Elevator Attitude Estimation Based on MEMS Quaternion Kalman Filter Algorithm
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    Abstract:

    The multi-dimensional MEMS sensor is applied to elevator monitoring. According to the working characteristics of the elevator, the quaternion complementary filtering method is modified to correct the gyroscopedata to solve the real-time attitude of the elevator, and then the Kalman filtering method is applied to further improve the attitude monitoring accuracy. The actual verification shows that the method can improve the accuracy of elevator attitude monitoring data,and use the attitude angle and acceleration kurtosis to analyze and compare, which can provide critical data basis for elevator safety and comfort assessment.

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郭威,吴允平,王廷银. MEMS四元数卡尔曼滤波算法的电梯姿态估计.计算机系统应用,2020,29(3):246-252

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History
  • Received:July 18,2019
  • Revised:August 22,2019
  • Adopted:
  • Online: March 02,2020
  • Published: March 15,2020
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