scholarly journals Mapping of the electromagnetic environment on the railway: Condition monitoring of signalling assets

2018 ◽  
Vol 234 (3) ◽  
pp. 246-256
Author(s):  
Alexander Knight-Percival ◽  
Christopher Johnson ◽  
Benjamin Richards ◽  
Scott Palmer ◽  
Nicholas Bowring
Keyword(s):  
Condition Monitoring ◽  
Detection System ◽  
Low Cost ◽  
Capital Outlay ◽  
Electromagnetic Environment ◽  
Analysis Techniques ◽  
Track Circuits ◽  
Condition Monitoring Systems ◽  
Advanced Analysis ◽  
Track Circuit

Conventional track circuit condition monitoring systems are fixed at the wayside, with each installation reporting on a single track circuit. In this work, we present a custom-built, sensitive, magnetic field detection system, which can be fitted to the underside of a rail vehicle. With this system installed, some characteristics of an operating track circuit can be monitored from the vehicle whilst it is in motion. By using appropriate analysis techniques, it is possible to identify the signatures of equipment relating to audio frequency track circuits, the topic of this work. Analysing the signatures of track circuit equipment demonstrated that there were clear differences between track circuit assets. By building on other research into the behaviours of failing track circuits, and continuing to conduct this research, the authors believe that it is possible, and beneficial, to perform condition monitoring of track circuits from low-cost equipment mounted on the train. Coupling this with advanced analysis techniques will allow predictive maintenance of track circuits with very little capital outlay.

Automated Duty Cycle Classification for Online Monitoring Systems

2007 ◽  
Author(s):  
Markus A. Timusk ◽  
Michael G. Lipsett ◽  
Chris K. Mechefske
Keyword(s):  
Condition Monitoring ◽  
Duty Cycle ◽  
Online Monitoring ◽  
Detection System ◽  
Operating Mode ◽  
Monitoring Systems ◽  
Physical Response ◽  
Condition Monitoring Systems ◽  
Real Time Information ◽  
Time Information

Transient operation of machinery can greatly complicate the task of vibration-based online condition monitoring. Because the operating mode of a machine affects the physical response and hence the diagnostic parameters, real-time information regarding the operating mode is likely to improve the performance of an online fault detection system. This paper proposes a method for automated duty cycle classification to augment the performance of vibration-based online condition monitoring systems for applications such as gearboxes, motors, and their constituent components. Experimental work is carried out on the swing machinery of an electromechanical excavator, which demonstrates how such a method might function on actual dynamic signals gathered from an operating machine. Several variations of the system are tested.

Automated Operating Mode Classification for Online Monitoring Systems

2009 ◽  
Vol 131 (4) ◽  
Author(s):  
Markus A. Timusk ◽  
Michael G. Lipsett ◽  
Jordan McBain ◽  
Chris K. Mechefske
Keyword(s):  
Condition Monitoring ◽  
Online Monitoring ◽  
Detection System ◽  
Operating Mode ◽  
Monitoring Systems ◽  
Transient Operation ◽  
Physical Response ◽  
Condition Monitoring Systems ◽  
Real Time Information ◽  
Time Information

Transient operation of machinery can greatly complicate the task of vibration-based online condition monitoring. Because the operating mode of a machine affects the physical response and hence the diagnostic parameters, real-time information regarding the operating mode is likely to improve the performance of an online fault detection system. This paper proposes a method for automated operating mode classification to augment the performance of vibration-based online condition monitoring systems for applications such as gearboxes, motors, and their constituent components. Experimental work has been carried out on the swing machinery of an electromechanical excavator, which demonstrates how such a method might function on actual dynamic signals gathered from an operating machine. Several variations of the system have been tested and found to be successful.

scholarly journals A Low-Cost, Small-Size, and Bluetooth-Connected Module to Detect Faults in Rolling Bearings

2020 ◽  
Vol 10 (16) ◽  
pp. 5645
Author(s):  
Erica Raviola ◽  
Franco Fiori
Keyword(s):  
Frequency Spectrum ◽  
Condition Monitoring ◽  
Acoustic Noise ◽  
Low Cost ◽  
Experimental Tests ◽  
Signal Acquisition ◽  
Rolling Bearings ◽  
Use Of Data ◽  
Condition Monitoring Systems ◽  
Remote Controller

Condition monitoring techniques have been successfully applied to detect damaged bearings. However, the signal acquisition and the subsequent processing are typically outsourced to expensive data acquisition boards and complex software, resulting in expensive solutions. As a side effect, the integration of condition monitoring systems in wireless sensor networks can be tough to achieve. Aiming to overcome such issues, a low-cost and small-size electronic module to be placed in the proximity of the bearing to be monitored was developed. The acoustic signal delivered by the bearing is acquired, and the corresponding frequency spectrum is evaluated on-board. Based on that, the developed module automatically detects the presence of defects and notifies the remote controller via a wireless connection only when a fault is detected, thus avoiding the use of data cables whilst minimizing the amount of transferred data. Experimental tests carried out on the proposed system assessed the accuracy of the evaluated frequency spectrum, resulting in an amplitude error within ±0.6%, as well as the fault detection capability in the presence of environmental acoustic noise.

scholarly journals Development of low-cost non-contact structural health monitoring system for rotating machinery

2018 ◽  
Vol 5 (6) ◽  
pp. 172430 ◽  
Author(s):  
Vanraj ◽  
Robin Singh ◽  
S. S. Dhami ◽  
B. S. Pabla
Keyword(s):  
Condition Monitoring ◽  
Low Cost ◽  
Industrial Applications ◽  
General Purpose ◽  
Rotating Machinery ◽  
Efficiency Condition ◽  
Contact Data ◽  
Condition Monitoring Systems ◽  
User Friendly ◽  
Friendly Graphical User Interface

Condition monitoring systems are increasingly being employed in industrial applications to improve the availability of equipment to increase the overall equipment efficiency. Condition monitoring of gearboxes, a key element of rotating machines, ensures to continuously reduce and eliminate costs, unscheduled downtime and unexpected breakdowns. This study demonstrates a low-cost microcontroller-based non-contact data acquisition system for condition monitoring of rotating machinery. Experimental validation of the proposed system was carried out by performing examination tests on a gearbox test rig. A user-friendly graphical user interface was also developed which facilitates users to perform signal processing in both real-time and offline mode. The proposed system can perform most of the functions available in complex, stand-alone vibration analysers. The use of a general-purpose PC and standard programing language makes the system simple, economical and adaptable to a variety of problems. The tests show the developed system can perform properly as proposed.

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.

Face recognition in an intelligent door lock with ResNet model based on deep learning

2021 ◽  
pp. 1-11
Author(s):  
Suphawimon Phawinee ◽  
Jing-Fang Cai ◽  
Zhe-Yu Guo ◽  
Hao-Ze Zheng ◽  
Guan-Chen Chen
Keyword(s):  
Face Recognition ◽  
Detection System ◽  
Low Cost ◽  
Ease Of Use ◽  
Raspberry Pi ◽  
Training Methods ◽  
Graphics Recognition ◽  
Face Images ◽  
The Face ◽  
Door Lock

Internet of Things is considerably increasing the levels of convenience at homes. The smart door lock is an entry product for smart homes. This work used Raspberry Pi, because of its low cost, as the main control board to apply face recognition technology to a door lock. The installation of the control sensing module with the GPIO expansion function of Raspberry Pi also improved the antitheft mechanism of the door lock. For ease of use, a mobile application (hereafter, app) was developed for users to upload their face images for processing. The app sends the images to Firebase and then the program downloads the images and captures the face as a training set. The face detection system was designed on the basis of machine learning and equipped with a Haar built-in OpenCV graphics recognition program. The system used four training methods: convolutional neural network, VGG-16, VGG-19, and ResNet50. After the training process, the program could recognize the user’s face to open the door lock. A prototype was constructed that could control the door lock and the antitheft system and stream real-time images from the camera to the app.

Development of a method for detecting trace metals in aqueous solutions based on the coordination chemistry of hexahydrotriazines

The Analyst ◽  
2015 ◽  
Vol 140 (15) ◽  
pp. 5184-5189 ◽  
Author(s):  
Rudy J. Wojtecki ◽  
Alexander Y. Yuen ◽  
Thomas G. Zimmerman ◽  
Gavin O. Jones ◽  
Hans W. Horn ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Coordination Chemistry ◽  
Trace Metals ◽  
Aqueous Solutions ◽  
Detection System ◽  
Low Cost ◽  
System P ◽  
Chemical Indicator

The detection of trace amounts (<10 ppb) of heavy metals in aqueous solutions is described using hexahydrotriazines as a chemical indicator and a low cost fluorimeter-based detection system.

Design of a low-cost detection system for laser-induced plasma spectroscopy

1999 ◽  
Vol 70 (9) ◽  
pp. 3519-3522 ◽  
Author(s):  
R. E. Neuhauser ◽  
B. Ferstl ◽  
C. Haisch ◽  
U. Panne ◽  
R. Niessner
Keyword(s):  
Detection System ◽  
Low Cost ◽  
Plasma Spectroscopy ◽  
Laser Induced Plasma
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