of fault diagnosis. A Simulink model of the ACS, that has been designed and validated by an industry partner, has been used for generation of sensor data for various fouling conditions.

This paper addresses the issues of data reduction, visualization, clustering and classification for fault diagnosis and prognosis of the Liquid Cooling System (LCS) in an aircraft. LCS is a cooling system that consists of a left and a right loop, where each loop is composed of a variety of components including a heat exchanger, source control units, a compressor, and a pump. The LCS data and the fault correlation analysis used in the paper are provided by Hamilton Sundstrand (HS) - A United Technologies Company (UTC). This data set includes a variety of sensor measurements for system parameters including temperatures and pressures of different components, along with liquid levels and valve positions of the pumps and controllers. A graphical user interface (GUI) is developed in Matlab that facilitates extensive plotting of the parameters versus each other, and/or time to observe the trends in the data.