Program overview
The application example of three-dimensional dimension measurement of structural parts belongs to the public industry application example of 3D visual measurement direction. For the detection of height, contour, gap, step difference, volume and assembly posture of structural parts, the imaging, point cloud processing and result output solutions of the 3D visual measurement system are presented. This page is geared towards project evaluation and solution matching. It does not disclose customer names, production line scales, business data or unconfirmed operating indicators. It focuses on what similar computer vision projects need to be evaluated, how to organize the technical route, how to confirm the delivery content, and what information should be prepared for early communication.
Project background
Three-dimensional measurement of structural parts focuses on height, step difference, contour, flatness, gap, volume and assembly posture. Two-dimensional images can only describe textures and edges. When encountering curved surfaces, reflective surfaces or complex contours, it is necessary to establish a stable basis for judgment through depth data and point cloud algorithms. In project communication, it is first necessary to clarify the detection objects, work station locations, sample differences, rhythm requirements, installation space, existing equipment interfaces and acceptance methods. For scenarios such as structural component measurement, assembly gap detection, volume measurement, and robot positioning, the same vision concept may require different camera angles, light source methods, lens focal lengths, trigger methods, and judgment rules at different sites. Therefore, JIS Technology usually starts with sample analysis and imaging verification, rather than directly applying a fixed template.
Customer needs and assessment points
Typical requirements for this type of project include height differences, outline dimensions, flatness, and assembly posture. In addition to the identification itself, it is also necessary to evaluate whether the test results need to retain pictures, whether the formula needs to be switched according to product model, whether it needs to be connected with PLC, robot, MES, WMS or host computer system, and whether batch reports need to be generated. The main pain points include: it is difficult for two-dimensional images to stably express height, step difference and surface contour; manual measurement efficiency is low, and it is difficult to automatically correlate detection results with production records; different product models require switching of measurement areas, thresholds and output formats. These issues need to be confirmed through sample testing and field condition analysis, and are not suitable to be replaced by unverified universal indicators.
Technical solution
The technical solution revolves around line laser, point cloud processing, and dimensional measurement, and is implemented in conjunction with the project delivery process. JIVISION will first evaluate the imaging stability, and then design the algorithm link and system interface. Solutions usually include: selecting line laser, structured light or RGB-D solutions based on accuracy, field of view and rhythm requirements; completing point cloud filtering, benchmark fitting, contour extraction, size calculation and abnormal marking; providing measurement results dashboards, report exports and PLC/MES data interfaces. In actual projects, traditional image processing, deep learning detection, OCR recognition, instance segmentation, point cloud processing or rule review processes can be combined according to object characteristics, so that the system can both identify targets and explain the basis for judgment.
System architecture
- 3D sensor selection
- Point cloud preprocessing
- Geometric fitting algorithm
- Measurement result output
Implementation process
The implementation process generally includes requirement confirmation, sample collection, imaging experiments, solution verification, algorithm training or rule development, interface definition, on-site deployment, acceptance testing, and operation and maintenance handover. At each stage, sample conditions, parameter versions, judgment rules, and abnormal sample records will be precipitated to facilitate subsequent review. When customers subsequently add product models, defect categories or on-site workstations, they can continue to iterate based on the original data and interfaces.
Delivery content
- 3D measurement algorithm
- Point cloud processing process
- Measurement results board
- Interface and reporting module
Acceptance and iteration
The acceptance indicators should be determined based on customer samples, on-site test results and testing standards confirmed by both parties. Common evaluation dimensions include recognition accuracy, risk of missed detection, false alarm handling, processing speed, stability under illumination changes, data traceability and maintenance convenience. The solution example description on the public page is used to illustrate the technical route and delivery method. The final project indicators should be based on the customer's real samples, deployment environment and contract agreements.
Applicable scenarios
This solution example is suitable for structural parts measurement, assembly gap detection, volume measurement, robot positioning and similar needs. It is also suitable for reference by customers who are evaluating machine vision inspection, computer vision algorithms, edge AI vision, 3D vision measurement, robot vision or visual data training. For projects with uncertain technical routes, sample evaluation, imaging testing, and small-scale solution verification can be conducted first to confirm feasibility before proceeding to system development and on-site deployment.
FAQ
Which project scenarios are suitable for the three-dimensional dimension measurement application examples of structural parts?
It is suitable for structural parts measurement, assembly gap detection, volume measurement, robot positioning and similar projects. It is especially suitable for customers who require 3D visual measurement, visual identification, visual measurement, data traceability or on-site equipment linkage.
What information needs to be prepared in the early stage of the project?
It is recommended to prepare representative samples, defect definitions, work station photos or videos, cycle times requirements, accuracy expectations, existing equipment interfaces and acceptance rules. The clearer the data, the more conducive it is to judge the imaging plan and algorithm route.
Can the content in the solution example be directly used as an acceptance indicator?
It cannot be directly equated with the basis for acceptance. The public solution examples are used to illustrate the technical route and delivery method. The final indicators need to be determined based on customer samples, field testing, deployment environment and acceptance criteria confirmed by both parties.