## 1 Introduction  
Nowadays, there is intense social pressure to decrease the negative influence of human civilization on the natural ecosystem, especially in terms of electricity production. The use of renewable energy sources is deemed a necessity. On the other hand, with increasing environmental requirements and, at the same time, growing demand for electricity, there are also increasing requirements on the security of energy supply and its quality. Therefore, despite some drawbacks, wind energy is still one of the essential elements of the electricity production system using clean power. Unfortunately, wind turbines (WTs) have significant weaknesses compared to non-renewable energy resources. The primary issue is the lower efficiency due to limited working time at variable and unpredictable weather conditions. An attempt to eliminate those drawbacks by increasing the rotor diameter or by locating wind farms in open waters introduces some factors which increase the risk of damage to critical components of the turbine mechanical system. The damage risk applies, in particular, to the blades, which are susceptible elements of the wind turbine structure, and at the same time crucial from the operating point of view. Appropriate design and manufacturing of blades makes it that the manufacturer guarantees the fatigue life for 20 to 30 years of exploitation [1; 2; 3]. However, it is not possible to predict all situations that could lead to damage. That is why the newly built installations are equipped with a comprehensive system for monitoring the technical condition of all of the most critical elements of the system, including the blade. The use of such a diagnostic system allows reducing the effects of possible failure, extending the life cycle of the device and even predicting the rate and direction of damage spread, which makes it possible to decide on the possibility of further operation or the need to replace the element. A large group of operating wind turbines are devices built several years ago, which are approaching the end of their life cycle and have no dedicated damage detection systems. In this case, periodic inspection is the only possibility to assess their condition. It should be pointed out that standard methods of damage detection and location in laminates such as ultrasound are time-consuming and require stopping the turbine. A large number of current publications focused on damage detecting methods for turbine blades indicates the high practical importance of this topic. A broad overview of the methods and monitoring systems used in the diagnostics of wind turbines including blades can be found in [4; 5; 6]. Issues related to the development of new diagnostic methods of wind turbine blades should be aimed at three different aspects connected with the selection of physical parameters to analysis, measurement methods and signal processing methods. A large group of researchers in the subject focuses on techniques related to the analysis of mechanical parameters such as vibroacoustic [7; 8], shape curvature [9; 10], including these which measurement is possible without contact at a long distance and no sophisticated equipment (e.g., image correlation [11] or thermography [12]). The methods of signal analysis are both a classical [13; 14; 15], as well as a novel approach using AI algorithms, etc. [16; 17]. Many of these methods are only applicable in laboratory conditions due to the high accuracy of the measurement, time-consumption of the measurement and calculation or complex measurement equipment required [18]. The results presented by authors in this paper are part of a broader investigation on the development of a fast and effective non-destructive testing method aimed to detect, localize and identify of failures of a wind turbine rotor blade. In the first stage of general research on the diagnostic method, the one-dimensional Continuous Wavelet Transform (abbreviated CWT) was used to analyze bending forms of natural vibrations of the turbine blade.