Companies Dominating the Fault Detection and Classification Landscape
- Cognex Corp.
- Company Overview
- Business Strategy
- Key Product Offerings
- Financial Performance
- Key Performance Indicators
- Risk Analysis
- Recent Development
- Regional Presence
- SWOT Analysis
- Clockworks Analytics
- Keyence Corp.
- KLA Corp.
- Microsoft Corp.
- OMRON Corp.
- Siemens AG
- DNV Group AS
- Lucy Electric
- einnoSys Technologies Inc.
- elunic AG
- INFICON Holding AG
Browse Key Market Insights with Data Illustration:
In the News
- Lucy Electric combined Advanced grid monitoring capabilities and AI for subterranean cable asset management and fault detection by utilizing a "digital twin" and sensors at the feeder and substation levels to identify irregularities in grid operation. Furthermore, combining this innovative technology with the GridKey monitoring system enhances fault management, resulting in considerable cost savings and fewer customer interruptions, and is regarded as a very successful method of identifying cable faults since it can locate little transients that are indicative of the beginning of a cable fault.
- A novel machine-learning model for forecasting the maintenance requirements of large-scale solar PV installations has been created by scientists from Malaysia and Thailand, which will aid in detecting irregularities in the expected electrical current of string modules, the tool seeks to circumvent "fault detection and classification," which is frequently present in standard operating systems and notifies operators when repair is necessary.
