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TSI Incorporated
Signal ProcessingSignal Processing
TSI LDV/PDPA Workshop & Training
Presented by Joseph Shakal Ph.D.
TSI Incorporated
Outline
• Nature of the Signal
• Processor Requirements
• FSA Architecture- Front End & Burst Detector
• FSA Architecture- Samplers
• FSA Architecture- Firmware Processor
• Burst Centering
• Dynamic Sampling Rate Selection
• Other Features
• Conclusion
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Nature of Doppler SignalsNature of Doppler Signals
• Amplitude not constant
• Lasts for only a short time, which itself varies
• Amplitude varies from burst to burst
• Presence of noise
• High frequency
• Random arrival
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Signal Processor - Key Signal Processor - Key RequirementsRequirements
• Use multi-bit sampling up to a high maximum frequency
• Detect and validate bursts based on SNR and amplitude
• Automatically optimize the sampling rate for each burst – Gives the best resolution in processing, even for a wide range of velocities
– This will ensure the maximum number of cycles are used
• Detect the burst center, before processing– Use the data from the middle portion of the burst first
– Use this value as the arrival time of the particle
– Detect burst duration separately
• Digitize and record additional analog and digital signals, including cyclic markers and the burst amplitude
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FSA Signal ProcessorFSA Signal Processor
Uses 8 bit sampling up to a 800MHz Detects and validates bursts based on patented real-time SNR
measurement, and also amplitude Automatically selects the optimum sampling rate for each burst,
which is also a patented technique Detects the burst center, since processing is done after sampling
process is complete The FSA EB option digitizes and records additional signals,
including cyclic markers Burst amplitude is measured as part of the patented Intensity
Validation technique
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Nature of Input SignalNature of Input Signal
Out of PMT Detector
Out of PDM
Noisy Signal
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Impact of Type of Burst Impact of Type of Burst DetectionDetection
Signal Method of Burst Detection
Source Amplitude Amplitude/Envelope Based
SNR Based
Small Particles Small Ignores Detects
Large Particles Large Detects Detects
Surface Reflections
Large DetectsIgnores
Other Noise, Spikes, etc.
Any Detects someIgnores
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The FSA Signal ProcessorThe FSA Signal Processor
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FSA ProcessorFSA ProcessorBurst Detector SubsectionBurst Detector Subsection
LUT/DFT
Amplitude Threshold
Controller
Signal Out
Burst Gate
Downmixer
Downmix Frequency
Ch 1
Frequency Estimate
Dynamic Optimum Sampling Rate
Selection
Burst Gate
Filters
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FSA ProcessorFSA ProcessorBurstBurst Sampling SubsectionSampling Subsection
Controller
Multibit A/D
SampleMemory
Signal Out
Burst Gate
Downmix Frequency
Frequency Estimate
Burst Gate
Optimally Sampled
Data
Firmware
Processing
LUT/DFT
Ch 1
Filters
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FSA ProcessorFSA ProcessorFirmware ProcessingFirmware Processing
DSPs
Burst Processing
FirewireInterface
Optimally Sampled Data
Burst gate &Burst center to PC
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FSA Block Diagram SummaryFSA Block Diagram Summary
to PC
Signals from PDM
Downmixer
Downmixfrequency generator
Amplitude threshold
Controller
8 bit A/D s Sample Memory
DSPs
Signal Out Burst Gate
FirewireInterface
Bandpassfilters
Ch 1
Ch 2
Ch 3
Frequency estimate
Burst gate
EIC/EB
pressure, temp
OPR or Shaft Encoder
LUT/DFT
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Burst Detection and Burst Detection and SamplingSampling
• Burst Detector
– Determines the approximate burst frequency
– Determines the beginning, end, and center of the burst
• Burst Sampler
– Dynamically selects the optimum sampling frequency (using the approximate frequency value) so that each and every burst is sampled at the optimum rate
– Obtains the 8 bit digital values, and passes them on to the Firmware Processing subsection
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Burst CenteringBurst CenteringBurst centering is automatically done by the FSA, and it helps give higher quality data by using only the high-SNR portion of the signal for processing. The center point of the burst is identified.From this reference point, samples are used out to a certain noise threshold, until the FSA’s data block is filled.Gate Time (transit time) is still based on the actual time the particle was in the measurement region, regardless of the portion of the signal used for processing.
BeginningEnd
Center ofburst
This portion used for processing
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Dynamic Sampling Rate Dynamic Sampling Rate SelectionSelection
Example
Burst gate
Particle 1 velocity = u sampling rate: F
Particle 2 velocity = 2u sampling rate: 2F
Particle 3 velocity = 4u sampling rate: 4F
Burst gate
Burst gate
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Flow and Size Analyzer (FSA)Flow and Size Analyzer (FSA)Other unique features and benefits of the FSA• Built in input buffer, for high data rate situations• Size measurement validation
– Patented intensity validation uses an independent measured quantity to validate the diameters. We do not need receiver masks, and we can see what is being rejected and what is being accepted.
– Phase validation, uses the degree of agreement between the two independent phase measurements to discriminate between reflection and refraction
• Short transit time flows (50ns minimum gate time)– Particle size measurements in dense sprays, where we need very
small measuring volumes, resulting in short-transit-time burst signals– Size measurements in (pulsed) high velocity sprays– Velocity measurements in supersonic flows
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Measured Parameters
Ch. 1Velocity Mean (m/sec) 20.390Velocity RMS (m/sec) 1.4284Turbulence Intensity (%) 7.01Frequency Mean (MHz) 6.3207Frequency RMS (MHz) 0.4428Frequency TI (%) 7.01Gate Time Mean (usec) 2.26Gate Time RMS (usec) 1.32Data Rate (Hz) 43245Valid Count 2663Invalid Count 0Elapsed Time (sec) 0.0616
Statistics
Plots
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ConclusionsConclusions
• Examined the nature of Doppler signals
• Looked at processor requirements
• FSA Architecture- Front End & Burst Detector
• FSA Architecture- Samplers
• FSA Architecture- Firmware Processor
• Saw how burst centering works and its benefits
• Looked at how dynamic sampling rate selection is done and its benefits
• Other benefits of the FSA, like high-speed capabilities for dense sprays and high speed flows, and FireWire connectivity
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