Acoustic Glass Classification via Knock and Echo Analysis
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Solution Overview
Problem
Conventional glass recycling methods face inefficiencies due to the mixing of different glass types, leading to low-quality products and increased manual sorting needs, as optical and machine vision methods struggle with accuracy and efficiency in classifying waste glass.
Innovation Solution
A computer-implemented method using acoustic analysis, involving a classifying apparatus that receives sound data from knocking glass objects and performs knock-sound and echo-decay analyses to differentiate between organic and inorganic glass, and further classify inorganic glass into types like crystal, borosilicate, and soda-lime glass.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If optical sensing and machine vision methods are used to classify glass, then automation is improved, but classification accuracy deteriorates due to lack of spectral features and color variations
Solution Approach 1:
The patent replaces optical sensing and machine vision methods with acoustic sensing methods. Instead of using cameras and optical sensors to detect glass properties, the system uses acoustic sensors to detect sound waves generated when glass objects are dropped or struck. This substitution of detection mechanism overcomes the limitation of optical methods that cannot reliably distinguish glass types due to color and spectral feature variations.
Solution Approach 2:
The patent changes the detection parameter from optical properties (color, spectral features) to acoustic properties (sound frequency, sound intensity, echo characteristics). By measuring the acoustic response of glass objects when subjected to mechanical impact, the system can identify glass types based on their unique acoustic signatures, which are determined by material composition, density, and structural properties rather than visual appearance.
2Productivity
If conventional recycling methods mix different glass types, then processing speed is improved, but product quality deteriorates due to contamination
Solution Approach 1:
The patent implements preliminary classification of glass objects by type before they are mixed for recycling processing. By using acoustic detection to identify and separate different glass types (such as soda-lime glass, borosilicate glass, and crystal glass) before the recycling process begins, the system ensures that each glass type can be processed separately, maintaining product quality while still achieving efficient automated processing.
Solution Approach 2:
The patent segments the glass waste stream into distinct categories based on acoustic characteristics. Instead of processing all glass together, the system divides glass objects into different groups (container glass, flat glass, crystal glass, etc.) based on their acoustic responses, allowing each segment to be processed appropriately for its specific material properties and ensuring high-quality recycled products.
3Measurement precision
If manual sorting is used to separate glass types, then classification accuracy is improved, but labor requirements and time consumption increase
Solution Approach 1:
The patent replaces manual sorting operations with automated acoustic detection and classification systems. Sensors detect the acoustic responses of glass objects as they move through the processing line, and a control system automatically identifies and directs different glass types to appropriate processing streams. This automation maintains the high classification accuracy of manual sorting while eliminating the time consumption and labor requirements.
Solution Approach 2:
The patent implements continuous classification of glass objects as they move through the recycling process, rather than requiring batch-by-batch manual sorting. The acoustic detection system operates continuously, identifying and categorizing glass types in real-time, which maintains accurate classification while dramatically reducing the time required compared to intermittent manual sorting operations.
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 enhances classification accuracy and reduces manual sorting labor by effectively distinguishing between various glass types through acoustic analysis, improving the efficiency of the glass recycling process.
Implementation Method 1
receiving, by a processor of the classifying apparatus, sound data of a sound of a knock generated by knocking the glass object from a sensor of the classifying apparatus
Implementation Method 2
receiving, by the processor, echo data of an echo induced by applying an ultrasonic-echo operation to the glass object from a transceiver of the classifying apparatus
Implementation Method 3
applying an ultrasonic-echo operation to the glass object
Data Source
AI summary
A method for classifying a glass object via acoustic analysis by a classifying apparatus is provided. The method including: receiving, by a processor, sound data of a knock sound generated by applying a knocking operation on the glass object; determining, by the processor, a type of the glass object by performing a knock-sound analysis to the sound data, wherein the type of the glass object includes an organic glass and an inorganic glass; if the type of the glass object is determined as the inorganic glass, receiving, by the processor, echo data of an echo induced by applying an ultrasonic-echo operation on the glass object; and determining, by the processor, a further type of the glass object by performing an echo-decay analysis to the echo data, wherein the further type of the glass object includes a crystal glass, a borosilicate glass and a soda-lime glass.