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MEMS四元数卡尔曼滤波算法的电梯姿态估计

郭威¹, 吴允平^1,2,3, 王廷银^1,2,3

(1.福建师范大学光电与信息工程学院, 福州 350007;2.数字福建环境监测物联网实验室, 福州 350117;3.福建省光电传感应用工程技术研究中心, 福州 350007)

Elevator Attitude Estimation Based on MEMS Quaternion Kalman Filter Algorithm

GUO Wei¹, WU Yun-Ping^1,2,3, WANG Ting-Yin^1,2,3

(1.College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China;2.Digital Fujian Environmental Monitoring IoT Laboratory, Fuzhou 350117, China;3.Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, Fuzhou 350007, China)

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本文已被：浏览 1151次下载 1735次
Received:July 18, 2019 Revised:August 22, 2019

中文摘要: 将多维MEMS传感器应用于电梯监测，根据电梯的工作特点，优化四元数互补滤波方法修正陀螺仪数据求解电梯的实时姿态，然后应用卡尔曼滤波方法进一步提高姿态监测精度.实际验证表明，该方法可以提高电梯姿态监测数据的准确性，利用运行的姿态角和加速度峰度进行分析、比对可为电梯安全舒适度评估提供关键的数据依据.

中文关键词: MEMS 电梯姿态卡尔曼滤波舒适度

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.

keywords: MEMS elevator attitude Kalman filter comfort

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基金项目:国家自然科学基金-海峡联合基金重点项目（U1805263）；福建省引导性项目（2019H0009）；福建省自然科学基金（2019J01427）

引用文本：
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
GUO Wei,WU Yun-Ping,WANG Ting-Yin.Elevator Attitude Estimation Based on MEMS Quaternion Kalman Filter Algorithm.COMPUTER SYSTEMS APPLICATIONS,2020,29(3):246-252

Author Name	Affiliation	E-mail
GUO Wei	College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China
WU Yun-Ping	College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China Digital Fujian Environmental Monitoring IoT Laboratory, Fuzhou 350117, China Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, Fuzhou 350007, China
WANG Ting-Yin	College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China Digital Fujian Environmental Monitoring IoT Laboratory, Fuzhou 350117, China Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, Fuzhou 350007, China	tywang@fjnu.edu.cn

Author Name	Affiliation	E-mail
GUO Wei	College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China
WU Yun-Ping	College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China Digital Fujian Environmental Monitoring IoT Laboratory, Fuzhou 350117, China Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, Fuzhou 350007, China
WANG Ting-Yin	College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou 350007, China Digital Fujian Environmental Monitoring IoT Laboratory, Fuzhou 350117, China Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, Fuzhou 350007, China	tywang@fjnu.edu.cn