Details

Autor(en) / Beteiligte

• Wu, Chao
• Zhao, Guolong
• Hu, Qiqi
• Zhao, Shenggang
• Gao, Ronghua

Titel

Attitude Signals Filtering Algorithm Based on Kalman and LSTM for Measurement While Drilling in Coal Mine

Ist Teil von

• Proceedings of the 2023 6th International Conference on Signal Processing and Machine Learning, 2023, p.333-342

Ort / Verlag

New York, NY, USA: ACM

Erscheinungsjahr

2023

Quelle

ACM Digital Library

Beschreibungen/Notizen

• In the drilling system of coal mine, due to the various spatial obstacles of the drilling site, the fading of communication, the strong vibration of the drilling equipment during operation, and the interference of magnetic field and temperature of different geographical locations, the accuracy of measurement results in real time is poor. After pre-processing the above problem by Kalman filtering, a back-sloping algorithm is introduced and a new one is obtained by parameter adjustment and test-and-simulation comparison. Experiments show that it is more accurate to simulate the pose problem by combining the new filtering algorithm with the above back-sloping algorithm.