During maintenance of fiber optical communication lines the cyclic seasonal temperature variations can cause movement of optical fibers in loose tubes and redistribution of curvature. This is especially true for aerial suspended optical cables there significant “pushing out” of fiber from tubes in optical closures can be observed after years. In previous papers two methods for estimation of optical fiber curvature distribution based on reflectometric measurement on two wavelength and using polarization reflectometry were proposed. The results of estimation of optical fiber curvature distribution in all-dielectric self-supporting cable during cyclic temperature variation in climatic chamber are represented in paper.
In this paper, an algorithm is proposed for sorting delivery lengths of optical cables according to the probability of failure and selection of the cable's lengths with the highest probability of failure on the route of the communication line section. The implementation of this algorithm is presented for two examples of cable lines built using the "micro cable-in-microtube" technology. The data obtained as a result of processing demonstrate the possibilities of applying the proposed algorithm in practice.
The paper presents a model for predicting the service life of an optical cable on an operated cable line. The results of calculations for two cables samples removed from the cable line after several years of operation are provided. The proposed approach allows us to take into account the piecewise regular distribution of loads on the optical fiber in the cable both in the past and in the future. The model allows you to calculate predicted estimates of the cable service life, provided that the load on the optical fiber in the cable in the future and the history of the load on the optical fiber in the past are known. This, in turn, requires knowledge of the statistical characteristics of technological processes for cable production, construction and technical operation of the cable line.
In the present work, we attempt to predict the lifetime of the cable, taking into account the random nature of the effects on the optical fiber during cable production. In the analysis, we considered only impacts during cable production and, accordingly, were limited to the prediction of cable lifetime after acceptance and delivery of the product at the manufacturer’s warehouse.
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