Acoustic Diagnostics for Additive Manufacturing Process Drift
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Solution Overview
Problem
Additive manufacturing processes face challenges with process drift over long build times, leading to waste and defects due to variations in process stability, nozzle wear, and nozzle blockage, which are not effectively monitored by existing methods.
Innovation Solution
Implementing an acoustic monitoring system with sensors to capture time-dependent acoustic data signals, transforming them into frequency-domain spectra, and using correlation modules to determine process attributes, enabling real-time control and feedback for maintaining process stability and preventing defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If acoustic monitoring is implemented to detect process attributes in real-time, then manufacturing precision and reliability improve, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical monitoring systems with acoustic field-based detection. Acoustic sensors capture sound waves generated during material deposition, and signal processing algorithms extract process attributes (nozzle wear, blockage, temperature) from these acoustic signals, substituting mechanical measurement methods with acoustic-based detection to reduce system complexity while maintaining precision
Solution Approach 2:
The patent introduces acoustic signals as an intermediary medium to indirectly measure process attributes. Instead of directly measuring physical parameters like nozzle wear or temperature, the system uses acoustic emissions as a mediator that carries information about these attributes, enabling non-contact, real-time monitoring through signal analysis
2Reliability
If real-time acoustic monitoring is used to detect nozzle wear and blockage, then reliability improves, but loss of time in processing and analyzing signals increases
Solution Approach 1:
The patent implements preliminary action by pre-processing acoustic signals through bandpass filtering and Fast Fourier Transform (FFT) conversion to frequency domain spectra in real-time. This preliminary signal processing prepares the data for rapid attribute extraction, reducing the computational burden and time required for subsequent analysis of process attributes
Solution Approach 2:
The patent applies partial action by focusing acoustic monitoring on specific frequency bands associated with particular process attributes. Instead of analyzing the entire acoustic spectrum, the system targets specific frequency ranges that correlate with nozzle wear, blockage, and temperature, reducing processing time while maintaining detection accuracy
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 real-time monitoring and control of additive manufacturing processes, reducing defects by detecting nozzle wear and blockage, and ensuring consistent quality through automated adjustments and alerts.
Implementation Method 1
at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of an acoustic signal generated by an additive manufacturing system
Data Source
AI summary
An example system includes at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of an acoustic signal generated by an additive manufacturing system performing a process possessing a plurality of process attributes. The process includes depositing material by interaction of an energy beam and a material stream on a build target to form a structure. The system includes a computing device including an acoustic data signal processing module configured to receive the at least one time-dependent acoustic data signal, and transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum. Each process attribute of the plurality of process attributes may be associated with at least one respective frequency band. The computing device may further include a correlation module configured to determine a process attribute of the plurality of process attributes by identifying at least one characteristic of the frequency-domain spectrum.