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What are the advantages of CNC machining of radiator parts?

For friends who have been in contact with the radiator component industry, they often see or hear "CNC machining", but too much exposure does not necessarily mean that many people understand. In fact, many questions are still about CNC machining. What are the advantages? Let's take a closer look. CNC machining is an index-controlled machine tool machining, which is a method of using digital information to control the machining process. Traditional mechanical processing is done manually by machine tools. During processing, the mechanical cutter is shaken to cut metal, and the accuracy is measured with calipers and other tools. However, traditional artificial intelligence processing is far from being able to meet the needs of production development. Therefore, the emergence of CNC machining provides the possibility for the standardization, precision and efficiency of mechanical product processing. The CNC machining process in the radiator component industry also shines. The

Investment Casting Materials and Manufacturing Process

Mold material The performance of the molding material should not only ensure the convenient production of investment molds with accurate dimensions and high surface finish, good strength and light weight, but also create conditions for the manufacture of mold shells and good castings. Molding materials are generally formulated with waxes, natural resins and plastics (synthetic resins). All mold materials mainly prepared with wax materials are called wax-based mold materials, and their melting point is low, 60~70 ° C; all mold materials mainly prepared with natural resins are called resin-based mold materials, with a slightly higher melting point, about 70 °C. ~120℃.   Precision Investment Castings China prototype company service include :  High Quality Investment Casting Parts Custom , Lost Wax Investment Casting Sand Casting , Lost Foam Casting , Gravity Casting , Die Casting , Graphite Casting , Casting Moldsmanufacturers . Manufacture of Folding Investments In t

알루미늄 합금 다이캐스팅의 단점을 해결하는 것이 편리합니다!

알루미늄 합금 다이캐스팅은 현재 현재의 전자제품 , 자동차 , 생활필수품 등 많은 산업과 분야에서 널리 사용되고 있습니다 . 그러나 알루미늄 합금 다이캐스팅에서 자주 발생하는 몇 가지 결함 및 해결 방법은 다음과 같습니다 .   알루미늄 합금 다이캐스팅   1. 불순물   알루미늄 합금 다이 캐스팅의 불순물 문제는 주로 특정 온도에서 알루미늄 , 규소 및 다량의 철 , 망간 , 크롬 및 기타 화합물을 포함하는 결정립과 일부 산화물로 구성됩니다 .   해결책 : 알루미늄 잉곳의 조성을 엄격하게 제어하고 , 제련로의 난로를 정기적으로 청소하고 , 정기적으로 슬래그를 처리하면 문제를 해결할 수 있습니다 .   2. 구강 문제   다공성은 다이캐스팅 부품의 내부 또는 표면에 나타나는 다양한 크기의 구멍을 말하며 , 이는 다이캐스팅 부품의 경도 부족으로 이어져 표면의 외관에 영향을 줍니다 .   Solution: 적절한 정제제를 사용하여 모공을 처리하고 , 공정을 조정하고 , 저속을 적절하게 줄이고 , 이형제가 너무 많이 분사되어 모공 문제가 해결되지 않는지 확인하십시오 .   3. 균열 문제   균열은 알루미늄 합금 다이캐스팅의 매트릭스가 파괴되고 , 외력의 작용에 따라 확장되는 경향이 있는 선형 또는 기타 라인인 기다란 틈이 형성되는 것을 의미합니다 .   솔루션 : 합금 조성을 올바르게 제어하고 , 냉각수 회로를 늘리고 , 알루미늄 합금 다이캐스팅의 구조를 변경하고 , 사출 위치를 변경하거나 증가시키면 해결할 수 있습니다 . PINJIN 서비스에는 다음이 포함됩니다 . 알루미늄 다이캐스팅 , 아연 다이캐스팅 , 마그네슘 다이캐스팅 , 투자 주조 , 모

Analysis of License Plate Recognition Technology

License plate recognition is a pattern recognition technology that uses the dynamic video or static image of the vehicle to automatically recognize the license plate number and the color of the license plate. The core of the technology includes license plate location algorithm, license plate character segmentation algorithm and optical character recognition algorithm.
The working principle of license plate recognition technology
Vehicle detection: Buried coil detection, infrared detection, radar detection technology, video detection and other methods can be used to sense the passing of the vehicle and trigger image capture.
Image collection: Real-time and uninterrupted recording and collection of passing vehicles through the high-definition camera capture host.
Preprocessing: noise filtering, automatic white balance, automatic exposure and gamma correction, edge enhancement, contrast adjustment, etc.
License plate location: Scan the rows and columns on the grayscale image after image preprocessing to determine the license plate area.
Character segmentation: After locating the license plate area in the image, through grayscale, binarization, etc., the character area is accurately located, and then the character segmentation is performed according to the character size characteristics.
Character Recognition: The segmented characters are scaled, feature extraction, and the standard character expression form in the character database template is matched and judged.
Result output: output the result of license plate recognition in text format.
License plate recognition technology workflow
The license plate recognition system adopts a highly modular design, which treats each link of the license plate recognition process as an independent module.
One, vehicle detection and tracking module
The vehicle detection and tracking module mainly analyzes the video stream, judges the position of the vehicle in it, tracks the vehicle in the image, and records a close-up picture of the vehicle at the best time of the vehicle position. Thanks to the addition of the tracking module, the system can be very good To overcome various external interferences, make more reasonable recognition results, detect unlicensed vehicles and output the results.
2. License plate positioning module
The license plate location module is a very important link and the basis of the follow-up link. Its accuracy has a huge impact on the overall system performance. The license plate system completely abandons the previous algorithmic ideas, and realizes a new algorithm for license plate positioning based on the fusion of multiple features based on learning, which is suitable for various complex background environments and different camera angles.
3. License plate correction and fine positioning module
Due to the limitation of shooting conditions, the license plate in the image is always inevitably tilted. A correction and fine positioning link is required to further improve the quality of the license plate image and prepare for the segmentation and recognition module. Using a well-designed fast image processing filter, not only the calculation is fast, but also the overall information of the license plate is used to avoid the influence of local noise. Another advantage of using this algorithm is that through the analysis of multiple intermediate results, the license plate can also be precisely located, which further reduces the impact of non-license plate areas.
Four, license plate segmentation module
The license plate segmentation module of the license plate system utilizes the grayscale, color, edge distribution and other characteristics of the license plate text, which can better suppress the influence of other noise around the license plate, and can tolerate the license plate with a certain tilt angle. This algorithm is conducive to applications such as mobile inspections where the license plate image is noisy.
Five, license plate recognition module
In the license plate recognition system, a combination of multiple recognition models is usually used for license plate recognition, and a hierarchical character recognition process is constructed, which can effectively improve the accuracy of character recognition. On the other hand, before character recognition, the use of computer intelligent algorithms for pre-processing of character images can not only preserve image information as much as possible, but also improve image quality, improve the distinguishability of similar characters, and ensure the reliability of character recognition.
Six, license plate recognition result decision-making module
Recognition result decision-making module, specifically, the decision-making module uses the historical record left by the process of a license plate through the field of vision to make intelligent decision-making on the recognition result. It obtains the comprehensive credibility evaluation of the license plate by calculating the number of observation frames, the stability of the recognition result, trajectory stability, speed stability, average credibility, and similarity, so as to determine whether to continue tracking the license plate or output Identify the result, or reject the result. This method comprehensively utilizes the information of all frames, reduces the accidental errors caused by the previous recognition algorithms based on a single image, and greatly improves the recognition rate of the system and the correctness and reliability of the recognition results.
Seven, license plate tracking module
The    license plate tracking module records various historical information such as the position, appearance, recognition result, credibility, etc. of the license plate in each frame of the vehicle’s driving process. Because the license plate tracking module uses a motion model with a certain fault tolerance and an update model, those license plates that are blocked or blurred for a short time can still be tracked and predicted correctly, and only one recognition result will be output in the end.

Link to this article:Analysis of License Plate Recognition Technology

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