Detection And Application Of Key Parameters In Multiphase System Based On Acoustic Emission Measurement

Chemical industry and its products play an important role in the national economy and daily life, however, purification and other physical process (known as chemical unit operation) of raw materials and reaction products are indispensable in the chemical production process. There may need to undergo several unit operations from raw materials to finished product. Nowadays, the design of unit operation equipment is developing rapidly toward multi-functional, highly integrated and automated with modern industrial development and the progress of science and technology. The resulting problems is the device internal highly complex fluid dynamic behavior, thus forming a nonlinear, multi scale, dynamic characteristics of complex systems, it’s bring quite a little difficulty for on-line fault detection and diagnosis. On the other hand, the traditional means of detection (such as temperature, pressure) only for process parameters, far from the requirements of sensitive, accurate, timely and high standards of modern industrial production, it cannot meet the needs of industrial production. Therefore, in view of the above problems, the system of unit operations used in the equipment characteristics, influence factors and the possible failure and coping strategies, to develop a simple, sensitive and accurate on-line detection technology is not only challenging, but also has great theoretical significance and practical value.In this paper, two common unit operations (drying and crystallization) are studied respectively, in the fluidized bed dryer and MSMPR crystallizer, with advanced non-destructive acoustic emission technique for on-line measuring means, as well as the application of frequency spectrum analysis and wavelet analysis signal analysis method. Systematic study of the particle moisture content, fluidized quality, crystallization metastable zone status with the AE signal (energy and spectrum) to qualitative and quantitative the relationship. This paper proposed a new method for detecting and diagnosising model based on acoustic emission signal. The analytical results provide guidelines for the continuous safe production of industrial fluidized bed dryer and MSMPR crystallization reactor. The proposed method also optimizes process operation and improves the product quality. The paper mainly focused on the following three aspects:First, we researched further on the AE signal which is produced by the fluidized bed on the particle moisture. The singnal is collected from different materials (granular material, moisture content, wall material of fluidized bed), different operating conditions (superficial gas velocity, gas temperature etc.) and different sampling locations. The predictive model for particle moisture content is obtained by analyzing acoustic emission singnal. In the light of Hou’s frequency model, we adopted the collision theory and statistical knowledge to derive the relationship between the acoustic frequency and the particle properties. Combining the AE signal obtained in the industrial fluidized bed dryer with the acoustic frequency used to the predictive model, a semi-mechanism and semi-empirical model was proposed, and this model worked well. In addition, multi-scale resolution was used for handling the AE signals generated by the different moisture content of particles, we select high-frequency energy associated with the moisture content to build the model based on the moisture content of the acoustic energy, and the model’s root mean square error was only0.0422. The factors that would impact acoustic energy is investigated further, including sampling location, and particulate matter (material, diameter), superficial gas velocity.Second, we used pressure fluctuation and AE technology to distinguish the fluidized state of the dry material in the fluidized bed dryer. The critical fluidization gas velocity Uc and critical moisture content Mc were acquired according the signal standard deviation and average absolute deviation. A quick and effective method to determine fluidized state (bubbling fluidization, turbulent fluidization) in the fluidized bed dryer were proposed. We obtained a criterion to determinate the fluidized state of PE and PVC in the laboratory cold model fluidized bed dryer, and studied the effect of different operating conditions on the detection results. Finally, this method was applied for a variety of drugs in industrial device. In this paper, a criterion for the status of fluidized bed was proposed, and the criterion was convenient for setting the operating parameters of the fluidized bed dryer. The drying material can be controlled in exactly the turbulent flow of the state, which not only achieves the purpose of drying fully and rapidly, but also enables energy consumption to a minimum.Third, we proposed a fast and effective detection method of crystallization reactor metastable in the MSMPR crystallization reactor with AE technology. In the laboratory scale cold model unit, we used the potassium sulfate and sodium acetate to do the cooling crystallization experiments, in the meantime, collected the AE data, and acquired the crystallization temperature using the AE signals. We also get the maximum supercooling, and do the further research on the effect of the different condition on the width of metastable zone. Finally, we validated the method in the iron-made MSMPR crystallization reactor. The validated result shows that this method has a good detection effect. In this study, a simple method was proposed for the detection of the crystallization process of the metastable zone, which is conducive to set up the operating parameters of the crystallization process, crystallization point can be controlled to obtain high quality crystals in the metastable zone, and it will have a broad prospects for industrial applications.