Enhanced Fault Isolation and Part Recommendation for Airplane Health Management with Hybrid Probabilistic Modeling

Abstract

Aircraft maintenance plays a crucial role in ensuring the safety and reliability of aircraft operations. Effective fault isolation and accurate part recommendation are essential tasks in the maintenance process. The accuracy of existing fault isolation solutions in complex situations (e.g. having multiple fault code scenarios) needs improvement. In this paper, we propose a novel approach of Hybrid Probabilistic Modeling based Fault Isolation Framework combining two solutions. One of the solutions is Pattern Similarity-based Probabilistic Modeling (PSPM) which leverages historical maintenance data to build a probabilistic model that captures patterns of faults and their associated parts replacement. By comparing the current fault symptoms to these patterns, this solution enables more accurate fault isolation and suggests suitable parts for replacement compared to legacy methods. On the other hand, the Physics Informed Probabilistic Modeling (PIPM) employs a Bayesian network to leverage system knowledge in terms of schematics, particularly in scenarios where historical data is sparse or non-existent. Both probabilistic modeling-based solutions complement each other, address gaps, and enhance the efficiency and effectiveness of aircraft fault isolation.

In this paper, we will first provide an introduction that outlines the significance of aircraft maintenance and the challenges associated with fault isolation. Following this, we will present a survey of existing fault isolation techniques, highlighting their strengths and limitations. We will then discuss the proposed hybrid solution and its advantages in improving fault isolation. Next, we will delve into the Pattern Similarity-based Probabilistic Modeling (PSPM) methodology, detailing its benefits and showcasing a case study that highlights its effectiveness. We will also explore the Physics Informed Probabilistic Modeling (PIPM) approach, presenting an overview of its theoretical foundations and a case study that illustrates its practical application. Finally, we will conclude with a summary of our findings and their implications for future research and practice in the field of aircraft maintenance.