| Student Name | School | Degree | Year | |
|---|---|---|---|---|
| Muhammad Naveed Akhtar | MCS | Undergraduate | Fourth | [email protected] |
| Faisal Mahboob | MCS | Undergraduate | Fourth | [email protected] |
| Maham Sajjad | MCS | Undergraduate | Fourth | [email protected] |
| Muzammil Abbas | MCS | Undergraduate | Fourth | [email protected] |
| Inter School Idea ? | No |
| Do you need expertises from another area: | No |
| If Yes please provide details of expertises you need: |
| Idea Name: | Condition Monitoring of Industrial Machines |
| Slogan: | Artificial Intelligence(AI) based Condition Monitoring of Industrial Machines |
| Supervisor Name: | Dr.Atta-ur-Rehman |
| Supervisor Designation: | Associate Professor |
| Supervisor School: | MCS |
| Supervisor Department: | Electrical Engineering |
| Contact number: | +92 3215275945 |
| Email ID: | [email protected] |
| Abstract: | |
| In this project we introduce the solution to the problem of Electrical machines by doing pre-detection of anomaly in Machine using Artificial Intelligence. We used unsupervised learning to train the machine against the Anomaly detection. We use vibration parameter. Sensors are mounted on the machine for Data Analysis and the graph to be displayed on the screen from which we can examine the Machine | |
| What is the unmet need in society that your idea will fulfill ? | |
| Even in the present time Machine are being Analyzed but its all happening manually with the help of inspection team, we will take it to automation. | |
| Who needs it ? How many would benefit ? | |
| Almost all the power sector regarding to industrial machine get benefit from it because all the inspection of machine are done Automatically there is no need to call the inspection team. | |
| How will the solution works | |
| Artificial Intelligence is a vast field to study but in this project, we used unsupervised learning to train the machine against the Anomaly detection. Sensors are mounted on the machine for Data Analysis and the graph to be displayed on the screen from which we can examine the Health of Machine. The existence of Outlier reading predict the Anomaly in the Machine, and alarm to take pre cautionary measures against it. | |
| Who are your competitors ? How is your solution different | |
| Our work is totally based on automation and the toddy's industries doing it by manually. | |
| Status: | new |
| Entry Date & Time: | 2022-12-15 (0526) |