Brain responses to odor mixtures with sub-threshold components

Although most odorants we encounter in daily life are mixtures of several chemical substances, we still lack significant information on how we perceive and how the brain processes mixtures of odorants. We aimed to investigate the processing of odor mixtures using behavioral measures and functional magnetic resonance imaging (fMRI). The odor mixture contained a target odor (ambroxan) in a concentration at which it could be perceived by half of the subjects (sensitive group); the other half could not perceive the odor (insensitive group). In line with previous findings on multi-component odor mixtures, both groups of subjects were not able to distinguish a complex odor mixture containing or not containing the target odor. However, sensitive subjects had stronger activations than insensitive subjects in chemosensory processing areas such as the insula when exposed to the mixture containing the target odor. Furthermore, the sensitive group exhibited larger brain activations when presented with the odor mixture containing the target odor compared to the odor mixture without the target odor; this difference was smaller, though present for the insensitive group. In conclusion, we show that a target odor presented within a mixture of odors can influence brain activations although on a psychophysical level subjects are not able to distinguish the mixture with and without the target. On the practical side these results suggest that the addition of a certain compound to a mixture of odors may not be detected on a cognitive level; however, this additional odor may significantly change the cerebral processing of this mixture. In this context, FMRI offers unique possibilities to look at the subliminal effects of odors

Diagnostics for Periodically Operated Actuators

Increasing constraints on quality, reliability and minimum downtime require the revision of existing maintenance approaches. Preventive maintenance, or even more reactive maintenance, require information about a system’s condition in order to enable predictive maintenance approach. Condition monitoring requires efficient sensing and data processing for extraction of condition-related signal features. Advances in both connectivity and embedded systems enable a wide range of possibilities in the field of condition monitoring. This thesis develops signal processing tools and hardware solutions optimized for, but not limited to, diagnostics of periodically operated actuators. These actuators are mechanical or electromechanical systems that experience non-uniform loads during an operating cycle. The platform presented in this thesis serves state-of-the-art vibration and acoustic measurements and combines the quality of high-end acquisition systems with the portability of IoT devices. This allows for temporary field installations and monitoring of critical industrial equipment. Cyclostationary analysis enables diagnostics based on signals with strong random components by extracting modulation signatures otherwise unattainable by conventional time or frequency domain analysis, as demonstrated with applications to diaphragm pumps and cutting tools. An extension to the Integrated-Electronics-Piezoelectric (IEPE) industry standard for vibration measurements stretches the applications to a wide range of measurands like temperature, pressure or mechanical strain. These stretched capabilities enable a more unified sensing strategy and decrease complexity of the condition monitoring systems; thus, it further supports miniaturization and on-the-edge applications.Ph.D