B-17 High Efficiency Condition Monitoring Method for Dynamic Plural Facilities based on a Parabolic Sound Reflector Type Microphone and Separation of Composed Sound

2016 ◽  
Vol 2016.69 (0) ◽  
pp. 71-72
Author(s):  
Satoshi Fukunaga ◽  
Hiromitsu Ohta ◽  
Makoto Nakamura
Keyword(s):  
Condition Monitoring ◽  
High Efficiency ◽  
Monitoring Method ◽  
Efficiency Condition

AI-Based Condition Monitoring of Hydraulic Valves in Zonal Hydraulics Using Simulated Electric Motor Signals

2021 ◽  
Author(s):  
Abid Abdul Azeez ◽  
Xu Han ◽  
Viacheslav Zakharov ◽  
Tatiana Minav
Keyword(s):  
Artificial Intelligence ◽  
Condition Monitoring ◽  
Electric Motor ◽  
High Efficiency ◽  
Development Stage ◽  
Monitoring Method ◽  
Extraction Algorithm ◽  
Mobile Machinery ◽  
Indirect Analysis ◽  
Motor Signals

Abstract Zonal hydraulics, in particular Direct Driven Hydraulics (DDH), is an emerging transmission and actuation technique that is proposed to be used for electrification of heavy-duty mobile machinery. In addition to the already demonstrated advantages of DDH, which include high efficiency, compactness, and ease of maintenance, it is also capable of condition monitoring. The condition monitoring features can be obtained through indirect analysis of the existing electric motor signals (voltage and current) using artificial intelligence-based algorithms rather than by adding extra sensors, which are normally required for conventional realization. In this paper, the valve condition monitoring method of the DDH through electrical motor signals is explored at an early development stage. Firstly, the hydraulic valve models, which involve the valve fault behaviors, are added to the basic DDH model. Secondly, healthy and faulty scenarios for the valves are simulated, and the data are generated. Thirdly, the preliminary artificial intelligence-based condition monitoring classifier is developed using the simulation data, including feature extraction, algorithm training, testing, and comparison of accuracy. The effects of modeling error on developing the condition monitoring function are analyzed. In conclusion, the preliminary outcomes for the valve condition monitoring of the DDH are achieved by taking advantage of modeling and simulation and by utilizing the existing electric motor signals.

scholarly journals Power-Based Non-Intrusive Condition Monitoring for Terminal Device in Smart Grid

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3635 ◽  
Author(s):  
Guoming Zhang ◽  
Xiaoyu Ji ◽  
Yanjie Li ◽  
Wenyuan Xu
Keyword(s):  
Smart Grid ◽  
Power Consumption ◽  
Real Time ◽  
Condition Monitoring ◽  
Resource Constraints ◽  
Detection System ◽  
Stable Operation ◽  
Detection Accuracy ◽  
Monitoring Method ◽  
Dsp Processors

As a critical component in the smart grid, the Distribution Terminal Unit (DTU) dynamically adjusts the running status of the entire smart grid based on the collected electrical parameters to ensure the safe and stable operation of the smart grid. However, as a real-time embedded device, DTU has not only resource constraints but also specific requirements on real-time performance, thus, the traditional anomaly detection method cannot be deployed. To detect the tamper of the program running on DTU, we proposed a power-based non-intrusive condition monitoring method that collects and analyzes the power consumption of DTU using power sensors and machine learning (ML) techniques, the feasibility of this approach is that the power consumption is closely related to the executing code in CPUs, that is when the execution code is tampered with, the power consumption changes accordingly. To validate this idea, we set up a testbed based on DTU and simulated four types of imperceptible attacks that change the code running in ARM and DSP processors, respectively. We generate representative features and select lightweight ML algorithms to detect these attacks. We finally implemented the detection system on the windows and ubuntu platform and validated its effectiveness. The results show that the detection accuracy is up to 99.98% in a non-intrusive and lightweight way.

Modeling and Parameter Identification for Condition Monitoring of Surface-Mount Permanent Magnet Machines Under Magnet Demagnetization

2020 ◽  
Author(s):  
Fanny Pinto Delgado ◽  
Ziyou Song ◽  
Heath F. Hofmann ◽  
Jing Sun
Keyword(s):  
Permanent Magnet ◽  
Condition Monitoring ◽  
High Performance ◽  
High Efficiency ◽  
Health Condition ◽  
Maintenance Cost ◽  
Parameter Estimator ◽  
Two Phase ◽  
Machine Model ◽  
Surface Mount

Abstract Permanent Magnet Synchronous Machines (PMSMs) have been preferred for high-performance applications due to their high torque density, high power density, high control accuracy, and high efficiency over a wide operating range. During operation, monitoring the PMSM’s health condition is crucial for detecting any anomalies so that performance degradation, maintenance/downtime costs, and safety hazards can be avoided. In particular, demagnetization of PMSMs can lead to not only degraded performance but also high maintenance cost as they are the most expensive components in a PMSM. In this paper, an equivalent two-phase model for surface-mount permanent magnet (SMPM) machines under permanent magnet demagnetization is formulated and a parameter estimator is proposed for condition monitoring purposes. The performance of the proposed estimator is investigated through analysis and simulation under different conditions, and compared with a parameter estimator based on the standard SMPM machine model. In terms of information that can be extracted for fault diagnosis and condition monitoring, the proposed estimator exhibits advantages over the standard-model-based estimator as it can differentiate between uniform demagnetization over all poles and asymmetric demagnetization between north and south poles.

Condition Monitoring of Tank Bore Surface Characteristics by an Integrated Measurement Technique

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Ramesh Shanmugam ◽  
D. Dinakaran ◽  
D.G. Harris Samuel
Keyword(s):  
Real Time ◽  
Condition Monitoring ◽  
Measurement Technique ◽  
Great Degree ◽  
Surface Characteristics ◽  
Integrated Approach ◽  
Thermal Camera ◽  
Monitoring Method ◽  
Measuring Surface ◽  
Combat Effectiveness

Accuracy and safety of tank guns are dependent a great degree on the condition of its gun bore. Many parameters affect accuracy and safety and have strong and complex interdependencies. While it is extremely difficult to monitor all these parameters during battle conditions, it is also essential to enhance the accuracy of the gun by measuring and compensating these parameters. Among all, bore wear and bore centreline are predominant factors. The surface characteristics of the bore also are indicative of potential accidents/deterioration, which should be monitored continuously. Hence, condition monitoring of tank gun bore characteristics in near real-time is an impending need with huge potential for enhancing the combat effectiveness of tank formations. This paper analyses various bore parameters affecting accuracy and safety and proposes a comprehensive condition monitoring method that uses vision camera, thermal camera and mechanical profiler. This integrated approach provides enhanced accuracy in measuring surface characteristics of tank bore that has been partially validated.

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