inverse integration method for distributed sound sources

Most acoustic imaging methods assume the presence of point sound sources and, hence, fail to correctly estimate the sound emissions of distributed sound sources (such as trailing– edge noise). In this contribution, three integration techniques are suggested to overcome this issue based on models considering a single point source, a line source and several line sources, respectively. Two simulated benchmark cases featuring distributed sound sources are used to compare the performance of these integration techniques with respect to other well–known methods. The considered integration methods provide the best performance in retrieving the source levels and require short computational times. In addition, the presence of unwanted noise sources, such as corner sources in wind–tunnel measurements, no longer affects the results negatively when using the last method. A sensitivity analysis shows that the integration technique based on a line source is robust with respect to the choice of the integration area (shape, position and mesh fineness). Practical recommendations are provided for the application of these methods to experimental cases.