Electrostatic Precipitation Wall-Climbing Inspecition Robot
Electrostatic Precipitators (ESP), as the crucial defense line for environmental emission in thermal power plants, directly determine the dust removal efficiency. However, manual inspection suffers from extremely low efficiency, numerous blind spots, low data recording accuracy, and poor quantification. The ESP wall-climbing inspection robot can perform fully automated inspection operations. Integrating three core sensing systems—HD vision, laser ranging, and electromagnetic ultrasonic thickness gauging—it is a mobile "NDT (Non-Destructive Testing) laboratory." It easily enters the confined spaces between ESP plates, adheres to and climbs vertical plates autonomously, and achieves "seamless cross-row" operations over wind baffles at the top of the plates without manual intervention. It conducts automated, comprehensive "physical examinations" of anode plates and cathode wires, capable of completing three core tasks in one pass: visual inspection, electrode spacing measurement, and wall thickness analysis. The vision module can penetrate darkness and dust to capture macro-defects such as plate deformation and wire detachment in high definition; the high-precision laser ranging module can measure electrode spacing in real-time with an accuracy of up to 1 millimeter and automatically generate electrode spacing distribution heat maps to prevent electric field breakdown; the core technological breakthrough lies in the electromagnetic ultrasonic thickness gauging module, which abandons the drawback of traditional ultrasonic testing requiring couplant application, and can directly penetrate surface dust and paint layers to non-destructively measure the metal substrate thickness, accurately assessing wear and pitting conditions. All inspection data is controlled and monitored via an industrial-grade remote control terminal and synchronized to an intelligent software platform. This platform is capable of establishing digital health archives for each plate, utilizing AI algorithms to assist in defect identification, and automatically generating comprehensive inspection reports containing thickness cloud maps, electrode spacing curves, and defect lists. This elevates the operation and maintenance mode from experience-dependent "qualitative inspection" to "quantitative assessment" based on millimeter-level data, achieving full inspection coverage with zero blind spots, providing core data support for predictive maintenance and precise repairs, ultimately realizing the core values of ensuring safety, improving efficiency, extending equipment life, and driving intelligent decision-making. Fine inspection operation speed: 2m/min, endurance: 4H, protection rating: IP65.