Design and Implementation of Nondestructive Evaluation Instrument for Acoustic-based Wood Modulus of...

Design and Implementation of Nondestructive Evaluation Instrument for Acoustic-based Wood Modulus of Elasticity Prediction

Design and Implementation of Nondestructive Evaluation Instrument for Acoustic-based Wood Modulus of Elasticity Prediction

Undergraduate Thesis

Abdurrachman Mappuji

12/329912/TK/39124

Department of

Nuclear Engineering& Engineering Physics

Presentation Outline

Introduction and Motivation

Nondestructive Evaluation of Wood

Instrumentation Design & Tests

Results and Discussion

Conclusion

Future Work

Q & A






Conclusion

Future Work

Q & A

Wood

Versatile material

Used in various applications

Construction

Furniture

Art

Etc.

Is an anisotropic material

mechanical properties changes with direction along object

Graded by elastic properties e.g. MOE

Indonesia ranked 7th top wood exporters

based on Worlds Richest Country in 2015

Figure 1. Wood StackImage by Aora Smith

Wood Grading

A quantitative measurement of wood strength

Classified wood by its quality

SNI 7973-2013 used MOE as one of grading parameters

Nondestructive evaluations are involved
Quality CodeMOE (MPa)EEminE2525,00012,500E2424,00012,000E2323,00011,500E2222,00011,000E2121,00010,500E2020,00010,000E1919,0009,500E1818,0009,000E1717,0008,500E1616,0008,000E1515,0007,500E1414,0007,000E1313,0006,500E1212,0006,000E1111,0005,500E1010,0005,000E99,0004,500E88,0004,000E77,0003,500E66,0003,000E55,0002,500
Table 1. SNI Wood Grading

Modulus of Elasticity

Is the stiffness of a material

Used for wood grading

Some nondestructive evaluations are available

MOE = /

where,

= stress = F/A

= strain = L/L0

Figure 2. MOE illustration






Conclusion

Future Work

Q & A


Identifying the physical and mechanical properties of a piece wood material w/o altering its end-use capabilities [1]

Types of evaluation

Visual characteristics

Chemical tests

Physical tests

Mechanical tests

[1] Ross, R. J. (Ed.). (2015). Nondestructive Evaluation of Wood (2nd Ed.). Forest Product Laboratory U.S. Department of Agriculture.

Visual characteristics

Color

Presence of defects

Chemical tests

Composition

Presence of treatments

Preservatives (Pengawet)

Fire retardants

Physical tests

Electrical properties

Vibrational properties

Wave propagation

Acoustic emissions

Mechanical tests

Flexural stiffness

Proof loading

Bending

Tension

Compression

Probes/coring

8

Static Flexure Method

Is a simple mechanical evaluation

No advanced-tech equipment required

MOE = Pa(3L2 4a2) / 48I

(a)

(b)

Figure 3. Common static flexure setup (a), and alternative setup (b) [1]


Static Flexure Method

The drawbacks:

Need at least 2 tools i.e. load generator (e.g. an test weight cast iron, electrically induced load) and LVDT position sensor (for measuring the )

Often we need a variable load generator e.g. iron brick with multiple weight, or electrically induced load

(a)

(b)

Figure 4. Iron brick (a), and a wood loaded with electrically induced load (b)

Longitudinal Stress Wave Method (LSWM)

Is a simple physical evaluation wave propagation

Need a computer to perform FFT get resonant freq.

The MOE can be predicted by

MOE = 4f02L2, where

f0 :fundamental resonant frequency

L : length

: density

Figure 5. Longitudinal Stress Wave Method Setup [1]


11

Longitudinal Stress Wave Method

Determining the fundamental resonant frequency

(a)

(b)

Figure H1. LSW in time domain (a), and in frequency domain (b).

12


Performance

[2] Ayutyastuti. (2015). Studi Kelayakan Metode Nondestructive Test Berbasis Akustik untuk Memprediksi Nilai Modulus Elastisitas Kayu. Universitas Gadjah Mada.
Wood TypeScientific NameR2 SonokelingDalbergia latifolia Roxb.0.57TeakTectona grandis L.f.0.59SukunArtocarpus altilis0.63AcaciaAcacia mangium0.90MunggurPithecolobium Saman Benth0.90MahoganySwietenia spp.0.95
Table 2. The coefficient of determination R2 for the relationship between MOEd and MOEs [2]

13


The problems:

Tools

There is limited instrument implemented this method

Most of the time FFT is performed in a computer

Noise

Friction due to tapping the wood

We dont know whether the recorded signal is representing the longitudinal stress wave (LSW) or not

14

Proposed Solutions

Enhanced the longitudinal stress wave method

Implement method in a semi-automatic device

Proposed Enhanced Method

Detect presence of noise

Measure how much the recorded signal represent the LSW

Using the known characteristics of damped free vibration observing exponential decay of LSW

16


Constraints

We record an acoustic signal with microphone instead of using a sensor attached directly to the wood

Directly calculating exponential decay of LSW is difficult

(a)

(b)

Figure 6. Ideal damped free vibration (a), longitudinal stress wave of observed Sonokeling wood (b)

17


Solutions

Filter the LSW

Use envelope fitting method to derive exponential decay function

(a)

(b)

Figure 6. Envelope fitting of the transient response of an underdamped single-degree-of-freedom system. The illustration (a), the example on the implemented instrument (b)

18


Additional steps

Legend:

Figure 7. Proposed enhanced LSWM

19

Pre-research of the enhanced LSWM

Mahogany #1

Sonokeling #1

(a)

(b)

Figure 8. Recorded LSW of Mahogany #1 wood (a), recorded LSW of Sonokeling #1 wood (b)

Mahogany #1

Sonokeling #1

(a)

(b)

Figure 9. Signal spectrum of recorded LSW of Mahogany #1 wood (a), recorded LSW of Sonokeling #1 wood (b)

Mahogany #1

Sonokeling #1

(a)

(b)

Figure 10. Signal spectrum of filtered recorded LSW of Mahogany #1 wood (a), filtered recorded LSW of Sonokeling #1 wood (b)

Mahogany #1

Sonokeling #1

(a)

(b)

Figure 11. Filtered recorded LSW of Mahogany #1 wood (a), filtered recorded LSW of Sonokeling #1 wood (b)

Mahogany #1

Sonokeling #1

(a)

(b)

Figure 12. Envelope fitting result of LSW of Mahogany #1 wood (a), and LSW of Sonokeling #1 wood (b)






Conclusion

Future Work

Q & A

Design Specification

The purposes of the instrument are,

Record the stress wave

Perform the FFT algorithm

Assisted user to find the f0

Implement the refined method

The wood frequency range

800 4100 Hz


The wood frequency range

800 4100 Hz

Instrument Design

Instrument System Design

Software Architecture

User Interface Design

Main navigation

Plot area

Plot toolbar

Pointer position

Setting

Record

FFT

Pick f

Verify

Calc

Open

Implementation Testing

Microphone Test

FFT Test

Soundcard Test

Complete System Test

Data Collection

Soundcard Test

Data Collection

Microphone Test

Data Collection

Microphone Specs
Physical PropertiesSpecificationAudio Jack3.5 mmPlug Diameter3.5 mmFrequency Range0.1 5 kHzSensitivity-64 3 dBLength16 cmWeight12 g

Data Collection

FFT Validation

Check the implementation

Test implemented routine against various frequency

Damping Information Exploration

Envelope fitting R2envl vs. MOEs and MOEd R2ed






Conclusion

Future Work

Q & A

Physical Implementation

Successfully implemented

Semi-automatic device

Embedded enhanced LSWM

A 0.1 5 kHz microphone

Raspberry Pi 900 MHz clock speed

3.5 resistive touchscreen

12000 mAh power bank

Soundcard Performance Test

Square wave


Triangle wave


Sine wave


Sine wave (cont.)

Microphone Performance Test

Response of the microphone

Microphone Performance Test

SNR of the Microphone

Fast Fourier Transform Validation

Single frequency

Fast Fourier Transform Validation

Dual frequency

Exponential Decay of LSW

We define the following after some experiments:

The order of Butterworth filter is 3

The frequency cutoff of band-pass filter is 100

Analyzing the R2 of the envelope fitting of exactly same wood as researched by Ayutyastuti 2015 and Feliana 2014. We called this coefficient of determination as R2envl.

Compare this distribution with the R2 of the MOEd and MOEs correlation (called R2ed)
Wood TypeR2edPercentage R2envl > 0.95Sonokeling0.5746.67 %Teak0.5956.67 %Sukun0.6343.33 %Acacia0.9060.00 %Munggur0.9063.33 %Mahogany0.9573.33 %

Exponential Decay of LSW

Histogram of R2 of Envelope Fitting for Sonokeling (R2ed = 0.57)

Frequency0.50.550.60.650.70.750.80.850.90.951More0100120309140

R2envl

Frequency

Histogram of R2 of Envelope Fitting for Teak(R2ed = 0.59)

Frequency0.50.550.60.650.70.750.80.850.90.951More0000010417170

R2envl

Frequency

Histogram of R2 of Envelope Fitting for Sukun(R2ed = 0.63)

Frequency0.50.550.60.650.70.750.80.850.90.951More0011121254130

R2envl

Frequency

Histogram of R2 of Envelope Fitting for Acacia (R2ed = 0.90)

Frequency0.50.550.60.650.70.750.80.850.90.951More0001022214180

R2envl

Frequency

Histogram of R2 of Envelope Fitting for Munggur (R2ed = 0.90)

Frequency0.50.550.60.650.70.750.80.850.90.951More1000003502190

R2envl

Frequency

Histogram of R2 of Envelope Fitting for Mahogany (R2ed = 0.95)

Frequency0.50.550.60.650.70.750.80.850.90.951More2000000006220

R2envl

Frequency






Conclusion

Future Work

Q & A

Conclusion

A semi-automatic nondestructive evaluation instrument for predicting the MOE of wood called MyWood is successfully designed and implemented. Each building block of the instrument i.e. the sound card, microphone, and the FFT algorithm are well implemented and validated.

The test shows that the instruments able to accommodate any waveforms and able to work in a range of 800 4100 Hz which includes the frequency range of the longitudinal resonant frequency of the wood.

Conclusion

We introduced a novel method to measure how much the recorded LSW represent actual LSW. The method involves conventional LSWM method with additional band-pass signal filtering with resonant frequency as the center frequency of the filter, and the envelope fitting method.

We assessed the longitudinal stress wave data from previous researches and found an important parameter called R2envl which is the coefficient of determination of envelope fitting in our damping ratio calculation method. We found that if we record a longitudinal stress wave and we perform our damping ratio calculation method and get a low R2envl, it means that there is a high probability that our data is not representing the longitudinal stress wave signal and we need to repeat the recording procedure of LSWM.






Conclusion

Future Work

Q & A

Recommendation

In this research, we are not exploring the possibility of using the damping factor, h, that has been calculated using our procedure to define a refined model of measuring the MOE. A depth study about this area may enrich our knowledge of nondestructive evaluation of wood.

We test the implemented designs microphone with a flat response speaker. A further research which test the proposed designs microphone with tuning fork or a standardized calibrator will be appreciated.

DEMO

Thank you

Q & A

dB used in most of this research

dBFS- dB Full Scale

0 dBFS represents the highest possible level in digital gear. All other measurements expressed in terms of dBFS will always be less than 0 dB (negative numbers).0 dBFS indicates the digital number with all digits ="1", the highest possible sample.

The lowest possible sample is (for instance for 16 bit audio):0000 0000 0000 0001, which equals -96 dBFS. Therefore the dynamic range for 16-bit systems is 96 dB. For 20-bit digital audio it is 120 dB. For 24 bit digital audio it is 144 dB.Full-scale input level is the analog input voltage level that will cause the A/D converter to just equal full scale with no clipping on either positive or negative peaks.

Output full scale is defined as the analog output voltage produced while playing a 997 Hz digital full-scale sine wave, assuming the THD+N is less than -40 dB relative to the signal level.

The dynamic range of a digital system is the ratio of the full scale signal level to the RMS noise floor.

JimPrice.Com. (2007). Understanding dB. Retrieved March 23, 2017, from http://www.jimprice.com/prosound/db.htm

Least Square

Least Square

Start

RH < 20%

Place the wood in

the base with a

support on its

end.

Tap the wood in

one end

Record tap sound

(signal) with a

microphone at the

other end.

Find natural

frequency (f) with

frequency

analyzer

Insert fto the

formula

MOE = 4f

2

L

2

Finish

Perform drying

treatment

YES

NO

Perform

Butterworth band-

pass filter at f

x, where xis

obtained an

optimal solution

by trial and error

At the time

domain do

envelope-fitting

(obtained R

2

)

R

2

> = y, where yis

obtained optimal

solution by trial

and error

Make sure

the support is

strong and

does not

shift. Make

sure the next

tap is strong

enough but

not too hard.

YES

NO

Sensor:

Microphone

Sensor:

Microphone

Woods

longitudinal

stress wave

Signal

Conditioning:

A/D Converter

Signal

Conditioning:

A/D Converter

Microprocessor:

Software for User

Interface and Digital

Signal Processing in

RPi

Microprocessor:

Software for User

Interface and Digital

Signal Processing in

RPi

User

Interface:

Touchscreen

Display

User

Interface:

Touchscreen

Display

User

MyWood

Function

Generator

Soundcard

Oscilloscope

Raspberry Pi

Audacity

Software in

RPi

Host

Computer:

Remote

Desktop

Function GeneratorSoundcardOscilloscopeRaspberry PiAudacity Software in RPiHost Computer:Remote Desktop

Transducer:

Flat Speaker

Air:

5 cm gap

Microphone

Tested

Soundcard

Raspberry Pi

Host

Computer:

Remote

Desktop

Audacity

Software in

RPi

Frequency

Generator

Software in

Host

Computer

Transducer:Flat SpeakerAir:5 cm gapMicrophoneTested SoundcardRaspberry PiHost Computer: Remote DesktopAudacity Software in RPiFrequency Generator Software in Host Computer

Design and Implementation of Nondestructive Evaluation Instrument for Acoustic-based Wood Modulus of...

Engineering

Transcript of Design and Implementation of Nondestructive Evaluation Instrument for Acoustic-based Wood Modulus of...