Stig Grundberg

Simulated grading of logs with an X-ray Log Scanner : Grading accuracy compared with manual grading

Today sawmills have started to use automatic methods for log grading. The methods used are either optical or gamma‐ray scanners. However, the signals from these scanners are too coarse for accurate...

Automatic grading of sawlogs: A comparison between X-ray scanning, optical three-dimensional scanning and combinations of both methods

As sawmills become increasingly efficient, the importance of focusing on value recovery becomes obvious. To maximize value recovery, sawmills require the ability to sort logs according to quality. This study compares four different combinations of three-dimensional (3D) and X-ray scanning that can be used to grade logs automatically. The study was based on 135 Scots pine (Pinus sylvestris L.) logs that had been scanned with both a 3D scanner and an X-ray scanner with two X-ray sources. The percentage of boards with correct grade sawn from automatically graded logs varied from 57% when using only 3D scanning to 66% when using a combination of 3D scanning and X-ray scanning in two directions. The highest possible result, with ideal log grading, was 81%. The result also shows that the combination of a 3D scanner and one X-ray direction results in higher accuracy than a scanner based on two X-ray directions.

Measuring the outer shape of Pinus sylvestris saw logs with an x-ray LogScanner

The accuracy of measuring the outer shape of Scots pine (Pinus sylvestris L.) saw logs with an X‐ray LogScanner has been compared with the accuracy of using a 2‐axis optical scanner, a 3‐axis optical scanner and an ideal 3‐D optical scanner. The different scanners were simulated using computed tomography (CT) data from the Swedish Stem Bank. The outer shape of 60 saw logs was measured every third centimeter. The error attributable to bark when using optical scanners was simulated separately. The results from the simulations showed that when measuring the outer shape on bark, the X‐ray LogScanner facilitated measurement of the minimum shadow diameter with the same accuracy as with a 3‐D optical scanner. The results also showed that the potential of combining the X‐ray LogScanner with a 3‐D optical scanner should be investigated.

Automatic grading of Scots pine (Pinus sylvestris L.) sawlogs using an industrial X-ray log scanner

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.

Modelling of adequate pretwist for obtaining straight timber

Abstract Wood in general and wooden studs in particular are often distorted owing to uneven shrinkage during the drying process in the sawmill. Twist is often the most detrimental of all types of distortion, and it is caused by spiral grain in combination with variations in moisture content. For sawmills, the objective is to produce dried, straight boards, and one method of dealing with boards with excessive spiral grain is to sort them out and then dry them in a pretwisted position to obtain straight boards after drying. A model using the finite element (FE) method for the simulation of drying twist distortions was first calibrated against laboratory experiments in which boards were dried with and without restraints and pretwists. After the calibration, the FE results were compared with industrial test results for boards that were dried without restraints or with restraints with zero pretwist, i.e. straight restraints. The FE model used an elastic–ideally plastic material model to obtain permanent deformations. The calibration was to set the yield stresses so that there was a good match between FE results and results from the laboratory experiments. The comparison between the industrial test results and the FE results showed that the FE model is capable of realistic simulations of drying boards with and without restraints and presumably also pretwists.