Helicopter Cockpit Audio Data Analysis to Infer Flight State Information

摘要

In recent years, the National Transportation Safety Board has highlighted the importance of analyzing flight data as one of the effective methods to improve the safety and efficiency of helicopter operations. Since cockpit audio data contain various sounds from engines, alarms, crew conversations, and other sources within a cockpit, analyzing cockpit audio data can help identify the causes of incidents and accidents. Among the various types of the sounds in cockpit audio data, this paper focuses on cockpit alarm and engine sounds as an object of analysis. This paper proposes cockpit audio analysis algorithms, which can detect types and occurrence times of alarm sounds for an abnormal flight and estimate engine-related flight parameters such as an engine torque. This is achieved by the following: for alarm sound analysis, finding the highest correlation with the short time Fourier transform, and the Cumulative Sum Control Chart (CUSUM) using a database of the characteristic features of the alarm; and for engine sound analysis, using data mining and statistical modeling techniques to identify specific frequencies associated with engine operations. The proposed algorithm is successfully applied to a set of simulated audio data, which were generated by the X-plane flight simulator, and real audio data, which were recorded by GoPro cameras in Sikorsky S-76 helicopters to demonstrate its desired performance.