Geometry and resolution in triangulation vision systems

Sioma, Andrzej

doi:10.1117/12.2580525

Cited by 9 publications

(8 citation statements)

References 10 publications

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“…As shown in Figure 13, the vision imaging model takes O as the optical center, and the plane W passes through the feature point P 1 and is parallel to the imaging plane. P 1 Q 1 is the image of the wood feature size P 1 M on the plane W. P 1 Q 1 is the image of the feature size P 1 M on the imaging plane and O is the intersection of the plane W and the optical axis [23].…”

Section: Solid Sawn Timber Optimizing Cross-cut 241 Betula Sawn Timbe...mentioning

confidence: 99%

Intelligent Automation Manufacturing for Betula Solid Timber Based on Machine Vision Detection and Optimization Grading System Applied to Building Materials

Zhang

Diao

et al. 2023

Forests

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Wood material is the foundation of wood structure architecture, and its production technology and equipment technology decide the development and upgrading of modern wood structure architecture. Aiming at the problems of low automation degree, low material utilization rate, low production efficiency and high labor costs in the process of traditional wood processing, we explore the integration and innovation of the traditional wood processing industry and modern industrial Internet information technology on the basis of studying the properties of Betula (Betula costata) solid wood materials, wood comprehensive utilization rate, wood structure component development and processing technology requirements, and form an intelligent, automatic and industrial production mode for building materials. Through technology and methods such as mechanical design, automation technology, machine vision, deep learning, optimization algorithm, electronic design automation, computer aided manufacturing, etc., the key technologies of intelligent automatic optimization of wood materials were studied, and intelligent automatic production lines of Betula species identification, log optimization sawing, solid timber longitudinal multiblade sawing, sawn timber quality detection and solid timber optimizing cross-cuts are built. Based on the machine vision method, features are extracted; a tree species, defect classification and recognition model database is established; an image processing algorithm with high recognition accuracy, as well as fast processing speed and high robustness are studied; non-destructive testing and classification methods of machine vision are optimized; key problems of online rapid classification, detection and optimization of sawing are solved and production quality and processing efficiency are improved. Finally, the timber defect detection accuracy and Betula timber yield are analyzed, and the comprehensive utilization value of optimized sawing timber is compared with the comprehensive utilization value of manually marking sawing timber. The processing cost and efficiency of Betula sawing timber with an intelligent automatic production line are calculated. The test results show that the average detection accuracy of timber defect type, size and location is 89.69%, 89.69%, 92.25% and 82.29%, respectively, and the detection stability is high. By adopting intelligent automatic detection, classification and optimization sawing production line of wood, the comprehensive utilization value of optimized sawing timber is 14.13% higher than that of manual marking sawing timber, and 16,089.29 m3 more building materials can be processed annually. In the process of intelligent automatic wood processing, the intelligent detection system is used to detect defects, improve production performance and production efficiency and reduce labor costs. Compared with the traditional wood processing process, the method studied in this paper is improved to optimize the production line processing performance and processing technology. The research and development of an intelligent automatic production system for solid wood can promote the application and development of an automatic industrial production mode for sawn timber for the wood structure construction industry, deepen the integration of artificial intelligence technology, Internet technology and the whole wood processing industry and lead the upgrading of building materials for wood structures to an intelligent manufacturing production mode.

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Section: Solid Sawn Timber Optimizing Cross-cut 241 Betula Sawn Timbe...mentioning

confidence: 99%

Intelligent Automation Manufacturing for Betula Solid Timber Based on Machine Vision Detection and Optimization Grading System Applied to Building Materials

Zhang

Diao

et al. 2023

Forests

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“…The vision sensor shown in Figure 1 is mainly composed of a monocular camera and two line laser transmitters. It adopts the spatial arrangement of oblique incidence-perpendicular receiving, which has the advantages of small detection error and compact structure [ 24 , 25 ]. Among them, the central axes of the two line laser transmitters are parallel, and the designed angle value between the optical axis of the camera and the central axes of the line laser transmitters is 30°, which makes the detected values of the vision sensor close to the actual values [ 26 ].…”

Section: Configuration and Detection Mathematical Model Of Vision Sensormentioning

confidence: 99%

Internal Parameters Calibration of Vision Sensor and Application of High Precision Integrated Detection in Intelligent Welding Based on Plane Fitting

Zhu

et al. 2022

Sensors

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Vision sensing is a key technology to realize on-line detection of welding groove sizes and welding torch relative position and posture parameters during the arc welding process of intelligent production. For the specially designed vision sensor based on combined laser structured lights, an integrated calibration method for its internal parameters is proposed firstly, which improves the efficiency, accuracy and comprehensiveness of internal parameter calibration for a line structured light vision sensor and provides a good foundation for industrial application of the vision sensor. Then, the high precision integrated detection algorithms are derived for the V-groove size parameters and the spatial position and posture (SPP) parameters of the welding torch relative to the welding groove based on a single modulated laser lines image. The algorithms make full use of the data in a single modulated laser lines image, adopting data segmentation and plane fitting to realize the 3D reconstruction of V-groove surfaces and its adjacent workpiece surfaces of planar workpiece, so solving the parameters with high precision. In the verification tests, the relative detection error of V-groove size parameters of planar workpiece is less than 1%, and the relative detection error of SPP parameters of welding torch relative to the welding groove is less than 5%, which separately shows the effectiveness and accuracy of the calibration method and the detection algorithms. This research work provides a good technical support for the practical application of the specially designed vision sensor in the intelligent welding production.

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Section: Measurement Of Beam Motion In Vibration-damping Processmentioning

confidence: 99%

“…The imaging resolution resulting from the size of the field of view and the area of the matrix used to record the image was 0.159 mm per pixel. The resolution of determining the position of the point marked on the beam was 0.01 mm [28]. The algorithm for determining the location of all characteristic points was performed for each image in the recorded sequence.…”

Section: Measurement Of Beam Motion In Vibration-damping Processmentioning

confidence: 99%

Vision Analysis of the Influence of Piezoelectric Energy Harvesting on Vibration Damping of a Cantilever Beam

Grzybek

Sioma

2021

Energies

Self Cite

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A cantilever beam, manufactured from a steel-carrying substrate and two patches of Macro Fiber Composite of P2 type, was a subject of laboratory research. MFC patches were glued on both sides of the carrying substrate and were parallelly connected. An experimental determination of an optimal resistance for both energy harvesting and vibration passive damping of the cantilever beam was the purpose of the conducted laboratory research. The research contained 10 experiments in which courses of the energy-harvesting process and resistive passive damping of vibration were estimated. Energy harvesting was estimated by measurements of the generated current for the given load-resistance values. Resistive passive damping of vibration was assessed by using a vision method that enabled the displacements’ measurements of 10 selected points in the beam structure for the given shunt-resistance values. Values of both load resistance and shunt resistance were chosen on the basis of analytically calculated optimal load resistance and optimal shunt resistance. On the basis of the conducted experiments, the resistance range for which both the energy-harvesting process and the vibration-damping process are most effective was determined.

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Geometry and resolution in triangulation vision systems

Cited by 9 publications

References 10 publications

Intelligent Automation Manufacturing for Betula Solid Timber Based on Machine Vision Detection and Optimization Grading System Applied to Building Materials

Intelligent Automation Manufacturing for Betula Solid Timber Based on Machine Vision Detection and Optimization Grading System Applied to Building Materials

Internal Parameters Calibration of Vision Sensor and Application of High Precision Integrated Detection in Intelligent Welding Based on Plane Fitting

Vision Analysis of the Influence of Piezoelectric Energy Harvesting on Vibration Damping of a Cantilever Beam

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