Masana'antu sassa Smart gani ganewa kayan aiki

A matsayin sanannen kayan aiki na kayan aiki na kayan aiki na kayan aiki na kayan aiki na kayan aiki na kayan aiki na kayan aiki na kayan aiki na kayan aiki,Shanghai Armor sarrafa kansa Technology Co., LtdThe fasaha sabis samar da fasaha mafita ga kasar Sin masana'antu tare da kasa da kasa synchronized masana'antu sassa mai hankali gani ganowa kayan aiki. Masana'antu sassa Smart gani ganewa kayan aikiAikace-aikace ga: Pharmaceutical, abinci, abin sha, rana chemical, kiwon lafiya kayayyakin, lantarki, lantarki, sinadarai, mota masana'antu da filastik da kayan aiki da sauran manyan masana'antu!

Masana'antu sassa Smart gani ganewaNa'uroriaFasahar sarrafa hoto ta dijital ita ce masana'antar fasaha mai tasowaAn riga an yi amfani da su a fannoni kamar tsarin sarrafa kansa, gano sassan mota da ganewa mai hankali. Ya zama daya daga cikin mahimman hanyoyin ganowa na gargajiya tare da jinkirin ganowa da ƙarancin ingancin ganowa. Saboda a ainihin samarwa, sassan masana'antu suna da lahani da yawa a cikin cikakkun bayanai, saboda haka yana da mahimmanci a zaɓi algorithm mai dacewa don ganowa da ganowa daidai. Wannan labarin ya shafi sassan akwatin bayan akwatin mota, ya tsara tsarin gano hoto gaba ɗaya, ya gina dandalin kayan aikin gwaji, kuma ya bayyana cikakken tsari na na'urori daban-daban da tsarin haske da aka yi amfani da tsarin gani, sannan ya yi daidaitawar tsarin kyamara, ya kammala gyaran tasirin karkatarwa. Bayan samun hoton da aka gyara, an mayar da hankali kan mahimman fasahohi kamar pre-processing na hoton, ganowa na gefe, auna sigogin lissafi na sassa. A cikin pre-processing, da farko an bincika nau'ikan amo na hoton, kwatanta daban-daban tacewa algorithms don gano tacewa algorithms da suka dace da hoton wannan labarin. Bugu da ƙari, a cikin ganewar gefen hoto, an kwatanta algorithm na ganewar gefen gargajiya don samar da tushe don cire fasali na gaba. A lokacin gano tushen halaye na hoton, an gano zagaye da layi daidai a cikin hoton daban-daban, kuma an inganta sigogin sakamakon ganowa don inganta tasirin gano zagaye da layi daidai. Lokacin gano ramin a cikin hoton, an yi amfani da algorithm na daidaitawa na samfurin don gano daidai wurin ramin. Bayan shiga cikin gwajin girman sassa, a cikin rubutun kuma ya bincika hanyoyin ganewar rarrabuwa uku na sassa masu kyau, sassan waldi da sassan scratching. Da farko, ta hanyar gano gefen, a kan tabbatar da cewa gefen hoto ya bayyana da cikakkiyar tushe, amfani da algorithm na gradient direction histogram don cirewar halaye, da kuma amfani da hanyoyin sadarwar jijiyoyi na yiwuwa da SVM don ganewar rarrabawa, ya sami kyakkyawan sakamakon rarrabawa. Koyaya, siffofin vector masu girma, bayanan cire siffofin suna haɗuwa don haka muhimman bayanan hoto suna da wuya a yi amfani da su sosai. An inganta algorithm na histogram na hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar hanyar Aikace-aikacen wannan batun yana dogara ne akan Visual C ++ da MATLAB, gami da ci gaban dubawa na tsarin gani da rubutun algorithms. Wannan labarin ya aiwatar da ganewar halayen sassa, tare da ganewar nau'ikan rarraba sassa daban-daban. Sakamakon binciken da aka samu a cikin rubutun ya nuna wasu darajar injiniya, yayin da yake ba da wasu ma'ana game da aikace-aikacen fasahar auna hoto da ganewar rarraba sassa.

Intelligent visual inspection equipment

As a well-known packaging intelligent automation equipment research and development enterprise at home and abroad, Shanghai Lujia Automation Technology Co., Ltd. provides technical solutions for the Chinese manufacturing industry to synchronize intelligent visual inspection equipment for industrial parts. Widely used in: pharmaceutical, food, beverage, daily chemical, health care products, electronics, electrical appliances, chemicals, automotive industry and plastics and hardware industries!

Intelligent visual inspection equipment for industrial components is an emerging technology industry in digital image processing technology. It has been widely used in automation systems, automotive parts inspection and intelligent identification. It has become one of the important solutions for slow manual detection and low detection efficiency. Due to the defects in the details of industrial parts in actual production, it is necessary to use an appropriate algorithm to accurately identify and detect them. In this paper, the overall scheme of the image detection system is designed for the back part of the car energy-absorbing box. The experimental hardware platform is built, and the components of the various components and lighting systems used in the vision system are introduced in detail. Then the camera system is calibrated and completed. Correction of distortion effects. After obtaining the corrected image, key technologies such as image preprocessing, edge detection and part geometric parameter measurement were studied. In the preprocessing, the noise class of the image is first analyzed, and various filtering algorithms are compared to find the filtering algorithm suitable for the image. Furthermore, in the image edge detection, the classic edge detection algorithm is compared, which provides the basis for the subsequent feature extraction. When detecting the basic features of the image, the circles and lines in the image are detected separately, and the parameters of the detection result are optimized to improve the detection effect of the circle and the line. When detecting the slot in the image, a template matching algorithm is used to accurately identify the position of the slot. After the inspection of the part size, the classification and identification methods of the intact parts, the solder joint parts and the scratch parts were also studied. Firstly, through the edge detection, on the basis of ensuring the image edge is clear and complete, the gradient direction histogram algorithm is used for feature extraction, and the probabilistic neural network and SVM are used for classification and recognition, and a good classification effect is obtained. However, the feature vector dimension is high, and the feature extraction information is aliased, so that the key information of the image is difficult to fully utilize. In this paper, the gradient direction histogram algorithm is improved, and the gradient direction histogram feature extraction algorithm is bilinearly interpolated. The feature vector which can reflect the detailed features is obtained, and then the neural network and support vector machine are used for recognition. The anti-aliasing effect of the value also improves the accuracy of classification and recognition of images. The implementation of all modules of this topic is based on Visual C++ and MATLAB, including visual system interface development and algorithm writing. This paper realizes the detection of part features and the classification and identification of different types of parts. The research results in this paper reflect a certain engineering value, and provide some reference for the application of image measurement technology and the classification and identification of parts.