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Adjusting a Traverse01:12

Adjusting a Traverse

59
In the site survey of a four-sided traverse, internal angles are essential to ensure geometric accuracy. The survey revealed that the sum of the measured internal angles was 359 degrees and 48 minutes, which is 12 minutes less than the expected 360 degrees. This discrepancy signals an error likely arising from measurement inaccuracies during the fieldwork.To rectify this error, the adjustment process involved distributing the 12-minute shortfall equally across the four internal angles. By...
59
Errors and Mistakes in Surveying01:19

Errors and Mistakes in Surveying

78
Errors and mistakes in surveying refer to inaccuracies in measurements and data recording. The errors are deviations from the actual value caused by human sensory limitations, equipment flaws, or environmental effects. These errors are typically unintentional and can result from the inherent imperfections in the instruments used, atmospheric conditions, or the observer’s inability to perceive exact measurements. On the other hand, mistakes are caused by the surveyor's lack of...
78
Distance Corrections01:15

Distance Corrections

28
To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
28
Errors in Taping01:18

Errors in Taping

26
Errors in taping arise from multiple factors that can significantly impact measurement accuracy in surveying. Misalignment of the tape, often due to human error, is one primary source. A skilled rear tapeman, using a telescope, can help correct alignment by guiding the head tapeman; however, human limitations still lead to small inaccuracies. These errors may include misplacement of pins or inaccurate tape readings due to common visual confusions, such as mistaking a six for a nine. Such...
26
Profile Leveling and Cross Sections01:26

Profile Leveling and Cross Sections

230
Profile leveling and cross-sections are surveying methods used to determine and document terrain elevations for infrastructure projects such as highways, railroads, canals, and pipelines. These methods provide data for earthwork planning and alignment of proposed routes.  Profile leveling involves measuring elevations along a fixed line to create a vertical terrain profile. A surveyor sets up a leveling instrument at the benchmark (BM) and records a backsight (BS) to determine the...
230
Latitudes and Departures01:27

Latitudes and Departures

89
Latitudes and departures are essential concepts in surveying, providing a systematic way to analyze the projections of traverse lines. These projections allow surveyors to interpret a line's north-south and east-west components, which are crucial for precisely calculating areas, bearings, and lengths. Latitude is the north-south projection of a line, calculated as the product of the line's length and the cosine of its bearing. Departure, conversely, is the east-west projection obtained by...
89

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Related Experiment Video

Updated: Jul 4, 2025

Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling
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Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling

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Railway track surface faults dataset.

Asfar Arain1, Sanaullah Mehran1, Muhammad Zakir Shaikh1,2

  • 1NCRA MUET, NCRA Condition Monitoring Systems Lab, Mehran University of Engineering and Technology, Jamshoro, Sindh, Pakistan.

Data in Brief
|February 1, 2024
PubMed
Summary
This summary is machine-generated.

A new dataset of railway track surface defects, captured by EKENH9R cameras, aids research in railway maintenance and computer vision. This resource supports developing Machine Learning (ML) and Deep Learning (DL) for automated track inspection.

Keywords:
Computer VisionCondition monitoringFault identificationRail surface faultsRailway

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Area of Science:

  • Civil Engineering
  • Computer Vision
  • Data Science

Background:

  • Railway infrastructure maintenance is vital for transportation safety and efficiency.
  • Track surface defects like cracks and spallings challenge track integrity.
  • Existing research requires comprehensive datasets for advanced analysis.

Purpose of the Study:

  • Introduce a novel dataset of railway track surface faults.
  • Provide a valuable resource for railway maintenance and computer vision research.
  • Facilitate the development of ML/DL algorithms for defect detection.

Main Methods:

  • Collected data using EKENH9R cameras on a railway inspection vehicle.
  • Ensured diverse real-world fault representation under various conditions.
  • Provided detailed annotations and metadata for precise classification.

Main Results:

  • A comprehensive dataset of diverse railway track surface faults is now available.
  • The dataset includes images under varied environmental and lighting conditions.
  • Annotations enable precise fault classification and severity assessment.

Conclusions:

  • The dataset is a significant asset for ML/DL and image processing in railway maintenance.
  • It supports the development of automated inspection and predictive maintenance systems.
  • Encourages community utilization for advancing track condition monitoring research.