Identification of the Relationship Between Equilibrium Moisture Content, Dry Bulb Temperature, and Relative Humidity Using Regression Analysis

Authors

  • Charles D. Ray
  • Neelesh Gattani
  • Enrique del Castillo
  • Paul R. Blankenhorn

Keywords:

Regression, EMC prediction, dry kiln control

Abstract

This paper evaluates the performance of equilibrium moisture content (EMC) predictions using the least squares regression equation given in The Dry Kiln Operator's Manual (Simpson 1991). The fit of the regression equation in The Manual was found to be adequate only when the dry bulb temperature is below 110°F. At temperatures above 110°F, it generally overestimates EMC. A new polynomial regression equation is presented in this paper to predict EMC at dry bulb temperatures above 110°F. Comparisons between the old and new regression equations show an improvement in the root mean squared error of the predictions of about 44% when using the new equation. The proposed equation facilitates better control of the drying process in computer-controlled kiln applications using prediction equations for EMC estimates.

References

Draper, N., and H. Smith. 1998. Applied regression analysis, 3rd ed. John Wiley & Sons, Inc, New York, NY.nSimpson, W. T. (Ed.). 1991. Dry Kiln Operator's Manual. Agricultural Handbook No. 188, United States Department of Agriculture, Madison, WI. 274 pp.nGattani, N., E. del Castillo, C. Ray, and P. R. Blankenhorn. 2005. Times series analysis and control of dry kilns. Wood Fiber Sci.37(3):472-483.nHoerl, A. E., and R. W. Kennard. 1970. Ridge regression: Biased estimation for nonorthogonal problems. Technometrics, 12(3):55-67.nMontgomery, D.C. 2001. Design and analysis of experiments, 5th ed. John Wiley & Sons, Inc, New York, NY.nNeter, J., W. Wasserman, and M. Kutner. 1985. Applied linear statistical models. 2nd ed. R. D. Irwin.n

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Published

2007-09-27

Issue

Number 2 / April 2007

Section

Research Contributions

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