1769-L31
产品的视觉检查是许多行业中质量控制的一个重要步骤。例如，它有助于确保瓶子或罐子的正确灌装，或确保包装内容的完整和正确定位。这些检查具有高度的重复性，手动执行容易出错。但同时，视觉检查涉及大型数据集以及模糊的错误定义，使其自动化非常复杂。
"这就是人工智能发挥作用的地方，" Kumar说，"它可以根据模式而不是严格的阈值或规则，检测数据集中的异常情况，并识别正确或不正确的部分。"
他引用了西门子印刷电路板（PCB）制造业务中的一个质量控制应用，其中一个基于AI的质量系统已被成功部署，以检测丢失、错误焊接或错位的组件。AI初是在云环境中使用包含无缺陷和有缺陷的PCB图像的大型数据集进行训练。然后在Simatic IPC520A Tensorbox系统上实现该算法。
在那里，AI应用检查视觉系统的PCB图像是否有异常，并对算法检测到的异常的可靠程度给予评价。这种反馈有助于改进训练算法。由于算法的计算密集型训练在一个单独的（云）系统上运行，图像识别和分析需要很少的现场资源，这让检测既准确又快速：通常，异常检测需要不到100毫秒。
PCI-DDA04/12 4-Channel 12-Bit Analog Output Board
Omron CJ1W-ID261 CJ1WID261 Input Unit
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ICOS IVC-1000 IVC 1000 OP771 Camera
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National Instruments PCMCIA-GPIB Card 186736C-01
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Olympus Neo SPlan NeoSPlan 10 10X objective lens
Olympus Neo SPlan NeoSPlan 20 20X objective lens
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KDI 64537 PQ-1846 Microwave RF Directional Coupler
MELLES GRIOT 59LLS393 LASER SCAN LENS
Parker Compumotor AT6400 4-Axis Indexer AUX1-120V
Omron CPM1A-40CDR-D PLC
Omron CPM1A-40CDR-D-V1 PLC
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OMEGA HH506R Dual Input THERMOMETER
BECKHOFF KL2541 Stepper motor With incremental encoder
Nikon 33X / 6 Eyepieces
ORION 210A PH METER WITH COMB.PH PROBE (910600)
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SBS TECHNOLOGIES 85224036 21-100-2 PCI HOST
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Acromag 983EN-4012 Ethernet Modbus TCP/IP Module
GE Fanuc IC693UDR005LP1 Micro 90 PLC Controller
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HP 8493B Fixed Attenuator 3dB 6dB 20dB 30dB DC to 18GHz
IMAGING TECHNOLOGY OFG-VP1100 OFGVP1100 Frame Grabbers
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