Injecting Mold Protection Method Based on Machine Vision

Abstract

Aimed at solving the problem of mold damage caused by a foreign body in the mold before mold clamping, this paper proposes a solution, which applies image processing technology such as background updating and the difference image algorithm to solve it. Not only can it judge whether there is a foreign body in the mold but it can also detect whether the product is perfect by comparing the foreground image with the background image at the appropriate time (before mold clamping or after mold opening) and by calculating the qualified rate of pixel in all ROIs (Region of Interest). To eliminate the influence of vibration and of changes in brightness in the surrounding environment on the detecting results, this paper utilizes near infrared illumination technology and the background updating algorithm. In addition, the ROI is set to improve the detecting speed and accuracy.

EMP: Extended Kalman Filter Based Self-Adaptive Mold Protection Method on a Toggle Mechanism

“…U and L are upper deviation current curve and lower deviation current curve, respectively; and the dimension of U and L is m. ∆ is true error. Regarding Equation (18), the safety range at every position should be between the maximum and minimum currents within n self-adaptive processes. Note that ∆ is necessary because the self-adaptive time n is limited.…”

“…Wang et al [18] presented a method that applied technologies, such as near infrared illumination technology, the background updating algorithm, and the region of interest, to fulfill MP. Yang et al [19] applied key technologies, including the methods for pretreatment of the cavity image, template matching of the cavity image, and cross-correlation of an abnormal cavity situation, into MP.…”

A novel vision-based mold monitoring system in an environment of intense vibration

“…The selection of each device proposed in the detection system must consider these two points. The mold protection system described in this paper is generally divided into three parts: an image acquisition and processing module, a signal transmission module, and a module that controls lighting and other auxiliary components according to the actual demand [12]. Figure 1 shows the basic workflow of the mold monitoring system, its components, and their links in detail.…”

“…Recently, some noncontact detections based on machine vision have been used more widely in many situations such as precise tool positioning [10], measurement of gear parameters [11], and monitoring the injection mold machine [1]. In [12], background updating and the difference image algorithm were applied to protect the mold from damage by a foreign body in the mold before mold clamping. In [13], a method was proposed to ensure compliance with online testing requirements…”

Anomaly detection in periodic motion scenes based on multi-scale feature Gaussian weighting analysis

“…A characteristic of the main manufacturing procedure in most processing machines is periodic motion, which ensures highly stable production quality [1]. However, the production process often involves anomalies, such as splashing of foreign bodies and loosening of machine parts [2,3], which result in workpiece damage, waste products, and even equipment damage and device malfunction, causing significant economic losses [4]. Therefore, anomaly monitoring of processing equipment has become an important method for ensuring normal operation.…”