Of course, such a radical departure from the norm was initially met with a fair degree of scepticism along the lines of ‘It can’t be that easy otherwise why would people use Vibration?’ A fair point in its time! The only answer was to relentlessly demonstrate instant fault detection on the shop floors of those who were interested but doubtful. A not untypical example of readings from such a demonstration is shown below for one-off measurements taken with a portable AE based CM instrument (MHC type) on the various white metal bearings of a generating set in a power station. (Note: for this instrument the common interpretation for all types of machines, bearings and rotational speeds down to 35 rpm is that an item is suspect if Distress® is 10 or more.)
Prior to these measurements being taken, the client believed that the main exciter was as good as new! However upon seeing the readings the client explained that the exciter had previously shown problems of arcing in the bearings and the resulting surface damage had been blended out prior to the bearing being returned to service.
The high SNR which AE signals enjoy has other consequence too, as will now be described:
HP Rotor DE
HP Rotor NDE
IP Rotor DE
IP Rotor NDE
LP1 Rotor DE
LP1 Rotor NDE
LP2 Rotor DE
LP2 Rotor NDE
Generator Rotor DE
Generator Rotor NDE
Very slowly rotating machinery
At slow rotational speeds the rate at which AE signals are generated reduces, even becoming infrequent at the lowest speeds. However, this does not necessarily pose a problem provided signals are processed accordingly since AE sensors are insensitive to the low frequency sounds and vibrations which are ever present on the shop floor. Commercially available AE instrumentation is able to easily monitor down to 0.25 rpm without requiring special expertise.
Non-repetitive or random fault types
Because AE signals can be simply analysed directly in the time domain, without recourse to frequency analysis, they are equally sensitive to non-repetitive signals. One example of this has been the detection of carbonisation of oil in a high temperature white metal bearing where the small particles of carbon were crushed in the bearing as they randomly formed. Another example has been the detection of sporadic air bubbles in the oil flowing through a plain bearing.
It is normal to get load reversals, valve openings/closures, sliding actions and gas transfers during the operation of reciprocating machinery and each of these has an associated AE signature. A full interpretation of the AE signal requires knowledge of the timing sequence of all these actions but it can also be useful to simply observe occasional or persistent variations from the norm. This is illustrated in the Figure below which shows the maximum, minimum and mean values of the AE envelope signal as a function of time within the cycle of a diesel engine over 12 successive engine cycles. Comparison of the minimum and mean waveforms clearly indicates an occasional drop out of part of the operating process (thought to be due to a sticking valve) which is only detectable because of the high SNR of AE signals – a low SNR would have required averaging to reveal the waveform in the first place thus masking exceptional occurrences.