Blended Filter-Based Detection for Thruster Valve Failure and Control Recovery Evaluation for RLV

Abstract

Security enhancement and cost reduction have become crucial goals for second-generation reusable launch vehicles (RLV). The thruster is an important actuator for an RLV, and its control normally requires a valve capable of high-frequency operation, which may lead to excessive wear or failure of the thruster valve. This paper aims at developing a thruster fault detection method that can deal with the thruster fault caused by the failure of the thruster valve and play an emergency role in the cases of hardware sensor failure. Firstly, the failure mechanism of the thruster was analyzed and modeled. Then, thruster fault detection was employed by introducing an angular velocity signal, using a blended filter, and determining an isolation threshold. In addition, to support the redundancy management of the thruster, an evaluation method of the nonlinear model-based numerical control prediction was proposed to evaluate whether the remaining fault-free thruster can track the attitude control response performance under the failure of the thruster valve. The simulation results showed that the method is stable and allowed for the effective detection of thruster faults and timely evaluation of recovery performance.

Recent Advances in Intelligent Algorithms for Fault Detection and Diagnosis

“…Quantitative feature extraction strategies include PLS/PCA, ANNs (artificial neural networks), and SVMs (support vector machines) [ 4 , 6 , 14 , 17 , 23 ]. We assume without further investigation that there exists both the measurement data collected from nominal and problematic system behavior and a model used for residual generation.…”

“…A failure occurs when the system cannot complete its intended task because of an unending delay. Therefore, the failure indicates that a process unit’s role has concluded and is caused by some interrelated factors [ 4 ]. Based on their predictability, failures may be classified as random (unpredictable), deterministic, or systematic/casual.…”

“…As a consequence, process-based models and practical estimating methodologies have found widespread application in the field. In particular, there has been a lot of interest in a wide variety of effective process monitoring and fault diagnosis (PM-FD) systems built upon multivariate statistical methods since the advent of sensor technology that enables the regular collection of data on a large number of process variables [ 4 ]. Systems like this are intended to detect and isolate issues in real-time in a process.…”

“…Systems like this are intended to detect and isolate issues in real-time in a process. The study presented two well-known multivariate-based projection strategies for process monitoring [ 4 ]. The principal component analysis (PCA) and partial least squares (PLS) techniques are the names given to these methodologies, respectively.…”

“…Collecting bad information that accurately represents each failure scenario takes a lot of time and effort. As a result, the available training data and the number of possible fault realizations are not the same [ 3 , 4 ].…”