Non-Destructive Testing of Fruit Firmness with Real-Time constraints

1. Non-Destructive Testing of Fruit Firmness with Real-Time constraints Christopher Mills Supervisors: Dr. Andrew Paplinski Mr Charles Greif

2. Contents • Research aims • Fruit Firmness • Non-destructive testing (NDT) • Methods • Completed work • Future work • Conclusions • References

3. Project Aims • With our background research in Ultrasonic imaging, the aim is to design a simple system that will grade fruit firmness using NDT • And as part DigSys we are interested in an ASIC application of these algorithms. They can execute up to one hundred times faster in hardware. • Ensure that the system could be used in an industrial setting, i.e. testing fruit on a rapidly moving conveyer belt. • Work within hard real time constraints (ie 10 fruit/sec) • Be able to test fruit without actual contact with the skin of fruit (is this possible?)

4. Fruit Firmness Definition of fruit firmness – mechanical rigidity of fruit cell structure. It can be measured by conventional means; stress testing, Magness-Taylor Probing Measurement of Fruit Firmness is important because • Firmness affects the perception of enjoyment of food. • Perception of firmness is linked to freshness and the ripeness of fruit. • Such perception may be of greater importance for the preparation of fruit for later consumption. (Preservation: canning, preserve/jam, etc) Humans decide fruit firmness in a variety of ways • Feel/look as fruit is consumed. • Response to preparation/cooking.

5. Fruit Firmness (cont) • Biological factors of Fruit Firmness • Cell size/shape • Cell water content • Cell organization • Firmnessvaries with • Fruit type (apple, orange) • Fruit Age (under ripe, over ripe) • Conditions during maturation and storage • The image on the right, shows what apple cells look like at high magnification, the boundaries between the cells are visible. Image of boiled apple cells at 100x magnification

6. Fruit Firmness (cont) • Ultrasonic reflection can be used to measure firmness. • it will be the gaps between cells that will best respond to ultrasound and describe firmness. • The image to the right is a representation of a fruits internal structure. • Fruit firmness varies with ripeness and time, going from firm and unripe to soft and ripe or overripe. • The reason for this is that chemical changes within the fruit change the way the cells inside interact and the chemical composition within the fruit, eg starch being converted into sugars.

7. Fruit Firmness (cont) Fruit firmness testing is critical to industries involved in the sorting and grading of fruit. As sorting can be done based on fruit firmness measures. • For the duration of this project, a company called Colour Vision Systems (CVS) will be providing sponsoring for this project. • CVS build large scale fruit sorting machines, including computational circuits for automated sorting based on vision for blemish detection and near infrared for sugar content evaluation.

8. Non-Destructive Testing • NDT methods of testing are used on mechanical structures while they are in use or before use – and the structures can continue to be used post testing. • Various modalities of NDT exist, such as • Sound methods (ultrasound, acoustic, etc) • Wave energy response (laser, infrared, x-ray) • Vision (Video camera’s) • Physical Response to small force (Laser air puff, bounce test, micro-deformation) • Many researchers have attempted to develop methods for fruit firmness testing. For the next few slides I will detail some of these.

9. NDT-Examples, Laser scatter imaging Kang et al attempted to use laser-scatter imaging to grade quality of tomatoes. The method is reasonably simple, a laser beam is fired through a piece of fruit/vegetable, the scatter of the laser beam is recorded by a camera, and the extent of the scatter is an indication of quality.

10. NDT-Examples, Laser Air Puff McGlone et al describes a method based on the laser air puff test. The laser air puff test uses deformation in the target caused by air under pressure, this deformation is measured by a laser. It was found that while this method was reasonably accurate on average, there was an issue with confidence and resolution when testing firm fruit due to the decreased measurable deformation.

11. NDT-Examples, Bounce Test Delwiche et al attempted to build a fruit sorter based on the impact force (or Bounce) testing method. Based on previous work by the same researchers, built a system where fruit would fall with a speed of 76.7 cm/s. The force measurement was made by a force transducer mounted vertically on a large steel mass or impact mass. The fruit was dropped from a conveyor belt. Overall, the system could process fruit at 5 fruit/s. While the system was capable of sorting fruit based on firmness, the error rate was high, 26% for peaches. For this research, we will concentrate on ultrasonic methods to measure fruit firmness due to our experience in the area.

12. NDT-Examples, Acoustic Peleg et al built a fruit firmness sorter based on the principles of acoustic energy. • A small electrodynamic shaker, vibrates the bottom of the fruit • The root mean square (RMS) level of the input signal Xi is measured in the shaker head • The output RMS signal level Xo is measured by a miniature accelerometer attached to the top part of the fruit. • A Firmness index PFT is defined by: PFT=X0/(X0-Xi). Overall, the system performed well with reasonably high confidence and repeatability (>80%).

13. NDT-Examples, Acoustic The picture on the right shows the ‘sensor wheel’. • Fruit moves along the conveyor • Then it’s grabbed by the acoustic transducers • The fruit is held and tested until it reaches the lower conveyer The fruit is tested at a rate of 7.5 fruit/s per lane.

14. NDT-Examples, Acoustic • The table to the right shows some values of PFT vs Penetrometer force • It shows that the measure PFT is related to the force measured by the penetrometer • If the fruit is stored in a Controlled Atmosphere, the Penetrometer and PFT show similar increase in reading

15. NDT-Examples, Ultrasonic Mizrach et al attempted to estimate fruit qualities from a Ultrasonic measure of fruit firmness • The system used two transducers, one as receiver, the other as a transmitter • The resulting signal was processed • The Frequency response Analysed • And the speed of sound through the target measured • The experiment focused on Mangos as the test subject Representation of the system

16. NDT-Examples, Ultrasonic The graphs on the right show the received signal and the Fourier transform that of that signal. The results were compared to known values of firm and soft fruits and a firmness measure made based on the comparison. The accuracy of this method is reasonably high.

17. NDT-Examples, Ultrasonic • The scatter plots here represent the accuracy of the system • The table below gives a value called the Standard Error of Calibration (SEC)

18. NDT - Ultrasound Basics of Ultrasonic testing • Required equipment • Transmitter and Receiver transducers • Pulsar/Receiver unit • External/internal microcomputer to store results and control Pulsar/Receiver • Operation • Pulsar/receiver applies voltage to the transmitter • Transmitter vibrates and creates high frequency sound • Ultrasound reflects whenever a change in density occurs. • Receiver responds to sound and sends a voltage based on the amplitude of received signal

19. NDT - Ultrasound However, there is a problems with using Ultrasound. The most common method of ultrasound is called ‘contact using liquid immersion’. This is a problem because… • In an automatic system, contact with the fruit could be awkward and expensive. • Application of conducting liquid could also be awkward. One possible answer is to use Non-Contact Ultrasound (NCU). The system is very similar to liquid contact except • The Transducers do not contact the target • Noise due to lack of contact • large reflections caused by sound waves entering target considered as noise • To reduce reflection from transducer to air, an acoustic lens is used.

20. NDT – Ultrasound (NCU) The above image shows the behaviour of ultrasonic waves using NCU.

21. Research Method • Empirically determine response of the cellular structure of fruit to ultrasound • Possibly use Field 2, which can produce images based on simulation values or real readings from an ultrasonic system • However, we do not require images, just an overall characterization of fruit firmness • Devise a Neural Network structure or other type of system that is capable of determining fruit firmness (e.g. statistical methods) based on the training data. Early testing of Neural Net to be done in Matlab This is an example of Field 2 taking a source image and simulating how it would look through ultrasonic testing. The same could be done with a mock up of fruit internals.

22. Proposed system • Use Ultrasound on fruit via non-contact transducers to measure fruit firmness. • Process Ultrasound response via a neural network that will require training for each available fruit type, and evaluate fruit firmness. • Integrate with existing system manufactured by CVS • such as a vision system to detect blemishes (Some blemishes are caused by fruit diseases that would effect firmness also) • Weight and volume information (fruit density could prove useful in determining fruit firmness)

23. Proposed system The card to the right is called the OPCARD. • It is a PCI add on card • It is an Oscilloscope card designed for ultrasound • It has an 8bit DAC • Highly Configurable • 12.5MHz … 100MHz SampF • High pass and low pass filters The Transducer shown here is the AT50 from Airmar • Air contact transducer • Output signal Frequency of 50MHz

24. Work Completed • Research into Non-Contact Ultrasound (NCU) • Based on what I have learned, NCU is a very appropriate technology for this application. However, it is a relatively new method compared to liquid immersion ultrasound, and apparently despite its advantages not widely used so sourcing NCU transducers has been difficult. • Classification system • At this stage, a neural network is the most likely system to use for classification of Fruit Firmness • Other systems are possible, such as pattern recognition methods including statistical analysis. • Physical arrangement of system • Some ideas have been discussed, such as the angle between the emitter and receiver(s) • Angles of transducers to fruit surface

25. Future Work • Testing of various methods including • Acoustic/ultrasound • Determine accuracy of NCU • Machine Vision • Laser Air-puff • Non-destructive deformation • Sensor Fusion • Construction of a system based on results of testing

26. Conclusions • Ultrasonic testing can grade firmness with sufficient accuracy. • NCU is applicable in most situations where the more common liquid contact Ultrasonic testing methods are used. • Sensor fusion is a sensible option in fruit firmness testing.

27. References Texture - http://www.ba.ars.usda.gov/hb66/021texture.pdf Evolution Of Piezoelectric Transducers To Full Scale Non-Contact Ultrasonic Analysis Mode - http://www.ultrangroup.com/pdfs/WCNDT-NCU-64.pdf Non-Contact Ultrasound: The Last Frontier In Non-Destructive Testing And Evaluation - http://www.ultrangroup.com/pdfs/esm1.pdf Field 2 - http://www.es.oersted.dtu.dk/staff/jaj/field/index.html