IMU Tabanlı Dinamik Eğim Sensörü için Hibrit Filtreleme Yönteminin Geliştirilmesi ve Performans Analizi

Öz

MEMS (Mikro-Elektromekanik Sistemler) teknolojisindeki gelişmeler, çeşitli uygulamalarda IMU (Atalet Ölçüm Birimi) tabanlı eğim sensörlerinin doğruluğunu ve entegrasyon potansiyelini önemli ölçüde artırmıştır. Ancak dinamik ortamlarda, dış ivmeler ve titreşimler sensör performansını olumsuz etkilemektedir ve bu da gürültüye yol açmaktadır. Bu çalışma, 6 eksenli bir IMU'yu entegre eden ve açı ölçüm hatalarını en aza indirmeyi amaçlayan Kalman Filtresi, Hareketli Ortalama Filtresi ve Alçak Geçiren Filtre olmak üzere birden fazla filtreleme stratejisi uygulayan dinamik bir eğim sensörü cihazı önermektedir. Dinamik koşullar altında filtre performansını değerlendirmek için özel bir test platformu geliştirilmiştir. RMSE (Kök Ortalama Karekök Hatası) ölçümleri kullanılarak değerlendirilen sonuçlar, üç filtreyi birleştiren özel olarak tasarlanmış bir hibrit filtreleme yönteminin statik koşullarda 0,017° ve dinamik koşullarda 1,178° ortalama hata elde ettiğini göstermektedir. Bulgular, önerilen hibrit yaklaşımın literatürdeki mevcut çözümlere kıyasla güvenilir bir alternatif sunduğunu, endüstriyel uygulamalarda ölçüm kararlılığını ve doğruluğunu artırdığını göstermektedir.

Anahtar Kelimeler

• Dijital Filtre
• Dinamik Eğim Sensörü
• Eğimölçer
• Eğim Sensörü
• IMU
• MEMS

Development and Performance Analysis of a Hybrid Filtering Method for IMU-Based Dynamic Tilt Sensor

Öz

Advancements in MEMS (micro-electromechanical systems) technology have significantly improved the accuracy and integration potential of IMU (inertial measurement unit) based tilt sensors across various applications. However, in dynamic environments, external accelerations and vibrations adversely affect sensor performance and this leads to noise. This study proposes a dynamic tilt sensor device integrating a 6-axis IMU and implements multiple filtering strategies, that are Kalman Filter, Moving Average Filter, and Low-Pass Filter aimed at minimizing angle measurement errors. A custom test platform was developed to evaluate filter performance under dynamic conditions. The results, evaluated using RMSE (root mean square error) metrics, show that a specially designed hybrid filtering method combining the three filters achieves an average error of 0.017° in static and 1.178° in dynamic conditions. The findings demonstrate that the proposed hybrid approach offers a reliable alternative comparable to existing solutions in literature, enhancing measurement stability and accuracy in industrial applications.

Anahtar Kelimeler

• Digital Filter
• Dynamic Tilt Sensor
• IMU
• Inclinometer
• MEMS
• Tilt Sensor

Kaynakça

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