Abstract:

The detection of crane braking descent distance faces numerous challenges in practical engineering applications, primarily due to limitations in the measurement accuracy of existing detection equipment, the complexity of on?site operations, and high equipment costs. A method is proposed to obtain the braking descent distance by using inertial sensors to collect acceleration and angular velocity data during the crane braking process, performing attitude calculation, and combining it with a double integration algorithm. First, a Lagrangian dynamic model of the crane is established to analyze the coupling relationship between the braking descent distance and the equipment environment. Second, a data acquisition device is designed, the detection steps are described, and data synchronous transmission is employed to enhance signal reliability. Finally, the data processing method is investigated, a complete data processing workflow is designed, complex integration algorithms are compared and analyzed, and practical feasibility is verified. The results indicate that this detection method can prevent serious accidents such as load dropping caused by insufficient braking performance, offering superior comprehensive performance, strong feasibility, and promising market prospects.

Key words: Crane, Mathematical model, Acceleration, Compound Simpson's integral, Braking slip

摘要：

起重机制动下滑量检测在实际工程应用中面临诸多挑战，主要受限于现有检测设备的测量精度、现场操作的复杂程度以及高昂的设备成本等因素。提出了利用惯性传感器采集起重机制动过程的加速度和角速度信息并进行姿态解算，结合二次积分算法获得制动下滑量的方法。首先，建立起重机的拉格朗日动力学模型，分析制动下滑量与设备环境之间的耦合关系；其次，设计数据采集装置，阐述检测步骤，并通过数据同步传输提高信号可靠性；最后，对数据处理方法展开研究，设计完整的数据处理流程，对复杂积分算法进行比对分析，并验证方法的实践可行性。结果表明，通过该检测方法可避免因制动性能不足导致重物坠落等严重事故的发生，具有综合性能优越、可行性强的优点，且具备较好的市场前景。

关键词: 起重机, 数学模型, 加速度, 复化辛普森积分, 制动下滑量