Precision Acoustic Detection for Partial Discharge
Partial discharge (PD) is a leading indicator of insulation breakdown and impending transformer failure, but detecting it early, reliably, and without interference remains a major operational challenge.
By capturing high-frequency acoustic signals beyond the range of conventional microphones, BROADSONIC identifies discharge events with exceptional sensitivity and precision. Immune to electromagnetic interference and capable of detecting signals up to 5 MHz, it delivers clarity where other sensors fall silent.
Proactive Risk Management
Avoid reactive repairs, unplanned shutdowns, and asset replacement with earlier insights into electrical degradation.
Asset Optimization
Monitor insulation health in transformers, extending operational life and improving maintenance planning.
Enhanced Safety
Enables earlier detection of conditions that could impact equipment containment or worker safety.
Easy Integration
The system streams real-time acoustic data directly to your computer via USB, making setup and monitoring fast, simple, and intuitive.
Operational Benefits
We’re currently partnering with select facilities to validate BROADSONIC in operational environments. If your facility is evaluating new approaches to PD monitoring, we’d be glad to explore how this technology could support your goals.
Performance Highlights
Ultrawide Bandwidth
Captures discharge signatures up to ~1 MHz — far beyond traditional acoustic sensors.
Exceptional
Signal-to-Noise Ratio
Enables detection of subtle PD activity even at distances >1m, reducing the need for proximity.
EMI-Immune
Optical Design
Operates reliably near high-voltage equipment without interference from electrical noise.
Omnidirectional Sensing
Omnidirectional sensing enables reliable, continuous monitoring without the need for manual repositioning — well-suited for permanent installation.
Research Snapshot
In a controlled validation test, BROADSONIC detected the acoustic signature of a piezoelectric spark — a PD analog — at 1 meter with a signal-to-noise ratio >103, demonstrating its ability to detect small events at distance. Frequency analysis showed signal content reaching ~1 MHz, well beyond standard sensor capabilities.
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