Evaluating machine suitability for diagnostics by determining parametric failures
https://doi.org/10.21266/2079-4304.2022.239.131-140
Abstract
During the operation of logging machines, scheduled inspections and maintenance are carried out in accordance with regulatory and technical documentation in order to maintain a serviceable condition throughout the entire period of operation. When a certain resource of machines is reached, malfunctions occur, which can accumulate and cause a decrease in performance. To identify such malfunctions, technical diagnostics are performed in order to identify malfunctions earlier, which can cause a decrease in productivity and, as a result, lead to premature downtime. To assess the fitness of machines for maintenance, it is necessary to take into account such indicators as the availability coefficient, the range of fuel lubricants, and the unification of tools. When performing maintenance, there is a possibility of the technical condition of the machines becoming faulty due to the occurrence of not only functional failures, but also parametric ones. Ensuring the fitness of machines for diagnostics must be formed taking into account the stages of development, which allows you to identify failures and ensure the operation of the machine above the level of the revenue rate. In the article, the dependence of the cost price on the load capacity is presented by the example of reducing the compression of the engine of a forest transport vehicle. In the case of an increase in the cost price above the level of the income rate due to a decrease in load capacity, a state of malfunction occurs, which is characterized by a parametric failure. Timely diagnosis is necessary to prevent parametric failure. The frequency of diagnostic work should be optimal in order to reduce operational losses. The definition of total operational losses is presented in the form of dependencies of the occurrence of a parametric failure at a constant time interval and at random moments with an unknown distribution law, as well as if failures may not occur at all.
About the Authors
V. N. ShilovskyRussian Federation
SHILOVSKY Veniamin N. – DSc (Technical), Professor of the Department of Transport and Technological Machines and Equipment
185910. Lenin av. 33. Petrozavodsk. Republic of Karelia
G. Y. Golshtein
Russian Federation
GOLSHTEIN Grigory Yu. – PhD (Technical), Associate Professor of Technical Sciences, Department of Transport and Technological Machines and Equipment
185910. Lenin av. 33. Petrozavodsk. Republic of Karelia
D. G. Konanov
Russian Federation
KONANOV Dmitry G. – PhD student, lecturer at the Department of Transport and Technological Machines and Equipment
185910. Lenin av. 33. Petrozavodsk. Republic of Karelia
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Review
For citations:
Shilovsky V.N., Golshtein G.Y., Konanov D.G. Evaluating machine suitability for diagnostics by determining parametric failures. Izvestia Sankt-Peterburgskoj lesotehniceskoj akademii. 2022;(239):131-140. (In Russ.) https://doi.org/10.21266/2079-4304.2022.239.131-140