Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.

Recycling concrete: An undiscovered source of ultrafine particles

While concrete recycling is practiced worldwide, there are many unanswered questions in relation to ultrafine particle (UFP; Dp<100nm) emissions and exposure around recycling sites. In particular: (i) Does recycling produce UFPs and in what quantities? (ii) How do they disperse around the source? (iii) What impact does recycling have on ambient particle number concentrations (PNCs) and exposure? (iv) How effective are commonly used dust respirators to limit exposure? We measured size-resolved particles in the 5-560 nm range at five distances from a simulated concrete recycling source and found that: (i) the size distributions were multimodal, with up to ~93% of total PNC in the UFP size range; and (ii) dilution was a key particle transformation mechanism. UFPs showed a much slower decay rate, requiring ~62% more distance to reach 10% of their initial concentration compared with their larger counterparts. Compared with typical urban exposure during car journeys, exposure decay profiles showed up to ~5 times higher respiratory deposition within 10 m of the source. Dust respirators were found to remove half of total PNC; however the removal factor for UFPs was only ~57% of that observed in the 100-560 nm size range. These findings highlight a need for developing an understanding of the nature of the particles as well as for better control measures to limit UFP exposure.

The educational pipeline for health care professionals : understanding the source of racial differences

The underrepresentation of blacks in the healthcare professions may have direct implications for the health outcomes of minority patients, underscoring the importance of understanding movement through the educational pipeline into professional healthcare careers by race. We jointly model individuals' postsecondary decisions including enrollment, college type, degree completion, and choosing a healthcare occupation requiring an advanced degree. We estimate the parameters of the model with maximum likelihood using data from the NLS-72. Our results emphasize the importance of pre-collegiate factors and of jointly examining the full chain of educational decisions in understanding the sources of racial disparities in professional healthcare occupations.

Field validation of controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

This article presents the field applications and validations for the controlled Monte Carlo data generation scheme. This scheme was previously derived to assist the Mahalanobis squared distance–based damage identification method to cope with data-shortage problems which often cause inadequate data multinormality and unreliable identification outcome. To do so, real-vibration datasets from two actual civil engineering structures with such data (and identification) problems are selected as the test objects which are then shown to be in need of enhancement to consolidate their conditions. By utilizing the robust probability measures of the data condition indices in controlled Monte Carlo data generation and statistical sensitivity analysis of the Mahalanobis squared distance computational system, well-conditioned synthetic data generated by an optimal controlled Monte Carlo data generation configurations can be unbiasedly evaluated against those generated by other set-ups and against the original data. The analysis results reconfirm that controlled Monte Carlo data generation is able to overcome the shortage of observations, improve the data multinormality and enhance the reliability of the Mahalanobis squared distance–based damage identification method particularly with respect to false-positive errors. The results also highlight the dynamic structure of controlled Monte Carlo data generation that makes this scheme well adaptive to any type of input data with any (original) distributional condition.

Standing surface waves in a dust-contaminated large-area planar plasma source

The effect of charged particulates or dusts on surface wave produced microwave discharges is studied. The frequencies of the standing electromagnetic eigenmodes of large-area flat plasmas are calculated. The dusts absorb a significant amount of the plasma electrons and can lead to a modification of the electromagnetic field structure in the discharge by shifting the originally excited operating mode out of resonance. For certain given proportions of dusts, mode conversion is found to be possible. The power loss in the discharge is also increased because of dust-specific dissipations, leading to a decrease of the operating mode quality factor.

NESSTI : norms for environmental sound stimuli

In this paper we provide normative data along multiple cognitive and affective variable dimensions for a set of 110 sounds, including living and manmade stimuli. Environmental sounds are being increasingly utilized as stimuli in the cognitive, neuropsychological and neuroimaging fields, yet there is no comprehensive set of normative information for these type of stimuli available for use across these experimental domains. Experiment 1 collected data from 162 participants in an on-line questionnaire, which included measures of identification and categorization as well as cognitive and affective variables. A subsequent experiment collected response times to these sounds. Sounds were normalized to the same length (1 second) in order to maximize usage across multiple paradigms and experimental fields. These sounds can be freely downloaded for use, and all response data have also been made available in order that researchers can choose one or many of the cognitive and affective dimensions along which they would like to control their stimuli. Our hope is that the availability of such information will assist researchers in the fields of cognitive and clinical psychology and the neuroimaging community in choosing well-controlled environmental sound stimuli, and allow comparison across multiple studies.

Performance evaluation of three-level Z-source inverters under semiconductor-failure conditions

This paper evaluates and proposes various compensation methods for three-level Z-source inverters under semiconductor-failure conditions. Unlike the fault-tolerant techniques used in traditional three-level inverters, where either an extra phase-leg or collective switching states are used, the proposed methods for three-level Z-source inverters simply reconfigure their relevant gating signals so as to ride-through the failed semiconductor conditions smoothly without any significant decrease in their ac-output quality and amplitude. These features are partly attributed to the inherent boost characteristics of a Z-source inverter, in addition to its usual voltage-buck operation. By focusing on specific types of three-level Z-source inverters, it can also be shown that, for the dual Z-source inverters, a unique feature accompanying it is its extra ability to force common-mode voltage to zero even under semiconductor-failure conditions. For verifying these described performance features, PLECS simulation and experimental testing were performed with some results captured and shown in a later section for visual confirmation.

Modulation and control of three-phase paralleled Z-source inverters for distributed generation applications

This paper presents a modulation and controller design method for paralleled Z-source inverter systems applicable for alternative energy sources like solar cells, fuel cells, or variablespeed wind turbines with front-end diode rectifiers. A modulation scheme is designed based on simple shoot-through principle with interleaved carriers to give enhanced ripple reduction in the system. Subsequently, a control method is proposed to equalize the amount of power injected by the inverters in the grid-connected mode and also to provide reliable supply to sensitive loads onsite in the islanding mode. The modulation and controlling methods are proposed to have modular independence so that redundancy, maintainability, and improved reliability of supply can be achieved. The performance of the proposed paralleled Z-source inverter configuration is validated with simulations carried out using Matlab/Simulink/Powersim. Moreover, a prototype is built in the laboratory to obtain the experimental verifications.

Evaluation of resonant damping techniques for Z-source current-type inverter

For the renewable energy sources whose outputs vary continuously, a Z-source current-type inverter has been proposed as a possible buck-boost alternative for grid-interfacing. With a unique X-shaped LC network connected between its dc power source and inverter topology, Z-source current-type inverter is however expected to suffer from compounded resonant complications in addition to those associated with its second-order output filter. To improve its damping performance, this paper proposes the careful integration of Posicast or three-step compensators before the inverter pulse-width modulator for damping triggered resonant oscillations. In total, two compensators are needed for wave-shaping the inverter boost factor and modulation ratio, and they can conveniently be implemented using first-in first-out stacks and embedded timers of modern digital signal processors widely used in motion control applications. Both techniques are found to damp resonance of ac filter well, but for cases of transiting from current-buck to boost state, three-step technique is less effective due to the sudden intermediate discharging interval introduced by its non-monotonic stepping (unlike the monotonic stepping of Posicast damping). These findings have been confirmed both in simulations and experiments using an implemented laboratory prototype.

Dual Z-source inverter with three-level reduced common mode switching

This paper presents the design of a dual Z-source inverter that can be used with either a single dc source or two isolated dc sources. Unlike traditional inverters, the integration of a properly designed Z-source network and semiconductor switches to the proposed dual inverter allows buck-boost power conversion to be performed over a wide modulation range with three-level output waveforms generated. The connection of an additional transformer to the inverter ac output also allows all generic wye- or delta-connected loads with three-wire or four-wire configuration to be supplied by the inverter. Modulation-wise, the dual inverter can be controlled using a carefully designed carrier-based pulse-width modulation (PWM) scheme that always will ensure balanced voltage boosting of the Z-source network, while simultaneously achieving reduced common-mode switching. Because of the omission of dead-time delays in the dual inverter PWM scheme, its switched common-mode voltage can be completely eliminated, unlike in traditional inverters where narrow common-mode spikes are still generated. Under semiconductor failure conditions, the presented PWM schemes can easily be modified to allow the inverter to operate without interruption and for cases where two isolated sources are used, zero common-mode voltage can still be ensured. These theoretical findings together with the inverter practicality have been confirmed both in simulations using PSIM with Matlab/Simulink coupler and experimentally using a laboratory implemented inverter prototype.

Dual Z-source inverter with three-level reduced common-mode switching

This paper presents the design of a dual Z-source inverter that can be used with either a single dc source or two isolated dc sources. Unlike traditional inverters, the integration of a properly designed Z-source network and semiconductor switches to the proposed dual inverter allows buck-boost power conversion to be performed over a wide modulation range, with three-level output waveforms generated. The connection of an additional transformer to the inverter ac output also allows all generic wye-or delta-connected loads with three-wire or four-wire configuration to be supplied by the inverter. Modulationwise, the dual inverter can be controlled using a carefully designed carrier-based pulsewidth-modulation (PWM) scheme that will always ensure balanced voltage boosting of the Z-source network while simultaneously achieving reduced common-mode switching. Because of the omission of dead-time delays in the dual-inverter PWM scheme, its switched common-mode voltage can be completely eliminated, unlike in traditional inverters, where narrow common-mode spikes are still generated. Under semiconductor failure conditions, the presented PWM schemes can easily be modified to allow the inverter to operate without interruption, and for cases where two isolated sources are used, zero common-mode voltage can still be ensured. These theoretical findings, together with the inverter practicality, have been confirmed in simulations both using PSIM with Matlab/Simulink coupler and experimentally using a laboratory-implemented inverter prototype.

Unbalance identification in large steam turbo-generator unit using a model-based method

Fault identification in industrial machine is a topic of major importance under engineering point of view. In fact, the possibility to identify not only the type, but also the severity and the position of a fault occurred along a shaft-line allows quick maintenance and shorten the downtime. This is really important in the power generation industry where the units are often of several tenths of meters long and where the rotors are enclosed by heavy and pressure-sealed casings. In this paper, an industrial experimental case is presented related to the identification of the unbalance on a large size steam turbine of about 1.3 GW, belonging to a nuclear power plant. The case history is analyzed by considering the vibrations measured by the condition monitoring system of the unit. A model-based method in the frequency domain, developed by the authors, is introduced in detail and it is then used to identify the position of the fault and its severity along the shaft-line. The complete model of the unit (rotor – modeled by means of finite elements, bearings – modeled by linearized damping and stiffness coefficients and foundation – modeled by means of pedestals) is analyzed and discussed before being used for the fault identification. The assessment of the actual fault was done by inspection during a scheduled maintenance and excellent correspondence was found with the identified one by means of authors’ proposed method. Finally a complete discussion is presented about the effectiveness of the method, even in presence of a not fine tuned machine model and considering only few measuring planes for the machine vibration.

Spectroscopic vibrations of austinite (CaZnAsO4⋅OH) and its mineral structure : Implications for identification of secondary arsenic-containing mineral

Austinite (CaZnAsO4⋅OH) is a unique secondary mineral in arsenic-contaminated mine wastes. The infrared and Raman spectroscopies were used to characterize the austenite vibrations. The IR bands at 369, 790 and 416 cm−1 are assigned to the ν2, ν3 and ν4 vibrations of AsO43− unit, respectively. The Raman bands at 814, 779 and 403 cm−1 correspond to the ν1, ν3 and ν4 vibrations of AsO43− unit respectively. The sharp bands at 3265 cm−1 for IR and 3270 cm−1 both reveals that the structural hydroxyl units exist in the austenite structure. The IR and Raman spectra both show that some SO4 units isomorphically replace AsO4 in austinite. X-ray single crystal diffraction provides the arrangement of each atom in the mineral structure, and also confirms that the conclusions made from the vibrational spectra. Micro-powder diffraction was used to confirm our mineral identification due to the small quantity of the austenite crystals.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

On-road rapid identification of high-polluting transport buses

Exhaust emissions from motor vehicles vary widely and depend on factors such as engine operating conditions, fuel, age, mileage and service history. A method has been devised to rapidly identify high-polluting vehicles as they travel on the road. The method is able to monitor emissions from a large number of vehicles in a short time and avoids the need to conduct expensive and time consuming tests on chassis dynamometers. A sample of the exhaust plume is captured as each vehicle passes a roadside monitoring station and the pollutant emission factors are calculated from the measured concentrations using carbon dioxide as a tracer. Although, similar methods have been used to monitor soot and gaseous mass emissions, to-date it has not been used to monitor particle number emissions from a large fleet of vehicles. This is particularly important as epidemiological studies have shown that particle number concentration is an important parameter in determining adverse health effects. The method was applied to measurements of particle number emissions from individual buses in the Brisbane City Council diesel fleet operating on the South-East Busway. Results indicate that the particle number emission factors are gamma- distributed, with a high proportion of the emissions being emitted by a small percentage of the buses. Although most of the high-emitters are the oldest buses in the fleet, there are clear exceptions, with some newer buses emitting as much. We attribute this to their recent service history, particularly pertaining to improper tuning of the engines. We recommend that a targeted correction program would be a highly effective measure in mitigating urban environmental pollution.