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| - | Third-party interference is widely documented as being a major cause of damage to buried pipelines. In addition | + | The trial has successfully demonstrated ROSEN’s |
| - | to routine surveillance, maintaining a minimum depth of cover is recognized as a key means of mitigation against | + | methodology to estimate the depth of cover over |
| - | third-party interference. We know that the depth of cover over pipelines can change with time. Current techniques | + | pipelines. This includes producing an accurate |
| - | available for measuring depth of cover on buried pipes require significant effort to produce a high-resolution survey for an entire pipeline. | + | pipeline centreline from data obtained during a |
| - | A UK Innovation project completed for National Grid Gas Transmission has successfully demonstrated a methodology to identify reduced depth of cover over an entire pipeline. This methodology combines ground elevation | + | routine internal inspection, combined with ground |
| - | data with high-resolution inertial measurement unit (IMU) data collected during inline inspection to calculate the | + | elevation data available from the Environment |
| - | pipeline depth of cover. | + | Agency (EA) to calculate depth of cover. |
| - | GPS and pipe depth measurements have been used to verify the accuracy of this method. Using the pipe centerline derived from the IMU data, and ground elevation data collected using light detection and ranging (LiDAR) | + | • The results of the calculation have been validated |
| - | techniques, depth of cover has been calculated to an accuracy of ±0.149 m root mean square error. | + | against infield depth of cover measurements obtained using a pipe and cable locator. The accuracy |
| - | This paper describes the key project steps associated with planning, data collection, data processing, and the validation of results to demonstrate that pipeline depth of cover over an entire pipeline can be accurately determined | + | of the depth of cover results has been calculated |
| + | using a root mean square (RMS) error method. This | ||
| + | has determined an overall accuracy of ±0.15 m using EA LiDAR data. | ||
| + | • Infield ground surface measurements were compared with the EA LiDAR and OS Terrain data. A | ||
