Time series insights from the shopfloor: A real-world dataset of pneumatic pressure and electrical current in discrete manufacturing.

Gathered from a real-world discrete manufacturing floor, this dataset features measurements of pneumatic pressure and electrical current during production. Spanning 7 days and encompassing approximately 150 processed units, the data is organized into time series sampled at 100 Hz. The observed machine performs 24 steps to process each unit. Each measurement in the time series, is annotated, linking it to one of the 24 processing steps performed by the machine for processing of a single piece. Segmenting the time series into contiguous regions of constant processing step labels results in 3674 labeled segments, each encompassing one part of the production process. The dataset enriched with labels facilitates the use of supervised learning techniques, like time series classification, and supports the testing of unsupervised methods, such as clustering of time series data. The focus of this dataset is on an end-of-line testing machine for small consumer-grade electric drive assemblies (device under test - DUT). The machine performs multiple actions in the process of evaluating each DUT, with the dataset capturing the pneumatic pressures and electrical currents involved. These measurements are segmented in alignment with the testing machine's internal state transitions, each corresponding to a distinct action undertaken in manipulating the device under observation. The included segments offer distinct signatures of pressure and current for each action, making the dataset valuable for developing algorithms for the non-invasive monitoring of industrial (specifically discrete) processes.

Measurement System for Piezoelectric Resonance Impedance Spectroscopy Under Combined AC and High-Voltage DC Loading.

Piezoelectric resonance impedance spectroscopy is a standardized measurement technique for determining the electromechanical, elastic, and dielectric parameters of piezoceramics. However, commercial measurement setups are designed for small-signal measurements and encounter difficulties when constant driving voltages/currents are required at resonances, higher fields, or combined AC and DC loading. The latter is particularly important to evaluate the DC bias-hardening effect of piezoelectrics. Here, we propose a novel measurement system for piezoelectric resonance impedance spectroscopy under combined AC and high-voltage DC loading that complies with established standards. The system is based on two separate output amplifier stages and includes voltage/current probes, a laser vibrometer, custom protection components, and control software with optimization algorithm. In its current form, the measurement setup allows the application of AC frequencies up to 500 kHz and DC signals up to ±10 kV on samples with impedance between 10-1 and 106 Ω . The operation of the proposed setup was benchmarked against commercial impedance analyzers in the small-signal range and reference equivalent circuits. Test measurements under combined AC and DC loading were performed on a soft Pb(Zr,Ti)O3 piezoceramic. The results revealed that a DC bias voltage applied along the polarization direction ferroelectrically hardens the material, while the material softens and eventually depolarizes when the DC bias voltage is applied in the opposite direction. The results confirm the suitability of the designed measurement system and open new exciting possibilities for tuning the piezoelectric properties by DC bias fields.

Interactions between cardiac, respiratory and EEG-delta oscillations in rats during anaesthesia.

We hypothesized that, associated with the state of anaesthesia, characteristic changes exist in both cardio-respiratory and cerebral oscillator parameters and couplings, perhaps varying with depth of anaesthesia. Electrocardiograms (ECGs), respiration and electroencephalograms (EEGs) were recorded from two groups of 10 rats during the entire course of anaesthesia following the administration of a single bolus of ketamine-xylazine (KX group) or pentobarbital (PB group). The phase dynamics approach was then used to extract the instantaneous frequencies of heart beat, respiration and slow delta-waves (within 0.5-3.5 Hz). The amplitudes of delta- and theta-waves were analysed by use of a time-frequency representation of the EEG signal within 0.5-7.5 Hz obtained by wavelet transformation, using the Morlet mother wavelet. For the KX group, where slow delta-waves constituted the dominant spectral component, the Hilbert transform was applied to obtain the instantaneous delta-frequency. The theta-activity was spread over too wide a spectral range for its phase to be meaningfully defined. For both agents, we observed two distinct phases of anaesthesia, with a marked increase in theta-wave activity occurring on passage from a deeper phase of anaesthesia to a shallower one. In other respects, the effects of the two anaesthetics were very different. For KX anaesthesia, the two phases were separated by a marked change in all three instantaneous frequencies: stable, deep, anaesthesia with small frequency variability was followed by a sharp transition to shallow anaesthesia with large frequency variability, lasting until the animal awoke. The transition occurred 16-76 min after injection of the anaesthetic, with simultaneous reduction in the delta-wave amplitude. For PB anaesthesia, the two epochs were separated by the return of a positive response to the pinch test at 53-94 min, following which it took a further period of 45-70 min for the animal to awaken. delta-Waves were not apparent at any stage of PB anaesthesia. We applied non-linear dynamics and information theory to seek evidence of causal relationships between the cardiac, respiratory and slow delta-oscillations. We demonstrate that, for both groups, respiration drives the cardiac oscillator during deep anaesthesia. During shallow KX anaesthesia the direction either reverses, or the cardio-respiratory interaction becomes insignificant; in the deep phase, there is a unidirectional deterministic interaction of respiration with slow delta-oscillations. For PB anaesthesia, the cardio-respiratory interaction weakens during the second phase but, otherwise, there is no observable change in the interactions. We conclude that non-linear dynamics and information theory can be used to identify different stages of anaesthesia and the effects of different anaesthetics.