Abstract

We describe the inline integration of the digital holographic sensor HoloTop in a precision turning plant. A fully automated part-handling system that fulfills the requirements for cycle time and stability was built and integrated into the production process. The inspection system has been running in multishift operation since 2015. For the first time, to the best of our knowledge, the results of one-year, long-term height measurements of 10 million parts under rough production conditions are presented to verify the suitability for industrial use.

© 2019 Optical Society of America

1. INTRODUCTION

Precision and safety demands on mechanical components are increasing steadily, especially for mass-produced parts in the automotive industry. It is important to measure each individual component precisely during production to avoid unnecessary waste or recalls of entire high-value assembled systems. Complete inspection, measurement, and documentation of all components will soon be standard practice. In many cases, the precise shape of components is essential for their function. In current mass production, a 100 percent quality control of many important parameters is only feasible qualitatively. Precise, quantitative measurements are possible only for a small random sample. This is no longer sufficient for the comprehensive demands of modern quality control.

Digital holography is an important technique for precise surface profile measurements. It is applied to characterize a large range of objects such as microelectromechanical systems, biological samples, or specularly reflecting objects [1,2]. Structure heights covering the range from several nanometers up to millimeters are accessible [14]. Predominantly, technical surfaces are optically rough and cause speckle patterns. Reliable measurements of such surfaces are possible using multiwavelength holography [5]. Therefore, digital holography is well qualified to control industrial processes [6].

Werner Gießler GmbH is an automotive supplier that produces precision turned parts used as a key component in piezo-driven fuel injection systems. The parts, which extend 18 mm in diameter and 5 mm in height, have a conically shaped surface that has to seal at pressures over 2500 bar as counterpart at the backside of the injection nozzle. The production process of turned parts starts from steel alloy bar stock. More than 40 turning machines produce round semi-finished goods simultaneously in multishift operation five to six days a week. Approximately one part per second corresponding to more than 10 million parts a year are manufactured. Subsequently the bulk goods are hardened by heating and cooling and wet-chemically deburred. After a cleaning process, parts are separated in a vibratory bowl.

The challenge is to inspect up to 10 million sample parts a year with one measurement system. Minimum to maximum tolerances of height deviations at the sealing surface are in the range of only 10 µm, requiring full field inspection of each part. Therefore, single point height repeatability must be less than 1 µm to keep slip and pseudo defect rate low and to pass the required measurement system analysis in the automotive industry. Lateral sampling of the surface must be in a range so that defects with a lateral extension of 50 µm can be measured.

To date, applications of digital multiwavelength holography have only presented data captured under measurement room or laboratory conditions [17]. To our knowledge, HoloTop is the first measurement system based on digital multiwavelength holography running inline in mass production. This paper describes the integration of the multiwavelength digital holographic sensor HoloTop under real production conditions on site at the automotive supplier Werner Gießler GmbH as shown in the video [8].

 figure: Fig. 1.

Fig. 1. (a) Part handling with clockwise working round table, pneumatic grippers, and optical inspection of sealing surface with digital multiwavelength sensor HoloTop at site. (b) Measurement head with directly mounted sample tray and test object.

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2. INLINE SETUP

This chapter first describes conditions and part handling in a precision turning production comparable to many metal processing companies all over the world. Requirements for the optical inspection concerning measurement time and isolation against vibrations are derived. Subsequently, the interferometric setup of the measurement head as a main part of the complete system is explained. A simulation of resonant vibration deformation of the housing is performed and shown to optimize its stiffness.

A. Conditions and Part Handling

After passing all production steps, all parts are transported as bulk material to the goods-leaving inspection that is in the same production shop with the turning machines that cause noise, vibrations, and oil dust. The production hall is not temperature controlled. Furthermore, a large roller door for trucks is located several meters next to inspection system. Temperatures between 10°C and 40°C are possible.

Parts are separated in a vibratory bowl and fed by a conveyor belt to a round table with 72 individual pneumatic grippers, as shown in Fig. 1(a). The diameter of the round table is approximately one meter. Each part is gripped at the shell surface and placed on a sample tray. The tray is mounted directly to the measurement head (b). During the measurement, the gripper opens slightly to decouple test sample and measurement head from the handling system mechanically. Additionally, the measurement head with sample holder is mounted on an actively controlled pneumatically vibration damped table to decouple measurements from high frequency floor vibrations ($ \gt {20}\,\,{\rm Hz}$). Due to short exposure times for image acquisition, which are in the range between 5 ms and 10 ms, vibrations at frequencies below 20 Hz are less critical.

The cycle time of the inspection process of each part is 1 s. 750 ms are necessary to grip a part, move to the next round table position, and drop the part on the sample tray. After opening the gripper over the sample tray, the part drops only 100 µm. Nevertheless, investigations of interference contrast have shown that a waiting time of additionally 150 ms is necessary for complete stop of sample motion. As a result, less than 100 ms remain for the complete surface measurement if the inspection is running in production cycle as required.

 figure: Fig. 2.

Fig. 2. (a) Sketch of the setup: Multiple laser sources are selected by a fiber switch inside the laser system (1). Single frequency laser light is guided by a single-mode polarization maintaining fiber to the measurement head (2) where the beam is expanded and coupled into a temporally phase-shifting interferometer. Both, laser system and measurement head are controlled by a PC (3). (b) Electrical control signals of the main devices during a complete measurement cycle compared to the production cycle of one second.

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B. Optical Setup

Figure 2 shows the complete HoloTop digital multiwavelength holographic measurement system, which consists of three basic units: (1) a multilaser system, (2) a PC with I/O interface, frame grabber and GPU, and (3) a measurement head.

In detail, three stabilized diode lasers emit the light of wavelengths between 633 and 638 nm. For good interferogram contrast, the lasers have to work in single-frequency and single-mode operation. The resulting synthetic wavelengths range from 80 µm to 1 mm. For these synthetic wavelengths, negative effects resulting from speckle decorrelation are negligible as surface roughness of the samples is two orders of magnitudes smaller than the synthetic wavelengths [9]. Each of the three laser sources is temperature controlled to avoid frequency drifts and mode hopping. The laser beams are coupled into fibers and connected to a fiber switch, which enables fast selection of the individual wavelengths for the measurement. Switching duration is specified to be less than 7 ms. The fiber switch is electrically connected to an output channel of a real-time I/O interface PC card so that the PC software can choose an individual laser source. The laser light is guided via a polarization-maintaining, single-mode glass fiber to the measurement head. After leaving the optical fiber inside the measurement head, the beam is divided into object and reference beam by a beam splitter cube, with both beams being expanded by a lens to fit the size of the object and the camera chip, respectively. The reference beam is deflected by a mirror mounted on a piezoelectric actuator, which is connected to an output channel of the same I/O interface PC card. Thus, the phase of the reference beam can be controlled by the PC software by moving the mirror slightly in the maximum range of one wavelength and executing temporal phase shifting [10]. The object beam illuminates the test sample. An objective lens images the light scattered by the sample onto the camera sensor where it is superimposed with the reference beam. A digital camera with a 12 MP CMOS sensor and Coax Press interface to the PC records three phase-shifted interferograms at each of the three wavelengths. In total, nine images with a square region of interest of ${3072} \times {3072}\,\,{\rm{pixels}}$ are captured within 60 ms and digitized with 10-bit resolution. The whole measurement process is controlled by PC software and triggered via a real-time I/O interface PC card. Additionally, the PC is equipped with a graphics processing unit (GPU) to accelerate reconstruction of the wavefront and image processing by using compute unified device architecture (CUDA) from Nvidia. The right image of Fig. 2(b) visualizes the electrical control signals of the main devices during a complete measurement cycle compared to the production cycle of one second depicted at the bottom. The whole data acquisition takes place in less than a tenth of the production cycle.

In the design of the interferometer, it was ensured that the housing has a maximum stiffness and low vibration level. The first eigenfrequency of vibration is at 605 Hz. Figure 3 shows a photo of the interferometer with all components (a) and a simulation of the spatial vibration amplitude distribution of the first eigenfrequency after simulated pulse excitation (b). The additional case cover was not simulated, but improves the interferometer’s stiffness further.

 figure: Fig. 3.

Fig. 3. (a) Photo of measurement head with all optical, mechanical, and electronic components, as depicted in Fig. 2. (b) Simulation of spatial vibration amplitude distribution after pulse excitation in arbitrary units. Result is the first eigenfrequency at 605 Hz. Not shown: Laser and PC, both in 19-inch racks.

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C. Data Processing

Numerical reconstruction of the objects height map is performed in two main steps. First, the complex wavefront in the hologram plane is calculated according to a method developed by Cai et al. [11], which makes the reconstruction more stable against vibration-induced changes of the phase between the object and reference beam during phase shifting. Next, the complex wavefront is propagated to the focused image plane without disturbing the twin image and zero order [5,12]. All phase-extraction computations and filtering operations are performed in parallel using CUDA on a consumer GPU. As a result, complete phase reconstruction at the multiple artificial wavelengths and evaluation of the combined height map is done in 100–300 ms, depending on data filtering settings. All required features (geometric features and deviations from the ideal shape) are extracted from the three-dimensional (3D) data in approx. 900 milliseconds. The most critical tolerances are defined on the sealing surfaces. The difference between the highest and lowest point after removal of the ideal surface shape must be less than $\sim{10}\,\, \unicode{x00B5}{\rm m}$ (depending on the respective sample type).

Image acquisition, data evaluation, and feature extraction are done in parallel to meet the requirements of the production cycle of 1 s. For a detailed description and mathematics of the numerical reconstruction procedure of digital multiwavelength holograms, we refer to [3,6,7].

 figure: Fig. 4.

Fig. 4. Measurement results on a groove standard: (a) Height map of a detail of the measurement; (b) 3D representation of the measured data; and (c) section along the dashed line in (a).

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 figure: Fig. 5.

Fig. 5. Measurement result of the shape of one test sample. (a) Colored height map of the sample surface. (b) Cross section along the dashed line shown in (a).

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 figure: Fig. 6.

Fig. 6. Height image, pseudo-3D representation of a detail of two sample surfaces and results of repeated measurements. (a) Height image without defect and (b) with intentionally generated impact mark. (c) and (d) Pseudo 3D representation of (a) and (b), respectively. (e) and (f) Result of 20 repeat measurements of the Pt-value on the data given in (a) and (b).

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3. RESULTS

To determine the accuracy and resolution of our setup for height measurement we have investigated the depth of a calibrated groove standard. A detail of the measurement result is given in Fig. 4. Five of the grooves corresponding to depths of 75.05, 24.03, 7.51, 2.40, and 0.76 µm can be clearly seen in the color height map (a) or the 3D representation (b). A section of the measurement result is given in (c). In each of the grooves, about 100 sampling points of the section are averaged to get a value for the groove depth. The determined mean values inside those five grooves are 74.78 µm, 23.85 µm, 7.80 µm, 2.31 µm, and 0.84 µm, respectively, and are in very good agreement with the expected values. The maximum deviation of the measured absolute depth is 0.29 µm. The measurement of the groove depths, which was repeated 25 times, yields corresponding standard deviations of 0.15 µm, 0.19 µm, 0.11 µm, 0.02 µm, and 0.04 µm, respectively. The standard uncertainty of these measurements can be calculated to be 0.05 µm.

The main task of the holographic inline measurement system is quality control of the surface of test samples and detection of small defects. Figure 5 shows a typical measurement result on one of the investigated samples. Figure 5(a) depicts a height image of a detail of the precision-turned surface of the part; (b) is a cross section of the surface. One can see the surface structure introduced by the turning process as circular grooves with a depth of less than 1 µm. One of the challenges for the image processing is the detection of the transition of the surface at its border into the rounded edge, which can be seen in the cross section given in (b) at a lateral x-position of approximately 3.5 mm.

To verify the repeatability of the HoloTop holographic measurement system, the same surface of two exemplary samples was measured 20 times. After each of these measurements, the respective sample was removed using the automatic handling system, and rotated and placed again in the sensor’s field of view. Thus, all impacts of the handling and the image processing contribute to the measurement results. Figure 6 illustrates the results of these measurements on a typical error-free sample (left side) and one containing an intentionally introduced defect (right side). Figures 6(a) and 6(b) show the height map of details of each of the two samples. 3D representations of these data sets are given in (c) and (d). The repeatability of the height measurements can be extracted from images (e) and (f). For the error-free sample, the Pt-value of the sample’s surface is shown in Fig. 6(e). Pt corresponds to the maximum peak-to-valley deviation of all measured points on the respective surface. The mean value for Pt on this surface over 20 measurements is calculated to 7.95 µm with a RMS-error of 0.42 µm. For the surface containing the impact mark, the deepest point of the mark is the most important value to extract from the dataset. The mean value for this depth is calculated to 16.3 µm with a RMS error of 0.75 µm. Thus, in both cases the RMS error is well below 1 µm, which is well suited for the presented application.

During the year 2018, the fully integrated holographic sensor HoloTop performed 9.86 million measurements. This corresponds to approximately 1000 TB of raw data (9.98 million ${\rm{measurements}} \times {3072} \times {3072}\,\,{\rm{Px}} \times {9}$ images sampled with 10 bit).

Figure 7 shows a photo of the inspected samples (a) and a graphical evaluation of one key feature over the complete year 2018 (b). The feature investigated here is the Pt-roughness on a plane surface in the central region of the sample, marked red in (a). The area of this surface is $10.2\,\,{\rm{mm}^2}$. The pixel resolution of the sensor is set to ${5.9}\,\,{\unicode{x00B5}{\rm m}} \times {5.9} \,\, {\unicode{x00B5}{\rm m}}$. Thus, a corresponding number of 280,000 3D measurement samples can be used to evaluate this feature. Data points are filtered using a ${9} \times {9}\,\,{\rm{pixel}}$-averaging filter followed by a ${7} \times {7}$ median filter. Despite the huge number of sampling points, the evaluated peak-to-valley deviation is very stable. The standard deviation of the investigated feature across the whole year is 2.6 µm, the mean value 8.8 µm. It should be noted that this standard deviation is the convolution of the measurement repeatability of the holographic sensor and the stability of the complete manufacturing process. A moving average with a window size of 80,000 samples–the approximate number of measured samples per day–is depicted as red line. The moving average is nearly constant during the measurement period of one year and ranging between 7.8 and 10.3 µm. Thus, there is hardly any long-term drift of the process as well as the measured data.

 figure: Fig. 7.

Fig. 7. (a) Photograph of the produced parts that are investigated using the holographic sensor, with the evaluated functional surface marked red. (b) Values of a feature (Pt) extracted from the holographic data recorded over one year (9.86 million 3D measurements). For visualization, the data points (blue) are plotted semi-transparent. The red dashed line illustrates the moving average over 80,000 measurements (approximately one day).

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4. CONCLUSION AND OUTLOOK

We demonstrated that digital holography is a versatile tool for 100 percent inline measurements. Even under harsh environmental conditions in a precision-turning shop for metal parts, long-term stability of height measurements in the one-micrometer dimension is possible. Neither day–night nor seasonal temperature drifts are observable in the data. In conclusion, holography is a serious alternative to time-consuming sample testing with coordinate measurement devices in a temperate-controlled measurement room.

During the first year, the automated inspection was done in parallel to manual optical inspection via microscope. Since 2016 the holographic measurement is used for 100 percent end-of-line inspection and laborious manual inspection was discontinued. To this day, the automated holographic inspection is running in a multishift operation up to five or six days a week. During this period, it was necessary to exchange one of the diode lasers due to degradation of the emitted light intensity. Additionally the camera and the frame grabber of the system had to be replaced due to electronic failures.

To our knowledge, no other technique is able to measure more than nine million 3D sample points in less than a tenth of a second with a single point absolute measurement accuracy of less than 0.8 microns (${1}\sigma $). The combination of speed, accuracy, and robustness makes digital holography a versatile tool for mass production, particularly in the automotive industry.

Other optical measurement techniques that provide comparable height maps on macroscopic technical surfaces concerning lateral sampling and accuracy of height measurement are white light interferometry, confocal microscopy, and shape from focus. All these techniques share a common process: that large amounts of image stacks must be recorded and evaluated to get the topography of an extended object (in particular, in height). For applications in the field of quality control, a digital holographic setup with three lasers is sufficient. It has to be emphasized that the length of the largest synthetic wavelength restricts only the unambiguity range but does not limit the height measurement range in general. As a result, for a complete measurement only nine images (three per wavelength) are recorded.

Moreover, from the knowledge of the complex object wave follows the possibility to reconstruct phase maps and corresponding height information of object surfaces located in an arbitrary distance to the sensor. The pure numerical focus of objects is possible. Application of autofocus methods to reconstructed speckle amplitude and phase maps are described in [13,14]. In practice, the decreasing numerical aperture restricts working distances due to the lower lateral resolution and less amount of object light on the sensor.

In the next step, we are aiming at the realization of a miniaturized wireless sensor to be used within a tooling machine [15] and to perform holographic measurements of continuously moving objects [16].

Funding

Bundesministerium für Wirtschaft und Energie (ZIM-KA 3398901 LP4).

Acknowledgment

Portions of this work were presented in Digital Holography and Three-Dimensional Imaging 2019, OSA Technical Digest (Optical Society of America, 2019), paper Tu4B.1.

REFERENCES

1. V. Pagliarulo, T. Russo, L. Miccio, and P. Ferraro, “Numerical tools for the characterization of microelectromechanical systems by digital holographic microscopy,” J. Micro/Nanolithogr. MEMS, MOEMS 14, 041314 (2015). [CrossRef]  

2. C. J. Mann, L. Yu, C.-M. Lo, and M. K. Kim, “High-resolution quantitative phase-contrast microscopy by digital holography,” Opt. Express 13, 8693–8698 (2005). [CrossRef]  

3. C. Wagner, W. Osten, and S. Seebacher, “Direct shape measurement by digital wavefront reconstruction and multiwavelength contouring,” Opt. Eng. 39, 79–85 (2000). [CrossRef]  

4. C. J. Mann, P. R. Bingham, V. C. Paquit, and K. W. Tobin, “Quantitative phase imaging by three-wavelength digital holography,” Opt. Express 16, 9753–9764 (2008). [CrossRef]  

5. D. Carl, M. Fratz, M. Pfeifer, D. M. Giel, and H. Höfler, “Multiwavelength digital holography with autocalibration of phase shifts and artificial wavelengths,” Appl. Opt. 48, H1–H8 (2009). [CrossRef]  

6. M. Fratz and D. Carl, “Novel industry ready sensors for shape measurement based on multi wavelength digital holography,” in Fringe 2013 (Springer, 2014), pp. 479–484.

7. M. Fratz, T. Beckmann, A. Schiller, T. Seyler, A. Bertz, D. Carl, and K. Buse, “Digital holography: evolution from a research topic to a versatile tool for the inline 100% 3D quality control in industry,” in Proceedings Sensor (2017), pp. 286–289.

8. “Holographic measurement technology at production for the Fraunhofer Award,” 2017, https://youtu.be/t1Sud60mXl0.

9. J. W. Goodman, “Some fundamental properties of speckle,” J. Opt. Soc. Am. 66, 1145–1150 (1976). [CrossRef]  

10. J. Burke and H. Helmers, “Spatial versus temporal phase shifting in electronic speckle-pattern interferometry: noise comparison in phase maps,” Appl. Opt. 39, 4598–4606 (2000). [CrossRef]  

11. L. Z. Cai, Q. Liu, and X. L. Yang, “Generalized phase-shifting interferometry with arbitrary unknown phase shifts for diffraction objects,” Opt. Lett. 29, 183 (2004). [CrossRef]  

12. T. Kreis, Holographic Interferometry: Principles and Methods (Wiley-VCH, 1996).

13. P. Memmolo, C. Distante, M. Paturzo, A. Finizio, P. Ferraro, and B. Javidi, “Automatic focusing in digital holography and its application to stretched holograms,” Opt. Lett. 36, 1945–1947 (2011). [CrossRef]  

14. P. Langehanenberg, B. Kemper, D. Dirksen, and G. von Bally, “Autofocusing in digital holographic phase contrast microscopy on pure phase objects for live cell imaging,” Appl. Opt. 47, D176–D182 (2008). [CrossRef]  

15. T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

16. A. Schiller, T. Beckmann, M. Fratz, A. Bertz, D. Carl, and K. Buse, “Multiwavelength digital holography: height measurements on linearly moving and rotating objects,” in SPECKLE 2018: VII International Conference on Speckle Metrology (2018).

References

  • View by:

  1. V. Pagliarulo, T. Russo, L. Miccio, and P. Ferraro, “Numerical tools for the characterization of microelectromechanical systems by digital holographic microscopy,” J. Micro/Nanolithogr. MEMS, MOEMS 14, 041314 (2015).
    [Crossref]
  2. C. J. Mann, L. Yu, C.-M. Lo, and M. K. Kim, “High-resolution quantitative phase-contrast microscopy by digital holography,” Opt. Express 13, 8693–8698 (2005).
    [Crossref]
  3. C. Wagner, W. Osten, and S. Seebacher, “Direct shape measurement by digital wavefront reconstruction and multiwavelength contouring,” Opt. Eng. 39, 79–85 (2000).
    [Crossref]
  4. C. J. Mann, P. R. Bingham, V. C. Paquit, and K. W. Tobin, “Quantitative phase imaging by three-wavelength digital holography,” Opt. Express 16, 9753–9764 (2008).
    [Crossref]
  5. D. Carl, M. Fratz, M. Pfeifer, D. M. Giel, and H. Höfler, “Multiwavelength digital holography with autocalibration of phase shifts and artificial wavelengths,” Appl. Opt. 48, H1–H8 (2009).
    [Crossref]
  6. M. Fratz and D. Carl, “Novel industry ready sensors for shape measurement based on multi wavelength digital holography,” in Fringe 2013 (Springer, 2014), pp. 479–484.
  7. M. Fratz, T. Beckmann, A. Schiller, T. Seyler, A. Bertz, D. Carl, and K. Buse, “Digital holography: evolution from a research topic to a versatile tool for the inline 100% 3D quality control in industry,” in Proceedings Sensor (2017), pp. 286–289.
  8. “Holographic measurement technology at production for the Fraunhofer Award,” 2017, https://youtu.be/t1Sud60mXl0 .
  9. J. W. Goodman, “Some fundamental properties of speckle,” J. Opt. Soc. Am. 66, 1145–1150 (1976).
    [Crossref]
  10. J. Burke and H. Helmers, “Spatial versus temporal phase shifting in electronic speckle-pattern interferometry: noise comparison in phase maps,” Appl. Opt. 39, 4598–4606 (2000).
    [Crossref]
  11. L. Z. Cai, Q. Liu, and X. L. Yang, “Generalized phase-shifting interferometry with arbitrary unknown phase shifts for diffraction objects,” Opt. Lett. 29, 183 (2004).
    [Crossref]
  12. T. Kreis, Holographic Interferometry: Principles and Methods (Wiley-VCH, 1996).
  13. P. Memmolo, C. Distante, M. Paturzo, A. Finizio, P. Ferraro, and B. Javidi, “Automatic focusing in digital holography and its application to stretched holograms,” Opt. Lett. 36, 1945–1947 (2011).
    [Crossref]
  14. P. Langehanenberg, B. Kemper, D. Dirksen, and G. von Bally, “Autofocusing in digital holographic phase contrast microscopy on pure phase objects for live cell imaging,” Appl. Opt. 47, D176–D182 (2008).
    [Crossref]
  15. T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).
  16. A. Schiller, T. Beckmann, M. Fratz, A. Bertz, D. Carl, and K. Buse, “Multiwavelength digital holography: height measurements on linearly moving and rotating objects,” in SPECKLE 2018: VII International Conference on Speckle Metrology (2018).

2015 (1)

V. Pagliarulo, T. Russo, L. Miccio, and P. Ferraro, “Numerical tools for the characterization of microelectromechanical systems by digital holographic microscopy,” J. Micro/Nanolithogr. MEMS, MOEMS 14, 041314 (2015).
[Crossref]

2011 (1)

2009 (1)

2008 (2)

2005 (1)

2004 (1)

2000 (2)

C. Wagner, W. Osten, and S. Seebacher, “Direct shape measurement by digital wavefront reconstruction and multiwavelength contouring,” Opt. Eng. 39, 79–85 (2000).
[Crossref]

J. Burke and H. Helmers, “Spatial versus temporal phase shifting in electronic speckle-pattern interferometry: noise comparison in phase maps,” Appl. Opt. 39, 4598–4606 (2000).
[Crossref]

1976 (1)

Beckmann, T.

M. Fratz, T. Beckmann, A. Schiller, T. Seyler, A. Bertz, D. Carl, and K. Buse, “Digital holography: evolution from a research topic to a versatile tool for the inline 100% 3D quality control in industry,” in Proceedings Sensor (2017), pp. 286–289.

T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

A. Schiller, T. Beckmann, M. Fratz, A. Bertz, D. Carl, and K. Buse, “Multiwavelength digital holography: height measurements on linearly moving and rotating objects,” in SPECKLE 2018: VII International Conference on Speckle Metrology (2018).

Bertz, A.

A. Schiller, T. Beckmann, M. Fratz, A. Bertz, D. Carl, and K. Buse, “Multiwavelength digital holography: height measurements on linearly moving and rotating objects,” in SPECKLE 2018: VII International Conference on Speckle Metrology (2018).

T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

M. Fratz, T. Beckmann, A. Schiller, T. Seyler, A. Bertz, D. Carl, and K. Buse, “Digital holography: evolution from a research topic to a versatile tool for the inline 100% 3D quality control in industry,” in Proceedings Sensor (2017), pp. 286–289.

Bingham, P. R.

Börret, R.

T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

Burke, J.

Buse, K.

M. Fratz, T. Beckmann, A. Schiller, T. Seyler, A. Bertz, D. Carl, and K. Buse, “Digital holography: evolution from a research topic to a versatile tool for the inline 100% 3D quality control in industry,” in Proceedings Sensor (2017), pp. 286–289.

A. Schiller, T. Beckmann, M. Fratz, A. Bertz, D. Carl, and K. Buse, “Multiwavelength digital holography: height measurements on linearly moving and rotating objects,” in SPECKLE 2018: VII International Conference on Speckle Metrology (2018).

Cai, L. Z.

Carl, D.

D. Carl, M. Fratz, M. Pfeifer, D. M. Giel, and H. Höfler, “Multiwavelength digital holography with autocalibration of phase shifts and artificial wavelengths,” Appl. Opt. 48, H1–H8 (2009).
[Crossref]

M. Fratz, T. Beckmann, A. Schiller, T. Seyler, A. Bertz, D. Carl, and K. Buse, “Digital holography: evolution from a research topic to a versatile tool for the inline 100% 3D quality control in industry,” in Proceedings Sensor (2017), pp. 286–289.

M. Fratz and D. Carl, “Novel industry ready sensors for shape measurement based on multi wavelength digital holography,” in Fringe 2013 (Springer, 2014), pp. 479–484.

A. Schiller, T. Beckmann, M. Fratz, A. Bertz, D. Carl, and K. Buse, “Multiwavelength digital holography: height measurements on linearly moving and rotating objects,” in SPECKLE 2018: VII International Conference on Speckle Metrology (2018).

T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

Dirksen, D.

Distante, C.

Ferraro, P.

V. Pagliarulo, T. Russo, L. Miccio, and P. Ferraro, “Numerical tools for the characterization of microelectromechanical systems by digital holographic microscopy,” J. Micro/Nanolithogr. MEMS, MOEMS 14, 041314 (2015).
[Crossref]

P. Memmolo, C. Distante, M. Paturzo, A. Finizio, P. Ferraro, and B. Javidi, “Automatic focusing in digital holography and its application to stretched holograms,” Opt. Lett. 36, 1945–1947 (2011).
[Crossref]

Finizio, A.

Fratz, M.

D. Carl, M. Fratz, M. Pfeifer, D. M. Giel, and H. Höfler, “Multiwavelength digital holography with autocalibration of phase shifts and artificial wavelengths,” Appl. Opt. 48, H1–H8 (2009).
[Crossref]

M. Fratz, T. Beckmann, A. Schiller, T. Seyler, A. Bertz, D. Carl, and K. Buse, “Digital holography: evolution from a research topic to a versatile tool for the inline 100% 3D quality control in industry,” in Proceedings Sensor (2017), pp. 286–289.

M. Fratz and D. Carl, “Novel industry ready sensors for shape measurement based on multi wavelength digital holography,” in Fringe 2013 (Springer, 2014), pp. 479–484.

T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

A. Schiller, T. Beckmann, M. Fratz, A. Bertz, D. Carl, and K. Buse, “Multiwavelength digital holography: height measurements on linearly moving and rotating objects,” in SPECKLE 2018: VII International Conference on Speckle Metrology (2018).

Giel, D. M.

Goodman, J. W.

Grün, V.

T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

Helmers, H.

Höfler, H.

Javidi, B.

Kemper, B.

Kim, M. K.

Kreis, T.

T. Kreis, Holographic Interferometry: Principles and Methods (Wiley-VCH, 1996).

Langehanenberg, P.

Liu, Q.

Lo, C.-M.

Mann, C. J.

Memmolo, P.

Miccio, L.

V. Pagliarulo, T. Russo, L. Miccio, and P. Ferraro, “Numerical tools for the characterization of microelectromechanical systems by digital holographic microscopy,” J. Micro/Nanolithogr. MEMS, MOEMS 14, 041314 (2015).
[Crossref]

Osten, W.

C. Wagner, W. Osten, and S. Seebacher, “Direct shape measurement by digital wavefront reconstruction and multiwavelength contouring,” Opt. Eng. 39, 79–85 (2000).
[Crossref]

Pagliarulo, V.

V. Pagliarulo, T. Russo, L. Miccio, and P. Ferraro, “Numerical tools for the characterization of microelectromechanical systems by digital holographic microscopy,” J. Micro/Nanolithogr. MEMS, MOEMS 14, 041314 (2015).
[Crossref]

Paquit, V. C.

Paturzo, M.

Pfeifer, M.

Russo, T.

V. Pagliarulo, T. Russo, L. Miccio, and P. Ferraro, “Numerical tools for the characterization of microelectromechanical systems by digital holographic microscopy,” J. Micro/Nanolithogr. MEMS, MOEMS 14, 041314 (2015).
[Crossref]

Schiller, A.

M. Fratz, T. Beckmann, A. Schiller, T. Seyler, A. Bertz, D. Carl, and K. Buse, “Digital holography: evolution from a research topic to a versatile tool for the inline 100% 3D quality control in industry,” in Proceedings Sensor (2017), pp. 286–289.

A. Schiller, T. Beckmann, M. Fratz, A. Bertz, D. Carl, and K. Buse, “Multiwavelength digital holography: height measurements on linearly moving and rotating objects,” in SPECKLE 2018: VII International Conference on Speckle Metrology (2018).

Seebacher, S.

C. Wagner, W. Osten, and S. Seebacher, “Direct shape measurement by digital wavefront reconstruction and multiwavelength contouring,” Opt. Eng. 39, 79–85 (2000).
[Crossref]

Seewig, J.

T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

Seyler, T.

T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

M. Fratz, T. Beckmann, A. Schiller, T. Seyler, A. Bertz, D. Carl, and K. Buse, “Digital holography: evolution from a research topic to a versatile tool for the inline 100% 3D quality control in industry,” in Proceedings Sensor (2017), pp. 286–289.

Ströer, F.

T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

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von Bally, G.

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C. Wagner, W. Osten, and S. Seebacher, “Direct shape measurement by digital wavefront reconstruction and multiwavelength contouring,” Opt. Eng. 39, 79–85 (2000).
[Crossref]

Yang, X. L.

Yu, L.

Appl. Opt. (3)

J. Micro/Nanolithogr. MEMS, MOEMS (1)

V. Pagliarulo, T. Russo, L. Miccio, and P. Ferraro, “Numerical tools for the characterization of microelectromechanical systems by digital holographic microscopy,” J. Micro/Nanolithogr. MEMS, MOEMS 14, 041314 (2015).
[Crossref]

J. Opt. Soc. Am. (1)

Opt. Eng. (1)

C. Wagner, W. Osten, and S. Seebacher, “Direct shape measurement by digital wavefront reconstruction and multiwavelength contouring,” Opt. Eng. 39, 79–85 (2000).
[Crossref]

Opt. Express (2)

Opt. Lett. (2)

Other (6)

T. Kreis, Holographic Interferometry: Principles and Methods (Wiley-VCH, 1996).

T. Seyler, M. Fratz, T. Beckmann, A. Bertz, D. Carl, V. Grün, R. Börret, F. Ströer, and J. Seewig, “Extensive microstructural quality control inside a machine tool using multiwavelength digital holography,” in SPECKLE 2018-VII International Conference on Speckle Metrology (2018).

A. Schiller, T. Beckmann, M. Fratz, A. Bertz, D. Carl, and K. Buse, “Multiwavelength digital holography: height measurements on linearly moving and rotating objects,” in SPECKLE 2018: VII International Conference on Speckle Metrology (2018).

M. Fratz and D. Carl, “Novel industry ready sensors for shape measurement based on multi wavelength digital holography,” in Fringe 2013 (Springer, 2014), pp. 479–484.

M. Fratz, T. Beckmann, A. Schiller, T. Seyler, A. Bertz, D. Carl, and K. Buse, “Digital holography: evolution from a research topic to a versatile tool for the inline 100% 3D quality control in industry,” in Proceedings Sensor (2017), pp. 286–289.

“Holographic measurement technology at production for the Fraunhofer Award,” 2017, https://youtu.be/t1Sud60mXl0 .

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Figures (7)

Fig. 1.
Fig. 1. (a) Part handling with clockwise working round table, pneumatic grippers, and optical inspection of sealing surface with digital multiwavelength sensor HoloTop at site. (b) Measurement head with directly mounted sample tray and test object.
Fig. 2.
Fig. 2. (a) Sketch of the setup: Multiple laser sources are selected by a fiber switch inside the laser system (1). Single frequency laser light is guided by a single-mode polarization maintaining fiber to the measurement head (2) where the beam is expanded and coupled into a temporally phase-shifting interferometer. Both, laser system and measurement head are controlled by a PC (3). (b) Electrical control signals of the main devices during a complete measurement cycle compared to the production cycle of one second.
Fig. 3.
Fig. 3. (a) Photo of measurement head with all optical, mechanical, and electronic components, as depicted in Fig. 2. (b) Simulation of spatial vibration amplitude distribution after pulse excitation in arbitrary units. Result is the first eigenfrequency at 605 Hz. Not shown: Laser and PC, both in 19-inch racks.
Fig. 4.
Fig. 4. Measurement results on a groove standard: (a) Height map of a detail of the measurement; (b) 3D representation of the measured data; and (c) section along the dashed line in (a).
Fig. 5.
Fig. 5. Measurement result of the shape of one test sample. (a) Colored height map of the sample surface. (b) Cross section along the dashed line shown in (a).
Fig. 6.
Fig. 6. Height image, pseudo-3D representation of a detail of two sample surfaces and results of repeated measurements. (a) Height image without defect and (b) with intentionally generated impact mark. (c) and (d) Pseudo 3D representation of (a) and (b), respectively. (e) and (f) Result of 20 repeat measurements of the Pt-value on the data given in (a) and (b).
Fig. 7.
Fig. 7. (a) Photograph of the produced parts that are investigated using the holographic sensor, with the evaluated functional surface marked red. (b) Values of a feature (Pt) extracted from the holographic data recorded over one year (9.86 million 3D measurements). For visualization, the data points (blue) are plotted semi-transparent. The red dashed line illustrates the moving average over 80,000 measurements (approximately one day).

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