Modelling of Cupping Suction System based on System Identification Method

Kavindran Suresh, M. R. Ghazali, Mohd Ashraf Ahmad
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Abstract

The detection of cupped suction system plants using a standard model based on a modified Sine Cosine Algorithm (mSCA) is presented in this research. According to the findings, the mSCA-based technique can produce optimal parameters of model that provides an identified output response comparable to the actual experiment's cupping suction system output, with an integral square error for various random input surfaces and its objective function. The input and output data were used to create this modelling output variable of the cupping suction system detected by connecting the differential pressure sensor to the cup. In contrast, the input variable is determined by the speed of the pump applied in various locations. The transfer function model also makes use of the continuous-time transfer function.
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基于系统辨识法的拔罐抽吸系统建模
提出了一种基于改进正弦余弦算法(mSCA)的标准模型对吸力系统植物的检测方法。根据研究结果,基于msca的技术可以产生最优的模型参数,提供与实际实验的拔罐吸力系统输出相当的识别输出响应,并且对各种随机输入曲面及其目标函数具有平方误差。输入和输出数据被用来创建拔罐抽吸系统的建模输出变量,通过将差压传感器连接到杯子上来检测。相反,输入变量是由泵在不同位置的转速决定的。传递函数模型还利用了连续时间传递函数。
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