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The largest mechanical pulp production units are high-consistency refiners. In the high-consistency refiners, in-situ measurements of pulp quality are rare. Temperature profile is one of the measurements that is industrially applicable to estimate pulp quality. It measures the steam temperature in the refining area-but how it can detect deteriorated pulp quality will be shown. This paper analyzed the high-consistency refiner plate temperature and its correlation to pulp quality in a 1.34 MW pilot-scale Sunds RGP-44 variable speed refiner in a variety of operating conditions and particularly at production rates close to maximum refiner capacity. The study showed that there was a narrow band of optimal refining conditions at the maximum refiner production level just before pulp quality drastically decreased. When the refiner was pushed above this optimal point of operation, the plate temperature rapidly increased above normal refining temperature, causing reduction of fiber length and consequently lower pulp strength and quality. Thus, refiner plate temperature measurement was found to be a quick way and an effective tool for preventing low-quality pulp production through overloading the refiner.

Conference of 61st IEEE International Electron Devices Meeting, IEDM 2015 ; Conference Date: 7 December 2015 Through 9 December 2015; Conference Code:119534; International audience; Since the rapid development of post-CMOS technologies in the last decade, there has been a growing interest in utilizing them for implementing neuromorphic or brain-like computing machines. Besides attempts to build realistic circuits that would mimic the functioning of biological neurons as close as possible [1][2], our team is focused on implementing neuromorphic circuits suitable for embedded applications. This objective puts the emphasis on two majors concerns: integration and energy efficiency. In our quest for ultimate integration, we first report on investigating for the best synapse-like technology among the realm of potential candidates. We then report our investigations on the feasibility of large crossbars of synapse-like devices and show that there is still a long way ahead. Finally in an effort to tackle the energy problem, we introduce spike based coding for deep neuromorphic architectures and discuss our argument that spike coding combined with memristive synaptic devices could pave the way for future embedded neuromorphic circuits.