The pulp and paper manufacturing industry usually faces a lack of real time measurement of product and process variables. This on-line unavailability of critical process variables can lead to undesirable variability, out of specifications production and higher energy consumption. A soft sensor provides on-line, accurate estimates of these variables, eliminating additional energy and production cost associated with out of specifications production. Soft sensors can also play a significant role in more complex systems used for process optimization, such as fault and diagnosis systems, and control systems.
A soft sensor is the correlation from various raw data sources to create a new source of useful information. It is an empirical model that infers process state and product quality variables that are difficult to measure on-line (composition, melt index, molecular distribution, etc.) from readily available process measurements (temperature, pressure, flow, etc.).
Riveja performed a scoping study for a possible longer-term research and development program (R&D) that would ultimately aim at increasing the adoption of soft sensors or "virtual analyzer" for process and energy performance in the pulp and paper industry.
This scoping study consists of the identification of the processes in the pulp and paper, which are the most promising candidates to the development and implementation of soft sensors. Also, the scoping study will help define a roadmap toward long term R&D program in this area with information from process experts and operators, R&D experts and sensors and control systems developers and providers.
Soft Sensors for Monitoring and Control of Industrial Processes. Soft sensors serve the same function as physical sensors, except that values for the variable are not measured directly, but are obtained from a model of the physical sensor using other known variables as inputs. A soft sensor consequently enhances variable monitoring by increasing sampling frequency and replacing inaccurate measurements.
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