Baikal-GVD: status and prospects

Baikal-GVD is a next generation, kilometer-scale neutrino telescope under construction in Lake Baikal. It is designed to detect astrophysical neutrino fluxes at energies from a few TeV up to 100 PeV. GVD is formed by multi-megaton subarrays (clusters). The array construction started in 2015 by deployment of a reduced-size demonstration cluster named "Dubna". The first cluster in its baseline configuration was deployed in 2016, the second in 2017 and the third in 2018. The full scale GVD will be an array of ~10000 light sensors with an instrumented volume of about 2 cubic km. The first phase (GVD-1) is planned to be completed by 2020-2021. It will comprise 8 clusters with 2304 light sensors in total. We describe the design of Baikal-GVD and present selected results obtained in 2015-2017.Comment: 9 pages, 8 figures. Conference proceedings for QUARKS201

Operational Modal Analysis of Rotating Machinery

International audienceHarmonic excitation of structures caused by rotating equipment is a problem faced by many engineers in the field of Operational Modal Analysis (OMA). Several methods to discard the influence of harmonic inputs over systems natural responses has been proposed in the literature and implemented in various software solutions. This paper recalls some of the most used techniques and uses a new time domain method for removing harmonics from measurements. Deployed method does not rely on filtering, statistical detection nor on non-linear fitting. Instead, it predicts the harmonic part of the time series and deploys an orthogonal projection of the latter onto the raw measurements to remove the harmonic part of the signal. The new technique is a part of an semi-automated framework for OMA of structures contaminated with harmonics, whose flow is presented in this paper. The merit of the framework is discussed in the context of OMA of a full scale operating ship with rotating machinery on-board

Orthogonal projection-based harmonic signal removal for operational modal analysis

International audienceA presence of a high amplitude periodic signals in the output responses from operating structures often pose a challenge for output-only system identification and, in case of health monitoring, damage detection/localization methods. This paper introduces a pre-processing approach that removes the harmonic part from the output signals directly in the time domain. The new method uses orthogonal projections of the harmonic realization of the signal onto the raw time series within the stochastic subspace framework. Proposed algorithm is tested on two experimental examples. First, an aluminum plate excited with both random white and periodic excitations. Second, a full-scale industrial case of a ferry excited by a random environmental load with harmonic interference from a rotating machinery on-board. In both cases the proposed method removes the harmonics from the structural responses while leaving the random part of the output signal