A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Intelligent engineering machinery operation attitude prediction method and system
The invention discloses an intelligent engineering machinery operation attitude prediction method and system. The method comprises the following steps: acquiring current operation attitude information of engineering machinery; based on the current operation attitude information of the engineering machinery, predicting the next operation attitude of the engineering machinery by adopting an intelligent extended Kalman filtering algorithm; according to the method, firstly, optimization is carried out by adopting the dogvessel alveolar algorithm, when the dogvessel alveolar algorithm falls into a local optimal state, the particle swarm algorithm is fused into the dogvessel alveolar algorithm, the search space is increased, and the improved dogvessel alveolar algorithm is obtained through multiple times of circulation. And optimizing a system noise covariance matrix in the extended Kalman filtering algorithm by using the improved doliolaria algorithm to obtain an intelligent extended Kalman filtering algorithm. Based on attitude information obtained by measurement and analysis of the inertial measurement unit, the next action of the engineering machinery is predicted by adopting an intelligent extended Kalman filtering algorithm, so that the precision of an operation attitude prediction result of the engineering machinery is improved.
本发明公开了一种智能工程机械作业姿态预测方法及系统，所述方法包括以下步骤：获取工程机械当前的作业姿态信息；基于工程机械当前的作业姿态信息，采用智能扩展卡尔曼滤波算法预测工程机械的下一步作业姿态；本发明首先采用樽海鞘算法进行寻优，当樽海鞘算法陷入局部最优状态时，将粒子群算法融入樽海鞘算法并增大搜索空间，多次循环得到改进的樽海鞘算法。利用改进樽海鞘算法优化扩展卡尔曼滤波算法中的系统噪声协方差矩阵，得到智能扩展卡尔曼滤波算法。基于惯性测量单元测量分析得到的姿态信息，采用智能扩展卡尔曼滤波算法预测工程机械的下一步动作，提高了工程机械作业姿态预测结果的精度。
Intelligent engineering machinery operation attitude prediction method and system
The invention discloses an intelligent engineering machinery operation attitude prediction method and system. The method comprises the following steps: acquiring current operation attitude information of engineering machinery; based on the current operation attitude information of the engineering machinery, predicting the next operation attitude of the engineering machinery by adopting an intelligent extended Kalman filtering algorithm; according to the method, firstly, optimization is carried out by adopting the dogvessel alveolar algorithm, when the dogvessel alveolar algorithm falls into a local optimal state, the particle swarm algorithm is fused into the dogvessel alveolar algorithm, the search space is increased, and the improved dogvessel alveolar algorithm is obtained through multiple times of circulation. And optimizing a system noise covariance matrix in the extended Kalman filtering algorithm by using the improved doliolaria algorithm to obtain an intelligent extended Kalman filtering algorithm. Based on attitude information obtained by measurement and analysis of the inertial measurement unit, the next action of the engineering machinery is predicted by adopting an intelligent extended Kalman filtering algorithm, so that the precision of an operation attitude prediction result of the engineering machinery is improved.
本发明公开了一种智能工程机械作业姿态预测方法及系统，所述方法包括以下步骤：获取工程机械当前的作业姿态信息；基于工程机械当前的作业姿态信息，采用智能扩展卡尔曼滤波算法预测工程机械的下一步作业姿态；本发明首先采用樽海鞘算法进行寻优，当樽海鞘算法陷入局部最优状态时，将粒子群算法融入樽海鞘算法并增大搜索空间，多次循环得到改进的樽海鞘算法。利用改进樽海鞘算法优化扩展卡尔曼滤波算法中的系统噪声协方差矩阵，得到智能扩展卡尔曼滤波算法。基于惯性测量单元测量分析得到的姿态信息，采用智能扩展卡尔曼滤波算法预测工程机械的下一步动作，提高了工程机械作业姿态预测结果的精度。
Intelligent engineering machinery operation attitude prediction method and system
一种智能工程机械作业姿态预测方法及系统
YAN WEI (author) / SUN FANGZHE (author) / LIU SHUQIANG (author) / WANG JIN (author) / HU BIN (author) / LI GUOXIANG (author)
2024-03-08
Patent
Electronic Resource
Chinese
IPC:
G06F
ELECTRIC DIGITAL DATA PROCESSING
,
Elektrische digitale Datenverarbeitung
/
E02F
Baggern
,
DREDGING
/
G01C
Messen von Entfernungen, Höhen, Neigungen oder Richtungen
,
MEASURING DISTANCES, LEVELS OR BEARINGS
/
G06N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
,
Rechnersysteme, basierend auf spezifischen Rechenmodellen
| European Patent Office | 2020
Engineering machinery system with intelligent monitoring function
| European Patent Office | 2021
Intelligent multifunctional machinery lifting type engineering machinery transferring device
| European Patent Office | 2020