Large aircraft aviation big data fault detection and causal reasoning system and method based on deep random forest algorithm

Abstract

The invention provides a large aircraft aviation big data fault detection and causal reasoning system and method based on a deep random forest algorithm. The system comprises a fault diagnosis platform, a fault reason reasoning platform, a database storage computer and a client. The method comprises the following steps of comprehensively monitoring and acquiring operation parameters of each systemof an airplane in real time to form massive data sources, acquiring typical characteristics of the signals through calculation of the characteristic parameter spectrum, and extracting and describingfault characteristics in residual signals using the characteristics as parameters and storing the characteristics into a parameter database. The airplane parameter database is established through thefault diagnosis computer and the fault reason reasoning computer, so that fault information of an airplane or possible faults of the airplane is covered, faults and reasons are determined through diagnosis of the fault diagnosis computer and reasoning of the fault reason reasoning computer, a maintenance / isolation scheme is provided, and health monitoring and fault diagnosis of all systems of thewhole airplane are further realized.

Description

technical field [0001] The invention belongs to the field of health monitoring and fault detection of large aircraft operating systems, and in particular relates to a large aircraft aviation big data fault detection and causal reasoning system and method based on a deep random forest algorithm. Background technique [0002] In view of the complexity of large aircraft, whether it can quickly enter the ready state from the troubleshooting process has become an urgent requirement for modern aviation to achieve sustainable large traffic volume. Compared with decades of experience in design, development, and operation of foreign military and civilian transport aircraft, the development, manufacture, and testing of large aircraft in my country have just started, lacking a large amount of actual operating data, and the safety, maintainability, and reliability of large aircraft. etc. are still in the exploratory stage. However, domestic civil aviation has successfully operated more ...

AI Technical Summary

Problems solved by technology

Such a one-to-one monitoring and diagnosis method cannot take into account the possible cascading failures of the entire system or between different systems

However, system failures and cascading failures between systems are two types of failure modes that are difficult to resolve in existing large aircraft health monitoring systems

During the operation of the aircraft, a large amount of operational data will be generated. The use of aviation big data is a possible way to solve the above problems, but it has not yet been systematically proposed.

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