Redundant System Research Articles

Robust Geometry Self-Calibration Based on Differential Kinematics for a Redundant Robotic Inspection System

Robust Geometry Self-Calibration Based on Differential Kinematics for a Redundant Robotic Inspection System

A Comprehensive Reliability Strategy for Managing Assets of Redundant Customer Delivery Systems

A reliability strategy was developed in 2020 for the purpose of improving the reliability of the dual element spot network (DESN) stations. The strategy utilized the transmission outage data system (TODS) data-base and some reliability models to identify DESN stations with the worst reliability performance so that investment dollars can be directed towards the reliability improvement of those stations. Recently, a comprehensive reliability strategy has been developed to do a similar task of improving the overall reliability of the DESN stations. The new strategy first maps the delivery point interruption data to the TODS outage data to determine the frequencies of the main causes of supply interruptions to delivery points. Then, it identifies action plans (or remedial actions) that are needed in order to reduce the frequencies of the dominant outage causes. Finally, the strategy uses a benefit/cost analysis to select the preferred action plans in order to improve the overall reliability of the DESN stations. The new strategy is more practical and has numerous advantages over the existing one. The purpose of this paper is to describe the new reliability strategy, its advantages over the existing one and to show how to apply it in the DESN stations.

Distributed Collaborative Control of Redundant Robots Under Weight-Unbalanced Directed Graphs

In consideration of the limitation of the communication and the possibility that redundant robots might deliver information at different power levels, cases under weight-unbalanced directed graphs from the network topology perspective are in larger accordance with those in multiple redundant robot systems. By moving forward along this direction, a distributed controller is proposed in this paper to handle circumstances of collaborative control of multiple redundant robots under weight-unbalanced directed graphs. This kind of control problem is modelled into generalized quadratic programming (QP) problems with equality and inequality constraints. Then, the above QP problems are solved by a proposed neural-dynamics-based method, whose stability and convergence are theoretically proved subsequently. Besides, several experimental examples are conducted, and related comparisons are provided to demonstrate the feasibility of the proposed controller.

Multi-cloud resource scheduling intelligent system with endogenous security

<abstract> <p>A secure and reliable intelligent multi-cloud resource scheduling system in cyberspace is especially important in some industry applications. However, this task has become exceedingly challenging due to the intricate nature of information, the variety of knowledge representations, the compatibility of diverse knowledge reasoning engines, and the numerous security threats found in cloud networks. In this paper, we applied the endogenous security theory to the multi-cloud resource scheduling intelligent system and presented a novel model of the system. The proposed model incorporates various knowledge representations and inference engines, resulting in a multi-cloud resource scheduling intelligent system that ensures endogenous security. In addition, we have devised a scheme for an intelligent system that schedules multi-cloud resources using dual-channels and has an endogenous security mechanism, which we have named Dynamic, Heterogeneous, and Redundant (DHR). Finally, we have used the multi-cloud resource scheduling intelligent run log database to carry out numerous experiments to validate the efficiency of the dual-channel redundant reasoning system with the endogenous security mechanism's DHR property. The results of the experiment demonstrated that the multi-cloud resource intelligent scheduling system model with an endogenous security mechanism was superior to the current single-channel inference system scheme in regards to security and reliability.</p> </abstract>

Estimation of the parameters of triple modular redundancy system under step partially accelerated life tests using Frechet distribution

Triple modular redundancy system (TMR) is repetition of important components or functions of the system. It aims to increase the reliability and reducing the failure rate. This study is focused on the estimating of the distribution’s parameters of the "TMR system" under the partly life test with gradual stress, as it included every component in the system that follows The Frechete distribution. This research aimed to analysis the reliability of this triple modular system. The optimal time for stress change was determined using two criteria according to the accelerated stress strategy under the new distribution, as well as estimating the reliability of the system by using the maximum likelihood (MLE) method. The efficiency of the " MLE" in estimate the parameters of the new distribution is one of the most important conclusions in this study. Therefore, the design of the "TMR” system can have a lengthy lifetime and higher safety, reducing the risks of unexpected failure and the economic losses.

Green hospitals face to climate change: Between sobriety and resilience

Climate change poses a critical challenge to global health, influencing social and environmental determinants such as housing, air and water quality, and food security. This article explores the profound impact of climate change on health, projecting an additional 250,000 annual deaths from various climate-related diseases between 2030 and 2050. Healthcare systems significantly contribute to global carbon emissions. The concept of the “Green Hospital” is introduced as a paradigm shift in healthcare, focusing on optimizing resource efficiency and minimizing environmental impact. This concept encompasses renewable energy integration, natural lighting, sustainable materials, green roofs, and smart building management systems. Several challenges remain major, such as medical waste management, water conservation, chemical use, pollution, and plastic usage in healthcare settings. Moreover, obstacles to green hospital initiatives should be resolved, including system redundancy, regulatory compliance, operational demands, financial constraints, and cultural resistance. Conclusively, an urgent reformation of healthcare systems is needed to align with eco-friendly and sustainable practices, highlighting the necessity to reduce CO2 emissions and manage resources and waste more effectively to meet the evolving health needs of a growing and aging global population.

Monitoreo de la confiabilidad del sistema hombre-máquina del área de mecanizado mediante la distribución de Weibull

This publication presents the development of a method that seeks to monitor the parameters β (shape) and η (scale) for each component-subsystem combination following the Weibull distribution, necessary for the calculation of the reliability of the man-machine system in the machining area. This system defines the workshops of the metal-mechanic, with high-mix and low-volume batch production where conventional and Computerized Numerical Control (CNC) machines are involved, which share the manufacturing of parts that sometimes are unique, or their manufacturing period is short. The design of the man-machine system is based on the analysis of the failures of non-conforming parts in the machining area and on the failure rates, which the statistical model is developed for its evaluation, considering the 2-parameter Weibull distribution, and a redundant system with series-parallel configuration. The results obtained were based on the theoretical-practical, using mathematical and statistical models, as well as the Study Case. With the use of mathematical and statistical models, it is demonstrated that the probability of failure (risk) of the man-machine system is time-dependent and is generated by mechanical type stresses, which occur in the manufacture of parts.

A genetic algorithm for cost optimization in queueing models of machining systems with multiple working vacation and generalized triadic policy

This study presents a generalized approach for implementing the Triadic control policy in queueing modeling of a redundant machining system with multiple servers. The machining system further integrates a policy for servers that allows for multiple working vacations. The fluctuation of active servers is based on the count of accumulated failed machines in the system. This alteration occurs individually at every stage of service completion or the arrival of a failed machine. The recursive approach is employed to generate analytical closed-form solutions of the system in terms of steady-state probabilities. The performance metrics of the system are determined, and their response to varying system parameters is demonstrated through tables and graphs. A cost function is proposed for the system and subsequently examined with different configurations. A Genetic Algorithm technique is used to acquire the most optimal input parameters to minimize the cost function.

Design and implementation of a redundant control system for variable speed hydro generators

Hydro plant control system (HPCS) has gained a high level of attention in recent years because of their flexibility, reliability, and easy-to-use. This paper analyzes the performance of a 250 MW doubly-fed induction machine (DFIM) under different speed sensor faults (omission, gain, and saturation) that will clarify the need for technically feasible redundancy. The control redundancy, which consists of fault detection, speed estimation, and reconfiguration circuit, is implemented to enhance the permanence and reliability of the DFIM. The logic-based fault detection technique is implemented to detect the speed sensor fault. A second-order sliding mode controller (SOSMC) based model reference adaptive system (MRAS) estimator is implemented to estimate the rotor speed. The proposed redundancy circuit is modeled for a 250 MW hydrogenerating unit using the MATLAB/Simulink environment. It is observed that the proposed redundancy circuit is robust against uncertainty in the machine parameters. Experimental validation is performed in a scaled-down laboratory prototype. The simulation and experimental results demonstrate the efficacy of the proposed redundancy circuit. Fault detection and reconfiguration of the control redundancy circuit are performed within 20 ms.

An Improved Fault Detection and Isolation Method for Airborne Inertial Navigation System/Attitude and Heading Reference System Redundant System

The integrity of airborne inertial navigation systems (INSs) is the key to ensuring the safe flight of civil aircraft. The airborne attitude and heading reference system (AHRS) is introduced into the construction of a redundant inertial navigation system. As a backup system for an airborne INS, the AHRS exhibits a different device performance. A sequential weighted generalized likelihood ratio test (SWGLT) method, based on a principal component parity vector (PPV), is proposed. The PPV method improves the adaptability of the detection threshold to the inertial sensors’ noise and improves the probability of correct detection. At the same time, the multiscale problem of a heterogeneous redundant system error is solved by sequential weighting, and the false alarm rate is reduced. Simulation experiments show that the proposed method can improve fault detection sensitivity, reduce false alarm rates, and ensure the integrity of civil aircraft navigation systems.

An Open-Source Wireless Electrophysiology System for In Vivo Neuronal Activity Recording in the Rodent Brain: 2.0.

Current trends in neurobiological research focus on analyzing complex interactions within brain structures. To conduct relevant experiments, it is often essential to employ animals with unhampered mobility and utilize electrophysiological equipment capable of wirelessly transmitting data. In prior research, we introduced an open-source wireless electrophysiology system to surmount these challenges. Nonetheless, this prototype exhibited several limitations, such as a hefty weight for the wireless module, redundant system components, a diminished sampling rate, and limited battery longevity. In this study, we unveil an enhanced version of the open-source wireless electrophysiology system, tailored for in vivo monitoring of neural activity in rodent brains. This new system has been successfully tested in real-time recordings of in vivo neural activity. Consequently, our development offers researchers a cost-effective and proficient tool for studying complex brain functions.

Numerical Investigation of a Floating-Type Support Structure (Tri-Star Floater) for 9.5 MW Wind Turbine Generators

A numerical investigation of floating-type substructures for wind turbine generators was conducted by using time-domain simulation. A Tri-Star floater for 8–10 MW generators, which was developed by Samsung Heavy Industries (SHI), was chosen as the floating substructure. To make the anchor system, catenary mooring lines, considering redundancy, were installed on the floater. The main sources of external force on the wind turbine generator are wind, waves, and currents. To consider severe environmental conditions, Design Load Cases (DLCs) 1.6 and 6.1 of the IEC guidelines (IEC 61400-3-1) were chosen. From the measured environmental data for the installation site, the main parameters for the simulation conditions were obtained. The tilt angle and horizontal movement of the floater and the mooring tension for the different mooring systems were checked. The response of the floater during the failure of the mooring was also studied, and the critical failure of the mooring was confirmed. During the failure of the mooring, the redundancy system worked well, in which the movement of the floater was constrained within the criteria for all scenarios.

Game Analysis and Optimization for Evolutionary Dynamic Heterogeneous Redundancy

Dynamic Heterogeneous Redundancy (DHR) has been considered as a proactive defense architecture against unknown vulnerabilities and backdoors. It is a heterogeneous, fault-tolerant, and redundant system, which ensures the security by constantly switching heterogeneous executors. However, a limited number of heterogeneous executors can be merely switched and combined statically. It is difficult to cope with persistent threats. In this paper, we propose an evolutionary DHR system, add evolutionary sub-strategies of executors to solve this problem, optimizing defense mechanisms of DHR. To demonstrate theoretical validity, a game-theoretic analysis of the DHR security mechanism is performed under dynamic incomplete information, and the dilemma of defense is discussed. We construct a DHR game model based on evolutionary, and the results are extended to the general case to analyze the Bayesian equilibrium when each service strategy has a different number of evolved sub-strategies. In addition, the correlation factor is added to the game to investigate the impact of the correlation between different heterogeneous executors on defense results. Finally, Gambit and NS2 simulation experiments for the proposed method are shown. To verify the applicability of the physical system, a prototype DHR system based on dynamic evolution was constructed. We collect key configuration information and modified them randomly. It ensures that the information scanned by the attacker is different each time. Finally, the effectiveness of the physical system is verified by nmap and metasploit tools.

Profit Analysis of a k-out-of-n: G Redundant System with Conditional Repair and Service Facility: Toxic Waste Incinerator Application

Profit Analysis of a k-out-of-n: G Redundant System with Conditional Repair and Service Facility: Toxic Waste Incinerator Application

Research on Fault-tolerant Control Allocation Technology for X-rudder UUV

X-rudder UUV is a typical redundant control system with high reliability and high control difficulty. This article researches the reconfigurable control allocation technology of X-rudder UUV control, analyzes and sorts out typical fault types of X-rudder UUV, and designs a reconfigurable control allocation algorithm without changing the high-level control law. In the case of partial failure of the rudder surface, the remaining rudder surface is used to complete the movement of UUV, improving the robustness of UUV to faults and damage. The effectiveness of the proposed fault-tolerant control allocation method is verified by simulation.

Markov-based reliability model for a mixed redundant system and parallel genetic algorithm with knowledge archives for a redundancy allocation problem

Markov-based reliability model for a mixed redundant system and parallel genetic algorithm with knowledge archives for a redundancy allocation problem

Analyzing the Effects of Repairman Failure in Stochastic Models of Non-Identical Redundant Systems

A stochastic analysis is presented here of a repairable system containing two non-identical units, one of which is a duplicate and the other is a main unit. When the units are operative, they have a direct complete failure. During his work with the main unit, a single repairman may encounter problems that may cause his work to fail. During the repair of the duplicate unit, the repairman encounters no problems. Duplicate units receive priority for repair and operation over primary units. After receiving treatment, the repairman can perform his duties with full efficiency. For failure rates of the units, negative exponential distributions were used, while for repair and treatment rates, arbitrary distributions were used. The semi-Markov process and regenerative point technique studied various possible transition states. The reliability characteristics of the system model have been examined numerically and graphically for various parameter values. The profit of the system has also been analyzed for some fixed values of repair and other maintenance costs.

Robust in-vehicle heartbeat detection using multimodal signal fusion

A medical check-up during driving enables the early detection of diseases. Heartbeat irregularities indicate possible cardiovascular diseases, which can be determined with continuous health monitoring. Therefore, we develop a redundant sensor system based on electrocardiography (ECG) and photoplethysmography (PPG) sensors attached to the steering wheel, a red, green, and blue (RGB) camera behind the steering wheel. For the video, we integrate the face recognition engine SeetaFace to detect landmarks of face segments continuously. Based on the green channel, we derive colour changes and, subsequently, the heartbeat. We record the ECG, PPG, video, and reference ECG with body electrodes of 19 volunteers during different driving scenarios, each lasting 15 min: city, highway, and countryside. We combine early, signal-based late, and sensor-based late fusion with a hybrid convolutional neural network (CNN) and integrated majority voting to deliver the final heartbeats that we compare to the reference ECG. Based on the measured and the reference heartbeat positions, the usable time was 51.75%, 58.62%, and 55.96% for the driving scenarios city, highway, and countryside, respectively, with the hybrid algorithm and combination of ECG and PPG. In conclusion, the findings suggest that approximately half the driving time can be utilised for in-vehicle heartbeat monitoring.

Robust in-vehicle respiratory rate detection using multimodal signal fusion

Continuous health monitoring in private spaces such as the car is not yet fully exploited to detect diseases in an early stage. Therefore, we develop a redundant health monitoring sensor system and signal fusion approaches to determine the respiratory rate during driving. To recognise the breathing movements, we use a piezoelectric sensor, two accelerometers attached to the seat and the seat belt, and a camera behind the windscreen. We record data from 15 subjects during three driving scenarios (15 min each) city, highway, and countryside. An additional chest belt provides the ground truth. We compare the four convolutional neural network (CNN)-based fusion approaches: early, sensor-based late, signal-based late, and hybrid fusion. We evaluate the performance of fusing for all four signals to determine the portion of driving time and the signal combination. The hybrid algorithm fusing all four signals is most effective in detecting respiratory rates in the city (P = 62.42), highway (P = 62.67), and countryside (P = 60.94). In summary, 60% of the total driving time can be used to measure the respiratory rate. The number of signals used in the multi-signal fusion improves reliability and enables continuous health monitoring in a driving vehicle.

Fault Mode Analysis and Convex Optimization-Based Fault-Tolerant Control for New Type Dissimilar Redundant Actuation System of Near Space Vehicle

A new type dissimilar redundant actuation system (NT-DRAS), which is composed of an electro-hydrostatic actuator (EHA) and an electro-mechanical actuator (EMA), is applied in high value unmanned aerial vehicles such as the future near space vehicles to improve their reliability and performance index simultaneously. Further improvement in the flight safety is achieved with the fault-tolerant control (FTC) technique which deals with system faults. This paper proposes a novel convex optimization-based fault-tolerant control (CO-FTC) strategy for the NT-DRAS subject to gradual faults which are included in the state space representation of the system. A convex analysis-based treatment for system uncertainty caused by gradual faults is applied to determine the control gain matrix. The existence condition of the control gain matrix is optimized in the linear matrix inequality (LMI) form. Finally, the determined subsystems based on the novel technique is used to solve the modeled robust FTC problem. Case studies of NT-DRAS subject to different gradual faults have been accomplished to illustrate the FTC necessity for NT-DRAS. Furthermore, the effectiveness of the proposed CO-FTC strategy is validated by comparative analysis of the simulation results.