Detection of Pipeline Deformation Induced by Frost Heave Using OFDR Technology

Oil and gas pipelines are critical structures. For pipelines in the seasonal frozen soil area, frost heave of the ground will result in deformation of the pipeline. If the deformation continually increases, it will seriously threaten the pipeline safety. Therefore, it is important to monitor the deformation of the pipeline in the frozen soil area. Since optic frequency–domain reflectometer (OFDR) technology has many advantages in distributed strain measurement, this paper utilized the OFDR technology to measure the distributed strain and use the plane curve reconstruction algorithm to calculate the deformed pipeline shape. To verify the feasibility of this approach, a test was conducted to simulate the pipeline deformation induced by frost heave. Test results showed that the pipeline shape can be reconstructed well via the combination of the OFDR and curve reconstruction algorithm, providing a valuable approach for pipeline deformation monitoring.

Hermite Interpolation Based Interval Shannon-Cosine Wavelet and Its Application in Sparse Representation of Curve

Using the wavelet transform defined in the infinite domain to process the signal defined in finite interval, the wavelet transform coefficients at the boundary are usually very large. It will bring severe boundary effect, which reduces the calculation accuracy. The construction of interval wavelet is the most common method to reduce the boundary effect. By studying the properties of Shannon-Cosine interpolation wavelet, an improved version of the wavelet function is proposed, and the corresponding interval interpolation wavelet based on Hermite interpolation extension and variational principle is designed, which possesses almost all of the excellent properties such as interpolation, smoothness, compact support and normalization. Then, the multi-scale interpolation operator is constructed, which can be applied to select the sparse feature points and reconstruct signal based on these sparse points adaptively. To validate the effectiveness of the proposed method, we compare the proposed method with Shannon-Cosine interpolation wavelet method, Akima method, Bezier method and cubic spline method by taking infinitesimal derivable function cos(x) and irregular piecewise function as an example. In the reconstruction of cos(x) and piecewise function, the proposed method reduces the boundary effect at the endpoints. When the interpolation points are the same, the maximum error, average absolute error, mean square error and running time are 1.20 × 10−4, 2.52 × 10−3, 2.76 × 10−5, 1.68 × 10−2 and 4.02 × 10−3, 4.94 × 10−4, 1.11 × 10−3, 9.27 × 10−3, respectively. The four indicators mentioned above are all lower than the other three methods. When reconstructing an infinitely derivable function, the curve reconstructed by our method is smoother, and it satisfies C2 and G2 continuity. Therefore, the proposed method can better realize the reconstruction of smooth curves, improve the reconstruction efficiency and provide new ideas to the curve reconstruction method.