2results about How to "Efficient automatic detection" patented technology

This utility model discloses a surface defect detection device for rubber roller production, comprising a feeding assembly, a rotary drive assembly, a discharging assembly, and a vision inspection assembly. The feeding assembly includes a feed plate for the rubber rollers to be inspected, a feed lifting ramp, and a lifting assembly for orderly conveying the rubber rollers to be inspected. The rotary drive assembly includes an active drive shaft for roller rotation, a passive drive shaft for roller rotation, a roller rotation drive motor, and a drive shaft mounting bracket to ensure stable rotation of the rubber rollers. The discharging assembly includes a discharge lifting ramp and a collection trough for collecting the inspected rubber rollers. The vision inspection assembly includes a translational drive rail and a surface defect detection camera to achieve omnidirectional scanning of surface defects on the rubber rollers. This equipment has a high degree of automation, accurate detection, effectively improves the quality control level of rubber roller production, and ensures the surface quality of the rubber rollers.

This application relates to the field of underwater robot technology and discloses a multimodal fusion intelligent detection method for bridge defects using underwater robots. The method includes: acquiring a set of underwater environmental parameters; dynamically adjusting imaging parameters by optimizing the light propagation path to overcome problems such as light attenuation and scattering in the underwater environment; utilizing multi-sensor data fusion technology, combining sonar and optical imaging data to generate a high-quality sequence of bridge surface images; extracting, classifying, and weighting defects in the images to generate an intermediate image set containing defect features; and performing multi-dimensional verification and local correction to ensure the accuracy of the defect features; finally, by evaluating the quality of the intermediate image set, standardized image data is generated to provide reliable input for defect extraction. This application can provide efficient and accurate technical support for bridge maintenance and safety assessment.