System Identification of the Upgraded LHPOST6 Reaction Mass at the University of California San Diego

Andres Rodriguez-Burneo; Jose I. Restrepo; Joel P. Conte

Home/Archive/arXiv

arXiv · 2405.04704

System Identification of the Upgraded LHPOST6 Reaction Mass at the University of California San Diego

Andres Rodriguez-Burneo·Jose I. Restrepo·Joel P. Conte

View original source ↗Read source document ↗Export metadata ↓

Abstract

Upon completing the upgrade from one to six degrees of freedom of the Outdoor Shake Table at UCSD in 2019, forced vibration tests were carried out to identify the dynamic characteristics of the reaction mass and soil system. This report describes the motivation, execution, and results from such tests, which independently excited the reaction mass in four degrees of freedom: longitudinal, transverse, yaw, and vertical. The report discusses the frequency response curves and deformation patterns from which the natural frequencies, damping ratio, mode shapes, and rigid body motion were determined. The first objective of the study was to investigate if the dynamic properties of the system had dramatically changed after the upgrade by comparing the results to those from forced vibration tests performed 20 years ago, during the construction of the facility. In addition, most recent tests also contributed with results from the vertical degree of freedom, which had never been tested. The second objective was to obtain high-quality response data of the system that will be used to develop a high-fidelity computational model of the reaction mass in future research. A comparison of results showed a slight difference of 0.5Hz in the natural frequency of 2 degrees of freedom. Moreover, maximum displacements in the recent tests were overall larger than the previous ones with few exceptions. The report thoroughly discusses the several sources of discrepancy between the past and most recent results. Finally, test results allowed us to estimate the system's response if the shake table actuators were to be used at their maximum nominal capacity. Small displacement and high damping results were consistent with those of previous tests and further validated the design of the reaction mass.

Explore related subjects

eess.SP

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Andres Rodriguez-Burneo, Jose I. Restrepo, Joel P. Conte. 2024-05-07. System Identification of the Upgraded LHPOST6 Reaction Mass at the University of California San Diego. https://arxiv.org/abs/2405.04704

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Low-Interference N-Continuous OFDM via Optimized Time-Domain Smoothing

A novel basis signal optimization method is proposed for reducing the interference in the N-continuous orthogonal frequency division multiplexing (NC-OFDM) system. Compared to conventional NC-OFDM, the proposed scheme is capable of improving the transmission performance while maintaining an identical sidelobe suppression performance imposed by the linear combination of two groups of basis signals. Our performance results demonstrate that with a low-complexity overhead, the proposed scheme is capable of striking a better trade-off among the bit error rate (BER), complexity, and the sidelobe suppression performance compared to its conventional counterparts.

eess.SP↗

arXiv2026

Self-Localizing MIMO Beam Mapping with Continuously Evolving Channel Memory

Machine learning has greatly advanced data-driven channel modeling and resource optimization. However, most existing methods require accurately location-labeled datasets, which are costly to collect and maintain in dynamic environments. This paper develops a self-localizing multiple-input multiple-output (MIMO) beam map framework that constructs a hierarchical wireless memory from highly sparse channel state information (CSI) measurements without explicit location labels. To reduce acquisition and processing overhead, we use beamdomain received signal strength (RSS) as compact inputs and theoretically show that they enable asymptotically unbiased spatial signature estimation. A dual-scale extractor captures intrasnapshot angular dependencies and inter-sample correlations for incomplete observations, and a hybrid temporal encoder is designed to consolidate recent CSI into stable short-term context for physical anchor inference. The inferred anchors spatially index a physically structured radio map embedding that stores long-term channel knowledge, which conditions a diffusion decoder for location-consistent full CSI reconstruction. Such a radio map embedding provides a persistent wireless knowledge representation that can be continuously updated and reused without full CSI acquisition. Experiments show that the proposed framework improves physical-anchor recovery accuracy by over 30% under sparse measurements and achieves more than 20% channel-capacity gain in non-line-of-sight (NLOS) beam tracking over Kalman-filter-based methods.

eess.SP↗

arXiv2026

Few-Shot Specific Emitter Identification via Integrated Complex Variational Mode Decomposition and Spatial Attention Transfer

Specific emitter identification (SEI) utilizes passive hardware characteristics to authenticate transmitters, providing a robust physical-layer security solution. However, most deep-learning-based methods rely on extensive data or require prior information, which poses challenges in real-world scenarios with limited labeled data. We propose an integrated complex variational mode decomposition algorithm that decomposes and reconstructs complex-valued signals to approximate the original transmitted signals, thereby enabling more accurate feature extraction. We further utilize a temporal convolutional network to effectively model the sequential signal characteristics, and introduce a spatial attention mechanism to adaptively weight informative signal segments, significantly enhancing identification performance. Additionally, the branch network allows leveraging pre-trained weights from other data while reducing the need for auxiliary datasets. Ablation experiments on the simulated data demonstrate the effectiveness of each component of the model. An accuracy comparison on a public dataset reveals that our method achieves 96% accuracy using only 10 symbols without requiring any prior knowledge.

eess.SP↗