A method of testing a functional unit includes an optical sensor system (28) for detecting an optical signal from at least a part of a moving material web (14), a data processing system (36) for valuating the optical signals, and a display (38) displaying a state of the material web (14) and arranged in a sensitive range (30) of the sensor system (28).

A method of testing a functional unit includes an optical sensor system (28) for detecting an optical signal from at least a part of a moving material web (14), a data processing system (36) for valuating the optical signals, and a display (38) displaying a state of the material web (14) and arranged in a sensitive range (30) of the sensor system (28).

An image inspection apparatus includes an illuminating section for irradiating illumination light, a line camera in which a plurality of imaging elements are arrayed to be linearly arranged, the line camera receiving the light irradiated from the illuminating section and reflected on the inspection target object, a display section for displaying an image captured by the line camera, an optical axis adjusting section for adjusting an optical axis of the line camera, a trigger setting section for specifying a trigger that specifies timing when the inspection target object is imaged by the line camera, an aspect ratio adjusting section for adjusting longitudinal and lateral pixel resolutions of the image captured by the line camera, and a display control section for displaying the optical axis adjusting section, the trigger setting section, and the aspect ratio adjusting section on the display section in order.

A curved substrate bubble detection method includes: providing, by a first light source and a second light source, parallel light incident to a to-be-tested substrate in different incident directions; obtaining, by a linear array camera, a first image including image information of a first side edge of the to-be-tested substrate; determining location information of a defect region of the to-be-tested substrate according to the first image, and generating a second image including image information of the defect region; binarizing the second image, and determining that the to-be-tested substrate has a bubble defect if there are at least two bright spots in an obtained binarized image, and a distance between any two first bright spots of at least two first bright spots is less than a first preset value. A curved substrate bubble detection system is also disclosed.

An image inspection apparatus includes an illuminating section for irradiating illumination light, a line camera in which a plurality of imaging elements are arrayed to be linearly arranged, the line camera receiving the light irradiated from the illuminating section and reflected on the inspection target object, a display section for displaying an image captured by the line camera, an optical axis adjusting section for adjusting an optical axis of the line camera, a trigger setting section for specifying a trigger that specifies timing when the inspection target object is imaged by the line camera, an aspect ratio adjusting section for adjusting longitudinal and lateral pixel resolutions of the image captured by the line camera, and a display control section for displaying the optical axis adjusting section, the trigger setting section, and the aspect ratio adjusting section on the display section in order.

A manufacturing apparatus of an electrode assembly includes first and second machine visions provided on driving-direction front ends of first and second electrodes from a winding core to measure first non-overlap widths between first width-direction end portions of the first and second electrodes and first width-direction end portions of first and second separators, respectively; a controller collecting vision data obtained from the first and second machine visions; setting a non-overlap width between the first separator and the second separator to 0 through vision data, computing a third non-overlap width between the first width-direction end portions of the first and second electrodes, and judging a meandering defect with the computed third non-overlap width; a data processing unit configured to accumulate and process defect judgment data through machine learning; and an input unit configured to automatically input a meandering reference value based on the data processed by the data processing unit.

A curved substrate bubble detection method includes: providing, by a first light source and a second light source, parallel light incident to a to-be-tested substrate in different incident directions; obtaining, by a linear array camera, a first image including image information of a first side edge of the to-be-tested substrate; determining location information of a defect region of the to-be-tested substrate according to the first image, and generating a second image including image information of the defect region; binarizing the second image, and determining that the to-be-tested substrate has a bubble defect if there are at least two bright spots in an obtained binarized image, and a distance between any two first bright spots of at least two first bright spots is less than a first preset value. A curved substrate bubble detection system is also disclosed.

A diaphragm detection method includes acquiring a target image of an electrode plate to be detected. The electrode plate to be detected includes an anode electrode plate and diaphragms respectively stacked on two sides of the anode electrode plate. The method further includes performing image processing on the target image to determine a target image region in the target image, and performing diaphragm misalignment detection on the electrode plate to be detected based on the target image region.