Isolation Scheme Research Articles

Artificial Intelligence Algorithm-Based Arrangement Optimization of Structural Isolation Bearings

The determination of an isolation-bearing scheme usually depends on experience, and needs numerous iterative calculations, especially when considering many factors such as total cost of the scheme, various design indicators, eccentricity of stiffness center of isolation bearings and the center of gravity of superstructure, and so on. Moreover, during the usual optimization process, the isolation scheme is often limited in several kinds of sizes and fixed predetermined distribution of types of isolation bearings based on experience or trial calculations due to computational efficiency, which would make it incapable of exploring other possible schemes. In this paper, artificial intelligence technology is applied to optimize the layout of isolation bearings. Types of isolation bearings are predicted through a Convolutional Neural Network, and sizes of isolation bearings are optimized by Hunter–prey optimization algorithm to improve computational efficiency and optimal arrangements of bearings. To simplify the optimization process, an optimization objective function considering a seismic decrease coefficient, story drift ratio and total cost of isolation bearings is proposed. In this function, weight coefficients reflect significance of various factors during the optimization process. In order to investigate influence of different combinations of weight coefficients on the optimal layout, 12 groups of combinations of weight coefficients are designed and analyzed. The results show that the optimal layout method of isolation bearings based on the artificial intelligence algorithm has good convergence efficiency of optimization and makes it possible to search more practical isolation scheme with good performance. When focusing on total cost of bearings, the ideal weight coefficient of the total cost would be larger than 0.4. While the structural performance factors are mainly considered, the weight coefficient of the maximum story drift ratio or seismic decrease coefficient should be larger than 0.2. For factors that designers pay more attention to, the corresponding weight coefficient should be larger than others.

Microvibration transfer and suppression of satellite under multi-source coupling disturbances based on energy flow analysis

The accuracy of satellites is extremely dependent on the control of the micro-vibration while the transmission paths among multiple vibration sources are complex. To reduce the impact of micro-vibration on the payloads of satellites effectively, the transmission characteristics of micro-vibrations under multi-source disturbances were analyzed, and a specific vibration suppression scheme was proposed. Based on the theoretical derivation and energy flow analysis method, the coupling transmission characteristics of micro-vibrations in the satellite under single- and multi-source disturbances were compared. The transmission characteristics of the vibration in the satellite under multi-source disturbance were obtained to determine the main transfer path. The contributions of different waveforms for elastic waves generated by vibration, namely bending wave, longitudinal wave and shear wave, to the target point were obtained by calculating the net transfer ratio to find out the dominant transfer waveform of the vibration. The vibration along the main transmission path was blocked by means of stiffened plates and an optimal vibration isolation scheme was determined by comparing the fluctuations in the vibrational energy of the payload under various stiffened ways. The results showed that the vibration energy under multi-source disturbances could not be obtained by the superposition of that under the single source. The longitudinal wave was the dominant transfer waveform of vibration with the energy to the payload accounting for 92.26%. The optimal vibration isolation treatment on the main transmission path can reduce the vibration by 79.25% on average, up to one order of magnitude.

Noise protection from diesel generator units in a residential construction territory

Introduction: The article deals with the issues of protection against noise and vibrations of engineering equipment, which spread into the residential area through ventilation shafts, and the problems of bringing noise to standards during the operation of diesel generators. The purpose of this work was the development and implementation of methods and means to reduce the vibration levels of the walls of the technological room in which the diesel generator set was installed. Materials and Methods: The article presents studies using computational and graphical and resonance and statistical methods. Measurements of the noise level from the operation of a diesel generator located on the site of the residential buildings under consideration, as well as in residential premises, were carried out. Results and Discussion: The estimated calculation showed that the noise levels on the territory do not meet the requirements of sanitary standards. The results of measurements of the sound pressure level before and after noise protection measures for an individual living space gave an assessment of the qualitative and quantitative ratio of the accepted and new types of measures and materials. Conclusions: The effectiveness of vibration isolation of engineering equipment depends on the applied vibration isolation scheme; the wrong choice of vibration isolation scheme can lead to an uncontrolled increase in the amplitude of vibrations of the foundation of engineering equipment. To eliminate low frequencies, it is necessary to install vibration isolating supports under the foundation of the diesel generator set.

Robust Data-Driven Design for Fault Diagnosis of Industrial Drives

Due to the presence of actuator disturbances and sensor noise, increased false alarm rate and decreased fault detection rate in fault diagnosis systems have become major concerns. Various performance indexes are proposed to deal with such problems with certain limitations. This paper proposes a robust performance-index based fault diagnosis methodology using input–output data. That data is used to construct robust parity space using the subspace identification method and proposed performance index. Generated residual shows enhanced sensitivity towards faults and robustness against unknown disturbances simultaneously. The threshold for residual is designed using the Gaussian likelihood ratio, and the wavelet transformation is used for post-processing. The proposed performance index is further used to develop a fault isolation procedure. To specify the location of the fault, a modified fault isolation scheme based on perfect unknown input decoupling is proposed that makes actuator and sensor residuals robust against disturbances and noise. The proposed detection and isolation scheme is implemented on the induction motor in the experimental setup. The results have shown the percentage fault detection of 98.88%, which is superior among recent research.

Fault detection and isolation for a class of uncertain nonlinear systems: A dual-monitoring model-based approach

This paper presents a fault detection and isolation (FDI) scheme for a class of uncertain nonlinear systems with unknown faults, in which fault isolation process and control reconfiguration are integrated via a supervisory switching strategy. A group of adaptive estimators is performed together with the switching process. The proposed FDI approach, namely dual-monitoring model-based approach, can exploit information both from backstepping procedure and estimators, by which a set of monitoring functions is constructed to detect the occurrence of fault and also identify the specific fault type. In particular, based on some principles, the fault isolation process can be accelerated under a novel interacted isolation scheme. It can be seen that the tracking error can be always guaranteed within a prescribed performance in the existence of system faults.

High speed fault detection and localization scheme for low voltage DC microgrid

In this paper, a new differential protection scheme based on the sensitivity of the relay is proposed for fault detection and location estimation in DC microgrid having different renewable energy sources (RESs) namely PV, wind and battery. The sensitivity of each relay, connected at the bus terminal of the microgrid, is determined by using the magnitude of currents flowing through the cables. Once, Sensitivity factor (S-factor) for each relay is calculated, proposed scheme detects the fault by comparing S-factor of each relay with predefined threshold value. Further, the fault location is determined by measuring voltage and current at both ends of the faulty cable. The effectiveness of the proposed scheme is validated on a 380 V ring-type DC microgrid simulated under various fault conditions with different fault resistance values and at different fault locations. The simulation results obtained under different operating conditions indicate high selectivity and high speed of operation (less than 1.2 ms) of the proposed scheme for fault detection and isolation of faulty part. The proposed scheme ensures the effectivness and reliability when compared with other schemes mentioned in the literature.

Comparative Analysis of Potential Determinants of Resistance to Aminoglycosides in <i>Burkholderia pseudomallei</i> Strains with Different Level of Sensitivity to Gentamicin

The aim of the study was to identify and compare potential determinants of aminoglycoside resistance in gentamicin susceptible Burkholderia pseudomallei strains.Materials and methods. A bioinformatics analysis of whole genome shotgun sequences of three B. pseudomallei strains having different levels of sensitivity to gentamicin was carried out.Results and discussion. B. pseudomallei is intrinsically resistant to aminoglycosides. Such strains, as a rule, are not taken into account in the classical scheme of isolation and identification. At the same time, there were no significant differences in the clinical manifestations of melioidosis during infection with gentamicin-resistant and sensitive strains. In B. pseudomallei strains of different sequence types (ST70, ST948, and ST1566), point missense mutations were found in the genes of three efflux pumps of the RND family: AmrAB-OprA, BpeAB-OprB, BpeEF-OprC, and one with unknown functions, as well as in the gene aminoglycoside-6’-N-acetyltransferase AAC(6’)-III. All three strains had amino acid substitutions in the AmrA periplasmic linker: ARG160SER, Arg116Gln and Gly237Arg, Thr317Lys, respectively. In moderately sensitive strains (ST948 and ST1566), an identical Val222Met substitution was found in the repressor of the AmrAB-OprA operon, AmrR. It is likely that the intermediate level of sensitivity to gentamicin in the studied strains is mediated by the constitutive expression of the AmrAB-OprA operon, which partially compensates for the structural defects. It is also possible that a dinucleotide deletion in the AAC (6’)-III aminoglycoside-6’-N-acetyltransferase gene, as well as detected mutations in the homologues of the periplasmic linker (BPSL2234) of an uncharacterized efflux operon of the RND family, are involved in the loss of resistance to gentamicin.

Co-Evolutionary Location-Routing Model of Medical Isolation Areas for Major Public Health Emergencies Considering the Uncertainty of Future Traffic Environment

With the continuous development of the COVID-19 pandemic, the selection of locations for medical isolation areas has not always been optimal for the timely transportation of infected people, or those suspected of being infected. This has resulted in failure to control the rate of spread of infection cases in time. To address this problem, this paper proposes a co-evolutionary location-routing optimization (CELRO) model of medical isolation areas for use in major public health emergencies to develop a rapid location-routing scheme for epidemic isolation, including the selection of locations of medical isolation facilities per area and the optimal route per vehicle to each infected person. Specifically, this paper solves the following two sub-problems: (i) calculate the shortest transportation times and corresponding routes from any medical isolation area to any person infected or suspected of being infected, and (ii) calculate the location scheme for distribution of isolation areas. Different from previous studies, the vehicle operating characteristics and the interference of uncertainty of the traffic environment are considered in the proposed model. To find an appropriate scheme for location of medical isolation areas with the shortest travel times, a co-evolutionary clustering algorithm (CECA), which is a combination of some separated evolutionary programming operations, is proposed to solve the model. Various network sizes and uncertainty combinations are used to design some comparative tests, which aim to verify the effectiveness of the proposed model. In the experiment section, CELRO reduced travel time by at least 14% compared with other methods. This finding can provide an effective theoretical basis for optimizing the spatial layout of medical isolation areas or the location planning of new medical facilities.

Electrochemical Enrichment and Isolation of Electrogenic Bacteria from 0.22 µm Filtrate.

Ultramicrobacteria (UMB) that can pass through a 0.22 µm filter are attractive because of their novelty and diversity. However, isolating UMB has been difficult because of their symbiotic or parasitic lifestyles in the environment. Some UMB have extracellular electron transfer (EET)-related genes, suggesting that these symbionts may grow on an electrode surface independently. Here, we attempted to culture from soil samples bacteria that passed through a 0.22 µm filter poised with +0.2 V vs. Ag/AgCl and isolated Cellulomonas sp. strain NTE-D12 from the electrochemical reactor. A phylogenetic analysis of the 16S rRNA showed 97.9% similarity to the closest related species, Cellulomonas algicola, indicating that the strain NTE-D12 is a novel species. Electrochemical and genomic analyses showed that the strain NTE-D12 generated the highest current density compared to that in the three related species, indicating the presence of a unique electron transfer system in the strain. Therefore, the present study provides a new isolation scheme for cultivating and isolating novel UMB potentially with a symbiotic relationship associated with interspecies electron transfer.

How to Isolate Non-Public Networks in B5G: A Review

Non-public networks (NPNs) have drawn much attention due to their flexibility and efficiency with B5G. According to the requirements of various application scenarios, NPNs can be tailored to a number of deployments, sharing the B5G system totally or in part. The isolation of NPNs is a critical issue. This paper provides a survey of isolation schemes for B5G NPNs. First, we present an overview of various deployments and the corresponding isolation demands for B5G NPNs. To meet these isolation demands, three kinds of NPN isolation—i.e., spectrum isolation, RAN isolation and CN isolation—are discussed. Then, the corresponding isolation technologies are introduced and analyzed. Finally, open research challenges, such as wireless throughput capacity with spectrum isolation, operation with isolation requirements and data isolation of software-defined CN for B5G NPNs, are discussed.

B-type Proanthocyanidins with Dentin Biomodification Activity from Cocoa (Theobroma cacao).

To enable translational studies, a scalable preparative isolation scheme was developed for underivatized cocoa (Theobroma cacao) proanthocyanidins (PACs), affording six all-B-type oligomeric PACs, including a new tetramer 4. Their structures, including absolute configuration, were unambiguously established by comprehensive spectroscopic and chemical methods. Evaluation of the PACs' dentin biomodification properties employed dynamic mechanical and infrared spectroscopic analyses in dentin bioassay models. PAC treatment enhanced the biomechanical strength of dentin by 5- to 15-fold compared to untreated dentin. Among the PAC agents, the pentamer, cinnamtannin A3 (6), led to the highest complex modulus value of 131 MPa, whereas the "branched" tetramer, 4, showed the lowest, yet still significant bioactivity. This study of specifically singly linked medium-length oligomeric PACs indicates that the linkage site is paramount in determining the potency of these PACs as dentin biomodifiers.

ML-Based Delay Attack Detection and Isolation for Fault-Tolerant Software-Defined Industrial Networks.

Traditional security mechanisms find difficulties in dealing with intelligent assaults in cyber-physical systems (CPSs) despite modern information and communication technologies. Furthermore, resource consumption in software-defined networks (SDNs) in industrial organizations is usually on a larger scale, and the present routing algorithms fail to address this issue. In this paper, we present a real-time delay attack detection and isolation scheme for fault-tolerant software-defined industrial networks. The primary goal of the delay attack is to lower the resilience of our previously proposed scheme, SDN-resilience manager (SDN-RM). The attacker compromises the OpenFlow switch and launches an attack by delaying the link layer discovery protocol (LLDP) packets. As a result, the performance of SDN-RM is degraded and the success rate decreases significantly. In this work, we developed a machine learning (ML)-based attack detection and isolation mechanism, which extends our previous work, SDN-RM. Predicting and labeling malicious switches in an SDN-enabled network is a challenge that can be successfully addressed by integrating ML with network resilience solutions. Therefore, we propose a delay-based attack detection and isolation scheme (DA-DIS), which avoids malicious switches from entering the routes by combining an ML mechanism along with a route-handoff mechanism. DA-DIS increases network resilience by increasing success rate and network throughput.

Deformation‐based design of seismically isolated bridges

AbstractA performance‐based design procedure is proposed for seismically isolated bridges with/without supplemental energy dissipation devices. Considering multiple performance levels (PLs), the proposed method initially identifies the critical hazard level and “near‐optimal” alternatives of the isolation system. Both performance and economy are evaluated based on the inelastic response of reduced‐degree‐of‐freedom (RDOF) isolation and energy dissipation systems. Nonlinear response history analysis (NLRHA) of the multi‐degree‐of‐freedom (MDOF) system is employed in successive design steps, corresponding to different PLs, to refine the design solution through the control of a broad range of material strains and deformations. The above characteristics aim to deliver a rigorous and broadly applicable design method that reduces the high computational effort characterising complex design frameworks, while addressing identified deficiencies of alternative displacement‐based methods. The efficiency of the proposed design methodology is demonstrated by applying it to an actual bridge that was previously designed for ductile behaviour. Alternative isolation and energy dissipation schemes are investigated. Assessment of the design through NLRHA reveals in all cases enhanced seismic performance and cost reduction in the substructure design, thus rendering base‐isolation an appealing design alternative.

Dynamic and sensor fault tolerant control for an intensified heat-exchanger/reactor

In this paper, an active fault tolerant control system is proposed and applied to a new intensified heat exchanger/reactor system. This method consists of an adaptive observer-based fault detection, isolation, and identification scheme and a control law redesign method based on the backstepping approach. The objective of the application of the fault tolerant control system is to ensure the safety and productivity of this intensified heat exchanger/reactor even in the presence of a fault. Both parameter and sensor faults are considered. The effectiveness of the fault tolerant control method based on adaptive observers is validated by simulations on the heat exchanger/reactor system.

On-Orbit Implementation of Discrete Isolation Schemes for Improved Reliability of Serial Communication Buses

Serial communication buses are used in electronic systems to interconnect sensors and other devices, but two of the most widely used protocols, i.e., interintegrated circuit (I2C) and serial peripheral interface (SPI), are vulnerable to bus-wide failure if even one device on the bus malfunctions. For aerospace applications demanding increasingly more distributed processing and sensing capability, the compounding risk to system reliability as device count scales becomes a limiting factor in mission scope, performance, and lifetime. We propose a simple external circuit to be added to each node on a communication bus that automatically isolates the node in the event of device failure. By automatically isolating failed devices, the integrity of the bus is preserved without requiring additional signals or processing overhead from the host controller. In this article, I2C and SPI isolation circuits are simulated, fabricated, and experimentally verified to be effective at preserving bus integrity in the event of peripheral device failure. The isolation circuits were integrated into three spacecraft for the successful NASA V-R3x mission and found to significantly improve system reliability by eliminating single-point failure modes of the I2C and SPI buses. The developed protection schemes are a valuable tool for decoupling system reliability from serial bus device count and can readily be integrated into the existing aerospace systems.

A Dynamic-State-Estimator-Based Tolerance Control Method Against Cyberattack and Erroneous Measured Data for Power Systems

Cyberattacks against measured variables and faulty metering devices are among the most important threats to modern systems that should be detected and isolated, and the control actions based on the measured variables should be appropriate in order to keep the power system security. This article proposes a dynamic-state-estimation-based cyberattack-tolerant control method for modern power systems. The proposed method involves two new schemes: one is for dynamically detecting the cyberattack and the other isolates the location of the attack. These schemes are based on dynamic observer designs that can eliminate the effects of unknown inputs. This article also proposes a fault-tolerant control technique using these observer-based detection and isolation schemes. The proposed method can accurately track dynamic states, detecting both cyberattack against measured variables and faulty measuring devices, and isolating the cyberattack and fault locations. The results verify its superiority in comparison with other techniques.

An Improved Protection Scheme for DFIG-Based Wind Farm Collector Lines

The conventionally used single-ended overcurrent relaying schemes find limitation in providing secured protection to large-scale wind farm medium voltage collector lines due to sensitivity and selectivity problems. In this paper, a two criteria-based improved relaying algorithm is proposed for effective protection of these collector lines. In the proposed method, the faulted line is identified first in a multi-feeder collector line of a doubley-fed induction generator (DFIG)-based wind farm using the transient energies derived from the voltage and current measurements near the collector substation bus. Once the faulted collector line is identified, then a time-time transform assisted fault classfication technique is proposed using only the current measurements of the faulted collector line. The efficacy of the relaying algorithm is validated on numerous fault and non-fault test cases simulated on different collector lines of DFIG-based grid-connected wind farm test system and modified IEEE 39-bus New England system through MATLAB/Simulink®. The algorithm is also implemented on OPAL-RT (OP4510) make real-time digital simulation platform. The simulation results justify the applicability of the proposed relaying scheme for effective detection, classification and isolation of faults in wind farm collector lines.

Design Methodology for Robust Model-Based Fault Diagnosis Schemes and its Application to an Aircraft Hydraulic Power Package

In a system’s design phase, where knowledge about the actual behavior of the system is shallow, the design of an efficient and robust system diagnostics is a complex task. In order to simplify this process, this paper presents a modelbased methodology for the design of fault diagnosis schemes. The methodology analyzes the structure of available behavioral models of the system and proposes minimal sets of sensors to fulfill diagnostic requirements. In order to choose an optimal set of sensors, the method evaluates the sets in terms of costs and diagnostic robustness. The proposed fault detection, isolation and identification schemes rely on the robust evaluation of model-based residuals using Monte-Carlo methods and highest density regions to account for measurement and parameter uncertainty. To show the design capabilities, the presented method is applied to an aircraft hydraulic power package and the resulting schemes are tested on a real test rig.

Reinforcement learning-based integrated active fault diagnosis and tracking control

Reliable and real-time active diagnosis of system faults with uncertainties is strongly dependent on the input design. This paper establishes a data-driven framework for integrated design of active fault diagnosis and control while ensuring the tracking performance. To be specific, the input design is formulated as a constrained optimization problem that can be solved with the aid of constrained reinforcement learning algorithms. Moreover, based on the maximum mean discrepancy metric, a novel active fault isolation scheme is proposed to implement model discrimination using system outputs. At the end, the effectiveness of the proposed approach is evaluated in two case studies in the presence of probabilistic disturbances and uncertainties.

DC motor fault detection and isolation scheme with the use of directional residual set

The subject of research is presented as online-estimation of characteristics of DC motors under various loads. The paper is devoted to a modern approach to solve the problem of detecting DC motor failures. Proposed detection method is based on the set of full state Luenberger observers. Isolation scheme uses directional residual set and relationships between fault direction and residual vector. The procedure of synthesizing the fault detection and isolation algorithm for DC motor is designed. This scheme performance is proved with computer modeling of typical DC motor RK 370CA with faults caused by unaccounted force momentum acting on rotor, input voltage disturbance, velocity and current sensors failures. The algorithm correctly defines motor state (fault presence or absence) and also properly isolates fault cause. Proposed method advantage is compared to other solutions based on hardware and timing redundancy, identification and observers lies in the opportunity to detect and isolate faults of input and output signals with trivial synthesis and absence of the need to expand system hardware. Proposed method is applicable to any second order system, and also there is a possibility to use it for higher order systems with the corresponding changing of the equation systems solving for observer synthesis. This algorithm allows realizing online fault isolation and does not require additional measuring which promotes decrease of diagnostic costs, repair and serving time saving, modern accident detection. The results can be applied to DC motor control to increase reliability and to develop DC motor control systems.