FPGA Materials Test Control With Parallel Feedback Loops
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Solution Overview
Problem
Modern materials testing requires scalability, adaptability, parallelism, and speed to handle the increasing variety of advanced materials with complex properties, but existing hardware-based systems lack these capabilities, making them inflexible and costly to update for new standards and materials.
Innovation Solution
The implementation of FPGA-based controllers that enable reconfiguration, parallelism, and high-speed data processing, allowing for adaptable and efficient materials testing by incorporating parallel control and data acquisition circuits, and implementing feedback control loops, actuator control, and digital signal monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional hardware-based testing systems are used, then system stability is maintained, but adaptability to new materials and standards deteriorates
Solution Approach 1:
The patent applies dynamics by transitioning from static hardware configuration to dynamic reconfigurability through FPGAs. The testing system can be dynamically reconfigured via software to accommodate different materials and standards without physical hardware changes, enabling the system to adapt its architecture and functionality on-demand.
Solution Approach 2:
The patent implements universality by designing a multi-functional testing platform where a single hardware system can perform multiple testing functions across different materials and standards. The FPGA-based architecture allows one system to universally handle various test types through software configuration rather than requiring dedicated hardware for each function.
2Speed
If sequential data processing is used, then system simplicity is maintained, but processing speed deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the data processing workflow into parallel segments that can be executed simultaneously. The testing system processes multiple data streams in parallel through separate processing channels, allowing simultaneous acquisition, analysis, and control operations rather than sequential execution.
Solution Approach 2:
The patent transitions from one-dimensional sequential processing to multi-dimensional parallel processing by introducing additional processing dimensions. Multiple data streams are processed concurrently across different computational planes, effectively adding temporal and spatial dimensions to the processing architecture.
3Measurement precision
If dedicated hardware is designed for each testing standard, then measurement precision is maintained, but cost-effectiveness deteriorates
Solution Approach 1:
The patent applies copying by creating virtual replicas of testing standards through software rather than physical hardware copies. Each testing standard is implemented as a software model that can be instantiated and configured as needed, allowing precise replication of standard requirements without duplicating expensive hardware for each standard.
Solution Approach 2:
The patent implements parameter changes by allowing the testing system to dynamically adjust its operational parameters through software configuration. The FPGA-based architecture enables changing testing parameters, measurement ranges, and control characteristics without hardware modification, maintaining precision across different standards through parameter adjustment rather than hardware redesign.
4Manufacturing precision
If feedback control loops are implemented, then control accuracy is improved, but system complexity increases
Solution Approach 1:
The patent implements feedback control loops that continuously monitor testing parameters and automatically adjust control signals to maintain desired performance. The system captures sensor data, compares it against target values, and generates corrective control actions in real-time, enabling precise control of testing processes through closed-loop feedback mechanisms.
Data Source
AI summary
Techniques are described for a materials test controller that includes a Field-Programmable Gate Array (FPGA). The FPGA is configured for acquiring sensor data from sensor device(s) that measure the current state of sample material(s) on which the materials testing is performed. For controlling the actuator device, the FPGA generates a waveform of setpoints; each setpoint represents a desired state of the materials testing. Based on the sensor data, the FPGA calculates process variable(s) for input to a control logic of the FPGA. Using multiple iterations to generate output signals for the actuator device, the control logic receives the process variable(s) and a setpoint of, and based at least on these received inputs, generates an output signal. The output signal of the FPGA causes the actuator device to transition from the current state to a new state that is closer to the desired state as measured by the sensor devices.