The interest about RF and microwave sensors for the measurement of dielectric properties of materials during industrial processes has been growing recently. Microwave sensors are particularly attractive for their ability of performing non-invasive measurements. An interesting field of application is the real-time moisture measurement during industrial processes. A smart active sensor for measuring the moisture content of felts used in the paper milling industry and more generally of sheet-like materials, is here proposed. The sensor consists of a cavity backed slot resonator interacting with the material under test through near fields. The design aspects of the sensor and the related measuring front-end are discussed with respect to the dielectric properties of the material, and to the resonator response. The parametric sensitivity of the measuring method with the distance between the sample and the sensor surface and the sample thickness is also analyzed. An inversion procedure based on an Artificial Neural Network (ANN) approach is proposed in order to determine the moisture content of the felts. Measurements on several reference felts, with different density, thickness, and moisture content levels, ranging from dry to waterlogged state, proved the effectiveness of the proposed sensor architecture and the ANN-based inversion procedure
Low Cost Microwave Sensor for Moisture Content Measurement in Paper Milling Industry / G. BIFFI GENTILI; C. RIMINESI; V. TESI. - In: SENSING AND IMAGING. - ISSN 1557-2064. - STAMPA. - 7:(2006), pp. 155-173. [10.1007/s11220-006-0027-2]
Low Cost Microwave Sensor for Moisture Content Measurement in Paper Milling Industry
BIFFI GENTILI, GUIDO;TESI, VASCO
2006
Abstract
The interest about RF and microwave sensors for the measurement of dielectric properties of materials during industrial processes has been growing recently. Microwave sensors are particularly attractive for their ability of performing non-invasive measurements. An interesting field of application is the real-time moisture measurement during industrial processes. A smart active sensor for measuring the moisture content of felts used in the paper milling industry and more generally of sheet-like materials, is here proposed. The sensor consists of a cavity backed slot resonator interacting with the material under test through near fields. The design aspects of the sensor and the related measuring front-end are discussed with respect to the dielectric properties of the material, and to the resonator response. The parametric sensitivity of the measuring method with the distance between the sample and the sensor surface and the sample thickness is also analyzed. An inversion procedure based on an Artificial Neural Network (ANN) approach is proposed in order to determine the moisture content of the felts. Measurements on several reference felts, with different density, thickness, and moisture content levels, ranging from dry to waterlogged state, proved the effectiveness of the proposed sensor architecture and the ANN-based inversion procedureI documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.