Remote automatic selection of suitable frequency intervals for improved leak detection

Constant improvement of leak detection techniques in pipe systems used for liquids transportation is a priority for companies and authorities around the world. If a pipe presents leakage problems, the liquid which is lost generates specific signals which are transmitted in the material of the pipe. Using accelerometers these signals can be recorded and analyzed with the purpose of identifying the location of the leak. An important data analysis tool which helps in the process of leak detection is the Cross Correlation Function (CCF). It is calculated between two simultaneously recorded specific signals with the purpose of time delay estimation (TDE). TDE leads to the identification of the leak position. However, a traditional implementation of the CCF may not be satisfactory. Recorded signals are affected by noise coming from pipe elbows, junctions or traffic. Further improvements are necessary. This paper presents an implementation of an algorithm which improves the quality of the calculated CCF. Being part of a more complex software application, the algorithm is based on the calculation of the coherence function (CF). The application will automatically select two frequency intervals (bands) for filtering the leak signals. After the filtering process, the calculation of the CCF shows an increased quality. The application can be accessed from distance if a remote user needs to study or save the CCF results. No filtering settings are required and the method assures good results.