Rail Defect Detection Using Fiber Optic Sensors and Wavelet Algorithms

2018 ◽  
Author(s):  
Saied Taheri ◽  
Behzad Moslehi ◽  
Vahid Sotoudeh ◽  
Brad M. Hopkins
Keyword(s):  
Defect Detection ◽  
Surface Defects ◽  
New Technology ◽  
Interaction Model ◽  
High Amplitude ◽  
Detection Algorithms ◽  
Simple Detection ◽  
Surface Irregularities ◽  
Signal Processing Algorithms ◽  
Low Amplitude

Early detection of rail defects can avoid derailments and costly damage to the train and railway infrastructure. Small breaks, cracks or corrugations on the rail can quickly propagate after only a few train cars have passed over it, creating a potential derailment. The current technology makes use of a dedicated instrumented car or a separate railway monitoring vehicle to detect large breaks. These cars are usually equipped with accelerometers mounted on the axle or side frame. The simple detection algorithms use acceleration thresholds which are set at high values to eliminate false positives. As a result, rail surface defects that produce low amplitude acceleration signatures may not be detected, and special track components that produce high amplitude acceleration signatures may be flagged as defects. This paper presents the results of a feasibility study conducted to develop new and more advanced sensory systems as well as signal processing algorithms capable of detecting various rail surface irregularities. A dynamic wheel-rail interaction model was used to simulate train dynamics as a result of rail defects and to assess the potential of this new technology on rail defect detection. In a future paper, we will present experimental data in support of the proposed model and simulations.

Elastic Modulus of Vulcanizates as Related to Carbon Black Structure

1973 ◽  
Vol 46 (4) ◽  
pp. 877-896 ◽  
Author(s):  
A. I. Medalia
Keyword(s):  
Elastic Modulus ◽  
Carbon Black ◽  
Surface Area ◽  
Network Structure ◽  
Dibutyl Phthalate ◽  
New Technology ◽  
Residual Effect ◽  
High Amplitude ◽  
Effective Network ◽  
Low Amplitude

Abstract The elastic modulus Gf′ of filled SBR vulcanizates has been measured as a function of strain amplitude A. At low loadings of carbon black (20 phr), where Gf′ is practically independent of A, the value of Gf′ (at 25° C, 0.25 Hz) can be predicted within 5 per eent from the gum modulus Gg′ by the Guth—Gold equation with due allowance for occluded volume, as calculated from the dibutyl phthalate absorption. At normal loadings (50 phr) the value of Gf′ can be predicted fairly well from this treatment if the measurements are made at high amplitude. At 25° C, 0.25 Hz, Gf′ is about 10 per cent higher than predicted due to the residual effect of the carbon black network. The dependence of the high-amplitude Gf′ on frequency and temperature is essentially the same for various reinforcing and semi-reinforcing blacks. Consequently, the value of Gf′ for one black can be calculated from the values found for other blacks. The dependence of Gf′ on A is primarily a function of surface area, but in two cases the dependence is unusually steep for different reasons. With graphitized blacks the low-amplitude Gf′ is higher than that of the ungraphitized blacks, but the high-amplitude Gf′ is low, probably due to molecular slippage. “New technology” blacks, including N339 and N351, give a high-amplitude Gf′ comparable to that of conventional blacks of the same dibutyl phthalate absorption, but give a higher Gf′ at low amplitude, indicating a more effective network structure.

scholarly journals A laser scanner based approach for identifying rail surface squat defects

2020 ◽  
pp. 095440972096225
Author(s):  
D De Becker ◽  
J Dobrzanski ◽  
L Justham ◽  
YM Goh
Keyword(s):  
Defect Detection ◽  
Surface Defects ◽  
Detection System ◽  
Laser Scanner ◽  
Repair Process ◽  
Flow Diagram ◽  
Repair System ◽  
Defect Identification ◽  
Detection Algorithms ◽  
The Uk

The defect identification process within the UK rail industry has seen significant improvements over the past decade with the introduction of new measurement systems and defect detection systems. Although significant work has been on the defect identification little work has been done on the process after the defect has been detected. This repair process is still extremely manual. Due to the current process being manual the repair operation has very little traceability and transparency. This paper has therefore presented the need for not only a defect detection system but a defect repair system for the UK railway industry. Further to this, this paper has acknowledged that the rise of defects occurring on the UK railway lines requires a solution that can fully repair a defect with little to no user intervention in a timely manner. To address this, this paper has taken the extremely manual process of rail repair and has laid out the possibilities to automate this process. By doing this a work flow diagram has been generated to show how the system could be used to repair surface defects with a specific focus being made on squat defects. To achieve this a defect detection and measurement system has been explored, as this will make up the first stage of the automated repair system. The literature on various defect detection algorithms was reviewed and two variations of existing defect detection algorithms were created, i.e. the Covariance method and the Normal Intersection method. These algorithms have been tested against 100 simulated squat defects and have been verified using 4 experimentally generated defects. Both algorithms have been proven to not only identify the approximate size of the defect but also its location. This successful defect identification will be integrated into an automated rail repair system.

Lightweight detection algorithm for fine-grained surface defects of aerospace seal rings

2021 ◽  
pp. 1-18
Author(s):  
Hui Liu ◽  
Boxia He ◽  
Yong He ◽  
Xiaotian Tao
Keyword(s):  
Feature Extraction ◽  
Defect Detection ◽  
Surface Defect ◽  
Surface Defects ◽  
Detection Algorithm ◽  
Seal Ring ◽  
Fine Grained ◽  
Aerospace Applications ◽  
Surface Defect Detection ◽  
The Mean

The existing seal ring surface defect detection methods for aerospace applications have the problems of low detection efficiency, strong specificity, large fine-grained classification errors, and unstable detection results. Considering these problems, a fine-grained seal ring surface defect detection algorithm for aerospace applications is proposed. Based on analysis of the stacking process of standard convolution, heat maps of original pixels in the receptive field participating in the convolution operation are quantified and generated. According to the generated heat map, the feature extraction optimization method of convolution combinations with different dilation rates is proposed, and an efficient convolution feature extraction network containing three kinds of dilated convolutions is designed. Combined with the O-ring surface defect features, a multiscale defect detection network is designed. Before the head of multiscale classification and position regression, feature fusion tree modules are added to ensure the reuse and compression of the responsive features of different receptive fields on the same scale feature maps. Experimental results show that on the O-rings-3000 testing dataset, the mean condition accuracy of the proposed algorithm reaches 95.10% for 5 types of surface defects of aerospace O-rings. Compared with RefineDet, the mean condition accuracy of the proposed algorithm is only reduced by 1.79%, while the parameters and FLOPs are reduced by 35.29% and 64.90%, respectively. Moreover, the proposed algorithm has good adaptability to image blur and light changes caused by the cutting of imaging hardware, thus saving the cost.

Frequency Response Analysis of Piecewise Nonlinear Vibration Isolator

2005 ◽  
Author(s):  
Patrick Stahl ◽  
G. Nakhaie Jazar
Keyword(s):  
Low Frequency ◽  
High Amplitude ◽  
Relative Displacement ◽  
Response Analysis ◽  
Frequency Response Analysis ◽  
State Behavior ◽  
Vibration Isolators ◽  
Short Period ◽  
Secondary Suspension ◽  
Low Amplitude

Non-smooth piecewise functional isolators are smart passive vibration isolators that can provide effective isolation for high frequency/low amplitude excitation by introducing a soft primary suspension, and by preventing a high relative displacement in low frequency/high amplitude excitation by introducing a relatively damped secondary suspension. In this investigation a linear secondary suspension is attached to a nonlinear primary suspension. The primary is assumed to be nonlinear to model the inherent nonlinearities involved in real suspensions. However, the secondary suspension comes into action only during a short period of time, and in mall domain around resonance. Therefore, a linear assumption for the secondary suspension is reasonable. The dynamic behavior of the system subject to a harmonic base excitation has been analyzed utilizing the analytic results derived by applying the averaging method. The analytic results match very well in the transition between the two suspensions. A sensitivity analysis has shown the effect of varying dynamic parameters in the steady state behavior of the system.

Application of instantaneous rotations to S‐wave vertical seismic profiling

Geophysics ◽  
1997 ◽  
Vol 62 (5) ◽  
pp. 1365-1368
Author(s):  
M. Boulfoul ◽  
Doyle R. Watts
Keyword(s):  
High Amplitude ◽  
Seismic Profile ◽  
P Wave ◽  
Petroleum Exploration ◽  
S Wave ◽  
Amplitude Variation With Offset ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Seismic Models ◽  
Low Amplitude

The petroleum exploration industry uses S‐wave vertical seismic profiling (VSP) to determine S‐wave velocities from downgoing direct arrivals, and S‐wave reflectivities from upgoing waves. Seismic models for quantitative calibration of amplitude variation with offset (AVO) data require S‐wave velocity profiles (Castagna et al., 1993). Vertical summations (Hardage, 1983) of the upgoing waves produce S‐wave composite traces and enable interpretation of S‐wave seismic profile sections. In the simplest application of amplitude anomalies, the coincidence of high amplitude P‐wave reflectivity and low amplitude S‐wave reflectivity is potentially a direct indicator of the presence of natural gas.

Variability of the dynamics of somatometric parameters in schoolchildren with different nutritional status (longitudinal study)

2020 ◽  
Vol 15 (5) ◽  
pp. 68-72
Author(s):  
V.L. Gritsinskaya ◽  
◽  
V.P. Novikova ◽  
A.I. Khavkin ◽  
◽  
...  
Keyword(s):  
Nutritional Status ◽  
High Amplitude ◽  
Physical Development ◽  
Growth Spurt ◽  
Pubertal Growth Spurt ◽  
Pubertal Growth ◽  
Normal Limits ◽  
Study Participants ◽  
Two Peaks ◽  
Low Amplitude

Objective. To identify specific features of pubertal growth spurt in adolescents depending on their nutritional status in prepuberty. Patients and methods. We analyzed the dynamics of height and weight in 645 children (331 boys and 314 girls) aged between 8 and 16 years. All study participants were divided into three groups depending on whether their weight and height at the age of 8 years were within the normal limits given in the ‘WHO Growth Reference 2007’: children with physical development; underweight children; and overweight children. Results. The dynamics of somatometric parameters during pubertal growth spurt varied between children with different nutritional status. Underweight boys demonstrated prolonged and low-amplitude pubertal growth pattern; in boys with normal physical development, the growth spurt was usually shorter and had high amplitude. In overweight boys, the pubertal growth spurt started with higher annual increase in height, had a more pronounced amplitude, and was shorter than in peers (р < 0.001 ÷ р < 0.05). Both underweight girls and girls with normal physical development demonstrated low-amplitude pubertal growth spurt lasting for two years. Overweight girls had two peaks of pubertal growth spurt, which usually started earlier than in other girls (р < 0.001 ÷ р < 0.01). Conclusion. Our findings can be used as a guide for predicting pubertal spurt in children during medical examinations, determining adequate physical activity in physical education classes at school and in sports sections. Key words: children, nutritional status, pubertal growth spurt

Oxygen Consumption by the Sea Anemone Calliactis Parasitica (Couch)

1980 ◽  
Vol 88 (1) ◽  
pp. 367-374
Author(s):  
A. E. BRAFIELD
Keyword(s):  
Oxygen Consumption ◽  
Oxygen Concentration ◽  
Low Frequency ◽  
High Amplitude ◽  
Total Oxygen ◽  
Strip Chart ◽  
Calliactis Parasitica ◽  
Cycle Lengths ◽  
Mean Cycle ◽  
Low Amplitude

Oxygen consumption by Calliactis parasitica, measured in a continuousflow polarographic respirometer, yielded a slope of 0·92 when plotted against body weight on log scales. This high value is discussed in terms of the sea anemone's basically laminate nature. Strip-chart records of the oxygen concentration of water which had just passed a specimen of Calliactis commonly showed rhythmic fluctuations, either of low amplitude and high frequency or high amplitude and low frequency (mean cycle lengths 11 and 34 min respectively). The fluctuations are explained in terms of rhythmic muscular contractions which irrigate the enteron for respiratory purposes. Analysis of the slow fluctuations indicates that the endoderm is responsible for about 18% of the total oxygen consumption. The oxygen concentration of water in the enteron, measured and recorded continuously, was 4–27% of the air-saturation level. These strip chart records also frequently showed rhythmic fluctuations (mean cycle length 12 min), apparently resulting from the muscular contractions.

Electrical Resistive Spiking of Fungi

2021 ◽  
pp. 1-7 ◽  
Author(s):  
Andrew Adamatzky ◽  
Alessandro Chiolerio ◽  
Georgios Sirakoulis
Keyword(s):  
Electrical Resistance ◽  
Electronic Devices ◽  
Low Frequency ◽  
High Amplitude ◽  
Average Amplitude ◽  
Average Width ◽  
C 23 ◽  
C 30 ◽  
Low Amplitude

We study long-term electrical resistance dynamics in mycelium and fruit bodies of oyster fungi P. ostreatus. A nearly homogeneous sheet of mycelium on the surface of a growth substrate exhibits trains of resistance spikes. The average width of spikes is c. 23[Formula: see text]min and the average amplitude is c. 1[Formula: see text]k[Formula: see text]. The distance between neighboring spikes in a train of spikes is c. 30[Formula: see text]min. Typically, there are 4–6 spikes in a train of spikes. Two types of electrical resistance spikes trains are found in fruit bodies: low frequency and high amplitude (28[Formula: see text]min spike width, 1.6[Formula: see text]k[Formula: see text] amplitude, 57[Formula: see text]min distance between spikes) and high frequency and low amplitude (10[Formula: see text]min width, 0.6[Formula: see text]k[Formula: see text] amplitude, 44[Formula: see text]min distance between spikes). The findings could be applied in monitoring of physiological states of fungi and future development of living electronic devices and sensors.

Computer Vision Based Technique for Surface Defect Detection of Apples

2014 ◽  
pp. 111-121
Author(s):  
C. J. Prabhakar ◽  
S. H. Mohana
Keyword(s):  
Computer Vision ◽  
Defect Detection ◽  
Surface Defects ◽  
Quality Standards ◽  
Production Costs ◽  
Automatic Inspection ◽  
Segmentation Technique ◽  
Surface Defect Detection ◽  
Fruit Grading

The automatic inspection of quality in fruits is becoming of paramount importance in order to decrease production costs and increase quality standards. Computer vision techniques are used in fruit industry for fruit grading, sorting, and defect detection. In this chapter, we review recent approaches for automatic inspection of quality in fruits using computer vision techniques. Particularly, we focus on the review of advances in computer vision techniques for automatic inspection of quality of apples based on surface defects. Finally, we present our approach to estimate the defects on the surface of an apple using grow-cut and multi-threshold based segmentation technique. The experimental results show that our method effectively estimates the defects on the surface of apples significantly more effectively than color based segmentation technique.

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