Berichte aus dem Lehrstuhl für Messtechnik und Sensorik
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15
Efforts in decarbonization lead to electrification, not only for road vehicles but also in the sector of mobile machines. Aside from batteries, those machines are electrified by tethering systems, nowadays featuring an AC low voltage system. Those systems are applied, e.g., to underground load haul dumpers with short tethering lines and low machine power. To expand tethering to further markets as agricultural machinery, this work proposes an HVDC tethering system allowing higher machine power and transmission length due to thinner, lighter tethering lines. The HVDC voltage is converted by distribution over a number of series connected DC/DC converters. Less blocking voltage on the semiconductors allows faster switching technology to reduce the converters’ weight and volume. The concepts modularity allows for flexible adaption on various application scenarios. Since comparable concepts exist for offshore wind farms connectivity, its applicability for this is discussed. A full bridge inverter/rectifier LLC resonance DC/DC converter is presented for the modules. A switched LTI converter model is developed and a Common Quadratic Lyapunov Function (CQLF) is computed for prove of stability. The converter control features soft startup and voltage control over all modules. The concepts are validated by simulation and on a scaled prototype.
14
Automation, Industry 4.0 and artificial intelligence are playing an increasingly central role for companies. Artificial intelligence in particular is currently enabling new methods to achieve a higher level of automation. However, machine learning methods are usually particularly lucrative when a lot of data can be easily collected and patterns can be learned with the help of this data. In the field of metrology, this can prove difficult depending on the area of work. Particularly for micrometer-scale measurements, measurement data often involves a lot of time, effort, patience, and money, so measurement data is not readily available. This raises the question of how meaningfully machine learning approaches can be applied to different domains of measurement tasks, especially in comparison to current solution approaches that use model-based methods. This thesis addresses this question by taking a closer look at two research areas in metrology, micro lead determination and reconstruction. Methods for micro lead determination are presented that determine texture and tool axis with high accuracy. The methods are based on signal processing, classical optimization and machine learning. In the second research area, reconstructions for cutting edges are considered in detail. The reconstruction methods here are based on the robust Gaussian filter and deep neural networks, more specifically autoencoders. All results on micro lead and reconstruction are compared and contrasted in this thesis, and the applicability of the different approaches is evaluated.
13
In the field of measurement technology, the use of unmanned aerial vehicles is becoming more and more popular. For many measurement tasks, the use of such devices offers many advantages in terms of cost and measurement effort. However, the occurring vibrations and disturbances are a significant disadvantage for the application of these devices for several measurement tasks. Within the scope of this work, a platform for measurement devices is developed. The platform is designed specifically for use on drones. The task of the platform is to isolate measurement equipments mounted on it from the drone disturbances. For this purpose we go through the product development process according to VDI 2221 to design a mechanical model of the platform. Then, control strategies are applied to isolate the platform. Since the disturbances acting on a drone are not always stationary, two control strategies known for their ability to handle uncertain systems are used. One of them comes from the field of acoustic.
4
The detection and characterisation of undesired lead structures on shaft surfaces is a concern in production and quality control of rotary shaft lip-type sealing systems. The potential lead structures are generally divided into macro and micro lead based on their characteristics and formation. Macro lead measurement methods exist and are widely applied. This work describes a method to characterise micro lead on ground shaft surfaces. Micro lead is known as the deviation of main orientation of the ground micro texture from circumferential direction. Assessing the orientation of microscopic structures with arc minute accuracy with regard to circumferential direction requires exact knowledge of both the shaft’s orientation and the direction of surface texture. The shaft’s circumferential direction is found by calibration. Measuring systems and calibration procedures capable of calibrating shaft axis orientation with high accuracy and low uncertainty are described. The measuring systems employ areal-topographic measuring instruments suited for evaluating texture orientation. A dedicated evaluation scheme for texture orientation is based on the Radon transform of these topographies and parametrised for the application. Combining the calibration of circumferential direction with the evaluation of texture orientation the method enables the measurement of micro lead on ground shaft surfaces.