Tobias Wahl

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Wahl

First Name

Tobias

ORCID

0000-0002-4200-3301

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Publications 1 - 8 of 8

Automated Detection of Visible Grinding Burn in Rail Grinding using Cameras and Machine Learning
Wahl, Tobias; Gharaei, Ali; Thalmann, Tobias; et al. (2022)
Excessive heat accumulation at the workpiece surface can cause grinding burn, which is often indicated by workpiece surface color changes. Grinding burn accelerates rail surface deterioration and can lead to cracks. Data-driven approaches based on in-process measurements require extensive data labeling either based on laboratory inspections or human visual inspection. Additionally, such approaches may not be suitable for complex processes like rail grinding, which would require an excessive amount of process data for training. This paper proposes an approach for automated grinding burn detection using a camera. Grinding experiments have been conducted with a resin bond corundum wheel on a rail steel workpiece (58CrMoV4). Image classification techniques using transfer learning are applied to identify visible grinding burns. Despite limitations in the provision of a controlled set-up for the camera in rail grinding, it is shown that trained image classifiers can be a promising replacement for human visual inspection. They can increase productivity in process monitoring and facilitate continuous learning for grinding burn identification.
Vorhersage der Werkstück-Oberflächenrauheit beim Hochleistungs-Trockenschleifen mittels Simulation
Gharaei, Ali; Wahl, Tobias; Kuffa, Michal; et al. (2022)
Topographie und Eigenschaften der Schleifwerkzeuge beeinflussen das Schleifergebnis massgeblich. Die richtige Werkzeugauswahl stellt in der Praxis oft einen iterativen experimentellen Prozess dar. In diesem Beitrag wird ein geometrisches Simulationstool namens iBRUS, institutseigene Entwicklung, vorgestellt, das fähig ist, die Oberflächenrauheit des Werkstücks für verschiedene Schleifwerkzeuge vorherzusagen und so die Werkzeugauswahl zu beschleunigen und zu verbessern. In einem Hochleistungs Trockenschleifprozess im Seiten-Planschleifen wird unter Berücksichtigung von Schleifwerkzeugen verschiedener Korngrössen und Kornarten die Anwendung illustriert. Die Validierung bezieht die Oberflächentopographie von Werkzeug und Werkstück ein. Bei der Validierung der Simulation mit experimentellen Prozessdaten kann gezeigt werden, dass geometrische Simulationstools die effektive Vorhersage der Werkstück-Oberflächenrauheit ermöglichen und erweitert werden können, um optimale Prozessparameter für die gewünschte Oberflächenqualität zu finden.
Picosecond pulsed laser ablation of dielectric rods: Angle-dependent ablation process model for laser micromachining
Börner, Paul; Hajri, Melik; Wahl, Tobias; et al. (2019)
Journal of Applied Physics
Acoustic Roughness Measurement of Railway Tracks: Laboratory Investigation of External Disturbances on the Chord-Method with an Optical Measurement Approach
Mauz, Florian; Wigger, Remo; Wahl, Tobias; et al. (2022)
Applied Sciences
For acoustic roughness monitoring of the railway network at train travelling speed, new direct measurement methods are required. Common direct measurement methods need the blocking of track sections, as they are based on manually operated devices. Indirect measurement methods such as accelerometer or microphone measurements can be installed on the train, but require a conversion of the obtained measurement data to rail roughness. Optical measurement methods allow a direct measurement from the moving train, even at higher speeds, due to the contact-free nature of the measurement. This paper investigates the influence of various disturbances on the measurement result, which are expected on the train. The frequently used chord method deploying laser triangulation sensors is used. Four sensors are integrated into the setup, thus providing the possibility to combine the results from four chord methods. The measurements of the optical system are compared with a tactile measurement of METAS (Swiss Federal Institute of Metrology) on a test bench equipped with a reference rail segment. It is shown that dust and water on the rail have a significant influence in the range of small wavelengths. Displacements and tilting of the sensor array, as well as vibrations, can be compensated to a certain level by the chord method, while a single sensor is significantly disturbed. The combination of four different chord lengths and selection of the theoretically optimal method for each one-third octave band shows an improvement of the measurement result. Based on the observations made, recommendations for practical tests on the train are concluded.
Acoustic Roughness Measurement of Railway Tracks: Implementation of a Chord-Based Optical Measurement System on a Train
Mauz, Florian; Wigger, Remo; Wahl, Tobias; et al. (2022)
Applied Sciences
A large part of the noise emissions from rail traffic originates from rolling noise. This is significantly determined by the surface roughness of the wheel and the rail. To quantitatively assess the noise generation from the wheel–rail contact, it is necessary to measure the surface roughness of the rail network. Direct measurements via trolley devices are usually associated with the need for a free track and limitation in velocity. Indirect measurements of rail roughness, such as measuring axle-box accelerations, enable operation during regular passage but only estimate the acoustic roughness. In this study, the potential of an optical and consequently contact-free measurement method using laser triangulation sensors to measure rail roughness from the train is investigated. The approach can combine the advantage of operation during regular passage with the characteristics of a direct measurement, enabling large-scale monitoring of the rail network. A measurement run with a train was carried out on a meter-gauge track at speeds up to 80 km/h The results of the optical measurement approach were compared with a tactile reference measurement on the track. The results show good agreement of the new measurement setup for dry rail surface conditions at 50 km/h, with a mean deviation of 1.48 dB.
Acoustic Roughness Measurement of Railway Tracks: Running Surface Detection and Compensation of Lateral Movements for Optical Measurements on a Train
Mauz, Florian; Wigger, Remo; Griesbaum, Loris; et al. (2023)
Sensors
Rolling noise is a significant contributor to railway noise. Wheel and rail roughness are decisive for the emitted noise level. An optical measurement method installed on a moving train is suitable for closer monitoring of the rail surface condition. A measurement setup based on the chord method requires the sensors to be positioned in a straight line along the direction of measurement and in a stable lateral position. Measurements should always be performed within the shiny and uncorroded running surface, even when there are lateral movements of the train. In this study, concepts for the detection of the running surface and the compensation of lateral movements are investigated in a laboratory setting. The setup consists of a vertical lathe with a ring-shaped workpiece that incorporates an implemented artificial running surface. The detection of the running surface based on laser triangulation sensors and a laser profilometer is investigated. It is shown that the running surface can be detected using a laser profilometer that measures the intensity of the reflected laser light. It is possible to detect the lateral position and the width of the running surface. A linear positioning system is proposed to adjust the lateral position of the sensors based on the running surface detection of the laser profilometer. When the lateral position of the measuring sensor is disturbed by a movement with a wavelength of 18.85 m, the linear positioning system can keep the laser triangulation sensor inside the running surface for 98.44% of the measured data points at a velocity of approximately 7.5 km/h. The mean positioning error is 1.40 mm. By implementing the proposed system on the train, future studies can be conducted to examine the lateral position of the running surface as a function of the various operational parameters of the train.
Acoustic roughness measurement of railway tracks: Implementation of an optical measurement approach & possible improvements to the standard
Mauz, Florian; Wigger, Remo; Wahl, Tobias; et al. (2022)
Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
The measure for assessing the acoustic quality of the rail surfaces, the acoustic roughness, is defined in the EN 15610 standard. It is shown that this standard contains gaps with regard to the applied procedures for processing the raw data to the quantity of acoustic roughness. Additions to the standard appear necessary to ensure better comparability of the results. A piece of rail tactilely measured by METAS (Swiss Federal Institute of Metrology) was used as a reference. Measurement data recorded by a laser triangulation sensor was used to quantify the adjustments to the standard. This paper provides an overview of the individual processing steps and systematically examines possible additions to the standard to improve the quality of the outcome. Special emphasis was given to a method for outlier removal, pre-filtering, spike removal, curvature correction and calculation of one-third octave bands. It becomes apparent that different implementations can have a significant impact on the final result. The filter used, the wavelength ranges, the methodology for removing outliers should be specified. The spike removal, curvature correction and the calculation of the one-third octave bands should be supplemented in detail to reduce ambiguities in the implementation.
Grinding Wheel Condition Monitoring using Acoustic Airborne Signals and Machine Learning
Gharaei, Ali; Wahl, Tobias; Ostad Ali Akbari, Vahid; et al. (2022)
Wear state of grinding tools has a significant influence on the grinding result. Depending on the tool wear mechanism, the grains’ cutting edges deteriorate which is referred to as grain dulling. When it happens to many active abrasive grains, large wear flats appear on the grinding tool surface, referred to as glazing. Under such circumstances, the contact area and frictional interactions between the abrasive grains and the workpiece increase. This leads to rising temperatures to high levels in the area of contact and heat accumulation whereby adhesion and chemical reaction between two surfaces are enhanced while material removal efficiency and overall grinding performance are undermined. In high-performance dry grinding processes that are often force-controlled and dressing-free, such grinding states may occasionally persist without tool self-resharpening. This paper introduces a methodology to identify the grinding process states in an automated way. A face grinding experiment is conducted with a resin-bonded corundum wheel. It has been observed that airborne acoustic signals can effectively be used to identify the glazing states of grinding tools. The solution supports process control, the performance evaluation of various grinding wheels, and an in-depth investigation of wear mechanisms.

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Tobias Wahl

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