超声致动泵无传感器温控系统研究

发布时间：2018-04-01 21:16

本文选题：心室辅助　切入点：超声电机　出处：《上海交通大学》2015年硕士论文

【摘要】：目前全世界心衰病人数量不断上升,而可供移植的心脏数量严重不足。大部分终末期心衰患者需要寻求一种机械循环支持系统,辅助或替代心脏的功能。本课题组开发的用于心室辅助的超声致动泵作为机械循环支持系统的一种,期望在将来可以作为心脏移植的有效补充,为心衰病人提供新的治疗和心室辅助手段。超声致动泵是通过超声电机驱动凸轮-推板挤压血腔,以收缩-舒张形式泵血的搏动式人工心脏。它可以产生类似于人体自身心脏活动的搏动流,而且通过转矩大、体积小的超声电机驱动挤压泵血,从而易于控制、有植入可能性。但是超声致动泵在工作中会产生较大的发热现象,这一现象对泵体的植入有着较大的影响。温升会破坏血液、体内器官组织,还会降低电机自身的寿命。为了在植入的状态下测量超声致动泵的温升并加以控制,设计了无传感器的无创泵体温度检测方法,以防止传感器的相关导线管路对人体的影响。本文设计了超声致动泵的无传感器温度预测与控制系统。首先量化了超声致动泵的整体发热情况,然后采用遗传算法改进型的神经网络通过易测的参数预测泵体温度,而且基于温度结果实现了调频控制,达到不使用传感器无创控制泵体温升的目的,最终通过实验验证这一控制方法可兼顾泵体的辅助效果与温升特性。目前所取得的成果有:1.研究了超声致动泵的发热机理,具体分析了超声电机和凸轮摩擦两部分的温升,而且量化了这两部分大致的功耗范围,为理解泵体的整体发热情况做了指导。2.通过分析在系统中选择易于测量且相关性强的驱动频率、主动脉压力和超声电机驱动电流三个参数,利用BP神经网络预测温升。使用遗传算法改进神经网络预测结果,并通过大样本的仿真验证精度。3.基于Compact RIO实时控制平台设计了超声致动泵温度无传感器控制系统,稳定了泵体运行温升特性。4.搭建了模拟体外循环系统,利用模拟的左心室、体循环系统和超声致动泵采集模拟的人体参数。用于预测温度和控制后,测量泵体压力流量特性曲线,验证控温后的辅助效果。
[Abstract]:The number of heart failure patients around the world is on the rise, and the number of heart transplants is severely inadequate. Most end-stage heart failure patients need to seek a mechanical circulatory support system. As a mechanical circulatory support system, we hope to be an effective complement to heart transplantation in the future. New treatments and ventricular aids are provided for patients with heart failure. The ultrasonic pump is driven by an ultrasonic motor to drive the cam-push plate to squeeze the blood chamber. A pulsatile artificial heart that pumps blood in the form of contraction and relaxation. It can produce a pulsatile flow similar to the human body's own heart activity, and it can be easily controlled by squeezing the blood through a large torque, small ultrasonic motor. There is a possibility of implantation. But ultrasonic pumps have a greater fever at work, which has a greater effect on the implantation of the pump body. Temperature rise can damage blood, organs and tissues in the body. In order to measure and control the temperature rise of ultrasonic driven pump in the implanted state, a non-invasive temperature measurement method is designed for non-invasive pump body. A sensorless temperature prediction and control system for ultrasonic driven pump is designed in order to prevent the influence on human body caused by the related wire lines of sensor. Firstly, the overall heating condition of ultrasonic driven pump is quantified. Then the improved neural network based on genetic algorithm is used to predict the temperature of pump body through easily measured parameters, and the frequency modulation control is realized based on the result of temperature, so that the temperature rise of pump body can be controlled without the sensor. Finally, the experiment proves that this control method can give attention to the auxiliary effect of pump body and the characteristic of temperature rise. The current achievements are: 1. The heating mechanism of ultrasonic driven pump is studied, and the temperature rise of ultrasonic motor and cam friction part is analyzed in detail. Furthermore, the approximate power consumption range of the two parts is quantified, which is used to guide the understanding of the whole heating condition of the pump body. 2. By analyzing the driving frequency which is easy to measure and has strong correlation in the system, Three parameters, aortic pressure and driving current of ultrasonic motor, are used to predict temperature rise using BP neural network. Genetic algorithm is used to improve the prediction result of neural network. Based on the real-time control platform of Compact RIO, the temperature sensorless control system of ultrasonic drive pump is designed, and the characteristic of temperature rise of pump body is stabilized. 4. The simulated external circulation system is built, and the simulated left ventricle is used. Body circulation system and ultrasonic drive pump were used to collect simulated human body parameters. After temperature prediction and control, the pressure and flow characteristic curves of pump body were measured to verify the auxiliary effect of temperature control.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：R541.6;TP273

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