The finite element model of a dual-rotor system was established by Timoshenko beam element. The dual-rotor system is a coaxial rotor whose supporting structure is similar to that of an aero-engine rotor system. The inner rotor is supported by three bearings, which makes it a redundantly supported rotor. The outer rotor connects the inner rotor by an intershaft bearing. The spectrum characteristics of the dual-rotor system under unbalanced excitation and misalignment excitation were analysed in order to study the influence of coupling misalignment of the inner rotor on the spectral characteristics of the rotor system. The results indicate that the vibration caused by the misaligned coupling of the inner rotor will be transmitted to the outer rotor through the intershaft bearing. Multiple harmonic frequency components, mainly 1x and 2x, will be excited by the coupling misalignment. The amplitudes of all harmonic frequencies increase with the misalignment in both the inner and outer rotors. The vibration level of the outer rotor affected by the misalignment is lower than that of the inner rotor because it is far from the misaligned coupling. Harmonic resonance occurs when any harmonic frequencies of the misalignment response coincide with a natural frequency of the system. In order to verify the theoretical model, experiments are performed on a test rig. Both the experimental and simulation results are in good accordance with each other.

In order to improve the thrust-weight ratio, modern aeroengines generally adopt a coaxial dual-rotor system. Factors such as manufacturing errors, assembly errors, bearing wear, and structural deformation can cause misalignment failures in a dual-rotor system. Supporting misalignment is one of the common types of misalignments in a dual-rotor system. To analyze the vibration characteristics of misalignment faults, in this study, we aim to build a finite element model of a dual-rotor system with supporting misalignment. The bearing loads caused by supporting misalignment are calculated using the three-bending moment equation method. Bearing loads are introduced into the dynamic model of the dual-rotor system. The influence of supporting misalignment at different bearings on the dynamic characteristics of the rotor system is investigated based on the supporting misalignment model. Studies have shown that supporting misalignment at different bearings has similar effects on the dynamic characteristics of the dual-rotor system. The proposed supporting misalignment model is more adaptable than the coupling misalignment model. It indicates that the damping of a rolling bearing should be considered in the dynamic analysis of a dual-rotor system although the value of the damping is not large. An experimental analysis is carried out. The simulation results are in good agreement with the experimental results.

Misalignment fault is the main factor that affects the normal running of dual-rotor system. Quantitative identification the misalignment fault is an important way to ensure the safe and stable service of the dual-rotor system, while the identification accuracy of traditional methods is low. Aiming at the above problems, this paper proposed a dual-rotor misalignment fault quantitative identification method based on DBN and D-S evidence theory improved by mutual information measure (MIMD-S). Seven groups experiments were conducted and several vibration signals were collected. By comparing it with the traditional methods D-S, and Pignistic improved D-S (PD-S) evidence theory, the results show that the method proposed in this paper improves the accuracy of the misalignment fault quantitative identification of the dual-rotor, the identification error rate was only 0.36%.

For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic–there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions.

To address the complexity of the crankshaft structure in reciprocating air compressors and the high cost of prototype testing, a scaled-model design method for reproducing torsional natural-frequency characteristics is proposed based on dynamic similitude theory. Taking the crankshaft of a certain air compressor as the research object, its lumped parameter model is established and the differential equation of vibration is derived. The similitude relation for torsional natural frequency is derived using the equation analysis method, and the preservation of the retained global torsional mode shapes during model condensation is quantitatively evaluated using the Modal Assurance Criterion (MAC). By preserving the prescribed rotational inertias and torsional stiffnesses, the crankshaft system is transformed into a three-dimensional model consisting of disks and elastic shafts, and a scaled model is designed according to the similitude criteria. Finite element modal analysis compares the natural frequencies of the equivalent three-dimensional model and the scaled-down model, showing agreement with the theoretical similitude predictions. A scaled-model test rig is constructed to provide limited experimental frequency-domain evidence for the first predicted frequency characteristic. The experimentally observed frequency component consistent with the first predicted torsional natural-frequency characteristic differs from the theoretical value by 0.55%; however, this deviation is not interpreted as a quantified measure of predictive accuracy. The experiment provides only partial supporting evidence for the proposed design procedure; the second torsional natural frequency, modal shapes of the scaled physical model, modal mass, modal stiffness, and modal damping are not independently validated experimentally in the present study. The results indicate that the proposed similitude design method can reproduce the torsional natural-frequency characteristics investigated in this study with a reduced model size, and may provide a potential approach for investigating the torsional natural-frequency characteristics of crankshaft-type systems, subject to system-specific recalculation and further validation.