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Study-pressure Drip Infusion Intelligent Monitoring System

Posted on:2014-11-20Degree:MasterType:Thesis
Country:ChinaCandidate:H Y YiFull Text:PDF
GTID:2268330425968354Subject:Pattern Recognition and Intelligent Systems
Abstract/Summary:PDF Full Text Request
This paper puts forward and designs a new type of intravenous drip infusion of intelligent monitoring system, which can automatically detect and display the droplet velocity, adjust the infusion speed automatically and display the liquid remaining quantity, through which we can also set the dropping speed on our own on the keyboard. The sound and light alarm function will be in action when infusion is finished or accident occurs. This system utilizes the MSP430microcontroller as the microcontroller core and the new-type26PCBFA6D pressure sensor to transform the pressure changes of the inside and outside of the dripping bucket into electrical signal output. Consequently, through testing the change of signal, monitoring purpose can be attained. As far as the processing of output electrical signal, we can first employ low-pass filter to reduce the external interference, and then conduct recuperated multistage amplification, and finally utilize the filtering isolation technique to reduce the interference of amplification circuit introduced. During the detection of the flow of the rest, the median average filtering method is employed to eliminate pulse interference and improve the measurement accuracy. As for the automatic control of intravenous drip speed, the parameter self-tuning fuzzy control (PSAFC) algorithm is adopted to control stepper motor and reversing, to adjust the bottle height, and to realize the effective control of intravenous drip speed. Master-slave communication adopts RS485communication mode, a mater engine supervising16slaves at the same time, through which the remote control can be achieved. The system has good stability, real-time performance, low cost, high accuracy, and wide promotion prospects.
Keywords/Search Tags:26PCBFA6D pressure sensor, Fuzzy control algorithm, Median averagefiltering method, Intelligent monitoring
PDF Full Text Request
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