Research on the Application Status of Machine Vision Technology in Furniture Manufacturing Process

Li, Rongrong; Zhao, Shengyu; Yang, Bokai

doi:10.3390/app13042434

Cited by 18 publications

(11 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 3 shows the hidden danger analysis process of transmission lines (the picture is quoted in Lightning risk assessment model for transmission lines with lift-based improved analytic hierarchy). [15]. Secondly, the radial optimization method is used to obtain the optimal solution of the transmission line.…”

Section: Analysis Of Potential Accidentsmentioning

confidence: 99%

“…AUTOMATIC ACQUISITION OF POWER LINE POINT CLOUD DATA BASED ON 3D DATA An automatic power line information extraction algorithm is studied under complex conditions. First, in the case of topographic relief, vegetation interference and other factors, top-down filtering is carried out based on raster data to remove surface object targets and use density descriptors based surface object segmentation[15]. Secondly, the radial optimization method is used to obtain the optimal solution of the transmission line.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Study on Real-Time Spatial Distance Acquisition Method of Transmission Line Based on Laser Point Cloud and Image Monitoring

Feiran Wang, Geng Han, Zilong Hou, Xinyang Guo

2024

jes

View full text Add to dashboard Cite

This paper introduces the principle of safety distance diagnosis of transmission lines by using airborne LiDAR detection technology. This project intends to realize the effective segmentation of ground objects and non-ground objects through the point cloud automatic filtering technology considering the surface fluctuation characteristics. Then, this paper realizes the initial recognition of ground objects based on spatial dimension information. Then this paper extracts the ground object information based on the image data with high precision. The 3D nodes of transmission lines are obtained by Hough transform and block centroid algorithm, and the floor features are extracted by area growth algorithm. The plant feature is extracted by using plant vertex and boundary point. The distance between the power line and the surrounding objects can be measured, and the elevation of the wire and the surrounding environment can be judged accordingly. The algorithm is tested by using the observation data of unmanned airborne LiDAR, and the simulation results show that the proposed method is feasible. Through the identification of buildings, plants and other objects along the line, the harm degree of them on the power line is judged and the effective treatment is carried out. This ensures the safe operation of transmission lines.

show abstract

Section: Analysis Of Potential Accidentsmentioning

confidence: 99%

mentioning

confidence: 99%

Study on Real-Time Spatial Distance Acquisition Method of Transmission Line Based on Laser Point Cloud and Image Monitoring

Feiran Wang, Geng Han, Zilong Hou, Xinyang Guo

2024

jes

View full text Add to dashboard Cite

show abstract

“…In previous studies, several researchers have considered machine vision-based evaluation tools for crack length [6], furniture manufacturing process [7], tracking floor eggs [8], grasping control robotic [9], review of surface defect detection [10], screening out conveyor lines [11],…”

Section: Introductionmentioning

confidence: 99%

A Real-Time Machine Vision System for Automatic Dimensioning of Various Shapes based on NI-VBAI

Cheng,

Saputra,

Shi

2024

Proceedings of the 11th International Applied Business and Engineering Conference, ABEC 2023, September 21st, 2023, Bengkalis,

View full text Add to dashboard Cite

This paper presents a Real-Time machine vision system based on the NI vision builder for automated inspection (NI-VBAI) platform for automatic dimensions of various shapes. Leveraging advanced machine vision techniques and intelligent NI-VBAI algorithms, the system achieves real-time dimensional accuracy in various forms. Seamless integration with existing industrial setups enables fast and precise measurements without human intervention. Extensive validation and performance evaluation demonstrate the system's robustness, highlighting its potential to revolutionize industrial automation, simplify production processes and ensure timely quality control in manufacturing environments. In this study, we conducted experiments on four objects with two shapes and two sizes. Each measurement process was repeated four times. The processing time for the NI-VBAI experiment can measure an object with 720 ms. The error rate obtained from each measurement process is 1%. Furthermore, the final results show that Ni-VBAI can perform the dimensional measurement process accurately and quickly. The final results can be used directly with configurations in other applications or machines directly for further purposes.

show abstract

“…Others have used machine vision to perform adaptive corrections for the height variation of welds caused by the thermal deformation of the welded workpiece, which significantly improves the welding quality [7,8]. In addition, deep learning combined with machine vision has been shown to achieve good results in irregular feature defect detection, enabling the detection of very small scratches [9,10]. This approach has also been applied in many food inspection scenarios, where color or texture features are used to identify food quality through a combination of various prediction models and algorithms [11,12].…”

Section: Introductionmentioning

confidence: 99%

Design and Experimentation of a Residual-Input Tube-End Cutting System for Plasma Bags Based on Machine Vision

Zhao

Liu

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

In response to the lack of plasma bag-breaking equipment and time-consuming manual recovery of plasma in China, this study focuses on the distal end cutting of a plasma bag residual-input tube and designs a machine-vision-based plasma bag residual-input tube cutting system. The system comprises a plasma bag rotation device, a bottom disc, an image acquisition device, a cutting device, and a device control system. The image acquisition device captures images of the rotating plasma bag and calculates the Euclidean distance from the end of the plasma bag input-tube distal end to the outer edge of the bottom support plate and the distance from the input-tube distal end to the centerline of the plasma bag. Two distinct value acquisition algorithms are designed for the two types of input tubes. The screw slide moves accordingly. When the plasma bag is above the cutting part, the cutting part cuts the end of the residual-input tube of the plasma bag. The prototype performance tests reveal that the cutting error is within 10% of the end of the plasma bag input tube distal end, the cutting success rate is 100%, and the processing time for each bag is 2.5 s, which meets the time requirements of the plasma bag breaker.

show abstract

Research on the Application Status of Machine Vision Technology in Furniture Manufacturing Process

Cited by 18 publications

References 62 publications

Study on Real-Time Spatial Distance Acquisition Method of Transmission Line Based on Laser Point Cloud and Image Monitoring

Study on Real-Time Spatial Distance Acquisition Method of Transmission Line Based on Laser Point Cloud and Image Monitoring

A Real-Time Machine Vision System for Automatic Dimensioning of Various Shapes based on NI-VBAI

Design and Experimentation of a Residual-Input Tube-End Cutting System for Plasma Bags Based on Machine Vision

Contact Info

Product

Resources

About