Study record

Measuring arrow impact points: Yu 2012 study

Measuring System for Impact Point of Arrow using Mamdani Fuzzy Inference System

Jung-Won Yu, Han-Soo Lee, Yeong-Sang Jeong, Sung-Shin Kim2012

Citation

Yu, J.-W., Lee, H.-S., Jeong, Y.-S., & Kim, S.-S. (2012). Measuring System for Impact Point of Arrow using Mamdani Fuzzy Inference System. Journal of Korean Institute of Intelligent Systems, 22(4), 521-526. https://doi.org/10.5391/jkiis.2012.22.4.521

Cite the study
APA

Yu, J.-W., Lee, H.-S., Jeong, Y.-S., & Kim, S.-S. (2012). Measuring System for Impact Point of Arrow using Mamdani Fuzzy Inference System. Journal of Korean Institute of Intelligent Systems, 22(4), 521-526. https://doi.org/10.5391/jkiis.2012.22.4.521

BibTeX
@article{yu2012impactpointfuzzy,
  author = {Yu, Jung-Won and Lee, Han-Soo and Jeong, Yeong-Sang and Kim, Sung-Shin},
  title = {Measuring System for Impact Point of Arrow using Mamdani Fuzzy Inference System},
  year = {2012},
  journal = {Journal of Korean Institute of Intelligent Systems},
  volume = {22},
  number = {4},
  pages = {521--526},
  doi = {10.5391/jkiis.2012.22.4.521}
}

Technical details

Design
Laboratory test
Population
Equipment tests, no archers
What was tested
Equipment, no participants
Level
Not stated
Discipline
Not stated
Type
Journal article
Language
Korean
Peer review
Yes
Published in
Journal of Korean Institute of Intelligent Systems (regional journal)

What it measured and what it found

The authors, engineers at Pusan National University, propose a system for measuring automatically where an arrow lands, intended for quality control in manufacturing. They start from a simple idea: if the same arrow is shot several times by a machine under the same conditions, rotating the nock each time, how close the impact points are shows how well the arrow is made; and analysing holes in a paper sheet by hand is imprecise, means changing the sheet often and makes it hard to put the group into numbers. The system detects the arrow, travelling at about 275 km/h, as it passes through a 65 by 65 cm frame placed about a metre in front of the target, and calculates its coordinates. As an example the paper compares several different arrows, each shot three times with the nock rotated by 120 degrees: the arrow with the lowest dispersion index (0.2707, number 2) is judged the best.

How it was measured

Two line lasers are mounted on the frame, each facing a row of photodiodes on the opposite side. When the arrow passes, its shadow covers at most four photodiodes; from the voltages of these photodiodes a Mamdani fuzzy inference system, with 33 hand-written rules and five levels of shading, estimates the centre of the shadow. From the two centres, using similar triangles, the system finds the point where the arrow crosses the frame, without needing to know the shaft diameter. The arrow is launched by a machine about one metre above the ground, with an adjustable angle, about 39 metres from the target. As a quality index the authors use the distance of the three impacts from their mean point: where the mean point lies does not matter, since the machine can be zeroed, only how tightly the shots are grouped.

The method explained: Reading the target with a camera, Shooting machines and robots in archery research

Limitations

The paper reports no accuracy check: it does not compare the system's coordinates with holes in a paper target, nor does it give the error in millimetres, so it is not known how reliable the method is. The arrow example is minimal: three shots per arrow, a number of arrows that can only be read off the figure, no information on model, spine or weight, and a dispersion index given without units. Three impacts are too few to estimate an arrow's dispersion, and the test was not repeated. The text is in Korean, with the abstract and captions in English.

What it means for archers

For archers the study matters only indirectly. It concerns how a manufacturer might measure the consistency of arrows leaving the factory, with a machine in place of the archer, and it follows the same logic as the checks many archers make by numbering their arrows and comparing where they land: an arrow that changes its point of impact when rotated on the nock differs from the others in some way (spine, straightness, weight or fletching). Here, though, the measurement is presented as an engineering idea and has not been validated, so it says neither which arrow is better nor by how much.

In the registry

The claims this study is evidence for, with its position and the current status.

Cite this record
APA

Campagna, M. (2026). Study record: Measuring System for Impact Point of Arrow using Mamdani Fuzzy Inference System. In Evidence Registry. matteocampagna.com. Retrieved 16 October 2026, from https://matteocampagna.com/en/evidence/yu-2012-impact-point-fuzzy

BibTeX
@misc{campagna2026_enevidenceyu2012impactpointfuzzy,
  author = {Campagna, Matteo},
  title = {Study record: Measuring System for Impact Point of Arrow using Mamdani Fuzzy Inference System},
  year = {2026},
  howpublished = {Evidence Registry, matteocampagna.com},
  url = {https://matteocampagna.com/en/evidence/yu-2012-impact-point-fuzzy},
  note = {accessed 2026-10-16}
}