# Fiber-Optic System for Monitoring Pit Collapse Prevention
## 1 Introduction
The decrease in the drift of the operating point of the interferometer due to the spatial localization of the interferometer while maintaining the length of the measuring base was observed. In addition, there is no information about testing a prototype in the field, so it cannot be argued that the proposed FOS is able to reduce the deviation of the output signal over time compared with the traditional electromechanical sensor from 12% to 2%. Only a functional diagram of a long-based strainmeter was presented, and the absence of photographs of a prototype can demonstrate the incompleteness of the studies and the absence of empirical data obtained as a result of studying full-scale FOS samples. Since there are no results of testing the FOS under conditions of changing the external temperature, it is impossible to unequivocally assert its effectiveness and complete solution of such an important problem for this device. It is known that the drift of the operating point can begin when the temperature changes within 1 \({}^{\circ}\)C [27], so there is a change in the intensity of the incident light wave on the surface of the photodetector. First of all, the phase of propagation of the light wave changes. The authors also did not indicate which fiber they used, since there are significant differences between the application of the multi- and single-mode OF [28]. The relative sensitivity of a strainmeter with a multi-turn sensitive element depends on the coefficient of elasticity k. The use in the FOS of a Mach-Zehnder interferometer is accompanied by the risk of the strainmeter output signal fade and the appearance of false signals about the displacement of rocks [26; 27; 28; 29; 30]. The rejection of a rather complex design that requires fine-tuning will significantly increase the FOS reliability. It should be noted that the high sensitivity of Distributed Fiber-Optic Sensors (DFOS) is an advantage of such devices and a cause of measurement interference. In order to achieve high accuracy, such devices are used with machine learning systems [31]. Signal processing is most often carried out by constructing two-dimensional graphs; however, there are methods of identifying damage using a three-dimensional transformation [32]. In another case, for example, for signal processing with the use of PPP-BOTDA, artificial intelligence based on the Random Sample Consensus (RANSAC) method [33] is used. Moreover, the use of neural networks, for example, convolutional neural networks (CNN), makes it possible to process the optical signal with high accuracy [34]. Such systems make it possible to increase the accuracy of measuring three-dimensional mechanical stresses,but at the same time, the disadvantages are the large size and cost of the equipment, as well as the complexity of information processing. Therefore, reducing the cost to develop a fiber-optic system will make it possible to use it in more facilities. This article presents a solution using a camera to track changes in a spot of light. In previous works on the development of a mine support pressure monitoring system [35; 36], it was found that not only the optical signal should be processed but also the electrical signal that supplies power to the optical radiation generator. At the same time, in attempts to develop a hardware-software complex, the elements of machine learning were used, which made it possible to distinguish noise in a signal when external impacts were exerted by such factors as the movement of a person or a machine [37]. These sources contain a detailed description of the main technical solution and all the advantages of the proposed system. Thus, this work proposes tracking crack displacements by such a parameter as the number of pixels of optical signal loss using a photomatrix, which is a fundamental difference from existing data processing methods using hardware-software complex algorithms to reduce external interference.