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EN
The horizontal movement of the pressure sensor in relation to air masses may cause erroneous indications of the altimeter due to the possible measurement of the total pressure, which is the sum of the static and dynamic pressure. This problem mainly concerns devices of small dimensions equipped with barometric altimeters made in MEMS technology, performing complex movements. Small dimensions make it difficult to arrange the pressure intake slots in a way that ensures the measurement of static pressure. Examples include drones (UAH) or bike computers. The aim of the research was to develop an altitude correction formula depending on the speed of the pressure sensor relative to air, which, contrary to those found in the literature, would take into account changes in air density with altitude. The theoretical analysis of the influence of the speed of movement on the indications of the barometric altimeter was evaluated in this paper based on the standard atmosphere model. Methods of correcting errors caused by the measurement of total pressure were proposed. The effectiveness of the proposed methods was verified with simulations (Matlab). Experimental studies were also carried out, which confirmed the theoretical considerations. The experiments performed showed that the problem of correcting errors caused by incorrect measurement of static pressure is very complex. The inertia of the barometer indications plays an important role. The direction of airflow and pressure distribution on the flowing object are also important. The results presented in this paper can be used in the design of systems that improve the quality of barometric altimeter readings. This is particularly important when designing low-budget drone navigation systems and it will improve flight safety.
EN
Based on the structural hierarchy theory, rock masses can be considered as a blocky rock system capable of storing various kinds of a large amount of energy. As the development and utilization of underground space has extended to thousands of meters, the increasingly frequent rockbursts pose a great danger to the constructors and equipment at the construction field. According to its mechanism, rockburst can be broadly divided into strain failure type caused by rock volume damage and sliding failure type caused by fault-slip event. This paper focused on investigating the triggering mechanism of sliding type rockbursts induced by external disturbance. With the simplified theoretical model of contact slipping between rock masses under the condition of initial stress, a non-dimensional impact energy parameter I was derived to quantify the critical conditions of different types of sliding failure events along structural plane. Then the necessary conditions for the occurrence of fault-slip rock burst were derived: Firstly, the contact surfaces of the rock block are in the quasi-stable state with the high initial stress in the tangential direction; secondly, the impact energy factor which characterizes the movement of the rock mass reaches a critical value under the dynamic disturbance. To verify the theoretical result, a series of sliding tests were carried out for purple sandstone blocky system under various horizontal pulls and vertical impact loadings. Both the irreversible displacement and sustained sliding instability are observed, and the critical energy conditions of above-mentioned phenomenon are obtained, which are consistent with the theoretical model. Furthermore, numerical modeling calculations considering rock mass vibration and the slip rate weakening mode of rock friction were performed to better understand the mechanism of sliding instability caused by external disturbances. These results provide a theoretical reference on the safety of underground tunnel construction.
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EN
The paper deals with the synthesis procedure of a closed-loop quadratic, near-optimal control of a linear, time-invariant system, subject to known, deterministic, external disturbances. On the basis of the approximate, open-loop control obtained for that system by application of Legendre polynomials method the state-feedback matrix and the input signal vector were found.
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