## 4 Verification of High-Performance Measurements
### Virtual Measurement Using Simulated DAQ Devices  
To test and validate the capabilities of the program, various DAQ devices were simulated using the NI Measurement and Automation Explorer (MAX) program. National Instruments provide a wide range of DAQ devices for various measurement applications. The simulated signals were harmonic, with limited noise. The write performance was regardless of the amplitude of values or the signal waveform. AE measurement systems, as well as high-performance measurement systems, are required to acquire and store large amounts of data from numerous channels at a high sampling rate. To test this system, a configuration of the DAQ devices was created with MAX using the NI cDAQ-9719 chassis, along with 16 NI-9223 modules. All the 56 available channels were measured at a sampling rate of 1 MS/s per channel. The three HDDs mentioned in Section 3 were employed. The operating window of the program with 56 measurement channels is shown in Figure 10.  
Several tests were conducted, accompanied by multiple configurations, as outlined below:  
1. **Store data. ** The NI-9223 module type has a 16-bit resolution, making the 2-byte number format recommended for storing the measured data. However, the 3-byte  
Figure 10: Operating window of the program in a high-performance measurement test. number format was selected to verify the capabilities of the program. This format provided a 24-bit resolution that was greater than that of the DAQ devices. It did not make sense to improve the accuracy of the stored values but instead increase the amount of data generated for testing. The actual input range of \(\pm\)10.7 V was set. As configured, this system acquired 56 mega-samples every second for all channels, producing 168 MB of data every second, thereby requiring a write rate of at least 168 MB/s. The average data write rates of the three HDDs were reported in Section 3 as 162, 172, and 138 MB/s, respectively. Therefore, only HDD #2 supported the required write rate and was selected to store the data. The target buffer size was set to 512 MB to maximize the write performance. The program automatically calculated and then applied an appropriate buffer size of 508 MB, which was closest to the target size. With this configuration, the buffer was filled every 3 s, and the entire dataset was written into the hard drive. The configuration for obtaining the measurements performed well. Another setting was also tested. Now, a combination of HDDs #1 and #3 was selected to store the data instead of HDD #2. A multidrive write was used for this measurement. The other parameters were configured as those for the previous test. This test was well implemented and successfully wrote the data into multiple files located across HDDs #1 and #3, even though neither drive could individually support the required write rate. 2. **Skipping samples for visualization. ** The number of samples acquired every second was significantly large, leading to the visualization of the signals, which consumed a large amount of computing resources. Plotting all samples can be time-consuming and can impact the computer performance for other tasks. Notably, all tasks on the current data must be completed before new data are available. This program provides an option for skipping samples during signal plotting. For instance, let us set the number of samples to 10. Accordingly, for each group of 10 samples, only the first sample is plotted, and the others are skipped. This configuration reduces the number of samples that need to be plotted 10 times and accelerates the plotting process. By skipping the samples, a plot can be generated more rapidly while still providing a reasonable representation of the signal. This feature helps conserve computer resources and improve the performance of other tasks. 3. **Alarm. ** In actual measurements using sensors, it is not always easy to recognize abnormal signals by simply observing the signal plots. This becomes even more difficult when the option of skipping samples for visualization is employed.