打破傳統設備的壁壘：AI技術與機器視覺檢測系統完美結合
發布時間：
2023-02-10 11:28
機器視覺工業產業鏈的深度布局進一步豐富產品線和產能建設，加強人工智能技術在機器視覺檢測系統工業檢測領域應用的研發。
The deep layout of the industrial chain of machine vision industry further enriches the product line and capacity construction, and strengthens the research and development of artificial intelligence technology in the field of machine vision industrial inspection.
傳統的檢測設備，完全依靠技術方設定的算法數據庫，只能重復性地檢出已知的已輸入的缺陷類型，對于新的、不常見的缺陷卻無法識別檢出。
The traditional detection equipment, completely relying on the algorithm database set by the technical side, can only repeatedly detect known types of defects that have been input, but can not identify and detect new and uncommon defects.
通過重新把缺陷的定義過程交還給一線員工，一線員工僅需對缺陷進行初步的標記分類，設備就會“記住”這些判定，并模擬人腦進行分析識別，隨著檢測數據量的不斷增加，數據庫的不斷擴大，檢測結果將越加精準。
By redefining the process of defect definition to the front-line staff, the front-line staff only need to carry out preliminary mark classification for defects, and the equipment will "remember" these judgments, and simulate the human brain for analysis and identification. With the increasing amount of detection data and the continuous expansion of the database, the detection results will be more accurate.
在應用案例上，將AI技術融入到晶硅電池視覺檢測中，打破了傳統自動化設備的壁壘，實現真正的智能化、數據化；目前，除了晶硅電池行業，利珀科技也將人工智能技術運用到了其他視覺檢測領域，AI技術的應用是缺陷檢測行業不可避免的趨勢。
In the application case, AI technology is integrated into the visual inspection of crystalline silicon battery, which breaks the barriers of traditional automation equipment and realizes real intelligence and data. At present, in addition to the crystalline silicon battery industry, Lipper technology also applies artificial intelligence technology to other visual inspection fields, and the application of AI technology is an inevitable trend in the defect detection industry.
通用機器視覺開發平臺，將數千個算子組合成了近百個核心的算法工具，用戶無需編寫任何代碼，只需要過“拖”、“拉”、“點”將各種算法工具進行組合，就可以實現各種視覺檢測任務，簡化機器視覺系統實現的復雜度，解決了項目開發周期長、人力物力成本高的行業痛點。
The general machine vision development platform combines thousands of operators into nearly one hundred core algorithm tools. Users do not need to write any code, but only need to combine various algorithms and tools through "drag", "pull" and "point", so as to realize various visual inspection tasks, simplify the complexity of machine vision system implementation, and solve the problem of long project development cycle and human and material resources cost High industry pain points.
機器視覺作為讓機器人等自動化設備更加智能化的技術在這些年廣受資本市場青睞，即便在資本“荒”的特殊時期，機器視覺仍然保持著較高的關注度，企業融資事件絡繹不絕。
Machine vision, as a technology to make robots and other automation equipment more intelligent, has been widely favored by the capital market in recent years. Even in the special period of capital shortage, machine vision still maintains a high degree of attention, and enterprise financing events continue to flow.
In the future, a greater breakthrough in the depth and width of AI technology applied to machine vision inspection system is a tool that can impart human knowledge and experience to equipment, so that robots can understand manufacturing and realize the ideal of real machine automation.
機器視覺檢測系統