This study presents an iterative learning framework for designing input shapers for crane systems operating under constant cable-length and hoisting conditions. Unlike conventional analytical approaches, the proposed method determines the shaped trolley acceleration directly through repeated input-output learning without requiring an analytical solution or linearization of the system dynamics. Standard, arbitrary maneuver-time, and multi-length zero-vibration shapers are developed using both step and ramp input functions. The proposed approach is evaluated under constant cable-length as well as linear and nonlinear hoisting conditions. The results demonstrate rapid convergence of the learning process and successful suppression of residual payload oscillations while satisfying the prescribed transportation requirements. The arbitrary maneuver-time shaper enables faster payload transportation, whereas the multi-length shaper significantly enhances robustness against cable-length variations. The results also indicate that the shaper performance is largely insensitive to the selected hoisting profile. The proposed framework provides a flexible, robust, and practical methodology for vibration suppression in crane systems and can be readily extended to more complex nonlinear applications.
In the present study, free vibration and aeroelastic stability (flutter) analyses are investigated for a three-directional functionally graded material (FGM) conical panel subjected to a yawed supersonic fluid flow in a thermal environment. It is assumed that the material is fabricated from a non- homogeneous combination of metal and ceramic. To describe the material gradation, it is assumed that the volume fractions of the metal and ceramic vary simultaneously in the meridional, circumferential, and transverse directions based on several distribution patterns. The panel is modeled based on the first-order shear deformation theory (FSDT), and the aerodynamic pressure is estimated according to the piston theory. The governing equations are formulated by using Hamilton’s principle and are solved for several boundary conditions by using the differential quadrature method (DQM). The effects of the mass fraction, material gradation, temperature, and boundary conditions on the natural frequencies and critical aerodynamic pressure (CAP) are examined through a parametric study. It is concluded that the flutter boundaries are affected more significantly by the material gradation in the transverse direction than by the material gradation in the meridional and circumferential directions. The present study is the first theoretical work regarding the free vibrational and aerothermoelastic stability characteristics of a three-directional FGM conical panel subjected to a yawed supersonic fluid flow.
Acoustic impulse response measurement campaigns conducted in performance venues under ISO 3382-1 are susceptible to a class of systematic field errors, including receiver position labelling swaps, spatial co-ordinate entry mistakes, signal-to-noise ratio failures at low frequencies, and level calibration interruptions, that have received little systematic documentation and whose downstream impact on quantitative analyses has not previously been characterised. This study presents a systematic data quality audit framework demonstrated on a 171-seat conference hall (Başöğretmen Atatürk Conference Hall, V = 1511 m 3 ); the methodology is applicable in principle to any ISO 3382-1 campaign pending multi-venue validation. Six independent error categories were identified and corrected through cross-checking between recorded source-receiver distances, architectural co-ordinate databases, Barron’s revised room acoustics theory, and physical parameter range constraints. Five of these errors were genuine field issues discovered through the audit; one (the G calibration interruption) was deliberately introduced as a blinded controlled-validation case to verify the detection mechanism against known ground truth. The impact of each error category on downstream machine learning prediction accuracy was quantified using a gradient boosting ensemble framework with cross-validated R 2 and held-out validation R 2 as performance metrics. Correcting these errors improved downstream cross-validated prediction performance, most clearly for the spatially-driven parameters: cross-validated R 2 for T 30 and ST rose by amounts exceeding the cross-validation uncertainty, and the calibration correction improved G prediction. Given the single-venue sample (54 training rows, 3-fold cross-validation, with fold standard deviations of 0.2–0.5), these effects are reported as directional evidence that undetected field errors propagate into spatial prediction models, rather than as precise effect sizes. The audit framework is formalised as six detection algorithms and an on-site verification protocol, providing a systematic illustration of how each measurement error category propagates through a machine learning acoustic prediction pipeline. All quantitative results derive from a single 171-seat conference hall; the reported Δ R 2 values are venue-specific effect sizes that carry substantial cross-validation uncertainty and await cross-venue replication.
Vibration analysis plays a crucial role in ensuring the reliability, safety and efficient operation of rotating machinery by enabling early fault detection and condition monitoring. In the present study, vibration characteristics of a high-speed vapor blower-gearbox assembly operating at speed from 1,000 to 16,000 rpm were investigated. Frequency-domain analysis and impact testing were performed using multi-axial acceleration data collected from key bearing locations at both the drive-end and non-drive-end to identify the primary excitation mechanisms. Experimental data reveal that structural resonance, rather than rotational imbalance, predominantly influences the peak vibration amplitudes. The critical natural frequencies, which are linked to the casing support, low-speed shaft coupling and base structure, have been identified in the range of 12,000 to 15,000 rpm. To address the issue of resonance amplification, ribs were strategically integrated into the structure, resulting in an additional mass of 2.5-3.0 kg to enhance stiffness. This modification effectively shifted the natural frequencies of the system away from the operational velocity range, yielding a 30–40% reduction in vibration levels. These findings demonstrate that stiffness optimization enhances dynamic stability, providing a robust foundation for condition monitoring and prognostics of high-speed turbo machinery.
In this paper, an exact analytical solution is presented to study the vibration of isotropic single-span and multi-span beams based on Levinson’s third-order shear deformation theory. The displacement field of the beam, which accounts for the variation of shear stress along the beam thickness, is defined. Based on Hamilton’s principle, the governing equations and boundary conditions of the problem are derived. The dynamics of beam vibration is captured by two coupled partial differential equations. These equations are solved by first separating the time and space response and then decoupling the two equations to obtain a single, sixth-order differential equation for beam deflection. An analytical solution is presented for this equation, which is able to exactly satisfy the beam’s boundary conditions. The natural frequencies and mode shapes are calculated for different boundary conditions and geometries of the beam and are compared with the results of Euler-Bernoulli, Rayleigh, and Timoshenko beam theories. The effectiveness of this solution for analysis of multi-span beams has been demonstrated by applying it to a two-span beam with various support arrangements. Finally, based on the results obtained, some conclusions are presented.
