Self-recovery System Research Articles

A Review on MPC Based Self Recovering Intelligent Advance Meter for Smart Grid: Scheme and Challenges

The Model Predict Control (MPC) based Intelligent Advance Metering (IAM) is a core maneuver of future smart grids (SG). SG is the advanced generation of electric power and utility system that improve operation technology (OT) and information technology (IT) to provide nonstop, self-recovery, self-configuration, low-cost, and security-based electricity to the consumer in real-time. Smart metering (SM) allows SG to connect the electric, gas, and oil utilities through sensors. Power plants, consumers, and utility companies will be received real-time wireless control IAM with fifth generation (5G) network technology. The aim of 5G network technology is to enable power grid digitalization (PGD) and facilitate the (IOT) Internet of Things for the future advance SG with benefits such as high-rate public safety, low latency, ultra-high speed, large number of connectivity, and reliability. In this paper, we analyze future predictions about energy needs by using MPC, fast self-recovery system, self-configuration, and upgradation, better performance of service provider, faster power connecting after an outage, control electric theft, minimize electric leakage, a large number of wireless connecting of IAM home-based, and real-time monitoring via human machine interface (HMI) and for customer end IAM operation over 5G networks to reduce billing price, reduce meter cost, lower outage cost, and as well as personalized control over electricity consumption and future challenge in this area.

Design and Development of Automated Self Recoverable Drone

This paper presents a smart self-recoverable drone equipped with advanced sensors, computing capabilities, and a fault detection and self-recovery system that enables it to operate autonomously and recover from unexpected situations. The system involves the integration of various advanced technologies and sensors, such as Spring assistance ejection, Manual disbalancing propeller, Solar recharge and Manual thread control, to enable the drone to avoid getting stuck in real-time. The paper evaluates the execution of the drone through extensive simulations and concludes that it is highly effective in completing difficult tasks with high precision and efficiency. Future research includes developing a drone recovery and damage control technology that will save humankind from suffering a severe loss.

Bionic Artificial Self-Recovery Enables Autonomous Health of Machine

This paper explores Engineering self-recoveries theory, which emerged from the research of Bionics to meet the great demand of modern high-risk process manufacturing and the development of aerospace vehicles. Bionics opens a new era in which artefact s learn from natural objects. With the rapid development of the industrial Internet and Artificial intelligence technology, we have gained a deep understanding of the law of fault generation and development, which provides an opportunity for the emergence of Engineering self-recoveries theory. Engineering self-recoveries expands the research field of Cybernetics and Engineering cybernetics, endows machines with the self-recovery mechanism, which is unique to humans and animals, and enables machines to store, supplement and activate self-recovery power to maintain body health. Bionics research on Artificial intelligence has greatly enhanced the function of imitating the human brain, but has ignored the important system and function of humans and animals to maintain their own health—the self-recovery system and self-recovery function. Artificial intelligence imitates the conscious thinking control behaviour of the human brain to realize automation and intellectualization, making machines smarter. Artificial self-recovery can imitate the self-recovery mechanism of human unconscious thinking, and prevent and suppress faults in operation to realize self-recovery, possibly making machines healthier. Artificial self-recovery technology includes self-repair, compensation, self-protection and self-recovery regulation. Engineering self-recoveries is the basis of the autonomous health of machines and even artificial systems, and a new research field of Bionics. This has broad application prospects in engineering.

Probability-driven identification mechanism for degradation of magnetic drive pumps

Pump-state prediction and health management have entered the intelligent era. Data analysis, feature extraction, and automatic classification are the critical stages of the state self-recovery regulation of machines. To explore the identification mechanism of degraded states in magnetic drive pumps, the wavelet packet transform is utilised to filter the raw vibration signals. A classification model is subsequently established based on K-means clustering analysis. The highly sensitive characteristic parameters are accessed via a corresponding pre-processing procedure. Herein, clustering points are acquired, and the detected states are classified. Moreover, the probability of operating states over time is ascertained using hidden Markov models. Thus, the healthy machine states are validated via comparison of the calculated results, indicating that the trigger mechanism can recognise the degraded machine states successfully. The proposed probability-driven identification mechanism makes the automatic identification and intelligent decision-making of self-recovery systems possible, and may be used to provide technical details for application to other rotating machinery systems.

Pneumatic-liquid Type Self-recovery Regulation System for the Imbalance Vibration of High-speed Hollow Shaft

Pneumatic-liquid Type Self-recovery Regulation System for the Imbalance Vibration of High-speed Hollow Shaft

A novel capsule-based self-recovery system with a chloride ion trigger.

Steel is prone to corrosion induced by chloride ions, which is a serious threat to reinforced concrete structures, especially in marine environments. In this work, we report a novel capsule-based self-recovery system that utilizes chloride ions as a trigger. These capsules, which are functionalized via a smart response to chloride ions, are fabricated using a silver alginate hydrogel that disintegrates upon contact with chloride ions, and thereby releases the activated core materials. The experimental results show that the smart capsules respond to a very low concentration of chloride ions (0.1 wt%). Therefore, we believe that this novel capsule-based self-recovery system will exhibit a promising prospect for self-healing or corrosion inhibition applications.

Design and Characterization of a Built-In CMOS TID Smart Sensor

This paper describes a total ionization dose (TID) sensor that presents the following advantages: it is a digital sensor able to be integrated in CMOS circuits; it has a configurable sensitivity that allows radiation doses ranging from very low to high levels; its interface helps to integrate this design in a multidisciplinary sensor network; and it is self-timed, hence it does not need a clock signal. We designed, implemented and manufactured the sensor in a $0.35 ~\mu \hbox{m}$ CMOS commercial technology. It was irradiated with a ${^{60}}{\rm Co}$ source. This test was used to characterize the sensor in terms of the radiation response up to 575 krad. After irradiation, we monitored the sensor to control charge redistribution and annealing effects for 80 hours. We also exposed our design to meticulous temperature analysis from 0 to $50^\circ{\rm C}$ and we studied the acceleration on the annealing phenomena due to high temperatures. Sensor calibration takes into account the results of all tests. Finally we propose to use this sensor in a self-recovery system. The sensor manufactured in this work has an area of $0.047 ~\hbox{mm} ^2$ , of which 22% is dedicated to measuring radiation. Its energy per conversion is 463 pJ.

A photochromic nano-system via self-recovery for stable photocatalytic hydrogen evolution by optimizing TiO2 surface energy

AgBr photochromic self-recovery system was introduced into TiO2 to repeatedly optimize its surface energy by the repeating Br2 adsorption.

Research on an Electromagnetic Driven Bi-Disc Compensator for Rotor Auto-Balancing

Many balancing devices have been created to reduce machinery vibration especially in a high-speed rotor system which is very sensitive to the rotating mass unbalance. The best solution is that this device can self-perceive vibration changes and then respond these changes in an optimized way according to the different situations, which means it is a self-recovery system. According to this consideration, an electromagnetic driven bi-disc compensator for rotor auto-balancing is proposed here. In this system, rotor unbalance is online identified and calculated, after that the balancing discs will be driven to the best compensating positions, so that the unbalance can be suppressed or eliminated. Long transition time and transient vibration enhancement are terrible roadblocks which limit the industry applications of such auto-balancing system. To solve these deficiencies, a freely rotation bi-disc strategy was established and the solutions of two special cases were also discussed. A rotor auto-balancing test rig was build up. Experiments using the new solution on this rig showed that the electromagnetic compensator could be moved more accurate and effective, by which not only the balancing time was reduced, but also the transient vibration enhancement was avoided.

Fault Damage Power and Self-Recovery System of Machinery

Animals possess the function of self-recovery for adapting the change in their living conditions. Can machinery, by bionic design, just like animals, also possess the function of self-recovery for making itself free of fault, or for eliminating fault automatically during operation In this paper, a new theory of Engineering Self-recovery is discussed, which could provide theoretical basis and new methodology for creating a new generation of machinery with fault self-recovery function. The engineering self-recovery theory is different from engineering cybernetics. Engineering cybernetics endows machinery with purposive behavior which originally is one of animal’s common characteristics, while engineering self-recovery theory endows machinery with the new function of fault self-recovery which originally is another one of animal’s common characteristics. Under the guidance of engineering cybernetics, the automation of machinery has come true. While under the guidance of engineering self-recovery theory, a new generation of machinery with the new function of fault self-recovery could also be realized. The self-recovery system, which can provide fault self-recovery force to restrain fault force, is investigated in detail. Based on fault mechanism and risk analysis, and by bionic design, a fault self-recovery system, which is a dynamic system to store, supplement and transfer the self-recovery force, is endowed to a machine with the ability to maintain the machine in a health state. Also, the research in engineering application of the new concept, fault self-recovery, is on the way. As an example, the new concept centrifugal compressor with fault self-recovery function is discussed here with axial displacement and flow induced vibration fault self-recovery as examples to show the steps of fault self-recovery system construction such as fault mechanism, necessity, determination, possibility, fault tolerance, limitation and execution.

情報収集型レスキューロボット「Baby II」における自己復帰メカニズム(レスキューシステム・レスキュー工学5)

情報収集型レスキューロボット「Baby II」における自己復帰メカニズム(レスキューシステム・レスキュー工学5)