## 1 Introduction  
Condition monitoring is a critical maintenance approach that measures the parameters of conditions in machines and structures. These parameters include vibration, noise, acoustic emission (AE), and temperature, which determine the machine health. Any abnormal parameter value can indicate a developing defect, and timely identification can prevent major breakdowns or failures. One of the essential configurations of a condition-monitoring system is the sampling rate. The sampling rate or frequency determines the number of samples per second (S/s) that are digitized using a data acquisition (DAQ) device. The required sampling rate depends on the maximum frequency of interest in the application. For instance, in the case of structural vibration measurements in two-stroke diesel engines, the frequency range of interest is 2-100 Hz. For sound measurements, the frequency range of interest is typically 20-20 kHz, which covers the audible range for humans. Nyquist's theorem and antialiasing filters play crucial roles in determining the minimum required sampling rates. According to [PERSON]'s theorem, the sampling rate should be at least twice that of the highest frequency component of interest. In practice, a sampling rate of 2.56 times the highest frequency component is recommended to account for antialising filter effects [1; 2; 3]. When an accurate representation of the signal waveform is required, a sampling rate of at least 10 times the maximum frequency of interest is recommended [4]. The AE technique [5; 6] is a special case of condition monitoring. In the industry, AE testing is preferred among nondestructive testing techniques [7], which allows the examination of an object or a material without damaging it. The AE technique offers real-time monitoring and rapid fault recognition with a high sensitivity. The installation of AE sensors is simple and does not disturb nearby sensors or the operation of the target mechanism. Using AE sensors, we can \"listen\" to the \"sounds\" generated by various types of faults, such as leaks [8; 9] and growing cracks [10; 11; 12], as well as those that have not yet appeared [13; 14]. By analyzing the AE parameters, the stage of material or structural degradation can be accurately determined. AE technology can also be used to locate [15; 16] and characterize [17] impending failures, making it possible to prevent accidents before they occur. AE frequency is an essential parameter for assessing the health and performance of materials or structures. This is based on the frequency of the elastic energy [18] released by irreversible changes in the internal structure of materials, such as crack formation or plastic deformation. Typically, the frequency of an AE ranges from a few kilohertz to several megahertz, although lower and higher frequencies can also be generated depending on the specific situation. In rare cases, AE has been reported at frequencies up to 100 MHz [19; 20; 21]. To ensure the accurate reconstruction of the signals after digitization, AE measurements require a very high sampling rate. Consequently, a large amount of data is acquired for each short consecutive period. Moreover, when multiple channels are simultaneously monitored, the amount of data that must be acquired and stored becomes even more significant. The write process must be sufficiently rapid to store the entire data being continuously streamed in real time. Advancements in computer technology have resulted in significant improvements in the transfer rates of hard drives. A standard hard disk drive (HDD) can now offer a sequential write rate of approximately 160 MB/s [22], which represents the maximum speed at which data can be continuously written into the drive. By contrast, solid-state drives (SSDs) demonstrate excellent write performance. A standard serial Advanced Technology Attachment (SATA) SSD can provide a sequential write rate of over 500 MB/s, whereas a nonvolatile memory express (NVME) SSD can offer a write rate of more than 5000 MB/s.