A lmdo-based method for abnormal detection of injection molding manipulator molds

An anomaly detection and injection molding machine technology, applied in the field of injection molding machines, can solve problems such as insufficient real-time performance and poor robustness to illumination changes, and achieve the effect of enhancing real-time performance and robustness, simplifying implementation, and solving system false detections.

CN104772880BInactive Publication Date: 2017-05-24ZHEJIANG UNIV OF TECH +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Publication Date
2017-05-24
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention provides an injection molding mechanical arm mold anomaly detection method based on an LMDO (Local Multilayered Difference Operator). The anomaly detection method comprises the following steps: (1) acquiring a standard template image when an injection molding machine opens a mold in place, and pre-processing to obtain a later difference background image; (2) waiting for working state information of the injection molding machine; upon detection of a situation that the injection molding machine is operated until the mold is opened in place, continuously acquiring the image of a mold cavity by a camera, extracting an average image of the plurality of images, and pre-processing the average image to do preparation for subsequent image processing, thereby obtaining a later difference foreground image; and (3) carrying out an anomaly detection algorithm based on the LMDO on the difference foreground image and the difference background image to obtain an abnormal region without a light illumination interference part. The injection molding mechanical arm mold anomaly detection method based on the LMDO, provided by the invention, has the characteristics of good instantaneity, strong robustness on illumination variation and the like; and whether the mold has an abnormal state or not can be monitored through mold opening information of the injection molding machine.
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Description

technical field

[0001] The invention relates to the injection molding machine industry in the field of industrial automation, and is an intelligent monitoring device for molds in the production process of an injection molding machine equipped with a manipulator. Background technique

[0002] In recent years, with the continuous expansion of the application field of plastic products, the demand for injection molding machines in the global manufacturing industry has shown a continuous and substantial increase. Modern injection molding machines are equipped with manipulators, which can imitate part of the functions of human arms, and can automatically take out injection molded products, so that they can be stacked, arranged and placed according to predetermined requirements. The manipulator is an automatic production equipment specially designed and developed for injection molding machines. It can reduce the heavy physical labor of workers, improve working conditions to ensure ...

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Embodiment Construction

[0035] The present invention will be further described below in conjunction with the accompanying drawings.

[0036] refer to Figure 1 to Figure 6 , a kind of injection molding manipulator mold anomaly detection method based on LMDO, described anomaly detection method comprises following process:

[0037] 1) Collect the standard template image when the injection molding machine is in place, and perform preprocessing as the subsequent differential background image;

[0038] 2) Wait for the working status information of the injection molding machine. When it is detected that the injection molding machine is running to the mold opening position, the camera continuously captures images of the cavity surface of the mold, extracts the average image of several images, and preprocesses the average image. Prepare for subsequent image processing as the subsequent difference foreground image;

[0039] 3) Execute the LMDO-based anomaly detection algorithm on the differential foreground...