Modeling of Some Important Mechanical Properties of Barley Straw using Fuzzy Logic

A fuzzy logic model was used to determine the optimum shearing and bending stress of barley straws. The input parameters of the fuzzy model were stem moisture content, internode position and cutting blade loading rate. In order to write the fuzzy rules for the first linguistic variable, stem moisture content, four membership functions (very low, low, medium and high), were defined. Three membership functions (low, middle and high) were considered for the second linguistic variable, stem internode position. In the case of the third linguistic variable, cutting blade loading rate, three membership functions (low, medium and high) were assigned. Three membership functions were also assigned to the two outputs of the fuzzy system, stem shearing stress and bending stress, including low, middle and high. In order to validate the fuzzy model, the mechanical properties of barley straws obtained through preliminary experimental tests were compared with those values acquired using the fuzzy logic rules. The results showed that the model accuracy to estimate the shearing stress of barley straws was 71.4%, 97.1% and 88.9%, respectively in high, middle and low ranges of shearing energy. In the case of bending stress and in high, middle and low ranges, the model accuracy was 92.3%, 95.3% and 75%, respectively.

[1]  Daniel E. Guyer,et al.  Apple Grading Using Fuzzy Logic , 2003 .

[2]  H. Zimmermann,et al.  Fuzzy Set Theory and Its Applications , 1993 .

[3]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[4]  Daniel L. Schmoldt,et al.  Simulation of Plant Physiological Process Using Fuzzy Variables , 1991 .

[5]  T. S. Colvin,et al.  TRAHFICABILITY DETERMINATION USING FUZZY SET THEORY , 1991 .

[6]  Emin Güzel,et al.  Bending and Shearing Characteristics of Sunflower Stalk Residue , 2005 .

[7]  Ajit K. Srivastava,et al.  Engineering Principles of Agricultural Machines , 1993 .

[8]  A. R. Ennos,et al.  Stem and root characteristics associated with lodging resistance in four winter wheat cultivars , 1994, The Journal of Agricultural Science.

[9]  Maria Luisa Dalla Chiara,et al.  Uncertainties , 2010, Sci. Eng. Ethics.

[10]  P Linko,et al.  Uncertainties, Fuzzy Reasoning, and Expert Systems in Bioengineering , 1988, Annals of the New York Academy of Sciences.

[11]  T Yoshida,et al.  Knowledge-based control of fermentation processes. , 1992, Biotechnology and bioengineering.

[12]  Shahin Rafiee,et al.  Effects of moisture content and level in the crop on the engineering properties of alfalfa stems , 2008 .

[13]  Seyed Saeid Mohtasebi,et al.  Some Engineering Properties of Barley Straw , 2009 .

[14]  M. Annoussamy,et al.  Change in mechanical properties of wheat straw due to decomposition and moisture. , 2000 .

[15]  János Abonyi,et al.  Learning fuzzy classification rules from labeled data , 2003, Inf. Sci..

[16]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[17]  M. Dohnal,et al.  Fuzzy bioengineering models , 1985, Biotechnology and bioengineering.