Thermo-mechanical-optical coupling within a digital twin development for automotive LiDAR

Tavakolibasti, Majid; Meszmer, Peter; Bottger, G. T.; Kettelgerdes, Marcel; Elger, Gordon; Erdogan, Hueseyin; Seshaditya, A.; Wunderle, Bernhard

doi:10.1016/j.microrel.2022.114871

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…Light detection and ranging (LiDAR) is a technology that can measure distances by shooting light pulses and recording the time they require to bounce back [24]. It is often used for creating accurate 3D maps or models, commonly in the form of point clouds (datasets composed of 3D points representing the surfaces of objects).…”

Section: Geospatial Feature Extractionmentioning

confidence: 99%

Implementing a Digital Twin of an Underground Utility Tunnel for Geospatial Feature Extraction Using a Multimodal Image Sensor

Lee

Park

et al. 2023

Applied Sciences

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The increasing interest in digital twin technology, the digitalization of worn-out social overhead capital (SOC), and disaster management services has augmented the usage of 3D spatial models and information to manage infrastructure. In this study, a digital twin of a subterranean utility tunnel was created, and spatial objects were identified using inbuilt image sensors. The novelty lies in the development of a unique algorithm that breaks down the structure of the utility tunnel into points, lines, and planes, identifying objects using a multimodal image sensor that incorporates light detection and ranging (LiDAR) technology. The three main conclusions of this study are the following: First, a digital twin of the utility tunnel was constructed using building information modeling integrated with a geographic information system (BIM-GIS). Second, a method for extracting spatial objects was defined. Third, image-sensor-based segmentation and a random sample consensus (RANSAC) were applied. In this process, the supplementary algorithm for extracting and updating 3D spatial objects was analyzed and improved. The developed algorithm was tested using point cloud data, showing easier object classification with more precise LiDAR data.

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Section: Geospatial Feature Extractionmentioning

confidence: 99%

Implementing a Digital Twin of an Underground Utility Tunnel for Geospatial Feature Extraction Using a Multimodal Image Sensor

Lee

Park

et al. 2023

Applied Sciences

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“…Although specialized analysis and design software are available for optical, mechanical, and thermal disciplines, they are unable to deal with dynamic interdisciplinary problems in the overall design and analysis of systems. Optical-mechanical-thermal integration analysis, a comprehensive interdisciplinary analysis technique that combines the disciplines of optics, structure, and thermology [13,14], was utilized as shown in Figure 1. and applied.…”

Section: Introductionmentioning

confidence: 99%

Optical–Mechanical Integration Analysis and Validation of LiDAR Integrated Systems with a Small Field of View and High Repetition Frequency

Li,

Xing,

Zhao

et al. 2024

Photonics

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Integrated systems are facing complex and changing environments with the wide application of atmospheric LiDAR in civil, aerospace, and military fields. Traditional analysis methods employ optical software to evaluate the optical performance of integrated systems, and cannot comprehensively consider the influence of optical and mechanical coupling on the optical performance of the integrated system, resulting in the unsatisfactory accuracy of the analysis results. Optical–mechanical integration technology provides a promising solution to this problem. A small-field-of-view LiDAR system with high repetition frequency, low energy, and single-photon detection technology was taken as an example in this study, and the Zernike polynomial fitting algorithm was programmed to enable transmission between optical and mechanical data. Optical–mechanical integration technology was employed to obtain the optical parameters of the integrated system under a gravity load in the process of designing the optical–mechanical structure of the integrated system. The experimental validation results revealed that the optical–mechanical integration analysis of the divergence angle of the transmission unit resulted in an error of 2.586%. The focal length of the telescope increased by 89 μm, its field of view was 244 μrad, and the error of the detector target surface spot was 4.196%. The continuous day/night detection results showed that the system could accurately detect the temporal and spatial variations in clouds and aerosols. The inverted optical depths were experimentally compared with those obtained using a solar photometer. The average optical depth was 0.314, as detected using LiDAR, and 0.329, as detected by the sun photometer, with an average detection error of 4.559%. Therefore, optical–mechanical integration analysis can effectively improve the stability of the structure of highly integrated and complex optical systems.

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“…Literature [2][3][4][5] shows that temperature fluctuations result in performance degradation by defocusing due to housing deformation and lens expansion, imaging errors due to thermal mismatch between lens and lens carrier and interconnects, creep in solder joints, and adhesive shrinkage, among others. Authors in [6][7][8] report about the various aberrations introduced into the system by the tilt and decentering of the lens elements.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of thermally-induced change in sharpness of automotive cameras by coupled thermo-mechanical and optical simulation

Pandey,

Unruh,

Kettelgerdes

et al. 2023

SPIE Future Sensing Technologies 2023

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This paper investigates the change in optical performance in a multi-element lens objective from a series production automotive camera, due to elevated temperature. The change in optical performance is evaluated by a coupled thermomechanical and optical finite element (FE) simulation. The change in the overall geometry of the objective at 85°C is calculated by thermo-mechanical simulation and caused by the expansion of individual elements. In addition, the change in the surface geometry of the lenses is obtained after smoothening the distorted FE mesh. Optical simulations are performed afterward on the deformed objective to evaluate the optical parameters including MTF (modulation transfer function) at 60 line pairs per millimeter (lp/mm). A shift of the best focus position of the lens is observed. Simulated MTF values are validated by measuring the MTF at 60 lp/mm of 10 lens samples by heating it in-situ on the measurement system. It is seen that change in MTF is about 10 percent when the lens is heated from room temperature to 85°C. Coupled optical simulations indicate the presence of astigmatism and coma, implying the asymmetric change in lens geometry at elevated temperature and tilt in one or more lens elements.

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Thermo-mechanical-optical coupling within a digital twin development for automotive LiDAR

Cited by 6 publications

References 11 publications

Implementing a Digital Twin of an Underground Utility Tunnel for Geospatial Feature Extraction Using a Multimodal Image Sensor

Implementing a Digital Twin of an Underground Utility Tunnel for Geospatial Feature Extraction Using a Multimodal Image Sensor

Optical–Mechanical Integration Analysis and Validation of LiDAR Integrated Systems with a Small Field of View and High Repetition Frequency

Evaluation of thermally-induced change in sharpness of automotive cameras by coupled thermo-mechanical and optical simulation

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