**1. Introduction**

For the safe use of various structures, a regular inspection is required. For critical infrastructures in particular, like aircraft, pressure vessels, and bridges as well as underground structures like mines, monitoring of their conditions is necessary. Therefore, methods for a reliable and automated monitoring are of great interest. Under these circumstances, structural health monitoring (SHM) has been an intriguing research topic in recent decades.

SHM is known as the continuous or periodical and automated method for monitoring and evaluating the condition of a monitoring subject. It is part of condition monitoring according to the International Organization for Standardization (ISO) 17359 [1]. This standard gives an overview of the basic procedures of condition monitoring and diagnostics programs for all types of machinery. The standard considers parameters such as vibration, temperature, flow rates, contamination, performance, and rotation speed, which are typically related to operation, state, and quality criteria. A concept is introduced of condition monitoring with the so-called root cause failure modes, which shows basic guidance on setting warning and alarm criteria, making diagnoses and predictions, and increasing their reliability.

A traditional means of monitoring big structures is visual inspection by trained personnel. Although simple, visual inspection is not successful for realizing all sources of damage, so a need exists for more reliable methods. A wide range of methods is now available for SHM of large structures such as bridges. These methods can be broadly classified as local methods for machine condition monitoring and global methods for monitoring of the whole structure (see Table 1) [2]. Machine condition monitoring is not strictly concerned with structural health (SH), but it requires information about the internal condition of the machine to be obtained externally. Vibration analysis is the most commonly applied method, and the analysis techniques have advanced greatly over the historic observation that if a machine is vibrating more than normal then it is likely to be faulty. These kinds of measurements are also used as predictive maintenance (PdM), which are performed to determine the condition of equipment in order to predict when maintenance should be done. One expects to save costs over routine or time-interval maintenance, because maintenance is carried out only when necessary or warranted. In order to identify wear particles or chemical contaminants, it is common to apply lubricant measurements, while the use of thermography to identify temperature anomalies is increasing.

**Table 1.** Type, aim, and characteristics of structural health monitoring (SHM) in machine condition, monitoring, and in monitoring of whole structures.


For SHM of entire structures, several non-destructive evaluation/testing (NDE/NDT) techniques are available. These techniques do not involve the destruction of the structure during testing, as the name implies. Most commonly used non-destructive techniques are based on the use of elastic waves e.g., ultrasonic and acoustic emission (AE) measurements, and fiber optics measurements. Further details on these methods can be found in [3–5].

Vibration measurements usually give the global figure, indicating damage in the entire structure, and can also locate and assess the damage. The basis of the principle is that the changes in the global properties e.g., mass, stiffness, and damping of a structure cause a change in its modal properties such as natural frequencies and mode shapes. The modal properties such as modal flexibility and strain energy are used for the identification of damage [6–8]. These global methods usually use accelerometers to measure the vibration of the structure for calculating the modal properties. But the use of a vibration-based method in large structures such as bridges can be uncertain, just then, if damage may only cause negligible change in dynamic properties and thus may go unnoticed. Moreover, in order to find the exact location of damage, local methods are often better alternatives.

AE measurements are applied for machine condition monitoring as well as SHM of large structures. In engineering materials, some common sources of AE are initiation and growth of cracks, yielding, failure of bonds, fiber failure, and pullout in composites. It should be noted that only active or growing cracks emitted elastic waves. If cracks are present but do not grow, no AE is emitted. Ono [9,10] gives in his papers a review on structural integrity evaluation and SH evaluation using AE.

Another application of SHM in the broadest sense is in situ AE monitoring in mines. This monitoring involves permanent AE measurements of microcracking in parts of the mine or the entire mine. A major task in underground storage like repositories for nuclear waste and deep mines is the safety assessment. Therefore, several geotechnical monitoring methods, for instance, micro-seismic measurements are used in many mines. This study demonstrates the capability of In situ AE monitoring for SHM in mines. Section 2 deals with fundamentals about in situ AE monitoring. After some comprehensive consideration of the scale between earthquakes and AE events, a list of various applications of in situ AE monitoring found in the literature (Section 2.2) is given. Sections 3–5 show examples on in situ AE monitoring in salt mines, gold mines, and underground research laboratories.
