What Is Acoustic Monitoring?

Sound consists of pressure waves traveling through a medium, usually air or water. Sound waves are a type of acoustic wave, typically described by their frequency or pitch (measured in hertz, or Hz) and amplitude or loudness (measured in decibels, or dB). These characteristics help quantify the behavior and intensity of sound in monitoring applications. Monitoring with acoustic sensors and analyzing the sounds that equipment produces can flag unexpected sonic characteristics for human review. 

^{Figure 1: Acoustic sensor}

Several types of sensors are commonly used in acoustic monitoring.

Microphones—These are the most common sensors used in acoustic monitoring, directly capturing airborne sound waves. Depending on the sound conditions, diaphragm or microelectromechanical systems (MEMS) microphones and ultrasonic microphones may be better suited to acoustic monitoring. Microphone arrays can be installed on or around equipment to monitor sound, where the phase can be used to pinpoint noise sources.

Accelerometers—While primarily used for vibration monitoring, accelerometers can supplement microphones to measure structure-borne sounds that travel through solid objects such as equipment casings or walls.

Hydrophones—Hydrophones are engineered to capture underwater sound pressure signals. Their corrosion-resistant design makes them ideal for industrial and scientific applications, including underwater testing, monitoring, and measurements.

^{Figure 2: Principles of Acoustic Monitoring}

Most machinery and industrial processes produce a consistent sound signature when operating correctly. Deviations from this baseline signature can signal developing faults or failures. Acoustic monitoring systems typically involve sensors, flexible data acquisition (DAQ) hardware platforms, and specialized analysis software to capture, convert, digitize, and analyze sound signals for unusual characteristics. Based on the analysis, maintenance can be scheduled, components can be repaired, or processes can be adjusted before significant problems arise.

Acoustic monitoring enables predictive maintenance that can prevent expensive repairs while extending equipment life and improving safety. Common data collection setups include the following types of systems.

Wired systems—Sensors are connected via wires or cables to a DAQ device and computer, offering high reliability and real-time data transmission. There are some disadvantages: Wired setups may be difficult to install, and cables are vulnerable to damage. It may be difficult to wire a system that is distributed over a very large area.

Wireless systems—Sensors transmit data wirelessly, allowing easy placement in difficult locations. However, wireless setups require considerations of battery life, signal transmission range, and information security.

Continuous (online) monitoring—Both wired and wireless methods typically provide continuous or frequent data for a real-time view of acoustic conditions. Continuous monitoring provides more real-time data but when failures gradually over long periods of time, it may not be necessary to capture this much data.

Periodic (offline) checks—A technician uses a portable instrument to measure sound levels periodically, offering flexibility but only providing snapshots in time. Periodic checks may not catch instantaneous events but work well to identify long-term trends. 

Acoustic monitoring focuses on capturing and analyzing audible noise and low-frequency sound waves, while ultrasonic monitoring targets high-frequency sound waves beyond the range of human hearing. Ultrasonic monitoring techniques are typically used to transmit signals through a material and detect changes caused by internal defects or structural breaks and often employed in materials inspection to check for internal flaws rather than active condition monitoring.

Acoustic data analysis involves reviewing and interpreting sound information, often using software like NI LabVIEW for building custom analysis applications. Here are some key techniques for analyzing acoustic data.

Frequency spectrum analysis—Uses techniques like the fast Fourier transform (FFT) to break down sounds into constituent frequencies, helping identify specific fault types.

Time-frequency analysis—Methods like wavelet analyses examine how frequency changes over time, useful for transient sounds.

Order analysis—Order analysis is used to analyze changes in harmonic values related to rotational machinery. This is especially useful when monitoring engines or motors for changes in how the systems works by correlating the noise in the system to the motor speed.

Pattern recognition and AI—Machine learning algorithms increasingly automate anomaly detection and classification of sounds linked to known issues. Identified issues can be flagged for review or trigger automated actions like alarms or shutdowns if critical thresholds are met or exceeded. The challenge in using AI for acoustic monitoring is training the AI model with enough data, including failures, for the AI model to know what to look for. 

Acoustic monitoring is used on a range of equipment, components and processes:

• Rotating machinery
• Bearings
• Motors
• Pumps
• Valves
• Hydraulic systems
• Gears
• Compressors
• Pipelines
• Electrical systems

Acoustic monitoring can identify the following types of potential equipment and component issues:

• Bearing wear or damage
• Gear wear
• Misalignment
• Overheating
• Blockages
• Cracks
• Leaks
• Over- or under-lubrication (ultrasonic)
• Electrical anomalies

Acoustic monitoring can offer significant benefits:

• Early fault detection to prevent major failures and downtime
• Cost savings from predictive maintenance and finding energy-wasting leaks
• Enhanced safety by detecting hazardous conditions
• Improved quality through acoustic signature verification
• Process optimization through insights from sound analysis

Acoustic measurements are critical during product design, validation, and test. Engineers perform acoustic analysis, often automating test sequences with tools like NI TestStand, to perform noise, vibration, and harshness (NVH) testing to meet noise emission standards or identify and mitigate sources of unwanted or excessive noise. Engineers can also verify the acoustic performance of components and detect flaws during development and durability testing.

NI provides a robust platform for sophisticated acoustic monitoring and analysis. NI CompactDAQ, NI PXI, and NI CompactRIO hardware interface directly with microphones and accelerometers. Our sound and vibration input modules offer features for accurate acoustic measurements, including signal conditioning, filtering, high dynamic range, and adherence to dynamic signal acquisition fundamentals.

We also offer powerful software tools like the NI LabVIEW graphical programming environment for custom system development and analysis. Configuration-based software like NI FlexLogger™ simplifies data logging, while NI DIAdem provides advanced capabilities for managing, analyzing, and reporting large datasets. Together, NI hardware and software enable customized acoustic monitoring solutions, turning sound data into actionable insights.

NI solutions for acoustic monitoring offer several advantages over other approaches:

• Our long history of measurements in many applications means that the measurements you take with NI equipment are higher quality than hardware designed specifically for condition monitoring. NI products are more accurate, with more stable timing, and more reliable measurements.
• NI platforms are built on a concept of modularity, so systems are more efficient to design and easier to maintain over the lifetime of the application. Unlike fixed-personality systems, you can easily expand systems by adding modules to gain new channels or measurements.
• NI high-speed systems can capture all of the data, not just periodic bursts. This means you can record events that other systems miss.