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The aim of this work was the development of new image processing methods for the analysis and optimization of rotary kiln processes. It is shown how the newly developed methods can be employed to analyze certain areas and effects of rotary kiln processes. Thereby gained new process information can be used in the process control to optimize rotary kiln processes in terms of economic and environmental objectives.

Drehrohrofen, Bildverarbeitung, Maschinelles Sehen, Prozessanalyse, Prozessoptimierungrotary kiln, image processing, computer vision, process analysis, process optimization

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Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc.

low-temperature co-fired ceramic (LTCC) --- capacitive accelerometer --- wireless --- process optimization --- performance characterization --- MEMS accelerometer --- mismatch of parasitic capacitance --- electrostatic stiffness --- high acceleration sensor --- piezoresistive effect --- MEMS --- micro machining --- turbulent kinetic energy dissipation rate --- probe --- microelectromechanical systems (MEMS) piezoresistive sensor chip --- Taguchi method --- marine environmental monitoring --- accelerometer --- frequency --- acceleration --- heat convection --- motion analysis --- auto-encoder --- dance classification --- deep learning --- self-coaching --- wavelet packet --- classification of horse gaits --- MEMS sensors --- gait analysis --- rehabilitation assessment --- body sensor network --- MEMS accelerometer --- electromechanical delta-sigma --- built-in self-test --- in situ self-testing --- digital resonator --- accelerometer --- activity monitoring --- regularity of activity --- sleep time duration detection --- indoor positioning --- WiFi-RSSI radio map --- MEMS-IMU accelerometer --- zero-velocity update --- step detection --- stride length estimation --- field emission --- hybrid integrated --- vacuum microelectronic --- cathode tips array --- interface ASIC --- micro-electro-mechanical systems (MEMS) --- delaying mechanism --- safety and arming system --- accelerometer --- multi-axis sensing --- capacitive transduction --- inertial sensors --- three-axis accelerometer --- micromachining --- miniaturization --- stereo visual-inertial odometry --- fault tolerant --- hostile environment --- MEMS-IMU --- mode splitting --- Kerr noise --- angular-rate sensing --- whispering-gallery-mode --- optical microresonator --- three-axis acceleration sensor --- MEMS technology --- sensitivity --- L-shaped beam --- n/a