Abstract: The invention discloses a node multi-electrode resistivity measurement system provided with a transmitter, a PC terminal, acquisition nodes, transmitting electrodes and receiving electrodes. The transmitter, acquisition nodes and PC terminal are connected by Wifi, and the transmitter and acquisition nodes are connected in series by a five-core cable. So the weight of the cable is greatly reduced, and each core can be wrapped by shielding layer, reducing the influence of electromagnetic coupling and ensuring the quality of collected data. The weight of the system is very light so that work efficiency has been improved. Synchronization between transmitter and acquisition nodes is carried out by GPS.

Abstract: The present invention provides a method for quantitatively identifying the defects of large-size composite material based on infrared image sequence, firstly obtaining the overlap area of an infrared splicing image, and dividing the infrared splicing image into three parts according to overlap area: overlap area, reference image area and registration image area, then extracting the defect areas from the infrared splicing image to obtain P defect areas, then obtaining the conversion coordinates of pixels of defect areas according to the three parts of the infrared splicing image, and further obtaining the transient thermal response curves of centroid coordinate and edge point coordinates, finding out the thermal diffusion points from the edge points of defect areas according to a created weight sequence and dynamic distance threshold ?ttr×dp_max, finally, based on the thermal diffusion points, the accurate identification of quantitative size of defects are completed.

Abstract: The present invention provides a method for quantitatively identifying the defects of large-size composite material based on infrared image sequence, firstly obtaining the overlap area of an infrared splicing image, and dividing the infrared splicing image into three parts according to overlap area: overlap area, reference image area and registration image area, then extracting the defect areas from the infrared splicing image to obtain P defect areas, then obtaining the conversion coordinates of pixels of defect areas according to the three parts of the infrared splicing image, and further obtaining the transient thermal response curves of centroid coordinate and edge point coordinates, finding out the thermal diffusion points from the edge points of defect areas according to a created weight sequence and dynamic distance threshold ?ttr×dp_max, finally, based on the thermal diffusion points, the accurate identification of quantitative size of defects are completed.