The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Johan Oja - One of the best experts on this subject based on the ideXlab platform.
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Sapwood Moisture Content Measurements in Scots Pine Sawlogs Combining X-ray and 3D Scanning
2010Co-Authors: Johan Skog, Tommy Vikberg, Johan OjaAbstract:Wood industry of today deals with large volumes in an almost automatic process, which is not fully adapted to the variability of the raw material. Consequently, it is crucial to sort the wood according to material properties in order to process the wood efficiently and to obtain high quality end products. One material property which could be used for sorting is the moisture content of the sapwood, an important parameter for both the processing and the end products. Most large Swedish sawmills are using 3D scanners for quality sorting of Scots pine (Pinus sylvestris L.) Sawlogs based on outer shape. Recently, some sawmills have also invested in X-ray log scanners in order to sort the Sawlogs based on inner properties. It has previously been shown that, by combining raw data from industrial 3D and X-ray log scanners using path length compensation, green sapwood density and dry heartwood density can be estimated. In this study, the dry heartwood density was used to find an estimate of the dry sapwood density, thus allowing the calculation of the sapwood moisture content. The log scanner data used in this study was simulated from 560 Scots pine Sawlogs which had previously been scanned in a computed tomography (CT) scanner. The estimated sapwood moisture contents were then compared to reference values calculated by drying samples to 9% moisture content. It was found that the moisture content estimate could be used to separate the logs into two groups with high and low moisture content, correctly identifying all logs with very low moisture content as dry logs. Out of all logs, 70% were correctly classified. The moisture content estimate could also be compared to the dry density dependent maximum moisture content and used to identify logs that have actually started to dry.
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Sapwood moisture-content measurements in Pinus sylvestris Sawlogs combining X-ray and three-dimensional scanning
Wood Material Science and Engineering, 2010Co-Authors: Johan Skog, Tommy Vikberg, Johan OjaAbstract:Abstract Because today's sawmill processes are not fully adapted to the variability of the raw material, it is crucial to sort Sawlogs according to material properties in order to process the wood efficiently and to obtain high-quality end-products. One material property that could be used for sorting is the moisture content (MC) of the sapwood, an important parameter for both the processing and the end-products. Most sawmills use three-dimensional (3D) scanners to sort logs and some have also invested in X-ray scanners. Previous studies have shown that, by combining raw data from 3D and X-ray log scanners, green sapwood density and dry heartwood density in Scots pine Sawlogs can be estimated. In this study, the method was used to estimate sapwood MC in green logs. It was found that the MC estimate could be used to separate the logs into groups with high and low MC, correctly classifying all logs with MC below 100% as low MC logs. Out of all logs, 70% were correctly classified. The MC estimate could also ...
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Combining X-ray and three-dimensional scanning of Sawlogs— Comparison between one and two X-ray directions
2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis, 2009Co-Authors: Johan Skog, Johan OjaAbstract:In many sawmills, presorting of Sawlogs is based on data from optical three-dimensional (3D) scanners. The use of X-ray log scanners is also becoming increasingly common and most sawmills installing an X-ray scanner already have a 3D scanner present.
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Automatic grading of Sawlogs : industrial experiences from x-ray scanning and optical 3D scanning
2003Co-Authors: Johan Oja, Johan Fredriksson, Stig Grundberg, Per E O BergAbstract:Automatic grading of Sawlogs : industrial experiences from x-ray scanning and optical 3D scanning
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Automatic grading of Scots pine (Pinus sylvestris L.) Sawlogs using an industrial X-ray log scanner
Computers and Electronics in Agriculture, 2003Co-Authors: Johan Oja, Stig Grundberg, Lars Wallbäcks, Erik Hägerdal, Anders GrönlundAbstract:Abstract The successful running of a sawmill is dependent on its ability to achieve the highest possible value recovery from the Sawlogs, i.e. to optimize the use of the raw material. Such optimization requires information about the properties of every log. One method of measuring these properties is to use an X-ray log scanner. The objective of the present study was to determine the accuracy when grading Scots pine ( Pinus sylvestris L.) Sawlogs using an industrial scanner known as the X-ray LogScanner. The study was based on 150 Scots pine Sawlogs from a sawmill in northern Sweden. All logs were scanned in the LogScanner at a speed of 125 m/min. The X-ray images were analyzed on-line with measures of different properties as a result (e.g. density and density variations). The logs were then sawn with a normal sawing pattern (50×125 mm) and the logs were graded depending on the result from the manual grading of the center boards. Finally, partial least squares (PLS) regression was used to calibrate statistical models that predict the log grade based on the properties measured by the X-ray LogScanner. The study showed that 77–83% of the logs were correctly sorted when using the scanner to sort logs into three groups according to the predicted grade of the center boards. After sawing the sorted logs, 67% of the boards had the correct grade. When scanning the same logs repeatedly, the relative standard deviation of the predicted grade was 12–20%. The study also showed that it is possible to sort out 10 and 16%, respectively, of the material into two groups with high quality logs, without changing the grade distribution of the rest of the material to any great extent.
Kangas Jyrki - One of the best experts on this subject based on the ideXlab platform.
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The use of airborne laser scanning to estimate sawlog volumes
Forestry, 2008Co-Authors: Korhonen Lauri, Peuhkurinen Jussi, Malinen Jukka, Suvanto Aki, Maltamo Matti, Packalen Petteri, Kangas JyrkiAbstract:Summary This study of estimation of the sawlog volume of clear-cut stands from airborne laser scanning data considers both theoretical and factual recoveries. Theoretical sawlog volume estimates for the trees were calculated with a taper curve and factual estimates were obtained by multiplying the result by a model-based sawlog reduction factor, to allow for defects. Dominant tree species-specifi c models for the estimation of sawlog volumes per hectare were constructed with laser-based canopy height metrics as independent variables. The models were tested with the use of independently collected test data that consisted of 14 harvester-measured forest stands. Test data included information on the tapering of the stems and the volumes of the actually harvested assortments. The results indicate that the direct laser models are capable of producing satisfactory estimates for both the theoretical and the factual sawlog volumes of a clear-cut stand, with root mean squared errors of 9.1 and 18.0 per cent in the test data, respectively. In conclusion, the method presented here is quite suitable for pre-harvest estimation of sawlog volume, even though in cases where unpredictable defects (e.g. decay as a result of disease) exist the sawlog recoveries may be signifi cantly overestimated.
Johan Skog - One of the best experts on this subject based on the ideXlab platform.
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Sapwood Moisture Content Measurements in Scots Pine Sawlogs Combining X-ray and 3D Scanning
2010Co-Authors: Johan Skog, Tommy Vikberg, Johan OjaAbstract:Wood industry of today deals with large volumes in an almost automatic process, which is not fully adapted to the variability of the raw material. Consequently, it is crucial to sort the wood according to material properties in order to process the wood efficiently and to obtain high quality end products. One material property which could be used for sorting is the moisture content of the sapwood, an important parameter for both the processing and the end products. Most large Swedish sawmills are using 3D scanners for quality sorting of Scots pine (Pinus sylvestris L.) Sawlogs based on outer shape. Recently, some sawmills have also invested in X-ray log scanners in order to sort the Sawlogs based on inner properties. It has previously been shown that, by combining raw data from industrial 3D and X-ray log scanners using path length compensation, green sapwood density and dry heartwood density can be estimated. In this study, the dry heartwood density was used to find an estimate of the dry sapwood density, thus allowing the calculation of the sapwood moisture content. The log scanner data used in this study was simulated from 560 Scots pine Sawlogs which had previously been scanned in a computed tomography (CT) scanner. The estimated sapwood moisture contents were then compared to reference values calculated by drying samples to 9% moisture content. It was found that the moisture content estimate could be used to separate the logs into two groups with high and low moisture content, correctly identifying all logs with very low moisture content as dry logs. Out of all logs, 70% were correctly classified. The moisture content estimate could also be compared to the dry density dependent maximum moisture content and used to identify logs that have actually started to dry.
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Sapwood moisture-content measurements in Pinus sylvestris Sawlogs combining X-ray and three-dimensional scanning
Wood Material Science and Engineering, 2010Co-Authors: Johan Skog, Tommy Vikberg, Johan OjaAbstract:Abstract Because today's sawmill processes are not fully adapted to the variability of the raw material, it is crucial to sort Sawlogs according to material properties in order to process the wood efficiently and to obtain high-quality end-products. One material property that could be used for sorting is the moisture content (MC) of the sapwood, an important parameter for both the processing and the end-products. Most sawmills use three-dimensional (3D) scanners to sort logs and some have also invested in X-ray scanners. Previous studies have shown that, by combining raw data from 3D and X-ray log scanners, green sapwood density and dry heartwood density in Scots pine Sawlogs can be estimated. In this study, the method was used to estimate sapwood MC in green logs. It was found that the MC estimate could be used to separate the logs into groups with high and low MC, correctly classifying all logs with MC below 100% as low MC logs. Out of all logs, 70% were correctly classified. The MC estimate could also ...
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Combining X-ray and 3D scanning of logs
2009Co-Authors: Johan SkogAbstract:In Scandinavia, Sawlogs are typically sorted upon arrival at the sawmill. Presorting of Sawlogs according to dimension, e.g., using an optical three-dimensional (3D) scanner, is used to make the sa ...
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Combining X-ray and three-dimensional scanning of Sawlogs— Comparison between one and two X-ray directions
2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis, 2009Co-Authors: Johan Skog, Johan OjaAbstract:In many sawmills, presorting of Sawlogs is based on data from optical three-dimensional (3D) scanners. The use of X-ray log scanners is also becoming increasingly common and most sawmills installing an X-ray scanner already have a 3D scanner present.
Tommy Vikberg - One of the best experts on this subject based on the ideXlab platform.
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Sapwood Moisture Content Measurements in Scots Pine Sawlogs Combining X-ray and 3D Scanning
2010Co-Authors: Johan Skog, Tommy Vikberg, Johan OjaAbstract:Wood industry of today deals with large volumes in an almost automatic process, which is not fully adapted to the variability of the raw material. Consequently, it is crucial to sort the wood according to material properties in order to process the wood efficiently and to obtain high quality end products. One material property which could be used for sorting is the moisture content of the sapwood, an important parameter for both the processing and the end products. Most large Swedish sawmills are using 3D scanners for quality sorting of Scots pine (Pinus sylvestris L.) Sawlogs based on outer shape. Recently, some sawmills have also invested in X-ray log scanners in order to sort the Sawlogs based on inner properties. It has previously been shown that, by combining raw data from industrial 3D and X-ray log scanners using path length compensation, green sapwood density and dry heartwood density can be estimated. In this study, the dry heartwood density was used to find an estimate of the dry sapwood density, thus allowing the calculation of the sapwood moisture content. The log scanner data used in this study was simulated from 560 Scots pine Sawlogs which had previously been scanned in a computed tomography (CT) scanner. The estimated sapwood moisture contents were then compared to reference values calculated by drying samples to 9% moisture content. It was found that the moisture content estimate could be used to separate the logs into two groups with high and low moisture content, correctly identifying all logs with very low moisture content as dry logs. Out of all logs, 70% were correctly classified. The moisture content estimate could also be compared to the dry density dependent maximum moisture content and used to identify logs that have actually started to dry.
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Sapwood moisture-content measurements in Pinus sylvestris Sawlogs combining X-ray and three-dimensional scanning
Wood Material Science and Engineering, 2010Co-Authors: Johan Skog, Tommy Vikberg, Johan OjaAbstract:Abstract Because today's sawmill processes are not fully adapted to the variability of the raw material, it is crucial to sort Sawlogs according to material properties in order to process the wood efficiently and to obtain high-quality end-products. One material property that could be used for sorting is the moisture content (MC) of the sapwood, an important parameter for both the processing and the end-products. Most sawmills use three-dimensional (3D) scanners to sort logs and some have also invested in X-ray scanners. Previous studies have shown that, by combining raw data from 3D and X-ray log scanners, green sapwood density and dry heartwood density in Scots pine Sawlogs can be estimated. In this study, the method was used to estimate sapwood MC in green logs. It was found that the MC estimate could be used to separate the logs into groups with high and low MC, correctly classifying all logs with MC below 100% as low MC logs. Out of all logs, 70% were correctly classified. The MC estimate could also ...
Korhonen Lauri - One of the best experts on this subject based on the ideXlab platform.
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The use of airborne laser scanning to estimate sawlog volumes
Forestry, 2008Co-Authors: Korhonen Lauri, Peuhkurinen Jussi, Malinen Jukka, Suvanto Aki, Maltamo Matti, Packalen Petteri, Kangas JyrkiAbstract:Summary This study of estimation of the sawlog volume of clear-cut stands from airborne laser scanning data considers both theoretical and factual recoveries. Theoretical sawlog volume estimates for the trees were calculated with a taper curve and factual estimates were obtained by multiplying the result by a model-based sawlog reduction factor, to allow for defects. Dominant tree species-specifi c models for the estimation of sawlog volumes per hectare were constructed with laser-based canopy height metrics as independent variables. The models were tested with the use of independently collected test data that consisted of 14 harvester-measured forest stands. Test data included information on the tapering of the stems and the volumes of the actually harvested assortments. The results indicate that the direct laser models are capable of producing satisfactory estimates for both the theoretical and the factual sawlog volumes of a clear-cut stand, with root mean squared errors of 9.1 and 18.0 per cent in the test data, respectively. In conclusion, the method presented here is quite suitable for pre-harvest estimation of sawlog volume, even though in cases where unpredictable defects (e.g. decay as a result of disease) exist the sawlog recoveries may be signifi cantly overestimated.
