Tunnel - Acoustic Emission (AE)

Target of Investigation

Acoustic emission (AE) technology is typically used to monitor existing cracks or detect cracks that are developing at a particular location in a steel structural member. AE technology can also be applied to monitor a retrofit that is intended to arrest cracks or stop new fatigue cracks from developing. AE has been used to assess deterioration of steel, such as in detecting and locating fatigue cracks in bridges and tunnels. (1-4)


AE is a nondestructive evaluation (NDE) technique developed for detecting, locating, and monitoring fatigue cracks in steel elements. AE technology is implemented by mounting one or more acoustic sensors on the surface of the material being tested to detect transient elastic stress waves produced by the evolution of damage in the material. Transient elastic stress waves could be produced, for example, when a crack increases in length because of the application of load. These waves spread through the material and are detected by the acoustic sensors. The waveform signals that the acoustic sensors detect are analyzed to determine the rate at which AE signals produced from damage evolution occur. This analysis helps locate the damage and estimate the rate at which the damage will progress. 

The progression of damage, such as the increase in the length of a fatigue crack, produces AE signals. Loading is a likely cause of damage progression. An AE system monitors a structure over time for crack growth caused by applied loads. If a fatigue crack is not increasing in length, AE signals are generally not produced. Consequently, AE is not an effective method for detecting arrested cracks or other damage not progressing under load application. The position of the AE source can be found by triangulating based on the arrival time of the acoustic waves and the wave velocity in the material. 

Figure 1 shows AE sensors mounted on a steel girder to detect the development of cracks in the weld between the web and diaphragm. 

Source: FHWA.
Figure 1. Photo. AE sensors mounted on a steel girder.

Physical Principle 

AE is defined as the rapid release of energy in the form of a transient elastic stress wave that an acoustic source generates. Crack growth, crack fretting, and corrosion act as acoustic sources during damage evolution, producing transient elastic stress waves. Acoustic waves can be detected by placing sensors on the surface of the material being tested. A stimulus, such as an applied load, results in increasing damage in a material, such as the extension of a crack. When crack extension occurs, one or more bursts of waves are released and propagate through the material. A sensor placed on the surface of a material detects the acoustic waves and records the waveform signals for analysis. The waveform signals are analyzed to detect the progression of damage in a material.(5,6) Figure 2 schematically illustrates the principles of AE. 

Source: FHWA. 
Figure 2. Illustration. AE sensors mounted on a compact tension specimen and connected to an AE data acquisition system with the typical AE waveform parameters. 

Data Acquisition 

AE monitoring equipment consists of acoustic sensors, data acquisition electronics, and a computer to analyze the data. Signals received from each sensor are digitized and analyzed using specialized software. 

Acoustic sensors are ultrasonic sensors with frequencies that range from 50 kHz to 1 MHz with integrated preamplifiers. Integrated preamplifiers are required to detect AE waveforms produced from damage in the material because acoustic signals are very low in amplitude. 

Data Processing 

Recorded waveforms are analyzed to determine if the source of a waveform is damage or simply ambient noise caused by nonrelevant sources, such as friction between surfaces, movement of bolted connection or bearings, etc. Figure 3 shows a typical AE waveform. Parameters that describe this waveform include the amplitude of the wave, rise time, total energy in the wave packet, and the number and duration of “counts” (recorded wave cycles that exceeded a certain threshold). Other parameters, such as the frequency characteristics of the waveform and geometric shape of the wave packets, may also be used. These parameters are then used to discriminate between acoustic waves corresponding to damage evolution and ambient noise. Waveforms that correspond to damage evolution are called “AE events.” 

Source: FHWA.  
Figure 3. Composite graph. AE monitoring scheme. 

Data Interpretation 

The rate of occurrence of AE events is interpreted to identify AE sources (i.e., damage) in the material. The location of the source of the AE signal is also used in the interpretation of results. For example, a high number of AE events emanating from a particular location in a structure during the application of loads may indicate damage at that location. The rate of AE events generally increases when damage increases. The increase in AE activity is interpreted as an indication that damage is increasing. The rate of increase in crack length can be estimated from the rate of increase in AE activity. 


Advantages of AE technology include the following: 

  • Can be used to examine large areas of a structure. 
  • Can detect crack growth and estimate crack growth rates. 
  • Can be used to evaluate complex geometries for which other NDE technologies may be ineffective. 
  • Can be used to monitor for damage in inaccessible areas. 


Limitations of AE technology include the following: 

  • Can complicate data interpretation of acoustic signals resulting from many damage sources. 
  • Can only detect increasing damage (i.e., a crack that is growing). 


  1. S.C. Lovejoy, Acoustic emission testing of beams to simulate SHM of vintage reinforced concrete deck girder highway bridges, SAGE Struct. Health Monit. 7 (4) (2008) 329–346.
  2. D.W. Cullington, D. MacNeil, P. Paulson, J. Elliott, Continuous acoustic monitoring of grouted post-tensioned concrete bridges, NDT E Int. 34 (2001) 95–105.
  3. L.M. Dou, X.Q. He, Monitoring the rock activity around a tunnel with AE, Appl. Acoust. 21.5 (2002) 25–29.
  4. Q.H. Guo, B.P. Xi, J.B. Tian, Z.W. Li, X.C. Zheng, Experimental research on mechanical property of tunnel concrete lining after high temperature of fire, Chin. J. Underground Space Eng. 11.5 (2015) 1316–1338
  5. American Society of Nondestructive Testing. (2005). Nondestructive Testing Handbook, Vol. 6, Third Edition, p. 32, Columbus, OH. 
  6. Huang, M., Jiang, L., Liaw, K.P., Brooks, R.C., Seeley, R., and Klarstrom, L.D. (1998). “Using Acoustic Emission in Fatigue and Fracture Materials Research.” JOM50(11), The Minerals, Metals, and Materials Society, Pittsburgh, PA. Available online: https://www.tms.org/pubs/journals/jom/9811/huang/huang-9811.html, last accessed October 10, 2019.