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Acoustic emission analysis (everything you need to know)

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Acoustic emission analysis (also known as sonic analysis) emerged in 1970 as a monitorização do estado technique. It makes use of sensors placed on the asset (called structure-borne analysis) or very near it (airborne analysis). These sensors detect transient elastic waves generated by the processes associated with wear and tear, such as friction, crushing and cracking. Though these processes may produce audible sounds, the AE method usually measures frequencies above the range of normal human hearing (a.k.a. ultrasonic).

Acoustic airborne sensors are essentially microphones, where sound waves in the air physically move a thin diaphragm (often made of plastic), which in turn moves a metal coil back and forth across a magnet, producing an electric current. They are notoriously sensitive to background noise and to anything standing in the path between the sensor and the object being monitored.

Acoustic structure-borne sensors often use piezoelectric accelerometers: devices that convert the mechanical force caused by a change in motion into a proportional electrical charge (Piezo comes from the Greek word meaning “to squeeze.”). Piezoelectric devices are most sensitive in a frequency range determined by the properties of the material used (commonly quartz or a synthetic ceramic). Their location and orientation on the machine also affect what they can detect, and how well. There’s also a tradeoff between the amplitude an accelerometer can measure and its sensitivity. Accelerometers can be thrown off by noise from the surrounding environment. These four points make it important to carefully assess the characteristics of both the asset and its surrounding environment in selecting and installing acoustic sensors.



How does acoustic analysis perform when it comes to fault detection?

Below is a P-F curve demonstrating how acoustic analysis compares to other técnicas de controlo do estado when it comes to fault detection in advance of an asset breakdown. This is a P-F curve for bearing failure in a specific production system.

For more information on the accuracy of acoustic analysis in comparison to other condition monitoring techniques, download the guia de comparação de monitorização de condições.

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Uma amostra da curva P-F para a falha de rolamentos num sistema de produção específico. As localizações das várias tecnologias na curva serão diferentes para cada peça de equipamento, ambiente de produção e modo de falha, por isso certifique-se de que a calcula para os activos e tipos de degradação específicos que pretende monitorizar.

Using acoustic analysis for fault detection: general rules of thumb

Every production system is different, meaning there’s no one-size-fits-all condition monitoring technology. However, we can state some general rules of thumb when it comes to areas where acoustic analysis is strong or weak in fault detection.

Forte no controlo:

  • um motor que acciona muitos activos
  • fugas
  • defeitos mecânicos
  • defeitos eléctricos
  • corrente contínua (DC)
  • máquinas rotativas
  • máquinas de rotação muito lenta

Fraco (ou não possível) no controlo:

  • activos remotos ou inacessíveis
  • activos localizados em zonas ATEX ou noutras condições adversas
  • activos localizados em ambientes ruidosos ou com vibrações
  • conhecimentos sobre energia

Compare acoustic analysis and other condition monitoring techniques

Download the condition monitoring comparison guide for a full comparison of acoustic analysis and other major techniques.

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