Nondestructive evaluation of wooden logs using ground penetrating radar

Halabe, Udaya B.; Agrawal, Sachin; Gopalakrishnan, Bhaskaran

doi:10.1080/10589750802474344

Cited by 30 publications

(9 citation statements)

References 3 publications

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“…Devices tested for RPW detection in date palm, including digital and thermal cameras, TreeRadarUnit™ (TRU) (Radar 2000, Radar 900), resistograph, magnetic DNA biosensor, and NIRS have been used for decades to detect anomalies in plants caused by biotic or abiotic stresses (Halabe et al, 2009, Li et al, 2018, Fracchiolla et al, 2013, Pallav et al, 2009). In the present study, the accuracy of digital and thermal cameras was around 50 to 60%, whereas visual detection was 87%.…”

Section: Resultsmentioning

confidence: 99%

“…This innovative technology is commonly used in arboriculture to observe the internal status of woody plants. Resistographs are reliable devices used to detect decay and cavities in woody trees (Butnor et al, 2009, Halabe et al, 2009, Li et al, 2018). It comprises a micro drill that is introduced horizontally into the trunk and the variation in resistance in the wood is depicted into a graph.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of some non-invasive approaches for the detection of red palm weevil infestation

Rasool

Husain

Salman

et al. 2020

Saudi Journal of Biological Sciences

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Red palm weevil (RPW) causes severe damage to date palm trees, leading to the death of trees if not detected and treated in time. A major obstacle in RPW control is the difficulty in identifying an early stage infestation In the present study, we measured the efficacy of some non-invasive optical devices including cameras (digital camera and thermal camera), TreeRadarUnit™ (TRU) (Radar 2000, Radar 900), resistograph, magnetic DNA biosensor, and Near-infrared Spectroscopy (NIRS) to detect RPW infestation in date palm trees under field conditions at Riyadh, Saudi Arabia. Date palm trees used in these experiments were selected based on visual observations. After inspection of date palm trees with different devices to detect RPW infestation, each tree was taken down and dissected in detail to validate the accuracy of each device. Results indicated that the visual RPW detection approach presented the highest accuracy (87%) followed by Radar 2000 (77%), Radar 900 (73%), resistograph (73%), thermal camera (61%), and digital camera (52%).Moreover, different stages of RPW placed in plastic cups were fastened onto the healthy date palm trunks to judge RPW presence, the magnetic DNA biosensor correctly detected RPW eggs 75% of the time, followed by detection of larvae (64%) and the control (empty cup) (54%). In another experiment where determinations were made in an open area, the efficiency of the DNA biosensor for detecting adults was 100%, followed by 83%, 63%, 60%, and 39% for pupae, larvae, eggs, and control, respectively. Absorption spectra generated through NIRS for infested, wounded, and control samples of date palm tissue showed a remarkable variation in the gradient of the corresponding peaks between 1850 nm and 1950 nm. Based on the detection efficiency of the tested devices, the resistograph and NIRS have the best potential to detect RPW infestation in date palm trees.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of some non-invasive approaches for the detection of red palm weevil infestation

Rasool

Husain

Salman

et al. 2020

Saudi Journal of Biological Sciences

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“…Halabe et al showed that GPR can be used to accurately identify subsurface defects such as knots, decay, and metallic nails inside logs that were not visible from outside observations. Combining the use of dielectric properties and the threshold method, the depth error detected at the sawmill was approximately 10% [22]. Lin et al reported a 17.78-52.61% error in the tree trunk decay area using a two-dimensional stress wave method for detection [23].…”

Section: Introductionmentioning

confidence: 99%

Detecting and Measuring Internal Anomalies in Tree Trunks Using Radar Data for Layer Identification

et al. 2018

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Radar detection has proven to be an effective, nondestructive test for the determination of the quality of wood-based materials, especially in the wooden structures of ancient buildings and trees. However, the results are usually inaccurate, and it is difficult to interpret internal anomalies due to the moisture content of wood, individual differences, and other factors. In this paper, a new measurement method is proposed based on the use of ground-penetrating radar (GPR) for abnormality localization and imaging. Firstly, the time delay of the reflected signal in the inner trees is analyzed with matched filter and Hilbert detections. Secondly, the two approaches are compared with the use of a forward model, and the Hilbert algorithm is found to be more accurate. Thirdly, a laser scanner is used to collect contour data and determine the location and characteristics of internal tree anomalies. Lastly, the proposed method is tested on ancient willows at the Summer Palace. The results show that the error in the depth and area estimates of the anomalies was within 10% and 5%, respectively. Consequently, the GPR method for locating the anomalies in trees is feasible, and a laser scanner combined with contour data can present the size of the abnormal regions within the trees.

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“…The basic steps involved in post-processing were the application of range gain, zero correction and noise filtering [6].…”

Section: Figure 3 the Software Analysis System Of Trees Based On Gprmentioning

confidence: 99%

“…Studies pointed out that these anomalies could be associated the inner discontinuities between the bark and the internal trunk and lower velocities correspond to living trees, while higher velocities are associated with timber [5]. Other studies located the position of internal defects and the algorithm for identifying the defects in wooden logs using GPR [6]; some others showed relations between relative permittivity and moisture content of the different wood samples [7]. In addition, some make evaluation of wood beams in buildings based on GPR [7][8].…”

Section: Introductionmentioning

confidence: 99%

A Method for Layered Identification of Defects in Trees Using Ground Penetrating Radar

Xiao¹,

Wen²,

Gao³

et al. 2017

IJCA

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Nondestructive evaluation of wooden logs using ground penetrating radar

Cited by 30 publications

References 3 publications

Evaluation of some non-invasive approaches for the detection of red palm weevil infestation

Evaluation of some non-invasive approaches for the detection of red palm weevil infestation

Detecting and Measuring Internal Anomalies in Tree Trunks Using Radar Data for Layer Identification

A Method for Layered Identification of Defects in Trees Using Ground Penetrating Radar

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