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The need for innovation around the control functions of inverters is great. PV inverters were initially expected to be passive followers of the grid and to disconnect as soon as abnormal conditions happened. Since future power systems will be dominated by generation and storage resources interfaced through inverters these converters must move from following to forming and sustaining the grid. As “digital natives” PV inverters can also play an important role in the digitalisation of distribution networks. In this short review we identified a large potential to make the PV inverter the smart local hub in a distributed energy system. At the micro level, costs and coordination can be improved with bidirectional inverters between the AC grid and PV production, stationary storage, car chargers and DC loads. At the macro level the distributed nature of PV generation means that the same devices will support both to the local distribution network and to the global stability of the grid. Much success has been obtained in the former. The later remains a challenge, in particular in terms of scaling. Yet there is some urgency in researching and demonstrating such solutions. And while digitalisation offers promise in all control aspects it also raises significant cybersecurity concerns.
The following work presents algorithms for semi-automatic validation, feature extraction and ranking of time series measurements acquired from MOX gas sensors. Semi-automatic measurement validation is accomplished by extending established curve similarity algorithms with a slope-based signature calculation. Furthermore, a feature-based ranking metric is introduced. It allows for individual prioritization of each feature and can be used to find the best performing sensors regarding multiple research questions. Finally, the functionality of the algorithms, as well as the developed software suite, are demonstrated with an exemplary scenario, illustrating how to find the most power-efficient MOX gas sensor in a data set collected during an extensive screening consisting of 16,320 measurements, all taken with different sensors at various temperatures and analytes.
The simultaneous operation of multiple different semiconducting metal oxide (MOX) gas sensors is demanding for the readout circuitry. The challenge results from the strongly varying signal intensities of the various sensor types to the target gas. While some sensors change their resistance only slightly, other types can react with a resistive change over a range of several decades. Therefore, a suitable readout circuit has to be able to capture all these resistive variations, requiring it to have a very large dynamic range. This work presents a compact embedded system that provides a full, high range input interface (readout and heater management) for MOX sensor operation. The system is modular and consists of a central mainboard that holds up to eight sensor-modules, each capable of supporting up to two MOX sensors, therefore supporting a total maximum of 16 different sensors. Its wide input range is archived using the resistance-to-time measurement method. The system is solely built with commercial off-the-shelf components and tested over a range spanning from 100Ω to 5 GΩ (9.7 decades) with an average measurement error of 0.27% and a maximum error of 2.11%. The heater management uses a well-tested power-circuit and supports multiple modes of operation, hence enabling the system to be used in highly automated measurement applications. The experimental part of this work presents the results of an exemplary screening of 16 sensors, which was performed to evaluate the system’s performance.
The choice of suitable semiconducting metal oxide (MOX) gas sensors for the detection of a specific gas or gas mixture is time-consuming since the sensor’s sensitivity needs to be characterized at multiple temperatures to find its optimal operating conditions. To obtain reliable measurement results, it is very important that the power for the sensor’s integrated heater is stable, regulated and error-free (or error-tolerant). Especially the error-free requirement can be only be achieved if the power supply implements failure-avoiding and failure-detection methods. The biggest challenge is deriving multiple different voltages from a common supply in an efficient way while keeping the system as small and lightweight as possible. This work presents a reliable, compact, embedded system that addresses the power supply requirements for fully automated simultaneous sensor characterization for up to 16 sensors at multiple temperatures. The system implements efficient (avg. 83.3% efficiency) voltage conversion with low ripple output (<32 mV) and supports static or temperature-cycled heating modes. Voltage and current of each channel are constantly monitored and regulated to guarantee reliable operation. To evaluate the proposed design, 16 sensors were screened. The results are shown in the experimental part of this work.
In the presented project, new approaches for the prevention of hand movements leading to hazards and for non-contact detection of fingers are intended to permit comprehensive and economical protection on circular saws. The basic principles may also be applied to other machines with manual loading and/or unloading. Two new detection principles are explained. The first is the distinction between skin and wood or other material by spectral analysis in the near infrared region. Using LED and photodiodes it is possible to detect fingers and hands reliable. With a kind of light curtain the intrusion into the dangerous zone near the blade can be prevented. The second principle is video image processing to detect persons, arms and fingers. In the first stage of development the detection of upper limb extremities within a defined hazard area by means of a computer based video image analysis is investigated.
The device (10) has a handrail (18) provided with an optical contactless monitoring device formed as an active sensor system, where the monitoring device is arranged in a region of a guide (14) of the handrail at a front base (16) of an escalator (12) or a moving pavement. The monitoring device has two transmission paths (28, 30) with wavelength bands that are different from each other, where one of the paths includes the handrail. Ratio or difference between signals of the paths is used for recognizing foreign bodies e.g. hands of adults and children.
The proper use of protective hoods on panel saws should reliably prevent severe injuries from (hand) contact with the blade or material kickbacks. It also should minimize long-term lung damages from fine-particle pollution. To achieve both purposes the hood must be adjusted properly by the operator for each workpiece to fit its height. After a work process is finished, the hood must be lowered down completely to the bench. Unfortunately, in practice the protective hood is fixed at a high position for most of the work time and herein loses its safety features. A system for an automatic height adjustment of the hood would increase comfort and safety. If the system can distinguish between workpieces and skin reliably, it furthermore will reduce occupational hazards for panel saw users. A functional demonstrator of such a system has been designed and implemented to show the feasibility of this approach. A specific optical sensor system is used to observe a point on the extended cut axis in front of the blade. The sensor determines the surface material reliably and measures the distance to the workpiece surface simultaneously. If the distance changes because of a workpiece fed to the machine, the control unit will set the motor-adjusted hood to the correct height. If the sensor detects skin, the hood will not be moved. In addition a camera observes the area under the hood. If there are no workpieces or offcuts left under the hood, it will be lowered back to the default position.