Aircraft Engine On-Line Diagnostics Through Dual-Channel Sensor Measurements: Development of a Baseline System

In this paper, a baseline system which utilizes dual-channel sensor measurements for aircraft engine on-line diagnostics is developed. This system is composed of a linear on-board engine model (LOBEM) and fault detection and isolation (FDI) logic. The LOBEM provides the analytical third channel against which the dual-channel measurements are compared. When the discrepancy among the triplex channels exceeds a tolerance level, the FDI logic determines the cause of the discrepancy. Through this approach, the baseline system achieves the following objectives: 1) anomaly detection, 2) component fault detection, and 3) sensor fault detection and isolation. The performance of the baseline system is evaluated in a simulation environment using faults in sensors and components. INTRODUCTION Aircraft gas turbine engines have evolved into a highly complex and sophisticated system to meet ever-increasing demands. The evolution of aircraft engine technologies has been driven by the need for improved fuel efficiency, reliability, operability, availability, and maintainability [1,2]. The reliability aspect of modern aircraft engines has been enhanced by equipping the engines with a dual channel fullauthority digital electronic control (FADEC). In this setup, a single engine parameter is measured by a dual-channel sensor, and the FADEC receives redundant measurements through dual channels. If a single channel fails, this failure is accommodated by utilizing the measurement on the other channel. Such an accommodation action can be taken only if the identity of the faulty sensor and its failed channel are known. Thus, in order to fully utilize the available redundancy for sensor fault accommodation, the ability to diagnose the sensors on line (real-time, in-flight) is required. The sensor fault detection and isolation process is initiated by cross-checking the redundant measurements of each dual-channel sensor. If both channels agree within a pre-established tolerance, the measurements on both channels are acceptable. If not, the cross-check fails, and one of the dual channels is considered faulty. A challenge arises in the subsequent process of identifying the faulty channel. Even if redundant measurements do not agree with each other, both of them may pass the range and rate checks [3]. Such a failure is called an in-range sensor fault and causes some difficulty in determining which channel is the failed one. The above problem can be addressed by providing an analytical third channel. This third channel functions as a referee in the decision making; the channel that disagrees most with the referee is likely the faulty channel. The analytical third channel is embedded within the FADEC in the form of an analytical representation of the real engine. This analytical representation is called an on-board engine model (OBEM) and has been a key element in on-line fault detection and † A dual-channel sensor is defined in this paper as a device which produces two measurements of the same engine parameter. The redundant measurements are referred to as channel A and channel B measurements. It is assumed that failures can occur in either one or both channels of the sensor. Aircraft Engine On-Line Diagnostics Through Dual-Channel Sensor Measurements: Development of a Baseline System Takahisa Kobayashi ASRC Aerospace Corporation Cleveland, Ohio 44135 Donald L. Simon National Aeronautics and Space Administration Glenn Research Center Cleveland, Ohio 44135 NASA/TM—2008-215228 1 accommodation since the advent of the FADEC [4,5]. The OBEM captures the real engine’s nominal behavior to some extent and provides expected engine output values in real time. In Ref. [3], a linear on-board engine model (LOBEM), which is composed of piecewise linear models generated at multiple operating conditions, is utilized for on-line sensor fault diagnostics. In this paper, an on-line diagnostic system that utilizes the LOBEM as an analytical third channel is developed for the aircraft engine application. This system is referred to as the baseline system, and it has a simple structure composed of the LOBEM and fault detection and isolation (FDI) logic. When the discrepancy among the triplex channels exceeds a tolerance level, the FDI logic determines the cause of the discrepancy. Through this approach, the baseline system achieves the following objectives: 1) anomaly detection, 2) component fault detection, and 3) sensor fault detection and isolation. Because of its simplicity, the baseline system can be executed with the computing power currently available in practice. Therefore, diagnostic performance representative of what is potentially achievable in the field can be determined through evaluation of the baseline system. In the following section, two main components of the baseline system—the LOBEM and the FDI logic—are discussed in detail. The influence of engine health degradation on the on-line diagnostic performance is also discussed. Then, the design approach is applied to a large commercial aircraft engine model. The performance of the baseline system is evaluated using simulated faults in sensors and components. NOMENCLATURE BST Booster CFS Component fault signature FADEC Full Authority Digital Electronic Control FDI Fault Detection and Isolation HPC High Pressure Compressor HPT High Pressure Turbine LOBEM Linear On-Board Engine Model LPT Low Pressure Turbine P2 Engine inlet pressure P25 HPC inlet pressure Pamb Ambient pressure PLA Power Lever Angle PS3 Combustor inlet static pressure T2 Engine inlet temperature T25 HPC inlet temperature T3 Combustor inlet temperature T49 LPT inlet temperature TMHS23 BST metal temperature TMHS3 HPC metal temperature TMHS41 HPT nozzle metal temperature TMHS42 HPT metal temperature TMHS5 LPT metal temperature TMHSBC Combustor case metal temperature TMHSBL Combustor liner metal temperature VBV Variable bleed valve VSV Variable stator vane WF36 Fuel flow XN12 Fan speed, measured XN25 Core speed, measured XNH Core speed, actual XNL Fan speed, actual e Environmental parameter vector h Health parameter vector href Reference health condition vector ucmd Control command vector v Sensor noise vector x State variable vector y Sensor output vector (controls/diagnostics) z Sensor output vector (ambient/engine inlet) DEVELOPMENT OF THE BASELINE SYSTEM FOR ON-LINE DIAGNOSTICS The objective of on-line diagnostics for aircraft engines is to detect, and if possible isolate, any fault as early as possible. With timely detection and accurate isolation of the fault, the necessary corrective actions can be taken to avoid undesirable engine operation and maintenance costs. To achieve this objective, the baseline system continuously monitors engine outputs for anomalous signatures induced by faults. The baseline system developed in this paper is composed of the LOBEM and FDI logic. Each component is described in this section. Linear On-Board Engine Model (LOBEM) An aircraft engine under consideration for on-line diagnostics is described by nonlinear equations of the following form: ( ) ( e u h x g y e u h x f x