System Response Signals Research Articles

Virtual vibration test rig for fatigue analysis of dozer push arms

AbstractTo obtain accurate fatigue life results for construction machinery components, acquiring load spectra is crucial, as their authenticity and validity directly determine the precision of the analysis. In working conditions, component attitudes change continuously, but they remain static on the vibration test rig (VTR), so the acquired target signals should match with the actual component attitudes in the driving signal generation. This paper proposes an efficient and economical simulation‐based virtual VTR for fatigue analysis of dozers. First, the relationship between the push arm rotation angle and the cylinder stroke is established, since the cylinder strokes can be measured easily in data acquisition experiments. Second, load decomposition is used to determine the attitude relationship between virtual VTR conditions and actual conditions, and target signals are calculated based on this attitude relationship and measured data. According to the system's frequency response function, the driving signals are iterated until the system's response signals converge with the target signals. Finally, the iteratively obtained load spectra are utilized for fatigue life analysis. The results show that the virtual VTR can effectively and accurately obtain the results of fatigue analysis and has engineering application significance.

A convolutional neural network deep learning method for model class selection

AbstractThe response‐only model class selection capability of a novel deep convolutional neural network method is examined herein in a simple, yet effective, manner. Specifically, the responses from a unique degree of freedom along with their class information train and validate a one‐dimensional convolutional neural network. In doing so, the network selects the model class of new and unlabeled signals without the need of the system input information, or full system identification. An optional physics‐based algorithm enhancement is also examined using the Kalman filter to fuse the system response signals using the kinematics constraints of the acceleration and displacement data. Importantly, the method is shown to select the model class in slight signal variations attributed to the damping behavior or hysteresis behavior on both linear and nonlinear dynamic systems, as well as on a 3D building finite element model, providing a powerful tool for structural health monitoring applications.

HPCA1 is required for systemic reactive oxygen species and calcium cell-to-cell signaling and plant acclimation to stress.

Reactive oxygen species (ROS), produced by respiratory burst oxidase homologs (RBOHs) at the apoplast, play a key role in local and systemic cell-to-cell signaling, required for plant acclimation to stress. Here we reveal that the Arabidopsis thaliana leucine-rich-repeat receptor-like kinase H2O2-INDUCED CA2+ INCREASES 1 (HPCA1) acts as a central ROS receptor required for the propagation of cell-to-cell ROS signals, systemic signaling in response to different biotic and abiotic stresses, stress responses at the local and systemic tissues, and plant acclimation to stress, following a local treatment of high light (HL) stress. We further report that HPCA1 is required for systemic calcium signals, but not systemic membrane depolarization responses, and identify the calcium-permeable channel MECHANOSENSITIVE ION CHANNEL LIKE 3, CALCINEURIN B-LIKE CALCIUM SENSOR 4 (CBL4), CBL4-INTERACTING PROTEIN KINASE 26 and Sucrose-non-fermenting-1-related Protein Kinase 2.6/OPEN STOMATA 1 (OST1) as required for the propagation of cell-to-cell ROS signals. In addition, we identify serine residues S343 and S347 of RBOHD (the putative targets of OST1) as playing a key role in cell-to-cell ROS signaling in response to a local application of HL stress. Our findings reveal that HPCA1 plays a key role in mediating and coordinating systemic cell-to-cell ROS and calcium signals required for plant acclimation to stress.

Effective improvement of scanning resonance through dynamic optimization of the probe

Scanning probes are widely used in industry due to high precision and efficiency. However, the insufficient dynamic performance of the probe, especially the first-order natural frequency, makes the measurement results under high-speed scanning easily interfered by the resonance effect. Based on Lagrangian dynamic model of the probe, this paper proposes a multi-objective optimization method for the three-dimensional (3D) structure, including a two-dimensional (2D) elastic mechanism and a ceramic stylus, and obtains an optimized probe with highly increased first-order natural frequency and sensitivity. The evaluation of the probe dynamics and scanning-deviation prediction shows that the optimized probe has a higher upper velocity limit within the same allowable measurement deviation and a better tolerance to resonance. Compared with the original probe, the optimized probe significantly suppresses the low-amplitude and high-frequency resonance components caused by the axial runout of the linear guide and improve the quality of the system response signals.

Measurement of Electropotential Waves in Intact Phloem Sieve Elements Using Microelectrodes.

Electropotential waves (EPW) are involved in plant responses to both abiotic and biotic stresses. Three different types of EPWs have been identified: action potential, variation potential, and system potential, all of which have been indicated to participate in phloem-based communication between plant organs. In this chapter we describe in detail how to measure EPWs in plants, including how to access the phloem, and how to insert microelectrodes. Such experiments can be used, for example, to study the local and systemic signaling in response to diverse stimuli like microbial threat or herbivore attack.

MAPE - An Alternative Fitness Metric for Prony Analysis of Power System Signals

Abstract Phasor Measurement Units have facilitated tracking of oscillations in power system response signals. This has provided an impetus for identifying unstable component modes directly from oscillatory signals. Prony analysis, the earliest method proposed for this purpose, throws up some trivial modes. These not only distract the analyzer but also prolong processing time thereby delaying corrective action. Hence the fitness metric chosen should serve to minimize the number of trivial modes. The conventional fitness metric is Signal-to-Noise Ratio (SNR), which is actually Signal-to- Estimation error Ratio (SER). This paper proposes that Mean Absolute Percentage Error (MAPE) can also serve well as a fitness metric. It is shown through case studies carried out on well-known four-machine power system that there are a few cases where MAPE performs better than SER while in some instances SER works better. This inference is verified even in the presence of measurement noise. Hence a novel fitness metric is proposed combining MAPE with SER. Case studies on simulated signals obtained from New England-power system prove that this novel metric can achieve considerable reduction in processing time. Besides, an exponential binary search has been suggested for determining the optimal model order in minimum number of iterations.

Evidence for the Involvement of Electrical, Calcium and ROS Signaling in the Systemic Regulation of Non-Photochemical Quenching and Photosynthesis.

In contrast to the function of reactive oxygen species, calcium, hormones and small RNAs in systemic signaling, systemic electrical signaling in plants is poorly studied and understood. Pulse amplitude-modulated Chl fluorescence imaging and surface electrical potential measurements accompanied by pharmacological treatments were employed to study stimuli-induced electrical signals in leaves from a broad range of plant species and in Arabidopsis thaliana mutants. Here we report that rapid electrical signals in response to a local heat stimulus regulate systemic changes in non-photochemical quenching (NPQ) and PSII quantum efficiency. Both stimuli-induced systemic changes in NPQ and photosynthetic capacity as well as electrical signaling depended on calcium channel activity. Use of an Arabidopsis respiratory burst oxidase homolog D (RBOHD) mutant (rbohD) as well as an RBOH inhibitor further suggested a cross-talk between ROS and electrical signaling. Our results suggest that higher plants evolved a complex rapid long-distance calcium-dependent electrical systemic signaling in response to local stimuli that regulates and optimizes the balance between PSII quantum efficiency and excess energy dissipation in the form of heat by means of NPQ.

Wavelet Approach to Damage Detection of Mechanical Systems and Structures

The damage detection methods of mechanical and civil structures have been drawing much interest from various fields. Many techniques to detect damage are based on the examination of the system response signals. Crack-like damages may contribute to the response signal the edges (also called slopes), i.e. the localized sharp transitions of signal values. A powerful tool to characterize such local feature signals is the continuous wavelet transform (CWT). Despite its name, the CWT can be calculated on discrete data and requires enormous computational cost. However, in many cases, the crack-like changes in the signal can be detected and localized using the discrete dyadic wavelet transform (DDWT) that has a fast transform algorithm. This paper presents application of the DDWT to detect and localize the response signal features (slopes) due to cracks in mechanical and civil structures. The wavelets used to calculate the DDWT are cubic box splines. The numerical results for a response signal simulating cracks in structures are presented in this article.

Diagnostics of the regime of hyperchaotic dynamics from sequences of threshold-crossing time intervals

We consider a method of hyperchaotic regime diagnostics in a system with self-sustained oscillations by monitoring point processes representing sequences of time intervals between the moments at which the system response signal crosses a threshold level. The possibility of determining two positive Lyapunov exponents from a single point process of short duration is demonstrated.

A Methodology for Capturing and Fusing Unconscious Cognition with Computation

Based on the potential power of human-computer symbiosis, we present a methodology to capture and fuse unconscious cognition with high-powered computer analysis to improve the solution to complex computational problems. Unconscious cognition can be captured using non-intrusive sensors such as eye trackers when stimuli are controlled, and this system's response signal has the resolution to differentiate between conscious deliberate movements from the unconscious. This post-processed response signal, when combined with the power of computation, will provide a dynamic pathway to enable enhanced discovery and understanding in complex problem-solving domains, aiding effective decision-making. A central result of this paper is a methodology that can rank order unconscious cognition responses for prioritization into the computational engine, demonstrated using eye-tracking measurements on visual search.

Label-Free Quantitative Proteomic Analysis of Systemic Responses to Local Wounding and Virus Infection in Arabidopsis thaliana

Plants are continuously exposed to changing environmental conditions and must, as sessile organisms, possess sophisticated acclimative mechanisms. To gain insight into systemic responses to local virus infection or wounding, we performed comparative LC-MS/MS protein profiling of distal, virus-free leaves four and five days after local inoculation of Arabidopsis thaliana plants with either Oilseed rape mosaic virus (ORMV) or inoculation buffer alone. Our study revealed biomarkers for systemic signaling in response to wounding and compatible virus infection in Arabidopsis, which should prove useful in further addressing the trigger-specific systemic response network and the elusive systemic signals. We observed responses common to ORMV and mock treatment as well as protein profile changes that are specific to local virus infection or mechanical wounding (mock treatment) alone, which provides evidence for the existence of more than one systemic signal to induce these distinct changes. Comparison of the systemic responses between time points indicated that the responses build up over time. Our data indicate stress-specific changes in proteins involved in jasmonic and abscisic acid signaling, intracellular transport, compartmentalization of enzyme activities, protein folding and synthesis, and energy and carbohydrate metabolism. In addition, a virus-triggered systemic signal appears to suppress antiviral host defense.

Sending Out an ROS

Plant Science Local stresses, such as the damage caused by an insect on a leaf, can produce signals that are transmitted systemically to parts of the plant that are not directly injured or stressed. These signals help the plant acclimate to environmental stress or defend against pathogens. Miller et al. show that the gene RbohD , which encodes a plant NADPH oxidase that generates reactive oxygen species (ROS), is critical for rapid systemic signaling in response to wounding by a scalpel, heating to 42°C, cooling in ice water, high-intensity light, or increased salinity. Sci. Signal. 2 , ra45 (2009).

The Plant NADPH Oxidase RBOHD Mediates Rapid Systemic Signaling in Response to Diverse Stimuli

Cell-to-cell communication and long-distance signaling play a key role in the response of plants to pests, mechanical wounding, and extreme environmental conditions. Here, we report on a rapid systemic signal in Arabidopsis thaliana that traveled at a rate of 8.4 centimeters per minute and was dependent on the respiratory burst oxidase homolog D (RbohD) gene. Signal propagation was accompanied by the accumulation of reactive oxygen species (ROS) in the extracellular spaces between cells and was inhibited by the suppression of ROS accumulation at locations distant from the initiation site. The rapid systemic signal was triggered by wounding, heat, cold, high-intensity light, and salinity stresses. Our results reveal the profound role that ROS play in mediating rapid, long-distance, cell-to-cell propagating signals in plants.

PMU configuration for system dynamic performance measurement in large, multiarea power systems

Effective assessment of the dynamic performance of the power system requires wide-area information from properly distributed phasor measurement units (PMUs). However, to maximize the information content of the captured signals, the sensors need to be located appropriately, with due account given to the structural properties underlying the given system. In this paper, two numerical algorithms are proposed to achieve this goal. They aim to maximize the overall sensor response while minimizing the correlation among sensor outputs so as to minimize the redundant information provided by multiple sensors. The sensor responses of interest are the bus voltage magnitude, and the angle and frequency coherency indexes, which are estimated by means of a statistical sampling of power system response signals from a transient-stability program. Through the successive addition scheme, one of these algorithms easily incorporates mandatory locations such as tie-line busses and large generator step-up transformers. The proposed approaches are first illustrated on the Hydro-Quebec transmission grid and then on a 9-area/67-bus/23-machine test network designed with well-defined geographical boundaries and pre-specified weak interties between electrically coherent areas.

PMU Configuration for System Dynamic Performance Measurement in Large Multiarea Power Systems

Effective assessment of the dynamic performance of the power system requires wide-area information from properly distributed phasor measurement units (PMUs). However, to maximize the information content of the captured signals, the sensors need to be located appropriately, with due account given to the structural properties underlying the given system. In this paper, two numerical algorithms are proposed to achieve this goal. They aim to maximize the overall sensor response while minimizing the correlation among sensor outputs so as to minimize the redundant information provided by multiple sensors. The sensor responses of interest are the bus voltage magnitude and the angle and frequency coherency indices, which are estimated by means of a statistical sampling of power system response signals from a transient-stability program. Through the "successive addition" scheme, one of these algorithms easily incorporates mandatory locations such as tie-line busses and large generator step-up transformers. The proposed approaches are first illustrated on the Hydro-Québec transmission grid and then on a 9-area/67-bus/23-machine test network designed with well-defined geographical boundaries and prespecified weak interties between electrically coherent areas.

A minimal realization approach to reduced-order modelling and modal analysis for power system response signals

The authors report on a numerical scheme for compressing in parametric form small signal electromechanical responses of multimachine power systems, originating from transient stability programs (TSPs) or actual field testing. The result is achieved by using a multi-input multi-output (MIMO) minimal realization algorithm based on singular value decomposition (SVD), which can explicitly take into account the critical impact of the input interactions. The resulting parametric model is a reduced order representation of the underlying complex system, yet it is optimal (in the least-squares sense). Besides compact storage of damping information, the balanced state-space realization as such retains the principal components of the response signals, and could thus be useful for the tuning of static volt-ampere reactive (VAr) systems (SVSs) and power system stabilizers (PSSs). When it is transformed in the modal space, the model also provides insight into modal interaction mechanisms. Several examples are included for illustration purposes and other applications and improvements are also discussed. >

Initial results in Prony analysis of power system response signals

Prony analysis extends Fourier analysis by directly estimating the frequency, damping, strength, and relative phase of modal components present in a given signal. The ability to extract such information from transient stability program simulations and from large-scale system tests of disturbances would be quite valuable to power system engineers. Early results of the application of this method to stability program output are reported. Also included are benchmarks against known models and a brief mathematical summary. >