OMA Methods Research Articles

Condition and structural assessment of a historic steel bridge according to the Italian guidelines for the evaluation of safety of existing structures

“Ponte dei Bersaglieri” is a historic bridge built in the early 1900s and rebuilt after the Second World War in San Donà di Piave, Venice, Italy. The bridge consists of four 53 m spans for a total length of 200 m. The spans are made of a steel lattice structure resting on concrete piles and abutments. At the request of the Managing Authority, a "Level 4" check and a serviceability check were planned in accordance with the Guidelines for Existing Bridges. The verification of such a bridge presents several difficulties related to the lack of basic information, as the documentation of the original project and the many interventions carried out over time were not available. Based on the scattered information collected, several surveys were organized to obtain certain information about the structure. Firstly, the geometry was measured globally by means of a point cloud produced by a drone survey, together with manual measurement of the thickness of individual members. A preliminary FEM model was then created, based on mechanical tests and inspections of existing materials. The aim of this phase was to determine the mechanical characteristics of both superstructures and substructures using destructive and non-destructive testing. An accelerometer data acquisition campaign was then planned to obtain the natural frequencies and mode shapes of the structure using the OMA method and to verify the compliance of the FEM model. At the end of the investigation campaigns, the FEM model can be finalized and it is possible to carry out level 4 verifications and serviceability checks.The inspection of the foundations in the riverbed will be conducted in the specific case with “multibeam technology to evaluate the erosion of the bottom of the riverbed and consequently the possible erosion of piers and abutments.This experience is representative as it describes some of the typical problems encountered during the verification of a historic steel bridge. The paper can be useful to other designers who are faced with similar situations, considering the large number of historic bridges currently present on Italian territory and the need to preserve them while ensuring their safety and functionality. What presented in the following has been developed within the scope of Level 4 assessments as outlined in the Guidelines for the classification and management of risk, safety assessment, and monitoring of existing bridges.

A novel and near-automatic mode tracking algorithm for civil infrastructure

Robustly and accurately tracking the evolution of modal parameters of large civil infrastructure is key for learning about their operational behaviour and performing modal-based structural health monitoring. This work proposes a new, two-step, mode tracking (MT) algorithm capable of automatically identifying which structural modes are to be tracked, tracking these modes even if they are subject to significant changes, and doing so independent of the (automatic) operational modal analysis (A)OMA method used for the modal identification. The MT algorithm is thoroughly tested using numerical benchmarking data, showing that the proposed algorithm can successfully and repeatedly identify and track structural modes, even if the modal detections are irregular, that the modal properties undergo cyclic variations, and that they are subject to abrupt changes. The MT algorithm is applied to two complex real-world cases, the Hardanger suspension bridge and the Bergsøysund floating pontoon bridge. It can identify and track all the expected modes in these two challenging cases.

Modal analysis of an operational offshore wind turbine using enhanced Kalman filter‐based subspace identification

AbstractOperational modal analysis (OMA) is an essential tool for understanding the structural dynamics of offshore wind turbines (OWTs). However, the classical OMA algorithms require the excitation of the structure to be stationary white noise, which is often not the case for operational OWTs due to the presence of periodic excitation caused by rotor rotation. To address this issue, several solutions have been proposed in the literature, including the Kalman filter‐based stochastic subspace identification (KF‐SSI) method which eliminates harmonics through estimation and orthogonal projection. In this paper, an enhanced version of the KF‐SSI method is presented that involves a concatenation step, allowing multiple datasets with similar environmental conditions to be used in the identification process, resulting in higher precision. This enhanced framework is applied to an operational OWT and compared to other OMA methods, such as the modified least‐squares complex exponential and PolyMAX. Using field data from a multi‐megawatt operational OWT, it is shown that the enhanced framework is able to accurately distinguish the first three bending modes with more stable estimates and lower variance compared to the original KF‐SSI algorithm and follows a similar trend compared to other approaches.

Effect of Environmental Parameters on Structural Health Status Assessment Using OMA Techniques

The data from a laboratory test on two aluminum rods are analyzed in this work. The rods are subjected to environmental excitation in an uncontrolled environment, attempting to replicate real operational conditions of structural health monitoring with external disturbances. Different damage levels are simulated on one of the two tension rods. Three of the most frequently used OMA methods are applied to evaluate the effects of the simulated damage on the dynamic behavior of the system. The complexity of the three applied OMA methods is gradually increased. The difference between the results from the different approaches is assessed. The aim of this work is to assess the performance of the proposed OMA methods, to understand their limits, and to assess the role of environmental disturbance parameters, such as temperature, in the evaluation of the health status of structures.

DYNAMIC POWER ALLOCATED SWIPT NOMA OVER RAYLEIGH FADING CHANNEL

Cooperative NOMA with simultaneous wireless information and power transfer is one possible method for enhancing the energy efficiency (EE) and spectral efficiency (SE) of fifth generation (5G) networks. Non-orthogonal multiple access (NOMA) offers superior spectrum efficiency than the traditional OMA method providing huge connectivity for machine-to-machine communication and enormous machine-type communication. In this paper, we first present a comparative study of dynamic power allocation method over fixed power allocation method to find the better schemes among them. Later, we use a dynamic power allocation scheme with cooperative communication (Cooperative NOMA) to find the performance of the far user with other transmission methods. Finally, we use the dynamic power allocation method for the far end user with SWIPT NOMA for the transmission and compare it with fixed power allocated SWIPT NOMA.

Spectral Efficiency of OTFS Based Orthogonal Multiple Access With Rectangular Pulses

In this paper, we consider Orthogonal Time Frequency Space (OTFS) modulation based multiple-access (MA). We specifically consider Orthogonal MA methods (OMA) where the user terminals (UTs) are allocated non-overlapping physical resource in the delay-Doppler (DD) and/or time-frequency (TF) domain. Well known OMA methods include, i) Guard Band (GB) based MA (GBMA), ii) Interleaved Delay Doppler MA (IDDMA), iii) Interleaved Time Frequency MA (ITFMA). The spectral efficiency (SE) performance of these OMA methods has <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">only</i> been studied for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ideal</i> transmit and receive pulses. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">With ideal pulses</i> , IDDMA and ITFMA are free from multi-user interference (MUI) and unlike GBMA they <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">do not</i> use guard bands in the DD/TF domain. Since ideal pulses are not realizable, in this paper we study the SE performance of these OMA methods with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">practical rectangular pulses</i> . For these OMA methods, we derive the expression for the received DD/TF domain symbols at the base station (BS) receiver and the effective DD domain channel matrix when rectangular pulses are used. Study of these expressions reveals the presence of MUI when rectangular pulses are used, although the amount of MUI in IDDMA is observed to be significantly smaller than that in ITFMA. We also derive the expression for the achievable sum SE. Through simulations, for practical values of the received signal-to-noise ratio, we observe that with rectangular pulses the sum SE achieved by the IDDMA method is significantly higher than that achieved by the ITFMA and GBMA methods.

Subband Decomposition Based Output-Only Modal Analysis

AbstractOutput-only modal analysis (OMA) is an indispensable alternative to experimental modal analysis for engineering structures while in operation. Conventional OMA often fails to identify the underlying modal structure with insufficient modal energy contribution. Such low modal participation is expected when the sampled response is subjected to sensor nonlinearity or when specific modes are not directly excited. A novel subband decomposition (SBD) method that resolves modal parameters even with biased modal energy distribution is proposed. It isolates the system response within a narrow frequency subband through a finite impulse response analysis filter bank. Whenever the filter subband captures a resonance, the filtered system response is close-to-singular and contains mainly the resonant mode contribution. A modal cluster metric is defined to identify the resonant normal modes automatically. The modal parameters are also identified and extracted within the subband possessing the locally maximal clustering measure. The proposed method assumes no a priori knowledge of the structure under operation other than the system should have any repeated natural frequencies. Therefore, the SBD algorithm is entirely data-driven and requires minimal user intervention. To illustrate the concept and the accuracy of the proposed SBD, numerical experiments of a linear cantilevered beam with various stationary and non-stationary loading are conducted and compared to other OMA methods. Furthermore, physical experiments on an aluminum cantilever beam examine the method’s applicability in field modal testing. Compared to traditional OMA methods, the numerical and physical experiments show orders of magnitude improvement in modal identification error using the proposed SBD.

Frequency Domain Decomposition Method: A Comparative Study on Signal Processing for Unbiased Damping Ratio Estimates

Frequency domain decomposition (FDD) is one of OMA methods in the frequency domain and this method has become well-known among engineering community engaged in the system modal identification due to its capability as a user-friendly and fast processing algorithm. Though, this method has problems in offering an accurate estimation of modal damping ratios, even though natural frequencies and mode shapes can be accurately estimated. The accurate estimation of modal damping is still an open problem and often leads to biased estimates since the errors are stemming from each step in FDD procedures and primarily caused by signal processing. Therefore, the identification of modal damping ratio turns out to be immensely essential in structural dynamics since damping is one of the crucial parameters of resonance. This study is to determine the appropriate signal processing for FDD because signal processing such as the time window, correlation function (CF) and the spectral density (SD) are the main contributors to the bias estimate. The goal of this paper is to provide necessary information on modal damping for reliable estimation.

Adaptive window function and window size based operational modal parameter identification for linear time-varying structure

In order to select the window function and window size adaptively before getting the results, we proposed adaptive moving window principle component analysis (AMWPCA) based OMA method to identify modal shapes and modal natural frequencies of slow LTV structures with weekly damped only from non-stationary vibration response signal online. The adaptive is achieved in two ways: change the window function or window size. We develop an adaptive indicator as the basis for window function and window size changes. Our adaptive approach is to make the difference between adjacent eigenvalues not too small. The operational modal parameter identification results in non-stationarity response signal dataset of a three-degree-of-freedom structure with slow time-varying mass show that comparing with fixed size moving window principle component analysis, our AMWPCA method can identify the modal shapes and modal frequencies better.

Outage Performance of URLLC NOMA Systems With Wireless Power Transfer

This letter considers an uplink short-packet ultra-reliable low latency communications (URLLC) system with finite blocklength (FBL). A quasi-static Rayleigh fading channel is adopted in this letter, and we employ wireless power transfer (WPT) to guarantee the data packets transmission of user equipment (UE). A novel non-orthogonal multiple access (NOMA) scheme with WPT under FBL is first proposed to improve reliability and reduce latency. Furthermore, we adopt outage probability (OP) as an important URLLC metric, and deduce two closed-form approximate bounds of system OP for finite and infinite battery capacities to characterize the relationship between reliability and latency. Simulation results verify that the derived bounds are tight with theoretical values, and the proposed scheme outperforms traditional OMA methods.

Enhanced frequency domain decomposition algorithm: a review of a recent development for unbiased damping ratio estimates

Enhanced frequency domain decomposition (EFDD) is one of OMA methods and has received significant interest from the engineering community involved in the identification of the modal structure. The great attention towards this method is driven by its capability as a user-friendly and fast processing algorithm. However, this method has drawbacks in providing accurate identification of damping ratios, despite natural frequencies and mode shapes can be computed through assuredly and reasonably accurate estimates. The exact practical computation of modal damping is still an open issue, often leading to biased estimates since the errors are coming from every step in EFDD procedures and mainly due to signal processing. Thus, the computation of modal damping becomes tremendously vital in structural dynamics because modal damping is one of the critical parameters of resonance. This review aims to provide relevant essential information on modal damping for a reliable estimation, reduce uncertainties and define error bounds. A literature review has been carried out to find the best practice criteria for modal parameter identification, in particular, modal damping ratio.

OMA analysis of a launcher under operational conditions with time-varying properties

The objective of this paper is the investigation of the capability of operational modal analysis approaches to deal with time-varying system in the low-frequency domain. Specifically, the problem of the identification of the dynamic properties of a launch vehicle, working under actual operative conditions, is studied. Two OMA methods are considered: the frequency-domain decomposition and the Hilbert transform method. It is demonstrated that both OMA approaches allow the time-tracking of modal parameters, namely, natural frequencies, damping ratios, and mode shapes, from the response accelerations only recorded during actual flight tests of a launcher characterized by a large mass variation due to fuel burning typical of the first phase of the flight.

Experimental identification of closely spaced modes using NExT-ERA

This article presents a study on the capability of the time domain OMA method, NExT-ERA, to identify closely spaced structural dynamic modes. A survey in the literature reveals that few experimental studies have been conducted on the effectiveness of the NExT-ERA methodology in case of closely spaced modes specifically. In this paper we present the formulation for NExT-ERA. This formulation is then implemented in an algorithm and a code, developed in house to identify the modal parameters of different systems using their generated time history data. Some numerical models are firstly investigated to validate the code. Two different case studies involving a plate with closely spaced modes and a pulley ring with greater extent of closeness in repeated modes are presented. Both structures are excited by random impulses under the laboratory condition. The resulting time response acceleration data are then used as input in the developed code to extract modal parameters of the structures. The accuracy of the results is checked against those obtained from experimental tests.

Modal parameter identification of a three-storey structure using frequency domain techniques FDD and EFDD and time domain technique SSI: experimental studies and simulations

The aim of this study is to modal parameter identification of a three-storey structure using operational modal analysis. In this research, available techniques in both time domain and frequency domain have been utilized. In time domain, the Stochastic Subspace Identification (SSI) technique, and in the frequency domain, Frequency Domain Decomposition (FDD) and Extended Frequency Domain Decomposition (EFDD) have been used. The modal parameters of a three-storey structure have been calculated using both experimental and finite element method. For this purpose, first, the three-storey structure was modeled in the ANSYS software and then, using the vibration analysis, structural responses are determined. The structure responses are used as inputs of the operational modal analysis algorithms and the modal parameters are obtained. Then, by constructing and exciting the structure by a variety of external excitation, the responses are measured and then, they are used as inputs to the operational modal analysis algorithm to obtain the modal parameters. Since the input signal in OMA method should be random, random, periodic random, pseudo-random, and burst random signals are used for exciting the structure. Finally, the calculated modal parameters from the finite element method and empirical method are compared with each other.

Operational Modal Analysis for Crack Detection in Rotating Blades

Abstract Vibration analysis has found widespread application for condition monitoring in a variety of applications and industries. With the continual development of cheaper and more powerful processing hardware, such systems have developed from utilizing simple checks on amplitude to those based around sophisti- cated spectral analysis. The paper presents application of the model based diagnostic method for early detection of faults in rotating machinery. The proposed diagnostics system based on modal analysis methods (OMA and OMAX methods). In the paper the diagnostic system based on such modelling is presented. The proposed system was verified during research on a specialized test rig, which can generate vibration signals.

Estimation of CNC machine–tool dynamic parameters based on random cutting excitation through operational modal analysis

Dynamic properties of the whole machine tool structure including tool, spindle, and machine tool frame contribute greatly to the reliability of the machine tool in service and machining quality. However, they will change during operation compared with the results from static frequency response function measurements of classic experimental modal analysis. Therefore, an accurate estimation of the dynamic modal parameters of the whole structure is of great value in real time monitoring, active maintenance, and precise prediction of a stability lobes diagram.Operational modal analysis (OMA) developed from civil engineering works quite efficiently in modal parameters estimation of structure in operation under an intrinsic assumption of white noise excitation. This paper proposes a new methodology for applying this technique in the case of computer numerically controlled (CNC) machine tools during machining operations. A novel random excitation technique based on cutting is presented to meet the white noise excitation requirement. This technique is realized by interrupted cutting of a narrow workpiece step while spindle rotating randomly. The spindle rotation speed is automatically controlled by G-code part program, which contains a series of random speed values produced by MATLAB software following uniform distribution. The resulting cutting produces random pulses and excites the structure in all three directions. The effect of cutting parameters on the excitation frequency and energy was analyzed and simulated. The proposed technique was experimentally validated with two different OMA methods: the Stochastic Subspace Identification (SSI) method and the poly-reference least square complex frequency domain (pLSCF or PolyMAX) method, both of which came up with similar results. It was shown that the proposed excitation technique combined successfully with OMA methods to extract dynamic modal parameters of the machine tool structure.

QuartetS: a fast and accurate algorithm for large-scale orthology detection

The unparalleled growth in the availability of genomic data offers both a challenge to develop orthology detection methods that are simultaneously accurate and high throughput and an opportunity to improve orthology detection by leveraging evolutionary evidence in the accumulated sequenced genomes. Here, we report a novel orthology detection method, termed QuartetS, that exploits evolutionary evidence in a computationally efficient manner. Based on the well-established evolutionary concept that gene duplication events can be used to discriminate homologous genes, QuartetS uses an approximate phylogenetic analysis of quartet gene trees to infer the occurrence of duplication events and discriminate paralogous from orthologous genes. We used function- and phylogeny-based metrics to perform a large-scale, systematic comparison of the orthology predictions of QuartetS with those of four other methods [bi-directional best hit (BBH), outgroup, OMA and QuartetS-C (QuartetS followed by clustering)], involving 624 bacterial genomes and >2 million genes. We found that QuartetS slightly, but consistently, outperformed the highly specific OMA method and that, while consuming only 0.5% additional computational time, QuartetS predicted 50% more orthologs with a 50% lower false positive rate than the widely used BBH method. We conclude that, for large-scale phylogenetic and functional analysis, QuartetS and QuartetS-C should be preferred, respectively, in applications where high accuracy and high throughput are required.

Aligning multiple protein sequences by parallel hybrid genetic algorithm.

This paper presents a parallel hybrid genetic algorithm (GA) for solving the sum-of-pairs multiple protein sequence alignment. A new chromosome representation and its corresponding genetic operators are proposed. A multi-population GENITOR-type GA is combined with local search heuristics. It is then extended to run in parallel on a multiprocessor system for speeding up. Experimental results of benchmarks from the BAliBASE show that the proposed method is superior to MSA, OMA, and SAGA methods with regard to quality of solution and running time. It can be used for finding multiple sequence alignment as well as testing cost functions.