## 1 Introduction  
The physical phenomena of Acoustic Emission (AE) and Ultrasonics (UT), the latter providing the basis for the Non-Destructive Test (NDT) method of Guided Ultrasonic Waves (GUW), have been observed and investigated since the early 1930s (see [1, 2, 3]). However, it took until the late 1960s for the implementation of AE and GUW as technically applicable NDT methods. These developments and selected industrial applications are described in, e.g., the NDT Handbooks on AE [4] and on UT [5] published by the American Society for Nondestructive Testing. AE and GUW [6] are complementary methods in the following sense: AE is passively monitoring and recording elastic waves (generated by material or test object specific mechanisms) that then propagate to the surface of the test objects, whereas GUWs, the same as UT, are elastic waves actively excited at a given location and time (often by a suitable UT-transducer) and then recorded after propagation in the test object by another UT transducer. Most commercial AE equipment can perform both AE and GUW. AE systems currently have a function for sending a \"short\" voltage pulse (duration of us or less) to the AE sensors in some systems adaptable or provided by a suitably amplified function generator signal. The transducers convert the pulse into a transient displacement of the piezoelectric sensing element, thus exciting a propagating elastic wave in the test object to which the exciting transducer is coupled. Initially, AE analysis included the simple counting of recorded single, transient AE signals called \"hits\" as a function of time or applied loads or stresses ([4] p. 34). In the 1960s, the extraction of a set of AE signal parameters from the analogue voltage signals generated by the AE sensors became a \"standard\" analysis approach [7]. In the last three decades, digital technology has played an important role in the further development of AE and GUW data recording and analysis. A first step, in the early 1990s, was the design of digital electronic equipment for data acquisition. This provided a suitable means for recording transient AE signals with sampling rates in the megahertz range (now up to 40 MHz) and increasingly higher resolution of signal magnitude (from initially 12 bit up to 18 bit). High-resolution records of transient AE waves also rendered identification of the different wave modes in so-called \"modal AE\" feasible [8]. Recently, modal AE data were complemented by Finite Element Models (FEM) and Fast Fourier Transform (FFT) for mode identification [9]. Digital technology development also continues to provide increasing computational power. As a next step, in the last decade, this enabled use of sophisticated approaches for the discrimination and identification of the physical source mechanisms of the AE signals. One successful approach combined unsupervised or supervised pattern recognition for signal classification with multi-physics simulation of model signal sources with signal initiation and signal propagation in the test object, also including the effects from the transfer function of the measurement chain [10; 11]. Another approach combined imaging with complementary NDT, such as in situ X-ray micro-tomography, with the AE signal classification from pattern recognition for identification of the source mechanisms. This combination yielded quantitative correlations between defect or damage size and the AE signal magnitude [12]. In situ X-ray radiography of fracture tests with contrast agent also yielded estimates of delamination increments per average AE signal amplitude [13]. Currently under way, the next step in digitalization of NDT with AE and GUW relates to what has been labelled \"Industry 4.0\" [14], still driven by increasing computational power on one hand but, on the other hand, also by major software developments. The latter, among others, comprises the use of artificial intelligence (AI) algorithms, such as machine learning or deep learning, various neural networks, support vector machine, random forest, etc. [15; 16; 17].