A processor implemented method , the method comprising: receiving , via a microphone array controlled by one or more hardware processors, a multi-channel acoustic mixed signal, from a plurality of spatially distributed acoustic sources, wherein the multi-channel acoustic mixed signal comprises a plurality of acoustic source signals interfered with each other, received from the plurality of spatially distributed acoustic sources, obtaining , by the one or more hardware processors, a plurality of beamformed source signals, by feeding the multi-channel acoustic mixed signal to a Delay-and-Sum beamforming, DAS-BF; computing , by the one or more hardware processors, a plurality of Mel-spectrograms corresponding to each of the plurality of beamformed source signals; estimating , by the one or more hardware processors, coefficients associated with each of the plurality of spatially distributed acoustic sources, from each of the plurality of Mel-spectrograms and a source specific dictionary learnt for each of the plurality of spatially distributed acoustic sources; estimating , by the one or more hardware processors, a plurality of separated acoustic source signals associated with the plurality of spatially distributed acoustic sources, using the learnt source specific dictionary and the coefficients associated with each of the plurality of spatially distributed acoustic sources; and analyzing , by the one or more hardware processors, the plurality of separated acoustic source signals with a normal machine sound template corresponding to each of the plurality of spatially distributed acoustic sources, using a threshold value, wherein a deviation beyond the threshold value is indicated as an anomaly. receiving , via a microphone array controlled by one or more hardware processors, a multi-channel acoustic mixed signal, from a plurality of spatially distributed acoustic sources, wherein the multi-channel acoustic mixed signal comprises a plurality of acoustic source signals interfered with each other, received from the plurality of spatially distributed acoustic sources, obtaining , by the one or more hardware processors, a plurality of beamformed source signals, by feeding the multi-channel acoustic mixed signal to a Delay-and-Sum beamforming, DAS-BF; computing , by the one or more hardware processors, a plurality of Mel-spectrograms corresponding to each of the plurality of beamformed source signals; estimating , by the one or more hardware processors, coefficients associated with each of the plurality of spatially distributed acoustic sources, from each of the plurality of Mel-spectrograms and a source specific dictionary learnt for each of the plurality of spatially distributed acoustic sources; estimating , by the one or more hardware processors, a plurality of separated acoustic source signals associated with the plurality of spatially distributed acoustic sources, using the learnt source specific dictionary and the coefficients associated with each of the plurality of spatially distributed acoustic sources; and analyzing , by the one or more hardware processors, the plurality of separated acoustic source signals with a normal machine sound template corresponding to each of the plurality of spatially distributed acoustic sources, using a threshold value, wherein a deviation beyond the threshold value is indicated as an anomaly. <EOS>