# The Evolution of Machine Learning in Vibration and Acoustics: A Decade of Innovation (2015-2024)
## 4 Results and Discussion
This may indicate a transition from concept formulation to practical testing, both in laboratory and industrial conditions. Such a trend suggests the maturation of the entire field and a growing emphasis on validating models in real-world scenarios. Case studies also gained importance--the number of publications in this category doubled, rising from 8 to 16. This shows that more and more research is based on concrete, real-life examples that help to better understand the application of ML algorithms in engineering practice. The fewest studies were recorded in the category of literature analysis--here, the increase was modest, from one to three publications. Although still a marginal part of the total, the presence of this category indicates that systematic literature reviews are beginning to appear in this field as well. The chart clearly shows the dominance of conceptual research but also a gradual increase in interest in experiments and practical applications. This can be interpreted as a sign of the field's maturation--from theory development, through model validation, to implementation in real technical environments. The growing methodological diversity indicates an increasingly comprehensive approach to exploring the topic of machine learning in technical diagnostics. Analyzing the data from Figure 8 and Table 3, it is clearly evident that interest in the topic of machine learning in the context of vibroacoustic signal analysis has significantly increased in recent years. In most countries, the number of publications from 2020-2024 was much higher than in 2015-2019--both in terms of total output and growth rate. The most spectacular increase was recorded in the United States, where the number of publications rose from 5 to 19. In India, which had already been an active research hub in this area, the number of publications doubled--from 11 to 22. In the United Kingdom, the number of studies increased from two to seven, and in China, from one to seven. This is a clear signal that these countries are not only maintaining but also strengthening their presence in this research domain. New publications also appeared from countries such as Italy, Japan, Poland, and Germany. Notably, these countries had no publications in 2015-2019, but in the following five years each contributed between three and seven papers. This suggests that the topic of ML in technical diagnostics is attracting attention from researchers in an increasingly international context. Figure 7: Comparison of the number of publications from 2015–2019 and 2020–2024 according to the research methodology used. A rise in publication activity is also evident in countries such as Iraq, Brazil, and Malaysia. Iraq increased its number of publications from one to four, Brazil from one to three, and Malaysia from one to two. Although the absolute numbers are lower, the growth trend is significant. The only country that did not record an increase was South Korea--the number of publications there remained stable at three. A chi-squared test applied to the entire group of countries yielded a result of \(\chi^{2}=11.78\) with df = 11 and \(p\) = 0.3802, indicating that there are no statistically significant differences between the two periods. However, despite the lack of formal significance, the data clearly illustrate a growing trend: the number of publications is increasing, and research activity is becoming more geographically dispersed. A chi-square test was conducted to determine whether the geographical distribution of publications significantly changed between the periods 2015-2019 and 2020-2024. The result is that no statistically significant association was found between the country of origin and the publication period. This suggests that the increase in the number of studies over the last decade was relatively proportionate across countries. While certain countries (e.g., India, the United States, and the United Kingdom) consistently led in publication volume,  
Figure 8: Comparison of the number of publications from 2015–2019 and 2020–2024 by country.