New methodology for NDT assessment of in-service wood poles
Bibliographic record
Abstract
Wood poles are extensively used in North America to support electrical lines and their service life is usually between 35 and 50 years. Nevertheless, factors such as temperature, moisture, bacteria or fungi may induce internal decay in the poles. The existence of decayed areas result in a reduction of the strength of a pole and sudden failures may occur. To ensure the reliability of the electrical network, the condition of the poles is assessed in maintenance programs usually through visual and sounding inspection. These methods have the disadvantage that they are subjective, they provide a local evaluation of the condition, and are unable of detecting early decay. This paper summarizes the results of a research project that included the development of a new methodology to assess the condition of wood poles based on ultrasonic waves, the construction and calibration of the testing device, numerical modeling of wave propagation in wood, laboratory and field tests. Methods based on changes of wave velocity have been used before for the evaluation of wood. However, these methods have not taken into account that wood presents different elastic properties in the longitudinal, radial and tangential directions. To perform a reliable evaluation using ultrasonic waves, it is essential to consider the variability of stiffness and mass density, as well as the effect of moisture content and temperature on wave parameters. The proposed methodology considers wood as an orthotropic material, takes into account the variability in the elastic and mechanical properties, and the effect of temperature and moisture content in these properties. The methodology uses two statistical indices: the overall dissimilarity index (ODI) and the condition rating index (CRI). ODI describes the overall condition of a pole in terms of ultrasonic measurements and estimates the deviation with respect to the expected values for a sound pole. Laboratory destructive testing was performed to correlate the CRI with the expected remaining strength ratio; which is used to determine the end of-life (EOL) of an in-service wood pole. The method has the advantage that is nonintrusive, provides quantitative measurements of the internal condition of wood poles and allows detecting early decay in wood poles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".