Annotation. The paper considers the principle of constructing a control system of energy-efficient mine ventilation by using new dust detectors that can function in difficult operating conditions. One of such automatic dust meter sensors is described, which contains two sources of radiation in the measuring and reference channels operating at wavelengths in the region of maximum and minimum dust absorption, the radiation which are transmitted sequentially using prisms and mirrors directed through the measuring and reference channels into a single light stream and then to the input of a broadband photodetector. To give the system the possibility to function in difficult operating condi-tions, the sensor comprises a blower device that contains a protective windows and a heating viewing windows that maintains the temperature of the measuring channel within specified limits. The use of such sensors makes it possible to quickly make decisions about the redistribution of air in mine con-trolled by the mine ventilation control system.

The paper considers methods for calculating the mode of a stationary random process when solving the problem of processing measurement results under conditions of a priori uncertainty. The results of the conducted studies allowed us to conclude that the most effective method for calculating the mode for a given sample is the proposed method, which allows to increase the accuracy of its calculation by at least 8 times, compared to methods based on the construction of histograms. It should be noted that the proposed method allows to provide an estimate with an error of at least 5% for samples with a number of measurements of about 5 value.

The internal state of the material formed as a result of technological processing, indirectly affects the state of the material surface. A non-contact method of non-destructive control of the state of materials based on a visual analysis of the surface, requires high-quality images which can be obtained either using lens objectives or lenseless technologies. The results of studying image processing obtained by lensless technologies are presented. We used methods for modeling phase masks and image processing based on Gerchberg – Saxton iterative algorithms, adaptive-additive and phase mask rotation based algorithms. Materials such as granite, graphite, sand and carbon steel were analyzed. It is shown that the construction of cameras can provide significant reduction of their dimensions at the same or even improved characteristics. The images obtained using lensless technologies and the proposed methods of image processing also provide a significant increase in the accuracy of visual inspection of materials. The results obtained can be used in refining lensless technologies, improving the quality of images and reducing time of their processing.

The paper discusses the issues of minimizing the error in selecting a useful signal in the presence of the “flip” effect of the approximating function, which are solved by compensating for the approximation error by eliminating the “flip” effect by mirroring it relative to a certain line, which is determined by the methods proposed in this work. The proposed method for choosing a line for mirroring the estimate of the useful signal function has m σ N 2 ¯ 8 times smaller, with a spread of values that is characterized by σ m ¯ σ N 2 2 ¯ which is more than 70 times less.

The paper discusses the issues of practical implementation of increasing the accuracy of signal extraction, which is achieved by eliminating the «flip» of the approximating function when dividing the measured process into intervals under conditions of a priori uncertainty about the signal function, which significantly increases the error of allocating a useful signal. The probability of a «flip» of the approximating function depends significantly on the variance of the additive noise and the sample length. The use of the proposed methods and their software implementation makes it possible to increase the accuracy of the useful signal extraction up to 30 percent in the absence of a priori information about the function of the measured process for complex signals and at least 20% for simpler ones. The use of the proposed methods will significantly increase the processing efficiency in the conditions of a priori uncertainty about the function of the measured process (useful signal) and the statistical characteristics of the additive noise components.