Quality Control of Wood-Pulp Chips Using A 3D Laser Scanner and Functional Pattern Recognition

López, Marcos; Vilán, José Antonio Vilán; Matías, J. M.; Taboada, J.

doi:10.1109/isie.2007.4374874

Cited by 5 publications

(7 citation statements)

References 11 publications

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“…Studies examining the distribution of shape and size in granular composite materials strongly relate it to the characteristics of the final products [10]. This happens in the wood panel production [6] as well as in many other industrial applications, like pharmacy [11], papermaking [12] or mining [13]. The analysis of particle distribution allows for detecting problems that occurred in production, like bias in the working point of the machines, wearing of the tools, wrong or poor quality in the basic materials [6].…”

Section: Related Workmentioning

confidence: 99%

“…Another approach to granulometric analysis employs more complex setups to generate 3D models of the particles. In the paper industry for instance, the work in [12] makes use of 3D laser scanners to detect the surface of wood chips, used for making wood-pulp. Also, the works in [13], [28] take advantage of the same technology to measure rock fragments.…”

Section: Related Workmentioning

confidence: 99%

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Improving OSB wood panel production by vision-based systems for granulometric estimation

Labati

Genovese

Muñoz

et al. 2015

2015 IEEE 1st International Forum on Research and Technologies for Society and Industry Leveraging a Better Tomorrow (RTSI)

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Oriented Strand Board (OSB) is a kind of engineered wood particle board widely adopted in manufacturing, construction and logistics. The production of OSB panels requires rectangular-shaped wood strands of specific size, arranged in layers to form the so-called "mattress" (mat) and bonded together with glue. The structural properties of the panel rely directly on the layer forming. In particular, the size distribution-namely granulometry-of the strands should fulfill standard measures to reach the mechanical properties expected from the panel. Offline granulometry of particle materials is the most commonly procedure used to evaluate the production process, but it is prone to several drawbacks owing to the manual intervention of human operators. Vision-based systems, instead, allow for performing granulometric analyses in an automatic and contactless manner. We propose a computer vision approach to estimate the granulometry of wood strands. The designed framework analyzes images of a mat of strands placed over a moving conveyor belt, and provides useful information and measurements to enhance the production of OSB panels. Because of the very large amount of wood strands on the mat, particle-overlapping is frequent and represents a main issue for measurement algorithms. In order to overcome this problem, our framework joins image processing and computational intelligence methods, such as edge detection and fuzzy color clustering. We tested the framework with real and synthetic images, useful to variate the conditions of the material's shape. The obtained results demonstrate the ability of our approach to evaluate the granulometry of the strands in real conditions, and robustness against the simulated variations of the production process.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Improving OSB wood panel production by vision-based systems for granulometric estimation

Labati

Genovese

Muñoz

et al. 2015

2015 IEEE 1st International Forum on Research and Technologies for Society and Industry Leveraging a Better Tomorrow (RTSI)

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“…The purpose of ISO 17225-4:2021 is to establish an unambiguous and transparent classification standard for graded wood chips. Several attributes fall under the wood chip quality standards, including MC [2,3,[5][6][7], ash content [5,18,19,28,33,41], particle size distribution [18,26,[46][47][48][49][50][51][52][53], and the amount of some inorganic elements such as chlorine.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive review on wood chip moisture content assessment and prediction

Rahman,

Marufuzzaman,

Street

et al. 2024

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Wood chips are the primary sources of raw materials for numerous industries, including pelleting mills, biorefineries, pulp-and-paper industries, and biomass-based power generation facilities. Unfortunately, when wood chips are utilized as a renewable and environmentally friendly resource, industries are constantly challenged by the consistency of the wood chip qualities (e.g., moisture/ash contents, size distributions) - a historically recognized problem on a global scale. Among other wood chip quality attributes, the moisture content is considered the most pressing one as it directly impacts the energy content, storage stability, and handling properties of the raw and finished products. Therefore, accurate wood chip moisture content prediction can help optimize the drying process and reduce energy consumption. In this review, a survey was conducted on various techniques and models employed for predicting wood chip moisture content. The advantages and limitations of these approaches, as well as their potential applications and future directions were also discussed. This review aims to provide a comprehensive overview of the current state-of-the-art in wood chip moisture content prediction and to highlight the challenges and opportunities for further research and development in this field.

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“…Laser line on the real image of interest is typically 1 to 10 pixels wide. Many laser line detection algorithms [4], [5] for 3D laser line scanners detect the laser line with pixel resolution. Usually those laser line detection algorithms are simpler and thus preferred in cases, where the accuracy of the laser scanner is not very important or where the processor recourses are limited.…”

Section: Introductionmentioning

confidence: 99%

Laser Scanner Calibration Dependency On the Line Detection Method

Molder

Märtens²,

Saar³

et al. 2015

ElAEE

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Calibration is an important step of 3D structured light laser scanners to be able to obtain an accurate measuring result. During the calibration a relation between the pixels in 3D laser scanner camera image and the real world units is made. Laser line detection method as part of the calibration process plays an important role in this calibration process, but this aspect has not been investigated before. In this paper the calibration and measurement result dependency from the laser line detection with pixel or sub-pixel resolution in the calibration process has been investigated. The calibration process of the developed 3D laser scanner has been described. The results show dependency between the laser line detection method in the calibration process and the final measurement results.

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Quality Control of Wood-Pulp Chips Using A 3D Laser Scanner and Functional Pattern Recognition

Cited by 5 publications

References 11 publications

Improving OSB wood panel production by vision-based systems for granulometric estimation

Improving OSB wood panel production by vision-based systems for granulometric estimation

A comprehensive review on wood chip moisture content assessment and prediction

Laser Scanner Calibration Dependency On the Line Detection Method

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