The Research On The Rapid Detection Methods And Equipments For The Moisture Content Of Mulberry Sawdust

With the rapid development of edible mushrooms industry, raw materials for culture medium of edible mushrooms are in the situation of deficiency. As a new and high quality raw materials, mulberry sawdust not only meets the requirement for rapid development of edible mushrooms industry, but also takes full advantage of recycling resource, protects the environment and increases additional value of silkworm production, accelerate the persistent development of edible mushrooms industry.In the process of making culture medium by automatic product line, the detection of moisture content (MC) is a challenge. Mulberry sawdust is a sort of loose and broken material with irregular shapes. With abundant mixture, variable tightness of the material caused by its surrounding, so the moisture content(MC) of the material is impossibly measured through traditional detective technology such as electrical measurement. And the raw material and the finished product of culture medium, which are the objects in detection, are just in the blind spots of MC detection, because of the excessive low-level MC or high level one. In addition, treated as offal at all times, the situation of relevant theories is naught.The dissertation presents the research on detective methods and equipments for mulberry sawdust MC.Firstly, the dissertation summarizes the advantage and disadvantage of all sorts of detective methods. Consequently, Weighing method, which includes vacuum drying and microwave drying, is figured out as the basic plan. By the experiments of vacuum drying and microwave drying, the dissertation presents the research on drying curve of both methods, analyzes the drying mechanisms, compares the advantage and disadvantage in the aspects of velocity and exactness. As a result, microwave drying is the optimal detective method.Secondly, the dissertation makes the analysis of factors in microwave drying by orthogonal drying test, then proposed the best combination of microwave drying craft parameter for low MC materials, which can be used in the practical detection of low MC. But, for the medium and high MC materials, the method is not suitable because of the lack of velocity and convenience.Aiming at the solution of detection of the the finished product with high MC, the dissertation constructs drying model of mulberry sawdust by system identification, which is based on the theory of artificial neural network, trains the network based by I/O data in system, obtains the relation hidden behind the I/O data. In the research, drying models are constructed through BP, RBF, Elman network. And the Elman is regarded as the best choice through comparison of the accuracy of forecast data.Lastly, the dissertation presents the detective system made up of C8051F005, PC, microwave oven, and finished the hardware and software design. Despite some faults, the dissertation explores the methods of detection for MC of mulberry sawdust.