The Study On The Data Measurement And Process System And Its Application

With the application of computer control techniques and data processing methods in chemistry and chemical engineering, a lot of analytical instruments can be controlled by computer gradually. Meanwhile the experimental data can be collected and restored by using measurement & process software and then processed with many data processing methods. The automation and work efficiency of chemical laboratory have been enhanced greatly because of the development of measurement & process software and data processing methods. In this dissertation, we have designed the data measurement & process system software, and studied the data processing methods.Firstly, data measurement & process system software is set up with object-oriented program-design and written by Visual Basic. This system software mainly consists of three parts: text module, data module and graphics module. It has friendly user-computer interface and supports text-editing, data processing , plotting , and so on.A software for battery charge-discharge measurement is developed based on the data measurement & process system software and VB communication control, which is mainly responsible for controlling battery charge-discharge measuring equipment, collecting data and calculating performance parameter of battery. The software has relatively all-sided functions and can be used widely.Secondly, We have studied the application of wavelet transform for noise filtering and resolution of overlapped peaks in chemical signals. Two new functions based on the property of bubble wavelet are proposed. An approximate 2nd derivative of an analytical signal can be obtained by applying n times of the wavelet transform to the signal, the signal-to-noise ratio can be enhanced greatly. At the same time it can resolve the overlapped peaks. In view of simple functions and programs, this method is an efficient approach to process measuring signals in chemistry.Furthermore, the data of X-ray diffraction is processed by using cluster analysis in SPSS statistical software. We can determine the phases of a series of samples which has less components by classifying the diffraction lines. If the sample has more components, the classified result appears some departure owing to the increase of overlapped peaks, however, it still offers some information to determine the phases of sample.