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Recent Advances and Applications of Optical and Acoustic Measurements
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Recent Advances and Applications of Optical and Acoustic Measurements

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: 20 June 2025 | Viewed by 4890

Special Issue Editors

Prof. Dr. Uma Maheswari Rajagopalan

E-Mail Website
Guest Editor
Department of Mechanical Engineering, College of Engineering, Shibaura Insitute of Technology, Tokyo 135-8548, Japan
Interests: scattering; optical coherence tomography; brain imaging; neuroscience; optics in biology; optics in environmental assessments; near-field optics; applied linguistics
Prof. Dr. Yoshikazu Koike

E-Mail Website
Guest Editor
Electronic Engineering, College of Engineering, Shibaura Institute of Technology, Tokyo 135-8548, Japan
Interests: ultrasonic actuator; fiber optic probe hydrophone; ultrasonic cleaning machine

Special Issue Information

Dear Colleagues,

This Special Issue invites articles from a vast range of topics that take optical and acoustic measurements in different environments, from biological to underwater settings. Optical and acoustic measurements both involve the usage of fundamental properties, such as diffraction, absorption, transmission, and scattering. Now, techniques such as optical coherence tomography and ultrasound are extensively used in clinical diagnostics worldwide. This Special Issue will not only present the advantages and the limitations of these techniques, but also inform readers about the combination of optics and sound, namely photoacoustic imaging. We welcome both review papers and original contributions related to an array of research fields. The topics of interest include, but are not restricted to:

  • Imaging;
  • Spectrometry;
  • Optical interferometric techniques;
  • Nano-optics;
  • Fiber optics;
  • Biomedical optics;
  • Photoacoustics;
  • Ultrasound in sensing;
  • Hydrophones;
  • Fiberoptic hydrophones;
  • Ultrasonic actuators;
  • Ultrasonic cleaning;
  • Ultrasonic fabrication and imaging.

Prof. Dr. Uma Maheswari Rajagopalan
Prof. Dr. Yoshikazu Koike
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • imaging
  • spectrometry
  • optical interferometric techniques
  • nano-optics
  • fiber optics
  • biomedical optics
  • photoacoustics
  • ultrasound in sensing
  • hydrophones
  • fiberoptic hydrophones
  • ultrasonic actuators
  • ultrasonic cleaning
  • ultrasonic fabrication and imaging

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Published Papers (5 papers)

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Research

15 pages, 4777 KiB  
Article
Multipoint Thermal Sensing System for Power Semiconductor Devices Utilizing Fiber Bragg Gratings
by Ridwanullahi Isa, Naveed Iqbal, Mohammad Abido, Jawad Mirza and Khurram Karim Qureshi
Appl. Sci. 2024, 14(23), 11328; https://doi.org/10.3390/app142311328 - 4 Dec 2024
Viewed by 272
Abstract
This study investigates the feasibility of using fiber Bragg grating (FBG) sensors for multipoint thermal monitoring of several power semiconductor devices (PSDs), such as insulated gate bipolar transistors (IGBTs), and rectifiers assembled on a common heatsink in a three-phase inverter. A novel approach [...] Read more.
This study investigates the feasibility of using fiber Bragg grating (FBG) sensors for multipoint thermal monitoring of several power semiconductor devices (PSDs), such as insulated gate bipolar transistors (IGBTs), and rectifiers assembled on a common heatsink in a three-phase inverter. A novel approach is proposed to integrate FBG sensors beneath the baseplates of the IGBT modules, avoiding the need for invasive modifications to the device structure. By strategically positioning multiple FBG sensors, accurate temperature profiles of critical components can be obtained. The experimental results demonstrate the effectiveness of the proposed method, with the temperature measurements from FBG sensors closely matching those obtained using thermal infrared (IR) cameras within ±1.1 °C. This research highlights the potential of FBG sensors for reliable and precise thermal management in power electronic systems, contributing to improved performance and reliability. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Optical and Acoustic Measurements)
►▼ Show Figures

Figure 1

Figure 1
<p>Schematic of a three-phase inverter.</p> Full article ">Figure 2
<p>Thermal network of a single IGBT module referenced to FBG sensor.</p> Full article ">Figure 3
<p>Thermal resistance network of multiple IGBTs.</p> Full article ">Figure 4
<p>Schematic of the calibration setup.</p> Full article ">Figure 5
<p>Temperature–wavelength correlation of FBG sensors.</p> Full article ">Figure 6
<p>(<b>a</b>) FBG array in a single optical fiber. (<b>b</b>) Installation settings of the sensors in the inverter circuit (<b>c</b>) FIBER1; vertical sensor configuration along the rectifier/IGBT baseplate. (<b>d</b>) FIBER2; horizontal sensor configuration along the rectifier/IGBTs baseplate.</p> Full article ">Figure 7
<p>(<b>a</b>) Tabletop experimental setup. (<b>b</b>) Thermal imaging of the IGBT.</p> Full article ">Figure 8
<p>Observed reflection spectra for the FBG sensors on the optical spectrum analyzer.</p> Full article ">Figure 9
<p>FBG temperature response to varying load power.</p> Full article ">Figure 10
<p>FBG temperature response to varying load power with minimized airgap effect.</p> Full article ">Figure 11
<p>(<b>a</b>) Thermal imaging of IGBT at time T1. (<b>b</b>) Thermal imaging of IGBT at time T2 (where T2 &gt; T1).</p> Full article ">Figure 12
<p>Predictions of hotspots using neural networks.</p> Full article ">
19 pages, 7813 KiB  
Article
A Spatial 4-DOF Laser Collimation Measurement System
by Han Jiang, Ke Zhang, Lufeng Ji, Ruiyu Zhang and Changpei Han
Appl. Sci. 2024, 14(22), 10491; https://doi.org/10.3390/app142210491 - 14 Nov 2024
Viewed by 387
Abstract
A compact and miniaturized laser collimation system was proposed to measure the four-degrees-of-freedom of an optical payload in high-altitude space. Compared with other systems, this system has a simple structure and low cost, high measurement accuracy, and a large measurement range. The optical [...] Read more.
A compact and miniaturized laser collimation system was proposed to measure the four-degrees-of-freedom of an optical payload in high-altitude space. Compared with other systems, this system has a simple structure and low cost, high measurement accuracy, and a large measurement range. The optical structure of the system was designed, the measurement principle of the four-degree-of-freedom was described in detail, the interference between the distance measurement and the angle measurement in the optical path was analyzed, and the installation error was analyzed. The error was minimized under different temperature conditions to improve the robustness of the system. An engineering prototype was built based on the system design scheme and an experiment was conducted to measure a target with a measured distance of 500 mm. The current indicators reached the requirements for the ground testing of optical payloads. The application of the system can be used to measure six degrees of freedom simultaneously by installing two systems in different coordinate systems. The system can also be used in industry; for example, by measuring the machine tool error in real time and compensating for it, the system can improve the positioning and motion accuracy. It can also be used for feedback control of the robot’s motion by measuring and controlling it. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Optical and Acoustic Measurements)
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Figure 1

Figure 1
<p>Optical schematic diagram of the system.</p> Full article ">Figure 2
<p>X/Y direction straightness ranging optical path.</p> Full article ">Figure 3
<p>X/Y direction ranging optical path.</p> Full article ">Figure 4
<p>Principal diagram of ranging light path.</p> Full article ">Figure 5
<p>The pitch angle in the X direction and yaw angle in the Y direction, which are used to measure the optical path.</p> Full article ">Figure 6
<p>Principal diagram of angle measurement light path.</p> Full article ">Figure 7
<p>System coordinates.</p> Full article ">Figure 8
<p>The angular cone prism, rotated around edge angle O.</p> Full article ">Figure 9
<p>The corner cone prism rotates around the non-edge O point.</p> Full article ">Figure 10
<p>CMOS installation error model.</p> Full article ">Figure 11
<p>Influence of CMOS translation installation error on the <span class="html-italic">X</span>-axis.</p> Full article ">Figure 12
<p>Neuronal structural model.</p> Full article ">Figure 13
<p>BP neural network temperature compensation model’s structure.</p> Full article ">Figure 14
<p>Four-degrees-of-freedom measuring system test device.</p> Full article ">Figure 15
<p>PI Company’s H-825 displacement table.</p> Full article ">Figure 16
<p>Calibration experiments: (<b>a</b>) X straightness calibration curve; (<b>b</b>) Y straightness calibration curve; (<b>c</b>) calibration curve of pitch in the X direction; (<b>d</b>) calibration curve of yaw in the Y direction.</p> Full article ">Figure 17
<p>Results of the stability experiments: (<b>a</b>) X straightness SD = 1.11 μm; (<b>b</b>) Y straightness; (<b>c</b>) pitch SD = 0.91 arcsec; (<b>d</b>) yaw SD = 0.90 arcsec.</p> Full article ">Figure 18
<p>Article’s technical route.</p> Full article ">
15 pages, 3263 KiB  
Article
Fast Assessment of Quality of Water Containing Inorganic Pollutants Using Laser Biospeckles in Microbioassay
by Arti Devi, Hirofumi Kadono and Uma Maheshwari Rajagopalan
Appl. Sci. 2024, 14(13), 5558; https://doi.org/10.3390/app14135558 - 26 Jun 2024
Cited by 1 | Viewed by 1746
Abstract
Recently, bioassay techniques have been gaining prominence in assessing water toxicity, offering comprehensive evaluations without identifying the individual chemical component. However, microscopic observation is a crucial component in microbioassays to know the critical features of the targeted microorganisms. However, as the microorganism’s size [...] Read more.
Recently, bioassay techniques have been gaining prominence in assessing water toxicity, offering comprehensive evaluations without identifying the individual chemical component. However, microscopic observation is a crucial component in microbioassays to know the critical features of the targeted microorganisms. However, as the microorganism’s size becomes smaller, observation becomes more difficult due to the narrower focal depth of the imaging system. To address this challenge, we propose a novel laser biospeckle non-imaging technique utilizing biospeckle patterns generated by microorganisms, enabling non-imaging assessments of their swimming ability. Paramecium and Euglena were used as microorganisms. Paramecium and Euglena were subjected to varying concentrations of heavy metal pollutants (Zn(NO3)2·6H2O and FeSO4·7H2O), and their swimming activity was quantified using a dynamic biospeckle analysis. The results show a concentration-dependent effect of Zn on both species, leading to decreased swimming ability at increased concentration. Conversely, Fe exhibited varying effects on Paramecia and Euglena, with the latter displaying tolerance at lower concentrations but a notable response at higher concentrations. The advantage of the method is that owing to the non-imaging system, an enormous number of microorganisms can be processed. Moreover, the method allows for an immediate and statistically significant estimation of their swimming ability in response to environmental pollution. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Optical and Acoustic Measurements)
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Figure 1

Figure 1
<p>A schematic of the sample cell used in the experiments (<b>a</b>) and a photograph of the actual cell (<b>b</b>). The cell gap was 1 mm, and the diameter of the probing area was 15 mm (red shaded area).</p> Full article ">Figure 2
<p>A schematic diagram of the experimental system consisting of M1~M2 mirrors, L1~L2 lenses, a polarizer, and a CCD camera. The parallel beam irradiated a sample cell (cell gap: 1 mm) containing microorganisms.</p> Full article ">Figure 3
<p>(<b>a</b>) The cross-correlation function as a function of time for Paramecia under different viscosity media. (<b>b</b>) The correlation time as a function of viscosity for Paramecia. The error bars indicate the standard deviation. *, ** indicated the statistical significance of data <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01. N = 9.</p> Full article ">Figure 4
<p>(<b>a</b>) Cross-correlation function of Paramecia per unit time under different Fe concentrations and (<b>b</b>) the correlation time as a function of varying Fe concentrations (mg/L) for Paramecia and Euglena *, ** indicated the statistical significance of data <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 (N = 9).</p> Full article ">Figure 5
<p>(<b>a</b>) The cross-correlation function of Euglena per unit time under different Fe concentrations and (<b>b</b>) the correlation time as a function of varying Fe concentrations (mg/L) for Euglena and Paramecia, *, ** indicated the statistical significance of data <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 (N = 9).</p> Full article ">Figure 6
<p>(<b>a</b>) The correlation function as a function of time for Paramecia under different Zn concentrations shown, (<b>b</b>) the correlation time as a function of Zn concentration (mg/L) for Paramecia. *, ** indicated the statistical significance of data <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01. N = 9.</p> Full article ">Figure 7
<p>(<b>a</b>) The cross-correlation function for Euglena under different Zn concentrations, (<b>b</b>) the cross-correlation time as a function of Zn concentration (mg/L) for Euglena. *, ** indicated the statistical significance of data <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01. N = 9.</p> Full article ">Figure 8
<p>(<b>a</b>) The correlation time for Paramecia and (<b>b</b>) Euglena as a function of Fe concentrations for 1.5, 24, and 48 h, (<b>c</b>) the correlation time for Paramecia and (<b>d</b>) Euglena as a function of Zn concentration for 1.5, 24, and 48 h.</p> Full article ">
14 pages, 3675 KiB  
Article
Modeling and Analysis of a Long-Range Target Localization Problem Based on an XS Anode Single-Photon Detector
by Yihang Zhai, Bin Wang, Xiaofei Wang and Qiliang Ni
Appl. Sci. 2024, 14(6), 2400; https://doi.org/10.3390/app14062400 - 12 Mar 2024
Viewed by 826
Abstract
With the development of space detection technology, the detection of long-range dark and weak space targets has become an important issue in space detection. Cross-strip anode photon imaging detectors can detect weak light signals with extremely low dark count rates and are well [...] Read more.
With the development of space detection technology, the detection of long-range dark and weak space targets has become an important issue in space detection. Cross-strip anode photon imaging detectors can detect weak light signals with extremely low dark count rates and are well suited to applications in long-range target detection systems. Since cross-strip anode detectors are expensive to develop and fabricate, a theoretical analysis of the detection process is necessary before fabrication. During the detection process, due to the dead time of the detector, some photon-generated signals are aliased, and the true arrival position of the photon cannot be obtained. These aliased signals are usually removed directly in the conventional research. But in this work, we find that these aliased signals are not meaningless and can be applied to center of mass detection. Specifically, we model the probabilistic mechanisms of the detection data, compute the average photon positions using aliased and non-aliased data and prove that our method provides a lower variance compared to the conventional method, which only uses non-aliased data. Simulation experiments are designed to further verify the effectiveness of the aliasing data for detecting the center of mass. The simulation results support that our method of utilizing the aliasing data provides more accurate detection results than that of removing the aliasing data. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Optical and Acoustic Measurements)
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Figure 1

Figure 1
<p>Schematic diagram of XS detector structure.</p> Full article ">Figure 2
<p>Electron cloud produced by two photons at the XS anode. (<b>a</b>,<b>b</b>) shows two possibilities of photons arriving corresponding to the same charge distribution.</p> Full article ">Figure 3
<p>The schematic diagram is the waveform superposition process during Gaussian shaping. <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>Q</mi> </mrow> <mrow> <mi>i</mi> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>Q</mi> </mrow> <mrow> <mi>i</mi> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> are two waveforms before superposition. <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>Q</mi> </mrow> <mrow> <mi>s</mi> <mi>u</mi> <mi>m</mi> </mrow> </msub> </mrow> </semantics></math> is the waveform after superposition. The peak of the superimposed waveform is attained at time <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>t</mi> </mrow> <mrow> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math>, which is between <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>t</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>t</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math>.</p> Full article ">Figure 4
<p>Mean (markers) and standard deviation (error bars) of the distribution of residuals between generated and reconstructed target positions versus detection time T at s = 10 MHz.</p> Full article ">Figure 5
<p>Mean (markers) and standard deviation (error bars) of the distribution of residuals between generated and reconstructed target positions versus rate s for detection time T = 1 μs.</p> Full article ">Figure 6
<p>Mean (markers) and standard deviation (error bars) of the distribution of residuals between generated and reconstructed target positions versus rate s for detection time T = 10 μs.</p> Full article ">Figure 7
<p>Mean (markers) and standard deviation (error bars) of the distribution of residuals between generated and reconstructed target positions versus diffusion spot diameters. The detection time is 10 μs, and s = 10 MHz. The horizontal axis indicates the diffuse spot diameter in pixel numbers.</p> Full article ">
15 pages, 2427 KiB  
Article
Performance Evaluation of Cross-Correlation Based Photoacoustic Measurement of a Single Object with Sinusoidal Linear Motion
by Kotaro Fujinami and Katsuaki Shirai
Appl. Sci. 2023, 13(24), 13202; https://doi.org/10.3390/app132413202 - 12 Dec 2023
Viewed by 1153
Abstract
Photoacoustic (PA) velocimetry holds the advantage of detecting ultrasound signals from selective targets sensitive to specific wavelengths of light irradiation. In particular, it is expected to be applied for measuring blood flow in microvasculature. However, PA velocimetry has not been sufficiently investigated for [...] Read more.
Photoacoustic (PA) velocimetry holds the advantage of detecting ultrasound signals from selective targets sensitive to specific wavelengths of light irradiation. In particular, it is expected to be applied for measuring blood flow in microvasculature. However, PA velocimetry has not been sufficiently investigated for small velocity ranges down to several tens of millimeters per second. This study evaluates the performance and uncertainty of PA velocity measurements using a single graphite cylinder (GC) as a moving object. A pair of short laser pulses irradiated the object within a brief time interval. The velocity was measured based on the cross-correlation peak of successive PA signal pairs in the time domain. The limiting measurement uncertainty was 3.4 mm/s, determined by the sampling rate of the digitizer. The object motion was controlled in a sinusoidal linear motion, realized using a loudspeaker. With the PA measurement, the velocity of the object was obtained with a time resolution in milliseconds and with directional discrimination. Notably, the PA velocity measurements successfully provided the local velocities of the object across a wide range, with the reference velocity obtained as the time derivative of the displacement data acquired using a laser displacement sensor (LDS). The PA measurement exhibited uncertainties ranging from 0.86 to 2.1 mm/s for the maximum and minimum velocities during the experiment. The uncertainties are consistent with those in stationary cases, and nearly constant in the investigated velocity range. Furthermore, the PA measurements revealed local fine velocities of the object, which were not resolved by the reference velocities of the LDS measurements. The capability of the PA velocity measurement was found to be advantageous for measurements of objects with dynamic variations in magnitude and direction. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Optical and Acoustic Measurements)
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Figure 1

Figure 1
<p>Principle of the velocity measurement using photoacoustic (PA) signals. PA signals are generated by irradiating an object with a pair of laser pulses separated by a pre-selected time delay <math display="inline"><semantics> <msub> <mi>t</mi> <mi>p</mi> </msub> </semantics></math>. When the time <span class="html-italic">t</span> = 0 s, the first pulse generates PA signal 1. After <math display="inline"><semantics> <msub> <mi>t</mi> <mi>p</mi> </msub> </semantics></math> seconds, the second pulse irradiates the object, generating PA signal 2. During the <math display="inline"><semantics> <msub> <mi>t</mi> <mi>p</mi> </msub> </semantics></math> seconds, the object undergoes movements, causing a time-shift <math display="inline"><semantics> <msub> <mi>t</mi> <mi>s</mi> </msub> </semantics></math> in the arrival time of the PA signal pairs.</p> Full article ">Figure 2
<p>Experimental setup of the PA velocity measurement (PD: photo detector, PRF: pulse repetition frequency, LS: loudspeaker, UST: ultrasound transducer). A pair of pulsed lasers was irradiated an object immersed in the water. The object, a GC, was affixed to the LS membrane via an arm. The pre-selected time delay was controlled by the delay generator. The irradiation timings were detected by the PD. The PRF and LS oscillation were regulated via the function generator. The generated PA signals were measured employing the oscilloscope through the UST.</p> Full article ">Figure 3
<p>Experimental setup for LDS measurement. The object was set to a cantilevered arm, and the LDS was carefully submerged in water aligned to the optical axis of the pulsed lasers. The sinusoidal linear motion of the object was operated by the LS. The object displacement was measured using the LDS aligned colinear to the irradiation axis of the laser pulses.</p> Full article ">Figure 4
<p>Typical PA and PD signals in time domain. (<b>a</b>) PA and PD signals with a time delay <math display="inline"><semantics> <msub> <mi>t</mi> <mi>p</mi> </msub> </semantics></math>. The red signal represents an extracted PA signal 1 from the first pulse irradiation, while the blue one illustrates an extracted PA signal 2 generated from the second pulse irradiation. (<b>b</b>) The pulse irradiation timings <math display="inline"><semantics> <mrow> <msub> <mi>t</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>t</mi> <mn>2</mn> </msub> </mrow> </semantics></math> detected by the central-difference of the PD signals. (<b>c</b>) Comparison of the extracted PA signals. The extraction timings were the irradiation timings <math display="inline"><semantics> <mrow> <msub> <mi>t</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>t</mi> <mn>2</mn> </msub> </mrow> </semantics></math>. The time shift <math display="inline"><semantics> <msub> <mi>t</mi> <mi>s</mi> </msub> </semantics></math> was calculated based on the CC of the extracted signals. (<b>d</b>) CC results of the extracted signals with the peak position defined as time shift <math display="inline"><semantics> <msub> <mi>t</mi> <mi>s</mi> </msub> </semantics></math>.</p> Full article ">Figure 5
<p>Result of PA velocity measurement with 5<math display="inline"><semantics> <mrow> <mo>°</mo> </mrow> </semantics></math> interval. The object underwent sinusoidal oscillation at 5 Hz, completing one period every 0.20 s. The black dots represent the velocities obtained from the PA velocity measurement, while the green line illustrates the averaged velocities of PA measurement. The positive maximum velocity <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>max</mi> </msub> <mo>=</mo> </mrow> </semantics></math>316 mm/s was recorded at 5.6 ms, while the negative maximum velocity <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>max</mi> </msub> <mo>=</mo> <mo>−</mo> </mrow> </semantics></math>292 mm/s was obtained at 0.11 s.</p> Full article ">Figure 6
<p>Result of LDS measurement. The blue line indicates the displacement of the object, while the gray line depicts the velocities calculated using a central-difference scheme of the displacement data. The positive maximum velocity reached <math display="inline"><semantics> <mrow> <mi>v</mi> <mo>=</mo> <mn>194</mn> </mrow> </semantics></math>mm/s at 8.3 ms, and the negative maximum velocity was <math display="inline"><semantics> <mrow> <mi>v</mi> <mo>=</mo> <mo>−</mo> </mrow> </semantics></math>191 mm/s at 0.11 s.</p> Full article ">Figure 7
<p>Comparative analysis of the measurement results based on the PA and the LDS. The gray line indicates the velocity measured by the LDS, while the green line represents the averaged velocities derived from the PA result. Notably, the LS oscillation exhibited a folding back at 0.055 s in all measurements. The PA measurement uncertainties ranged from 0.86 to 2.1 mm/s. The maximum deviation between the LDS and PA was 26 mm/s at 0.031 s.</p> Full article ">Figure 8
<p>Comparison of velocities measured using the PA and LDS in the range of 0 to 100 mm/s. The input signal to the LS was a sinusoidal waveform, with the resulting displacement measured with the LS being a cosine waveform. The PA data showcase the maximum velocities at the theoretical phases. The folding back of the LS oscillation occurs at 0.05 and 0.15 s, where velocities approach 0 mm/s. The LDS data were internally averaged before the output. The PA data were moving averaged over 12 neighbor points to match the temporal resolution of the LDS data. As a result, the PA (averaged) data shifted 0.033 s to the right.</p> Full article ">Figure A1
<p>Experimental setup for the comparative measurement. PA velocity measurements were conducted with two cases of the light absorbing objects with a single GC at a diameter of 0.5 mm and with three GCs at a diameter of 0.5 mm aligned laterally. In the positive direction of the movement toward the UST, the second PA signal (blue) arrived at the UST earlier than the first one (red).</p> Full article ">Figure A2
<p>Result of PA velocity measurement with 5<math display="inline"><semantics> <mrow> <mo>°</mo> </mrow> </semantics></math> interval. The object was oscillated sinusoidally at 5 Hz, completing one period every 0.20 s. The blue dots show the velocities of a GC with a diameter of 0.5 mm; the black dots show the 2.0 mm cylinder. Additionally, the orange dots show the velocity results of three cylinders with a diameter of 0.5 mm. These results are the ensemble average of five measurements. The SDs are shown as error bars.</p> Full article ">
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