Research On Automatic Enzyme-free Analysis System Loading Process Monitoring Technology

Enzyme linked immune-sorbent assay(ELISA) is a mature method of detection techniques, the technology is reliable and easy to operate. It has an irreplaceable value of clinical application. With the development of medical laboratory automation, the ELISA analysis system is developing rapidly in the direction of automation and high efficiency. Pipetting module is an important function of the pretreatment system of automatic ELISA analyzer system. The monitoring of pipetting includes liquid level detection, monitored air displacement and drip-resistant pipetting. It is a key technology of pipetting process, which ensures the precision of sample volume so as to ensure the correctness of the finial test result. Therefore, the precise control of pipetting modular is a significant technology of ELISA.The main research goes on at the monitoring of pipetting technology falls into the following aspects: fast and accurate detection of liquid level; determination of abnormality in the process of absorption/liquid separation; realized the process of aspirating and dispensing in the drip-resistant method.The main works of the thesis are as follows:1) Designation of a principle independent multi-mode liquid level detection system which is based on capacitive and pressure sensor. Probe capacitance sensor dynamic method is proposed and implemented to the liquid level detection of polar liquid, and pressure method to the level of the non-polar liquid.2) According to the pressure of gas in the pipetting vessel, it can distinguish the situation of shortage of sample, tip blocked and foam. It guaranteed the coordinate consistency and high precision of the sports system of full-automatic enzyme immunoassay instrument.3) The hardware circuit designation of the sample process monitoring system, which includes control of motor, liquid level detection based on capacitive sensor, monitored air displacement and drip-resistant pipetting.4) The software designation of the sample process monitoring system, at the same time a grey dynamic filtering based on dynamic GM(1,1) is used to improve the stability of capacitance and pressure sensor output. The amplitude and change of slope in a critical time period in the sample process pressure curve is compared in the lower machine. The abnormality could be identified and the alarm could be made in time.