先验规则和深度学习融合驱动的舰船电气图纸布局方法

Aiming at the problems of low automation degree of electrical drawing design, high labor consumption and er-ror-proneness in the current ship overall design process, an automatic layout of electrical drawings that integrated prior rules and deep learning, overall layout and wiring was proposed, which could be applied to engineering practice. According to the topological characteristics of the current ship electrical schematic layout, the typical prior rules were extracted based on the topology structure of the tree diagram; the electrical connection relationship was used as the input to automatically generate the preliminary electrical schematic diagram; the singular value decomposition method was used to extract connectivity features, and preliminary electrical schematic parameters were optimized using a deep neural network. Seven typical drawings of a certain type of ship were selected to carry out application verification. The results showed that: ①the proposed method could realize the task of automatic electrical design layout based on ensuring the correct connection relationship between drawings; ② in the wiring of large samples 9 9. 1% of the drawings could be routed within 10 seconds. This technology could be applied to all electrical wiring tasks where the connection relationship was a tree topology or could be converted into a tree topology to achieve correct, fast and reasonable automatic wiring layout of electrical drawings, which effectively improved the degree of automation in electrical layout and wiring work and the overall design capability and efficiency of the ship.