A method for detecting a structural anomaly in a pipeline supply network, the pipeline supply network configured to supply fluid to multiple receiving locations, comprising: receiving acoustic signal data from a selected location in the pipeline supply network; generating a first time window of acoustic signal data based on the acoustic signal data; benchmarking the first time window of acoustic signal data with respect to historical background acoustic signal data characterising the pipeline supply network to generate a corresponding background benchmarked first time window of acoustic signal data, wherein benchmarking the first time window of acoustic signal data with respect to historical background acoustic signal data characterising the pipeline supply network includes: determining an estimated spectral content difference between the first time window of acoustic signal data and the historical background acoustic signal data, wherein determining an estimated spectral content difference between the first time window and the background acoustic signal data includes: determining the spectral content of the historical background acoustic signal data; determining the spectral content of the first time window of acoustic signal data; and determining in frequency space the difference between the spectral content of the background acoustic signal data and the spectral content of the first time window of acoustic signal data; and removing the spectral content difference from the first time window of acoustic signal data to generate the corresponding background benchmarked first time window of acoustic signal data; and determining an anomaly measure for the background benchmarked first time window of acoustic signal data, wherein the anomaly measure indicates a presence of the structural anomaly. receiving acoustic signal data from a selected location in the pipeline supply network; generating a first time window of acoustic signal data based on the acoustic signal data; benchmarking the first time window of acoustic signal data with respect to historical background acoustic signal data characterising the pipeline supply network to generate a corresponding background benchmarked first time window of acoustic signal data, wherein benchmarking the first time window of acoustic signal data with respect to historical background acoustic signal data characterising the pipeline supply network includes: determining an estimated spectral content difference between the first time window of acoustic signal data and the historical background acoustic signal data, wherein determining an estimated spectral content difference between the first time window and the background acoustic signal data includes: determining the spectral content of the historical background acoustic signal data; determining the spectral content of the first time window of acoustic signal data; and determining in frequency space the difference between the spectral content of the background acoustic signal data and the spectral content of the first time window of acoustic signal data; and removing the spectral content difference from the first time window of acoustic signal data to generate the corresponding background benchmarked first time window of acoustic signal data; and determining an estimated spectral content difference between the first time window of acoustic signal data and the historical background acoustic signal data, wherein determining an estimated spectral content difference between the first time window and the background acoustic signal data includes: determining the spectral content of the historical background acoustic signal data; determining the spectral content of the first time window of acoustic signal data; and determining in frequency space the difference between the spectral content of the background acoustic signal data and the spectral content of the first time window of acoustic signal data; and determining the spectral content of the historical background acoustic signal data; determining the spectral content of the first time window of acoustic signal data; and determining in frequency space the difference between the spectral content of the background acoustic signal data and the spectral content of the first time window of acoustic signal data; and removing the spectral content difference from the first time window of acoustic signal data to generate the corresponding background benchmarked first time window of acoustic signal data; and determining an anomaly measure for the background benchmarked first time window of acoustic signal data, wherein the anomaly measure indicates a presence of the structural anomaly.