Aircraft instrument panel pointer reading method based on target detection and key point recognition

By constructing an instrument panel image dataset and training and optimizing it using the YOLOv11-Pose model, combined with numerical mapping algorithms, the accuracy and efficiency issues of automated instrument panel testing in existing technologies have been resolved. This ensures efficient and accurate detection of aviation instrument panels, indirectly safeguarding flight safety.

CN121686426BActive Publication Date: 2026-06-26NANCHANG HANGKONG UNIVERSITY
2 Cites 0 Cited by

Patent Information

Application Number
CN202610179539.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-02-09
Publication Date
2026-06-26
Estimated Expiration
2046-02-09

AI Technical Summary

Technical Problem

In existing technologies, automated testing methods for aviation instrument panels cannot accurately identify key points and convert them into numerical values, resulting in high computational resource consumption. This makes them unsuitable for embedded or real-time testing scenarios, and manual reading is prone to errors, affecting flight safety.

Method used

An aviation instrument panel image dataset was constructed, trained using the YOLOv11-Pose model, and optimized through sparse training and Slim pruning. Combined with a numerical mapping algorithm, accurate detection and reading conversion of instrument pointers were achieved. Sparse training and Slim pruning methods were used to optimize computational resources, and a differentiated algorithm was adopted to process different types of instruments.

Benefits of technology

It enables accurate target detection and key point identification for different types of instrument panels, reduces computing resource consumption, improves detection efficiency and accuracy, and ensures the reliability of aviation equipment and flight safety.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The present application relates to the technical field of aviation instrument automation testing, and specifically relates to an aviation instrument panel pointer reading method based on target detection and key point identification, comprising: constructing an aviation instrument panel image dataset and labeling; selecting a YOLOv11-Pose model for training and optimization to obtain an optimized instrument identification model; using the optimized instrument identification model to identify a to-be-tested aviation instrument panel image, outputting a rectangular detection frame coordinate of the instrument and a key point coordinate of the instrument pointer; converting the key point coordinate of the instrument pointer into a specific reading value of the instrument; comparing the specific reading value of the instrument obtained through mapping with background real data to determine whether the instrument display is correct, thereby achieving instrument automation testing. The present application realizes accurate target detection and key point identification of different types of aircraft instrument panels through the pruned instrument identification model, and the output position information and key point coordinates provide reliable data support for subsequent reading calculation, avoiding the subjectivity and errors of manual identification.
Need to check novelty before this filing date? Find Prior Art