Disturbance Frequency Research Articles

Parallel-filter-based observer control for unknown multiple narrow-band disturbance rejection

An observer-based control method with parallel Q-filter is proposed to reject unknown multiple narrow-band disturbances for line of sight stabilization in telescope systems. In general, wide-band or multiple narrow-band disturbances rejection of observer-based control can be transformed into designing Q-filter, which could be too high-order to achieve fully-accuracy digital implementation, resulting in degrading the closed-loop performance or even causing instability. Therefore, a new parallel type of Q-filters is proposed to flexibly adjust the number of Q-filter in the sensitivity function and effectively reduce the computational complexity. A sufficient condition of the effectiveness for the parallel Q-filter and the closed-loop stability is derived and verified through simulations. Furthermore, disturbance frequencies can be on-line identified to adaptively optimize the Q-filter parameters. The effectiveness of the proposed method is validated on the image-based stabilization subsystem of a segmented lightweight large-scaled diffractive telescope.

Modeling compound hydrologic disturbances in the Rio Grande Headwaters

AbstractIn recent decades, the western United States (U.S.) has experienced increasing magnitudes and frequencies of natural land cover disturbances that impact water budget partitioning. Post‐disturbance hydrologic response is often variable at the stream outlet and is difficult to detect and quantify with traditional before–after control–impact studies. This study uses a modified version of the U.S. Geological Survey's Monthly Water Balance Model (MWBM) to simulate and separate the hydrologic response to several forest disturbances, including (1) wildfire, (2) forest conversion (subalpine to mid‐elevation forest) and (3) a climate that is hotter and drier than present in the Rio Grande Headwaters (RGH) in Colorado, U.S. (this climate scenario was derived from an ensemble of climate scenarios from the Coupled Model Intercomparison Project phases 3 and 5, which were selected based on water stress potential in the state of Colorado). We leverage historic post‐disturbance vegetation data in the RGH to add quantitative vegetation representation to the MWBM, then modeled synthetic future (2021–2050) streamflow scenarios as both single and compound disturbances. Relative to a baseline scenario, modeled scenarios predict several changes to average annual water trends over the final simulation decade (2041–2050); (1) decreases in average annual water yield under a hot and dry climate (−14%), except during the rising limb of annual snowmelt; (2) increases in average annual water yield (+32%) and peak runoff under a fire simulation; and (3) increases in average annual water yield (+24%) along with earlier and higher peak runoff under compound (fire + hot/dry) conditions. These findings show the strengths of hydrologic models in separating compound disturbance signals at the stream outlet and a need for quantitative vegetation representation within models to adequately represent dynamic disturbance conditions.

Detection and Diagnostic with Random Forest Classifier (RFC) to Improve the Maintenance Management System in Steam Boiler of Power Plant

Industrial internet of things (IIoT), digital twin, and connected devices can continue to use smart equipment and improve access to data. While the data collected by sensors has been an invaluable asset to companies, the ability to understand and use this data to drive new insights. The development of Condition Monitoring (CM) technology and Computerized Maintenance Management System (CMMS) in power generation systems provides a validated set of operation and maintenance data with abundant event data. Maintenance decision-making is primarily based on equipment reliability and performance-based features for diagnosing equipment failure. The most critical asset and often reduces the reliability and availability of a Coal Fired Steam Power Plant (CFSPP) with the most frequency of disturbances is the steam boiler. As a departure from the idea of creating a digital twin, this article will focus on analyzing equipment health conditions and finding causes of failure of the tools, utilizing data for diagnostic purposes. Real-case used in this research are steam boilers, which are important assets in power plant generation. The online and Failure Mode and Effect Analysis (FMEA) module data will be combined to realize the concept of anomaly diagnosis which is driven by hybrid data. Hoping that accurate diagnosis result with the Random Forest Classifier (RFC) Algorithm can be obtained and be used to analyze the causes of failure and decrease in equipment performance resulting by a decrease of energy efficiency performance. The analytical approaches are carried out to have the goal of generating detection models and diagnostic insights of event data based on operational data and FMEA.

Self-tuning regulatory controller of cyclical disturbances using data-driven frequency estimator based on fuzzy logic

This paper proposes two learning-type regulatory controllers: adaptive fuzzy iterative learning controller (AF-ILC) and adaptive fuzzy repetitive generalized predictive controller (AFR-GPC). The proposed controllers can reject the cyclical disturbances with small range frequency variations present in many control loops of industrial processes. Moreover, they can estimate the disturbance cycle using fuzzy logic with rules based on the previous values of the integral of the absolute error between the setpoint and output. The estimated period of the disturbance cycle is sent to the regulatory controllers to define the specific control actions required to reduce the oscillations in the process output. The advantage of this technique is that adaptive controllers are automatically adjusted by a frequency estimator, which only depends on process output data. The performance levels of the developed adaptive controllers are compared in the computational simulator of a nonlinear mold level of a continuous casting process employed in the steel industry. This process counteracts the periodic oscillations in the mold level caused by bulging disturbance. The numerical results show that both AF-ILC and AFR-GPC can reduce the oscillations in the output when the disturbance frequency changes by up to 5.2% and 13%, respectively.

Numerical Investigation of Hypersonic Flat-Plate Boundary Layer Transition Subjected to Bi-Frequency Synthetic Jet

Transition delaying is of great importance for the drag and heat flux reduction of hypersonic flight vehicles. The first mode, with low frequency, and the second mode, with high frequency, exist simultaneously during the transition through the hypersonic boundary layer. This paper proposes a novel bi-frequency synthetic jet to suppress low- and high-frequency disturbances at the same time. Orthogonal table and variance analyses were used to compare the control effects of jets with different positions (USJ or DSJ), low frequencies (f1), high frequencies (f2), and amplitudes (a). Linear stability analysis results show that, in terms of the growth rate varying with the frequency of disturbance, an upstream synthetic jet (USJ) with a specific frequency and amplitude can hinder the growth of both the first and second modes, thereby delaying the transition. On the other hand, a downstream synthetic jet (DSJ), regardless of other parameters, increases flow instability and accelerates the transition, with higher frequencies and amplitudes resulting in greater growth rates for both modes. Low frequencies had a significant effect on the first mode, but a weak effect on the second mode, whereas high frequencies demonstrated a favorable impact on both the first and second modes. In terms of the growth rate varying with the spanwise wave number, the control rule of the same parameter under different spanwise wave numbers was different, resulting in a complex pattern. In order to obtain the optimal delay effect upon transition and improve the stability of the flow, the parameters of the bi-synthetic jet should be selected as follows: position it upstream, with f1 = 3.56 kHz, f2 = 89.9 kHz, a = 0.009, so that the maximum growth rate of the first mode is reduced by 9.06% and that of the second mode is reduced by 1.28% compared with the uncontrolled state, where flow field analysis revealed a weakening of the twin lattice structure of pressure pulsation.

Quantifying the Geomorphic Effect of Floods Using Satellite Observations of River Mobility

AbstractGeomorphologists have long debated the relative importance of disturbance magnitude, duration, and frequency in shaping landscapes. For river‐channel adjustment by floods, some argue that the cumulative hydrograph, rather than magnitude or duration, matters most. However, studies of flood‐induced river‐channel change often draw upon small data sets. Here, we combine Sentinel‐2 imagery with flow data from laterally active rivers to address this question using a larger data set. We apply automated algorithms in Google Earth Engine to map rivers and detect their lateral shifting; we generate a large data set to quantify planform erosion during 175 floods at 34 selected sites. Erosion during these floods is best explained by their duration and then their cumulative hydrograph. We use a random forest regression model to predict flood‐induced erosion, with potential applications for hazard management. Ultimately, better global data on sediment supply and caliber would help us to understand flood‐driven change to river planforms.

The Prevalence of Cognitive Impairment Among Medicare Beneficiaries Who Use Outpatient Physical Therapy.

The objective of this study was to estimate the prevalence of cognitive impairment (including cognitive impairment no dementia [CIND] and dementia) among Medicare fee-for-service beneficiaries who used outpatient physical therapy and to estimate the prevalence of cognitive impairment by measures that are relevant to rehabilitation practice. This cross-sectional analysis included 730 Medicare fee-for-service beneficiaries in the 2016 wave of the Health and Retirement Study with claims for outpatient physical therapy. Cognitive status, our primary variable of interest, was categorized as normal, CIND, or dementia using a validated approach, and population prevalence of cognitive impairment (CIND and dementia) was estimated by sociodemographic variables and Charlson comorbidity index score. Age-, gender- (man/woman), race-/ethnicity-adjusted population prevalence of CIND and dementia were also calculated for walking difficulty severity, presence of significant pain, self-reported fall history, moderate-vigorous physical activity (MVPA) ≤1×/week, and sleep disturbance frequency using multinomial logistic regression. Among Medicare beneficiaries with outpatient physical therapist claims, the prevalence of any cognitive impairment was 20.3% (CIND:15.2%, dementia:5.1%). Cognitive impairment was more prevalent among those who were older, Black, had lower education attainment, or higher Charlson comorbidity index scores. The adjusted population prevalence of cognitive impairment among those who reported difficulty walking across the room was 29.8%, difficulty walking 1 block was 25.9%, difficulty walking several blocks was 20.8%, and no difficulty walking was 16.3%. Additionally, prevalence of cognitive impairment among those with MVPA ≤1×/week was 27.1% and MVPA >1×/week was 14.1%. Cognitive impairment prevalence did not vary by significant pain, self-reported fall history, or sleep disturbance. One in 5 older adults who use outpatient physical therapist services have cognitive impairment. Furthermore, cognitive impairment is more common in older physical therapist patients who report worse physical function and less physical activity. Physical therapists should consider cognitive screening for vulnerable older adults to inform tailoring of clinical practice toward a patient's ability to remember and process rehabilitation recommendations.

Longitudinal Study of Early Adversity and Disturbing Dream Frequency: Moderating Role of Early Negative Emotionality.

Although disturbing dreams are prevalent in youth and are associated with psychopathology, little is known about their developmental course and risk factors. We aimed to examine the association between early social environment and subsequent disturbing dream frequency across adolescence as moderated by early negative emotionality. Measures of children's early social environment and negative emotionality were collected from the mothers of 410 children (5-42 months old) and measures of disturbing dream frequency directly from the children (13-18 years old). Preliminary steps identified subgroups of families with distinct profiles of social environment using latent variable mixture modeling, and captured changes in disturbing dream frequency using latent growth modeling. Regression and moderation analyses were conducted to test the study objectives. Results showed that the diverse family patterns were best captured by two profiles reflecting adverse and positive social environments and that overall disturbing dream frequency decreased during adolescence. Moderation analyses showed that when early negative emotionality was higher, DD frequency was not only more elevated in an adverse environment, but lower in a positive environment. These results indicate that the development of disturbing dreams is most strongly associated with a combination of individual and environment factors. Our study adds to the literature by refining our conception of individual traits and disturbing dream development and has implications for the prevention of bad dreams, nightmares, and associated psychopathologies.

Pneumothorax during manned chamber operations: A summary of reported cases

In-chamber pneumothorax has complicated medically remote professional diving operations, submarine escape training, management of decompression illness, and hospital-based provision of hyperbaric oxygen therapy. Attempts to avoid thoracotomy by combination of high oxygen partial pressure breathing (the concept of inherent unsaturation) and greatly slowed rates of chamber decompression proved successful on several occasions. When this delicate balance designed to prevent the intrapleural gas volume from expanding faster than it contracts proved futile, chest drains were inserted. The presence of pneumothorax was misdiagnosed or missed altogether with disturbing frequency, resulting in wide-ranging clinical consequences. One patient succumbed before the chamber had been fully decompressed. Another was able to ambulate unaided from the chamber before being diagnosed and managed conventionally. In between these two extremes, patients experienced varying degrees of clinical compromise, from respiratory distress to cardiopulmonary arrest, with successful resuscitation. Pneumothorax associated with manned chamber operations is commonly considered to develop while the patient is under pressure and manifests during ascent. However, published reports suggest that many were pre-existing prior to chamber entry. Risk factors included pulmonary barotrauma-induced cerebral arterial gas embolism, cardiopulmonary resuscitation, and medical or surgical procedures usually involving the lung. This latter category is of heightened importance to hyperbaric operations as an iatrogenically induced pneumothorax may take as long as 24 hours to be detected, perhaps long after a patient has been cleared for chamber exposure.

An Investigation into the Primary and Subharmonic Resonances of the Swing Equation

A study is conducted to obtain a deeper insight into the primary and subharmonic resonances of the swing equation. The primary resonance, which can result in increased oscillatory responses, voltage instability, and potential system collapse, happens when the external disturbance frequency coincides with the natural frequency of the system. Subharmonic resonance occurs when the disturbance frequency is an integer fraction of the natural frequency, leading to low-frequency oscillations and possible equipment damage. The purpose of this study is to provide an extension of the existing literature of the effects of primary resonance and further provide a thorough understanding of subharmonic resonance on the stability of a certain power system paradigm. Motivated by the rich nonlinear dynamical behaviour exhibited by this evergreen model, analytical and numerical techniques are employed to examine the underlying principles, creating an efficient control solution for this resonant-related problem. The main objective of this research is to provide a comprehensive understanding of the primary and subharmonic resonances considering the dynamical and bifurcational behaviour of the underlying swing equation, whereby both analytical and numerical techniques are employed, allowing for an identification of certain precursors to chaos that may lead and cater for the safe operation of practical problems.

Fundamental frequency disturbances in female and male singers' pitch glides through long tube with varied resistances.

Source-filter interaction can disturb vocal fold vibration frequency. Resonance frequency/bandwidth ratios (Q-values) may affect such interaction. Occurrences of fundamental frequency (fo) disturbances were measured in ascending pitch glides produced by four female and five male singers phonating into a 70 cm long tube. Pitch glides were produced with varied resonance Q-values of the vocal tract + tube compound (VT + tube): (i) tube end open, (ii) tube end open with nasalization, and (iii) with a piece of cotton wool in the tube end (conditions Op, Ns, and Ct, respectively). Disturbances of fo were identified by calculating the derivative of the low-pass filtered fo curve. Resonance frequencies of the compound VT+tube system were determined from ringings and glottal aspiration noise observed in narrowband spectrograms. Disturbances of fo tended to occur when a partial was close to a resonance of the compound VT+tube system. The number of such disturbances was significantly lower when the resonance Q-values were reduced (conditions Ns and Ct), particularly for the males. In some participants, resonance Q-values seemed less influential, suggesting little effect of source-filter interaction. The study sheds light on factors affecting source-filter interaction and fo control and is, therefore, relevant to voice pedagogy and theory of voice production.

Unsteady Simulation and Mode Analysis of Disturbed Cylinder Flow

The unsteady simulation of cylinder flow with inlet velocity disturbance is simulated and compared with that without disturbance. POD is adopted to analyze and capture the dominant modes of the vortex street in the cylinder wake. The results show that the POD method is efficient in reconstructing the flow field. When the inlet velocity disturbance exists, the number of modes required to reconstruct the flow field accurately is almost unchanged, but the energy proportion of each mode changes. The larger the disturbance frequency is, the smaller the shape and vorticity magnitude of the vortex street is, and the slower the generation speed is. If the frequency deviates too much from the original frequency of the flow field, the effect of inlet velocity disturbance will be shielded.

A new linear quadratic regulator model to mitigate frequency disturbances in the power system during cyber-attack

<span lang="EN-US">This paper proposes a new model integrating a linear quadratic regulator (LQR) controller to mitigate frequency disturbances in the power system during cyber-attack, called as linear quadratic regulator to mitigate frequency disturbances (LQRMFD). As we know, most of the existing models have a common problem with achieving significant performances in mitigating dynamic response parameters, such as frequency deviation and settling time. However, the key aspect of LQRMFD is to mitigate the above issues with remarkable performance improvements. An uncommon and stable power system model has been considered in LQRMFD first to reach such a goal. A numerical problem has been solved to derive a certain characteristic equation, where the Routh-Hurwitz array criterion is applied for determining the stability of such a power system. After that, a state-space equation is developed from the power system to activate the LQR controller. Thus, achieving diversity and eliminating the redundancy of the power system considered can be obtained in LQRMFD. To evaluate the performance of LQRMFD, a series of experiments was conducted using the MATLAB-Simulink tool. Rigorous comparisons were also made among the results of LQRMFD, self-implemented and existing models. Furthermore, a detailed analysis was reported among those models to find the performance improvement of LQRMFD in percentage.</span>

Drivers of Geomorphic Heterogeneity in Unconfined Non‐Perennial River Corridors

AbstractRiver corridors along non‐perennial stream networks provide diverse physical and ecological functions that are thought to be related to the spatial and temporal variability of geomorphic units, also known as geomorphic heterogeneity. While studies on the characteristics and drivers of geomorphic heterogeneity have been developed in perennial streams, similar studies in ephemeral streams are lacking. Given the ubiquity of non‐perennial streams globally, we aim to answer questions regarding the magnitude and drivers of geomorphic heterogeneity in ephemeral river corridors as well as how geomorphic unit assemblages reflect processes related to flood disturbance. Geomorphic units were mapped in 30 unconfined river corridors within six non‐perennial watersheds in Utah and Arizona, USA. Landscape heterogeneity metrics—Shannon's Diversity Index, Shannon's Evenness Index, and patch density—were used to quantify geomorphic heterogeneity within each reach. Additionally, variables that potentially constrain or drive heterogeneity were quantified, including floodplain shape, grain size, large wood abundance, and proxies for flood disturbance. While heterogeneity positively correlated with metrics for morphology and disturbance, statistical models suggest that morphologic context, particularly river corridor width, was a more important predictor for estimating geomorphic heterogeneity. Still, geomorphic units reflected aggradation processes indicative of a range of flood energies, suggesting a strong tie between heterogeneity and disturbance. Results suggest that geomorphic heterogeneity may be resilient to changes in flood disturbance frequency or magnitude, but future studies investigating long‐term temporal heterogeneity are needed.

The challenge of comparing pollen-based quantitative vegetation reconstructions with outputs from vegetation models – a European perspective

Abstract. We compare Holocene tree cover changes in Europe derived from a transient Earth system model simulation (Max Planck Institute Earth System Model – MPI-ESM1.2, including the land surface and dynamic vegetation model JSBACH) with high-spatial-resolution time slice simulations performed in the dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator) and pollen-based quantitative reconstructions of tree cover based on the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. The dynamic vegetation models and REVEALS agree with respect to the general temporal trends in tree cover for most parts of Europe, with a large tree cover during the mid-Holocene and a substantially smaller tree cover closer to the present time. However, the decrease in tree cover in REVEALS starts much earlier than in the models, indicating much earlier anthropogenic deforestation than the prescribed land use in the models. While LPJ-GUESS generally overestimates tree cover compared to the reconstructions, MPI-ESM indicates lower percentages of tree cover than REVEALS, particularly in central Europe and the British Isles. A comparison of the simulated climate with chironomid-based climate reconstructions reveals that model–data mismatches in tree cover are in most cases not driven by biases in the climate. Instead, sensitivity experiments indicate that the model results strongly depend on the tuning of the models regarding natural disturbance regimes (e.g. fire and wind throw). The frequency and strength of disturbances are – like most of the parameters in the vegetation models – static and calibrated to modern conditions. However, these parameter values may not be valid for past climate and vegetation states totally different from today's. In particular, the mid-Holocene natural forests were probably more stable and less sensitive to disturbances than present-day forests that are heavily altered by human interventions. Our analysis highlights the fact that such model settings are inappropriate for paleo-simulations and complicate model–data comparisons with additional challenges. Moreover, our study suggests that land use is the main driver of forest decline in Europe during the mid-Holocene and late Holocene.

Elimination of signal amplitude disturbance in ghost imaging using an auxiliary laser channel.

Ghost imaging can be used to detect objects in a nonstationary environment or in the presence of variable ambient light, making it attractive when conventional imaging methods are ineffective. However, the conventional ghost imaging algorithm is susceptible to temporal fluctuations in the detected signal. In this work, we propose a polarization-multiplexed auxiliary laser channel propagating along the same optical path with the main one. The signal in the auxiliary channel is used as a reference and allows the elimination of signal disturbance. A quantitative analysis and comparison of the proposed method's performance to the high-pass filtering method are demonstrated. For an illumination pattern refresh rate of 10Hz, effective suppression of bucket signal fluctuations has been experimentally demonstrated. For a disturbance frequency from 1Hz to 10Hz, the auxiliary channel method demonstrated a ghost image Pearson correlation coefficient (PCC) of not less than 0.70, while the high-pass filtering method showed a PCC sharp drop from 0.65 to 0.02.

Continuous estimation of power system inertia using convolutional neural networks

Inertia is a measure of a power system’s capability to counteract frequency disturbances: in conventional power networks, inertia is approximately constant over time, which contributes to network stability. However, as the share of renewable energy sources increases, the inertia associated to synchronous generators declines, which may pose a threat to the overall stability. Reliably estimating the inertia of power systems dominated by inverted-connected sources has therefore become of paramount importance. We develop a framework for the continuous estimation of the inertia in an electric power system, exploiting state-of-the-art artificial intelligence techniques. We perform an in-depth investigation based on power spectra analysis and input-output correlations to explain how the artificial neural network operates in this specific realm, thus shedding light on the input features necessary for proper neural-network training. We validate our approach on a heterogeneous power network comprising synchronous generators, static compensators and converter-interfaced generation: our results highlight how different devices are characterized by distinct spectral footprints - a feature that must be taken into account by transmission system operators when performing online network stability analyses.

Robust & nonlinear control of an ultra-supercritical coal fired once-through boiler-turbine unit in order to optimize the uncertain problem

The ultra-supercritical once-through boiler (OTB) unit is an advanced power generation technology with high plant efficiency and low emissions. However, it is difficult to realize a coordinate control for the ultra-supercritical OTB unit to achieve the fast and stable dynamic response during the load tracking and grid frequency disturbances and in the presence of unavoidable uncertainties. In this paper, an accurate grey box multivariable coupled nonlinear model of an ultra-supercritical boiler-turbine unit is considered. Steam pressure at throttle valve, specific enthalpy in separator and active power are adjusted at desired values by manipulation of the fuel rate command, feedwater rate command and throttle valve opening. In addition to the mentioned accurate model, limitations of operational parameters and uncertainty sources are considered in the controller design. This makes this research unique from previous works. According to affine nonlinear control theory, a nonlinear robust sliding mode controller is developed. Then using MATLAB μ - DK iteration syntax, a linear H-infinity (H∞) robust control is synthesized with selecting proper weight functions. This method is suitable for all types of power plants with a similar mathematical modeling approach. Simulations in MATLAB Simulink toolbox reveals that both designed controllers achieve appropriate performance in the presence of uncertainties and parameters’ limitations, but nonlinear controller has better performance. Finally, deficiencies of a linear controller with respect to the proposed designed robust controllers are denoted.

A Cross-Sectional Study of Sleep Disturbances in Children and Adolescents With Abdominal Pain-Associated Disorders of Gut-Brain Interaction.

The aims of the current study were to determine the frequencies of specific sleep disturbances in youth with abdominal pain-associated disorders of gut-brain interaction (AP-DGBIs) and to assess relationships with psychological dysfunction. This was a retrospective evaluation of 226 consecutive patients diagnosed with an AP-DGBI. All had undergone a systematic evaluation of gastrointestinal symptoms, the Sleep Disturbance Scale for Children, and the Behavior Assessment System for Children. Disorders of initiation and maintenance of sleep (DIMS; 40%) and disorders of excessive daytime somnolence (DOES; 14%) were each present in more than 10% of the patients. Both DIMS and DOES scores were more likely to be elevated in patients with anxiety and/or depression scores in the at-risk or elevated-risk ranges. Sleep disorders are common in youth with AP-DGBIs and are associated with anxiety and depression, even in those patients with anxiety and depression in the at-risk range.

Determination of the natural frequencies of the above-ground sections of pipelines transporting an incompressible fluid

Under certain conditions, above-ground sections of pipelines are subject to vibration. Increasing the vibration amplitudes beyond the limits can cause the object to fail. In order to assess the vibration resistance of pipelines and to find the most effective ways of detuning from the resonant frequencies of disturbances, it is necessary to determine the natural frequencies of oscillations and the characteristics of the oscillation processes. The authors of the article developed a mathematical model to determine the frequency of free vibrations of above-ground pipeline sections, taking into account the influence of internal pressure and the velocity of the pumped fluid. As a result, a numerical solution based on the Bubnov-Galerkin method was obtained and a sufficient number of series elements in the approximate solution was determined. The authors performed numerical experiments. These showed that the frequencies should be determined for each section under specific conditions according to the pumping mode.