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Introduction To Signal Processing, Instrumentation, And Control: An Integrative Approach (Hardcover): Joseph Bentsman Introduction To Signal Processing, Instrumentation, And Control: An Integrative Approach (Hardcover)
Joseph Bentsman
R3,786 Discovery Miles 37 860 Ships in 12 - 17 working days

This book stems from a unique and highly effective approach in introducing signal processing, instrumentation, diagnostics, filtering, control, and system integration.It presents the interactive industrial grade software testbed of mold oscillator that captures the mold motion distortion induced by coupling of the electro-hydraulic actuator nonlinearity with the resonance of the mold oscillator beam assembly. The testbed is then employed as a virtual lab to generate input-output data records that permit unraveling and refining complex behavior of the actual production system through merging dynamics, signal processing, instrumentation, and control into a coherent problem-solving package.The material is presented in a visually rich, mathematically and graphically well supported, but not analytically overburdened format. By incorporating software testbed into homework and project assignments, the book fully brings out the excitement of going through the adventure of exploring and solving a mold oscillator distortion problem, while covering the key signal processing, diagnostics, instrumentation, modeling, control, and system integration concepts.The approach presented in this book has been supported by two education advancement awards from the College of Engineering of the University of Illinois at Urbana-Champaign.

Introduction To Signal Processing, Instrumentation, And Control: An Integrative Approach (Paperback): Joseph Bentsman Introduction To Signal Processing, Instrumentation, And Control: An Integrative Approach (Paperback)
Joseph Bentsman
R2,367 Discovery Miles 23 670 Ships in 12 - 17 working days

This book stems from a unique and highly effective approach in introducing signal processing, instrumentation, diagnostics, filtering, control, and system integration.It presents the interactive industrial grade software testbed of mold oscillator that captures the mold motion distortion induced by coupling of the electro-hydraulic actuator nonlinearity with the resonance of the mold oscillator beam assembly. The testbed is then employed as a virtual lab to generate input-output data records that permit unraveling and refining complex behavior of the actual production system through merging dynamics, signal processing, instrumentation, and control into a coherent problem-solving package.The material is presented in a visually rich, mathematically and graphically well supported, but not analytically overburdened format. By incorporating software testbed into homework and project assignments, the book fully brings out the excitement of going through the adventure of exploring and solving a mold oscillator distortion problem, while covering the key signal processing, diagnostics, instrumentation, modeling, control, and system integration concepts.The approach presented in this book has been supported by two education advancement awards from the College of Engineering of the University of Illinois at Urbana-Champaign.

Signals, Instrumentation, Control, And Machine Learning: An Integrative Introduction (Hardcover): Joseph Bentsman Signals, Instrumentation, Control, And Machine Learning: An Integrative Introduction (Hardcover)
Joseph Bentsman
R5,519 Discovery Miles 55 190 Ships in 12 - 17 working days

This book stems from a unique and a highly effective approach to introducing signal processing, instrumentation, diagnostics, filtering, control, system integration, and machine learning.It presents the interactive industrial grade software testbed of mold oscillator that captures the distortion induced by beam resonance and uses this testbed as a virtual lab to generate input-output data records that permit unravelling complex system behavior, enhancing signal processing, modeling, and simulation background, and testing controller designs.All topics are presented in a visually rich and mathematically well supported, but not analytically overburdened format. By incorporating software testbed into homework and project assignments, the narrative guides a reader in an easily followed step-by-step fashion towards finding the mold oscillator disturbance removal solution currently used in the actual steel production, while covering the key signal processing, control, system integration, and machine learning concepts.The presentation is extensively class-tested and refined though the six-year usage of the book material in a required engineering course at the University of Illinois at Urbana-Champaign.

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