Injection Molding Plasticization Diagnosis With Multi-Position AE Sensors
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Solution Overview
Problem
Existing material monitoring apparatuses for injection molding machines lack sufficient three-dimensional and qualitative information about the plasticization process, making them less practical and effective in diagnosing the plasticized state of molding materials.
Innovation Solution
The apparatus employs multiple AE sensors positioned along the heating cylinder to detect AE waves, processing position data, attack numbers, and event counts to graphically display generation patterns, enhancing positional and qualitative understanding of plasticization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single AE sensor is disposed at a rear portion of the heating cylinder to detect acoustic emission waves, then the detection of quantitative acoustic emission data related to deformation or shear of the molding material is enabled, but the detection is not sufficient for obtaining specific and practical information such as the position where an acoustic wave is generated and the cause of the acoustic emission
Solution Approach 1:
The heating cylinder is divided into multiple detection zones by disposing several AE sensors (first AE sensor at rear portion, second AE sensor at forward portion) at different positions along the heating cylinder. This segmentation allows each sensor to monitor specific regions, enabling localization of acoustic wave generation positions and providing more comprehensive information about the plasticization process throughout the entire heating cylinder.
Solution Approach 2:
The detection system transitions from a single-point detection (one sensor at rear portion) to multi-dimensional detection by adding sensors at different positions along the heating cylinder's length. This dimensional expansion enables three-dimensional plasticization information to be obtained, including positional data about where acoustic waves are generated within the heating cylinder.
2Loss of information
If multiple AE sensors are disposed at different positions on the heating cylinder to obtain three-dimensional plasticization information, then the positional and qualitative understanding of plasticization is enhanced, but the device complexity increases
Solution Approach 1:
The data processing section is designed to perform multiple functions: it processes signals from multiple AE sensors, calculates arrival time differences, determines acoustic wave generation positions, counts attack numbers and events, and generates graphical displays. This multi-functional design consolidates what could be separate complex subsystems into a single integrated unit, managing the complexity while providing comprehensive analysis capabilities.
Solution Approach 2:
The system merges the detection functions of multiple AE sensors into a unified monitoring system where all sensors work together under a single data processing section. The graphical display section integrates information from all sensors into a single visual representation, combining multiple data streams into one comprehensive output that shows the overall plasticization state across the heating cylinder.
3Ease of operation
If quantitative detection of acoustic emission waves is performed using a single sensor, then the monitoring is simple and easy to operate, but the ability to diagnose plasticization quality and identify specific issues is limited
Solution Approach 1:
The system provides feedback through graphical displays that show acoustic wave generation positions, attack numbers, and event counts along the heating cylinder. This visual feedback enables operators to quickly identify problems such as incomplete plasticization or abnormal shear conditions at specific locations, improving diagnostic reliability while maintaining ease of operation through intuitive graphical interfaces.
Solution Approach 2:
The system replaces subjective visual inspection and manual diagnosis with automated acoustic emission detection and computer-based analysis. The data processing section automatically analyzes the acoustic signals and generates diagnostic information, substituting mechanical/manual diagnostic processes with automated electronic systems that provide more reliable and objective plasticization quality assessment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides accurate, convenient, and reliable monitoring of the plasticized state, allowing for efficient diagnosis of plasticization quality and potential issues, with flexible threshold settings and noise filtering for improved accuracy.
Implementation Method 1
an acoustic emission wave sensing sensor which senses an acoustic emission wave generated when the molding material is deformed or sheared within the heating cylinder and converts the sensed acoustic emission wave to an electric signal
Data Source
AI summary
A plurality of AE sensors 6r, 6f are provided on a heating cylinder 2 at a plurality of different positions Xr, Xf in a forward-rearward direction Fs so as to detect AE waves AE waves We. Position data Dx related to a position where each AE wave We is generated are obtained on the basis of arrival times Tr, Tf of the AE wave We obtained from the AE sensors 6r, 6f. For each combination of a predetermined sampling period Tp and a predetermined set of the position data Dx, the number of times AE wave signals Sfe, etc. related to the generated AE wave We have exceeded a threshold value L set beforehand is obtained as attack number data Da. The number of AE wave signal components Sp having exceeded a threshold value set beforehand is obtained as event count data De. At least a generation pattern Ps of sets of the attack number data Da and sets of the event count data De which correspond to sets of the position data Dx is graphically displayed.