Smart sensors for process analytical technology

Increased globalisation and competition are drivers for process analytical technologies (PAT) that enable seamless process control, greater flexibility and cost efficiency in the process industries. This research is carried out in collaboration with a project which aims to introduce an integrated process control approach, embedding novel sensors for monitoring in real time the critical control parameters of key processes in the minerals, ceramics, non-ferrous metals, and chemical process industries. The paper will review the development of a suite of affordable sensors along with smart sensor features and algorithms for easier integration, easier maintenance, metrological performance enhancement, process monitoring and control and sensor fusion for use within this versatile global control platform implementing PAT. Smart sensors will be investigated that match existing offline solutions in performance while enabling size reductions, low power consumption, low unit costs, low maintenance costs and data fusion.

[1]  Dongsheng Bu,et al.  Comparison of near infrared and microwave resonance sensors for at-line moisture determination in powders and tablets. , 2011, Analytica chimica acta.

[2]  Radu-Emil Precup,et al.  A survey on industrial applications of fuzzy control , 2011, Comput. Ind..

[3]  Clive E Davies,et al.  Non-invasive Velocity Measurements in Flows of Bulk Solids Using Sound , 1998 .

[4]  Giuseppe Cannazza,et al.  Broadband Reflectometry for Enhanced Diagnostics and Monitoring Applications , 2011, Lecture Notes in Electrical Engineering.

[5]  O. Postolache,et al.  IEEE 1451 Correction Engine to Temperature-compensation of Magnetoresistive Transducers , 2005, 2005 IEEE Instrumentationand Measurement Technology Conference Proceedings.

[6]  Massimo Piotto,et al.  Automatic compensation of pressure effects on smart flow sensors in the analog and digital domain , 2014 .

[7]  Cedric Briens,et al.  Continuous on-line measurement of solid moisture content during fluidized bed drying using triboelectric probes , 2008 .

[8]  Andrei M. Shkel.  Smart MEMS: micro-structures with error-suppression and self-calibration control capabilities , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[9]  H. Zangl,et al.  Mass Flowmeter for Screw Conveyors Based on Capacitive Sensing , 2007, 2007 IEEE Instrumentation & Measurement Technology Conference IMTC 2007.

[10]  John R. Pugh,et al.  Experimental investigation on heat transfer mechanisms of pneumatically conveyed solids׳ plugs as a means to mass flow rate measurement , 2014 .

[11]  Mohd. Fua'ad Rahmat,et al.  Review of Electrostatic Sensor Applications , 2014 .

[12]  Haiqing Li,et al.  An intelligent measurement system for powder flowrate measurement in pneumatic conveying system , 2002, IEEE Trans. Instrum. Meas..

[13]  M. Uematsu,et al.  Static Dielectric Constant of Water and Steam , 1980 .

[14]  Lutang Wang,et al.  Polyimide-Coated Fiber Bragg Grating Sensors for Humidity Measurements , 2012 .

[15]  Jun Wu,et al.  Guest Editorial Special Issue on Advancing Standards for Smart Transducer Interfaces , 2015 .

[16]  Masako Tanaka,et al.  An industrial and applied review of new MEMS devices features , 2007 .

[17]  A.K. Somani,et al.  IEEE 1451 standard and wireless sensor networks: An over view of fault tolerant algorithms , 2006, 2006 IEEE International Conference on Electro/Information Technology.

[18]  Charu C. Aggarwal,et al.  Neural Networks and Deep Learning , 2018, Springer International Publishing.

[19]  Axel H. Berndorfer,et al.  “Smart sensing” of Oil Degradation and Oil Level Measurements in Gasoline Engines , 2000 .

[20]  Josep M. Guerrero,et al.  Industrial Applications of the Kalman Filter: A Review , 2013, IEEE Transactions on Industrial Electronics.

[21]  Qiang Liu,et al.  Review of techniques for the mass flow rate measurement of pneumatically conveyed solids , 2011 .

[22]  F. Martinez-Pinon,et al.  Polymer optical fiber moisture sensor based on evanescent-wave scattering to measure humidity in oil-paper insulation in electrical apparatus , 2008, 2008 IEEE Sensors.

[23]  Tony E Grift.  Fundamental Mass Flow Measurement of Solid Particles , 2003 .

[24]  Ning Wang,et al.  Use of the smart transducer concept and IEEE 1451 standards in system integration for precision agriculture , 2005 .

[25]  Oliver Brand,et al.  Micromachined viscosity sensor for real-time polymerization monitoring , 1997, Proceedings of International Solid State Sensors and Actuators Conference (Transducers '97).

[26]  Leonardo Franco,et al.  Smart sensor/actuator node reprogramming in changing environments using a neural network model , 2014, Eng. Appl. Artif. Intell..

[27]  Gerard Franklyn Fernando,et al.  Fiber-optic sensor design for chemical process and environmental monitoring , 2009 .

[28]  S. Joe Qin,et al.  A survey of industrial model predictive control technology , 2003 .

[29]  K. V. Santhosh,et al.  Practically Validated Adaptive Calibration Technique for Thermocouple using Optimized ANN , 2014 .

[30]  Yun Xu,et al.  Development of an electrical resistance tomography reactor for pharmaceutical processes , 2008 .

[31]  Suman Gumudavelli,et al.  Demonstration of the plug and play of smart sensor nodes , 2010, 2010 IEEE Sensors Applications Symposium (SAS).

[32]  Kerem Durdag.  Solid state acoustic wave sensors for real‐time in‐line measurement of oil viscosity , 2008 .

[33]  D. Dewitt,et al.  Theory and practice of radiation thermometry , 1988 .

[34]  Gabriele Reich,et al.  Combining microwave resonance technology to multivariate data analysis as a novel PAT tool to improve process understanding in fluid bed granulation. , 2011, European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V.

[35]  Izidor Gertner,et al.  Multi-sensor fusion: an Evolutionary algorithm approach , 2006, Inf. Fusion.

[36]  E. Gaura,et al.  MEMS enabled sensing microsystems: bridging the gap from devices to systems , 2004, 2004 International Conference on Intelligent Mechatronics and Automation, 2004. Proceedings..

[37]  B. Drafts.  Acoustic wave technology sensors , 2001 .

[38]  Hattab Guesmi,et al.  Smart wireless sensor networks for online faults diagnosis in induction machine , 2015, Comput. Electr. Eng..

[39]  Randy Frank.  Understanding Smart Sensors , 1995 .

[40]  Fahd Banakhr,et al.  Using Algorithms on Smart Transducer: An IEEE Standard Perspective , 2015, IEEE Sensors Journal.

[41]  Zhong Liu,et al.  Adaptive fast consensus algorithm for distributed sensor fusion , 2010, Signal Process..

[42]  Laurent Foulloy,et al.  High functionalities for intelligent sensors, application to fuzzy colour sensor , 2001 .

[43]  S. Trabelsi,et al.  Inexpensive microwave moisture sensor for granular materials , 2007, 2007 IEEE Antennas and Propagation Society International Symposium.

[44]  D. Potter.  Smart plug and play sensors , 2002, IEEE Instrumentation & Measurement Magazine.

[45]  R.M. Newman,et al.  Smart, intelligent and cogent MEMS based sensors , 2004, Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004..

[46]  Rui Araújo,et al.  Adaptive fuzzy identification and predictive control for industrial processes , 2013, Expert Syst. Appl..

[47]  B. Calvo,et al.  Designing Adaptive Conditioning Electronics for Smart Sensing , 2010, IEEE Sensors Journal.