DBIS2022_P4 Computer Vision Project

max kellerman

Updated 2 years ago

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Classes (30)
0
1
2
3
Bent Insulator
Burned transformer
Cable Connector
Frayed Cable
Fuse Cutout
Insulator
Power_Cable
Power_cable
Tangled Object
cdien_gom_ban
cdien_gom_tt_vo
cdien_polyme_tt_cong
csv_gom_ban
csv_gom_tt_vo
csv_polyme_tt_rach
damper
ddan_tt_mon
ddan_tt_tua
ddan_tt_vatla
insulator plate
power cable
spacer
tower transformer
vday_tt

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Description

Here are a few use cases for this project:

  1. Grid Health Monitoring: The DBIS2022_P4 model can be used in power grid systems to automatically identify and monitor the condition of different components such as insulators, transformers, cables, etc. for damage or faults. This could significantly reduce the time and cost involved in manual inspections.

  2. Predictive Maintenance in Power Plants: The model can be used to predict possible failure points and schedule maintenance based on subtle changes in insulators or other components. This will increase safety and efficiency in power plants.

  3. Hardware Quality Control: Companies manufacturing power equipment can use the model to inspect their products (cables, insulators, transformers) for quality assurance purposes, identifying defective or sub-standard products.

  4. Damage Assessment during Natural Disasters: The model can assist in doing swift and accurate damage assessment of power infrastructure after natural disasters such as hurricanes and earthquakes, helping in prioritizing repairs and restoration of normal power supply.

  5. Electrician Training: The model could serve as a training aid for new electricians or electrical engineers, helping them understand different components and identify common issues like a bent insulator, frayed cable, or burned transformer.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            dbis2022_p4_dataset,
                            title = { DBIS2022_P4 Dataset },
                            type = { Open Source Dataset },
                            author = { max kellerman },
                            howpublished = { \url{ https://universe.roboflow.com/max-kellerman-cz98k/dbis2022_p4 } },
                            url = { https://universe.roboflow.com/max-kellerman-cz98k/dbis2022_p4 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

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