Measurements of Low Frequency Vibration in Subsea Piping Using ROV Video Analysis
Bibliographic record
Abstract
Abstract Vibrations in Subsea Production Systems are well recognized as a concern in the subsea industry. To identify the severity of the vibrations and potential accumulated fatigue damage, subsea vibrations need to be measured with great accuracy. Currently, accurate detection and subsea measurements are often performed by utilizing accelerometers, which have to be connected to the structure by ROV or a diver. ROV video analysis provides an alternative solution. Video analyses are widely utilized across different applications. With the increased quality of a HD camera on ROV, the accessibility of such measurements is an attractive substitute to other techniques. As a part of on-shore mechanical testing on a full assembled XT in St John’s Canada, a flowloop on a water injection XT was subjected to free vibrations. The vibrations were filmed using a commercial HD camera placed on a tripod. This test was done to validate data generated using video processing in which pipe vibration of an operating subsea XT was filmed using an ROV camera. A study that aimed to quantify the video processing accuracy, limitations and provide general guidance was conducted. For the onshore test filmed with a tripod the results of video analyses were compared with the measurements obtained by means of accelerometers. For the video of an operating subsea XT filmed by an ROV, the obtained vibration frequency and direction was compared with the free mechanical vibration obtained by a FEM model. The results obtained by means of the video analysis matched well with the accelerometer data. A high accuracy was reached, as vibration displacements as low as 20% of the pixel were accurately determined in the video analysis. With respect to detection frequencies, the upper cut-off frequency was around 15 Hz determined by the video framerate. The video analysis utilizing ROV videos was found to be applicable for low frequency vibration measurements, opening the opportunity for easier and more cost effective vibration detection and monitoring. The method is also reliable for subsea application in which the camera is placed on an ROV and is thus not affected by ROV movements, subsea lighting condition and moving ocean debris.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".