Dynamic Boundary Masks for Oscilloscope Anomaly Detection
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Solution Overview
Problem
Current oscilloscopes use a single static boundary mask for anomaly detection in waveform acquisitions, which can miss anomalies that do not cross the mask boundaries, limiting the detection of waveform irregularities.
Innovation Solution
Implementing a system with dynamic boundary masks that can change based on timing intervals or trigger events, allowing multiple boundary masks to be used for different waveform acquisitions, each with its own shape and segments, to enhance anomaly detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single static boundary mask is used for all waveform acquisitions, then the device complexity is reduced and ease of operation is improved, but the measurement precision of anomaly detection deteriorates because anomalies that do not cross the mask boundaries are missed
Solution Approach 1:
The patent transforms the static boundary mask into a dynamic system where multiple boundary masks are stored in memory, each associated with specific timing intervals. The processor automatically selects and switches between different boundary masks based on the current time, allowing the boundary mask system to adapt to varying waveform characteristics over time while maintaining automated operation.
Solution Approach 2:
The patent divides the single static boundary mask into multiple segmented boundary masks, where each mask corresponds to a specific time interval or waveform phase. This segmentation allows each boundary mask to be optimized for detecting anomalies in specific waveform conditions, thereby improving overall detection precision without requiring manual intervention.
2Adaptability or versatility
If a single static boundary mask is used, then the ease of operation is improved, but the adaptability to varying waveform shapes deteriorates, causing anomalies to be missed
Solution Approach 1:
The system becomes dynamic by storing multiple boundary masks in memory and automatically switching between them based on timing intervals. This dynamic adaptation allows the boundary mask system to match varying waveform shapes and characteristics over time without requiring manual reconfiguration, maintaining ease of operation while improving adaptability.
Solution Approach 2:
The patent changes the parameter of boundary mask selection from fixed to variable, where the active boundary mask changes based on time or trigger events. This parameter change enables the system to adapt to different waveform shapes and anomaly patterns that occur at different times, improving versatility without complicating user operation.
3Measurement precision
If multiple boundary masks with different shapes are used for different acquisitions, then the measurement precision of anomaly detection is improved, but the device complexity increases due to multiple masks and timing management
Solution Approach 1:
The system manages multiple boundary masks dynamically through automated processor control. The processor stores timing information in memory and automatically determines when to switch between boundary masks based on elapsed time or trigger events, eliminating the need for manual mask management while improving detection precision through multiple specialized masks.
Solution Approach 2:
The boundary mask system becomes self-managing through automated processor control. The processor automatically selects and switches between boundary masks based on pre-stored timing intervals and trigger events, eliminating the need for manual intervention in mask selection and timing management, thereby reducing operational complexity despite having multiple masks.
4Adaptability or versatility
If dynamic boundary mask switching is implemented, then the adaptability to varying waveform characteristics is improved, but the loss of time for mask switching and processing increases
Solution Approach 1:
The system performs preliminary actions by pre-storing multiple boundary masks and their associated timing information in memory before waveform acquisition begins. This preparation allows the processor to quickly switch between masks during acquisition based on pre-calculated timing intervals or trigger events, minimizing the time lost during mask switching while maintaining adaptability to varying waveform characteristics.
Data Source
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AI summary
A device is capable of receiving a waveform and capturing acquisitions of the waveform. Different boundary masks can be applied to the waveform acquisitions, depending on the timing of the acquisition. When a timing interval finishes, a different dynamic boundary mask can be loaded from memory. Boundary masks can include any number of segments, and can be used whenever desired.