کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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238912 | 465783 | 2008 | 6 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Monitoring of a rotary dryer using acoustic emissions Monitoring of a rotary dryer using acoustic emissions](/preview/png/238912.png)
Drying is a complex thermal process and a crucial stage in the manufacture of many products in various industries. Reliable and accurate process monitoring techniques are needed to achieve a consistent product quality. A new and innovative method was developed that uses passive acoustics as a non-invasive, real-time monitoring technique for end-point detection in rotary dryers.This study used molecular sieves as an example of solid particles for which tight control of product moisture is crucial. A higher than ideal moisture results in sieves with a poor adsorption performance while a lower moisture results in excessive attrition. Current end-point detection methods available for this critical manufacturing stage are inadequate and prevent the production of molecular sieves with the best possible adsorption capability.A microphone recorded acoustic emissions during the drying of molecular sieves in a 1.5 m diameter rotary dryer. Signal analysis revealed that the critical end-point, corresponding to maximum moisture removal without attrition, can be detected by standard deviation analysis of the acoustic emissions. This provides a useful monitoring technique that can prevent the significant losses associated with over-drying. Multi-linear regression analysis of the acoustic emissions using wavelets or power spectral density provides an effective method of achieving a specific moisture content. Passive acoustic monitoring for end-point determination can be easily implemented into current industrial drying processes to prevent over-drying, reduce production costs, and improve product quality and consistency.
A new and innovative method using non-invasive acoustic measurements was developed to monitor drying of molecular sieves in a rotary dryer. The standard deviation of the acoustic signals provided critical end-point detection while the moisture content of the sieves could be determined from Fourier or wavelet analysis of the acoustic measurements.Figure optionsDownload as PowerPoint slide
Journal: Powder Technology - Volume 181, Issue 2, 6 February 2008, Pages 115–120