Modern production requires shorter measuring cycles of measuring machines, which can be achieved with highly dynamic references causing dynamic deviations of the actual tool-center-point (TCP) position. To minimize the TCP tracking error, the considered measuring machine is extended with a redundant axis and a modular control concept is proposed. For this dual-stage actuation setting, a higher-level reference allocation module exploits the resulting redundancy and yields suitable position references for the lower-level controlled subsystems. On the higher-level, two dual-stage control concepts are presented, yielding both significantly reduced tracking errors in experiments compared to using only the main axis. Furthermore, to deal with strongly spatially varying friction of the main axis of the considered measuring machine, its lower-level control system is improved.

The experimental approach of a highly accurate imaging based stereo measurement setup with a total measurement volume of 140 mm x 100 mm x 50 mm is presented. The system can detect the position of multiple target points (LEDs) in a calibrated volume of 100 mm x 75 mm x 24 mm with an accuracy of sigma(x) = 0.367 mu m, sigma(y) = 0.373 mu m and sigma(z) = 0.437 mu m. This high accuracy is reached by holographically replicating each point light source to a predefined pattern (cluster) of spots on the camera sensor and averaging the center positions of all spots. We present a detailed description of the principle, the process and results of calibration including deformation compensation and stability measurements, as well as the results of two- and three-dimensional trajectory measurements. To validate the performance and accuracy of the measurement setup, interferometers are employed as reference sensors. The residual error of a two-dimensional trajectory of distance D = 277 mu m is sigma(d) = 0.242 mu m and for a three-dimensional trajectory of distance D = 57.2 mm it is sigma(d) = 0.674 mu m.

In this study we present a novel and flexibly applicable method to measure absolute and relative vibrations accurately in a field of 148 mm × 110 mm at multiple positions simultaneously. The method is based on imaging in combination with holographic image replication of single light sources onto an image sensor, and requires no calibration for small amplitudes. We experimentally show that oscillation amplitudes of 100 nm and oscillation frequencies up to 1000 Hz can be detected clearly using standard image sensors. The presented experiments include oscillations of variable amplitude and a chirp signal generated with an inertial shaker. All experiments were verified using state-of-the-art vibrometers. In contrast to conventional vibration measurement approaches, the proposed method offers the possibility of measuring relative movements between several light sources simultaneously. We show that classical band-pass filtering can be omitted, and the relative oscillations between several object points can be monitored. Introduction and state of the art Precise measurement of deformations and vibrations is required in a wide range of industrial applications. Classical approaches such as laser Doppler vibrometers (LDVs) offer the possibility of measuring object vibrations at high temporal and spatial resolution. However, as soon as multiple simultaneous measurements are required, the use of single LDVs quickly becomes impractical and costly. The market-driven need for simultaneous vibration measurements at multiple positions manifested itself in the development of LDVs with multi-beam and multisensor applications. In addition, commercial solutions consisting of multiple sensor heads are available, but these systems are either limited by the flexibility of beam orientation or costly in terms of adjustment of sensor heads, signal synchronization, and especially in terms of price. Scanning laser interferometers can be used to measure full-field vibrations, but the obtained signals cannot be acquired simultaneously, making it impossible to measure transient signals. Image-based vibration measurement techniques inherently offer the possibility of measuring the movement of an object remotely at multiple positions as well as measuring the displacement of several objects simultaneously. In many cases, planar, passive targets are used, reaching accuracies in the range of 0.6 mm at a distance of 100 m and 0.1 mm for a distance of 15 m and only low-frequency vibrations are detected. As an alternative to the planar target, active elements (LEDs) and edge detection can be used. Especially in the field of edge detection, a lot of research regarding motion magnification, a technique that © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article′s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article′s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Correspondence: Simon Hartlieb (Hartlieb@ito.uni-stuttgart.de) Institute for Applied Optics, University of Stuttgart, Pfaffenwaldring 9, Stuttgart 70569, Germany Institute for System Dynamics, University of Stuttgart, Waldburgstraße 17/19, Stuttgart 70563, Germany ACCEPTED ARTICLE PREVIEW

Modern industrial production requires fast and automated quality control using state-of-the-art surface metrology sensors embedded in fast high-precision measuring machines. In order to achieve both fast and precise positioning, active control systems with model-based compensation of dynamic positioning errors due to increased acceleration forces can be applied. However, these active control systems require an accurate estimate of the dynamic positioning errors of the tool-center-point (TCP) with respect to the precisely measured position of the drive axes. A novel optical camera sensor system with high subpixel precision based on multi-spot detection enables the direct measurement of the TCP position at a slower rate than the sampling time of the control system and with significant latency or dead-time. Based on a general yet simple deviation model with large model mismatch, three approaches to estimate the TCP position are presented and compared with simulation and test bench results of a modified Mahr MFU 100 measuring machine. First, a multi-rate Kalman filter with delay compensation is designed based on a simple physical modal model generalizing the applicability of the concept for different types of measuring machines and machine tools. Second, additional sensors in form of accelerometers placed at the TCP are used to obtain an indirect measurement of the TCP position at a fast sampling rate to reduce the effect of the model mismatch. Third, instead of additional sensors, an alternative concept consisting of enhanced Gaussian process modeling to improve the model accuracy with a data-based error model is incorporated in the Kalman filter framework in form of fast pseudo-measurements outperforming the other approaches.

Zusammenfassung Mit einem Multi-Punkt-Positionsmesssystem ist es möglich, Positionen und Orientierungen mit sehr hoher Genauigkeit bildbasiert zu messen. Das Messsystem besteht aus einem einfachen Kamerasystem, das um ein diffraktives optisches Element (DOE) erweitert wird. Durch die Multi-Punkt-Methode (MPM) werden Messunsicherheiten von deutlich unter 1/100 Pixel erzielt. Um dies in der Praxis anwenden zu können, ist eine entsprechend hochgenaue Kalibrierung nötig. In diesem Beitrag werden verschiedene Kalibrierverfahren und -funktionen vorgestellt und untersucht. Die Auswertung zeigt, dass sich zur Kalibrierung ein allgemeiner Polynomansatz zusammen mit der Nanomess- und Positioniermaschine NPMM-200 am besten eignet. Es werden Standardabweichungen des Restfehlers von 0,31 µm im Objektraum (etwa 6/1000 Pixel im Bildraum) auf einer Fläche von etwa 87 mm × 49 mm 87\hspace{0.1667em}\text{mm}\times 49\hspace{0.1667em}\text{mm} erreicht (Polynomgrad = 9).

The dynamics of measuring machines are typically limited and do not suffice to fully exploit state-of-the-art metrology concepts. Therefore, dual-stage approaches become increasingly popular in this field. This paper uses a modeling approach including the lumped dynamic deviations and couplings between the actuators based on which optimal design paradigms are derived. Furthermore, the model is used to exploit the degree-of-freedom in the reference allocation considering the dynamic characteristics and limitations of each stage in a model predictive control fashion. A simulation study shows the benefits of the dual-stage approach as well as the proposed two-degree-of-freedom optimal reference allocation control structure.

In this paper, the hydraulic cooling system of an automotive hybrid dual-clutch transmission is modeled for the purpose of observer-based fault-detection. The considered fault case is a blocking of a functionally relevant switching valve resulting in a critical lack of cooling capacity during the clutch actuation. Three different model-based fault detection schemes are presented, namely an augmented extended Kalman filter with a position-based fault detection strategy and two dual-model observers with a position-based and a gating-based fault detection strategy, respectively. The fault detection schemes are validated using data from a test bench showing promising results.

In this paper, a Kalman filter (KF) based method for the accurate estimation of the dynamic positioning error of the tool-center-point (TCP) of a high-precision measuring machine is presented. A generalizing approach consisting of a linear physical model of the dynamic TCP deviations and a data-based model, which is realized as an additive Gaussian process (GP) trained on the physical model error, is applied. On one hand, the TCP position can be measured using a novel camera-based sensor which yields the absolute positioning error at a relatively slow sampling rate. On the other hand, the GP predicts the model mismatch at the fast base sample rate and can be treated as an additional pseudo measurement. A multi-rate (MR) observer in the KF framework yields an improved estimate of the TCP position compared to a KF using only the camera measurements. Simulation results show the potential of the proposed MR-KF approach using a combined physical and data-based model.

In industrial automation, a huge number of motion systems are in use. Unfortunately, the manual tuning of controllers for these motion systems is a time consuming process. Assuming a basic system model is available, the manual tuning can be replaced by an automated tuning process. Based on the system model, performance requirements are formulated in frequency and time domain and are combined into a single objective function. The resulting optimization problem is solved using nonlinear optimization. The automated tuning process is applied to the velocity control loop of a ball screw drive and shows excellent results for several different configurations of the drive.