AE Sensor Kneading State Detection for Extrusion Molding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for determining the kneading state of raw materials in extrusion molding machines are indirect and rely on experience, as the variation in measured physical quantities is often small, making real-time monitoring unreliable.
Innovation Solution
A kneading state detection device that uses an AE sensor to acquire and analyze the change in intensity of acoustic emission signals over time, comparing them to a threshold to determine the kneading state of raw materials, allowing for real-time monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional indirect monitoring methods (pressure sensor, temperature sensor, torque variation) are used to determine kneading state, then the monitoring can be implemented with existing sensors, but the measurement precision is insufficient because the variation amount of physical quantities is very small
Solution Approach 1:
The patent replaces mechanical/thermal measurement systems (pressure sensors, temperature sensors, torque sensors) with an acoustic emission detection system. The AE sensor detects high-frequency sound waves generated during kneading, providing direct and precise measurement of the kneading state without relying on indirect physical quantity variations.
Solution Approach 2:
The patent changes the measurement parameter from indirect physical quantities (pressure, temperature, torque) to direct acoustic emission parameters (AE signal intensity, frequency characteristics). This parameter change enables direct detection of kneading state with higher precision, as AE signals directly reflect the mechanical activity during kneading.
2Reliability
If indirect monitoring methods are used, then the implementation is simpler, but the reliability of real-time detection is insufficient and requires experience and intuition
Solution Approach 1:
The patent implements a feedback mechanism where AE sensor signals are continuously monitored and processed to provide real-time information about kneading state. The determination unit compares AE signal characteristics against thresholds to automatically determine whether kneading is complete, eliminating the need for operator experience and intuition.
Solution Approach 2:
The patent introduces an intermediary processing system that includes an amplifier to boost weak AE signals and a determination unit that processes the signals using predetermined thresholds. This intermediary system transforms raw acoustic signals into reliable kneading state determinations, making the system easy to operate without requiring expert knowledge.
3Productivity
If conventional sensors are used for monitoring, then the device structure is simpler, but the detection is not direct and cannot provide real-time accurate monitoring
Solution Approach 1:
The patent replaces indirect mechanical sensing with direct acoustic emission sensing. The AE sensor directly detects the sound waves generated by material kneading, providing real-time information without the information loss inherent in indirect measurement methods.
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
Enables reliable real-time detection of the kneading state, reducing material waste and ensuring consistent product quality by directly monitoring the kneading process.
Implementation Method 1
acquires an output of an AE sensor installed on a housing of the extrusion molding machine
Implementation Method 2
an AE sensor that detects an acoustic emission wave
Data Source
AI summary
A kneading state detection device includes an acquisition unit that, when an extrusion molding machine that kneads a raw material or kneads a raw material and an additive is in operation, acquires an output of an AE sensor installed on a housing of the extrusion molding machine, and a determination unit that determines a kneading state of the raw material, based on a comparison between a change in intensity of the output of the AE sensor acquired by the acquisition unit and a threshold.