Abstract
Paper pulp mill chemical recovery boiler steam piping is monitored for leaks by an acoustic leak detection system responsive to atmospherically carried sound transmissions. Energy level amplitudes of respective analog electrical signals generated by a multiplicity of microphones are digitized in a rapid time sequence. Such digital values are temporarily stored in a data memory bank to be subsequently processed by a Fast-Fourier Transform analysis into amplitude vs. frequency domain data. Such amplitude vs. frequency data respective to each microphone is further refined for comparison to historical threshold data for a probability determination of a leak status.
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