## 5 Conclusions  
AE measurements adopting multiple channels require a high data write rate to store all the acquired sensor reading values in real time. To employ HDDs in such cases, it is necessary to boost the data write performance. Binary file formats offer many advantages over plain text file formats, including a smaller file size and unmatched speed. This study proposed new algorithms to maximize these benefits by optimizing data encoding and writing. A series of writing tests were conducted on three conventional HDDs to validate these algorithms. The following conclusions were drawn:  
1. To reduce the file size, values can be encoded using a specialized binary format regarding the measurement range and resolution of the employed DAQ device. The 3-byte number format requires 3 bytes to represent a value for a 24-bit resolution. This format reduces the size of files by 3.3 times compared with the text format with the same precision. For AE measurements, most DAQ devices are 16-bit resolution types, making the 2-byte format ideal for achieving 16-bit resolution and reducing file sizes by 4 times compared with the text format with the same precision. Additionally, the 4-byte number format can satisfy the data storage requirements for special cases that require a 32-bit resolution. 2. Regarding the write rate, storing sensor reading values into a file immediately after they become available results in poor write performance. To overcome this issue, the use of a larger self-created buffer is recommended to achieve a better write rate. The optimal buffer size range was 128 MB to 512 MB, beyond which the improvement became less significant. Furthermore, each write process should be performed by a new thread to allow the processing of newly acquired data while the previous data are being written. A new file can also be created for each write to avoid errors. Implementing these strategies resulted in a 10\(\times\) faster write rate, which, in combination with a 4\(\times\) smaller file size, achieved a 40\(\times\) reduction in the write time or a 40\(\times\) better write performance. HDD #2 exhibited a write rate of 172 MB/s, providing the capability to perform measurements at 86 MS/s. 3. Combining multiple hard drives to achieve the sum of the write rates of all drives can lead to a significant increase in write performance by multiples compared with a scenario using a single drive. This approach is similar to the RAID 0 technique but addresses all its drawbacks. Accordingly, the measurement data were written into multiple individual files located in order across the selected drives, and a configuration file was created to provide sufficient information to collect the individual files and subsequently merge them into a single large file. Alternatively, each data file could be  
Figure 14: Failure of the hydraulic accumulator after 29 h of the load test. read independently. This provides a simple yet effective approach to enhance the write performance for data storage, allowing for faster data acquisition and processing. In actual measurements, monitoring programs must perform multiple tasks simultaneously, in addition to simply writing data. In this study, the condition-monitoring program developed utilizing the proposed algorithms was successfully tested. These tests demonstrated the capability of the program to conduct high-performance measurements in various configurations, indicating its potential to provide an efficient and robust system for monitoring and collecting data. Conceptualization, Q.D.V., J.-w.L., and J.-L.; data curation, K.S. and H.C.; formal analysis, H.C. and J.-u.L. ; funding acquisition, J.-u.L. ; investigation, K.S., Y.K., and J.-w.L. ; methodology, Q.D.V. and J.-u.L. ; project administration, J.-u.L. ; resources, Q.D.V. and J.-u.L. ; software, K.S. and Y.K. ; supervision, J.-u.L. ; validation, Q.D.V., J.-w.L., and J.-u.L. ; visualization, Q.D.V., Y.K., and J.-w.L. ; writing--original draft, Q.D.V. ; writing--review and editing, J.-w.L. and J.-u.L.