Instrument supported tree evaluation in Hungary<br />Ferenc Divos<br />University of West Hungary<br />Jozsef Bodig wood N...
Content<br />Visual tree evaluation<br />Acoustic test, single path<br />Acoustic tomography<br />Acoustic root detection<...
Human case					Tree case<br />1st step: visual investigation<br />2nd step can be:<br />	- X-ray<br />	- Ultrasonic<br />	...
1.  Visual tree evaluation<br />Goal: tree related risk reduction.<br />Requirement: well trained expert.<br />Expert focu...
... holes<br />
... openings, truntcations<br />
... fungi fruits, wounds<br />
... crone structure, tree shape<br />
... soil conditions, environment<br />
Failure type 1.<br />
Failure type 2.<br />
Accident in Budapest, 2008<br />
2.  Acoustic defect detection<br />Single path (2 sensors)<br />
Principle of decay detection<br />Sound propagation in an intact and in a decayed tree.<br />
Principle of decay detection<br />
Principle of decay detection<br />
FAKOPP Microsecond Timer<br />Measurement perpendicular to the grain<br />
Evaluation of measurement results<br />The relative velocity change (RVC) is a measure of the defect size. If RVC is lower...
Sound propagation<br />Oak disk, grid size is 2 by 2 cm, time resolution is 20 s.<br />
The setup for wave mapping<br />
3. Acoustictomography<br />by using more sensors<br />
Intact poplar trunk<br />
Decayed poplar trunk<br />
FAKOPP 2D Acoustic Tomograph<br />
FAKOPP 2D<br />Acoustic Tomograph<br />
Linden and <br /> Nut tree<br />
4.  Acoustic Root Detection<br />
Signal attenuation in soil is high, high sensitivity sensor is required<br />Amplitude (mV)<br />Distance (m)‏<br />
P-vawe velocity in soil is 300 m/s<br />Distance (mm)‏<br />Propagation time (ms)‏<br />Velocity in root is 3000 m/s <br />
Theoretical wavefront around a tree<br />
Soil velocity depends on depth<br />
Setup for acoustic root detection<br />
High sensitivity (10V/g) <br />soil sensors<br />
Velocity distribution around a tree<br />
Root depth is measured by a steel bar.<br />
Limitation of acoustic root detection<br />Large rocks, fence, concrete roads guidesthe sound propagation.<br />Technique ...
5.  Pulling test<br />
Generalized <br />Inclination -<br /> tipping load curve<br />From Koch, 1989<br />
Inclination sensor<br />
Force sensor<br />
Force display<br />
Loading device<br />
Pulling test in progress<br />
Fitted curve and extrapolated maximum load<br />
Evaluation<br />Generalizedinclination curve:<br /> = 1/3 tan(p/73,85) +0,00005 p2- 0,0009 p<br />where:    	:	inclinati...
Inclination (degree)<br />Force (N)<br />
Inclination (degree)<br />Force (N)<br />
Results of pulling test<br />
Limitations of pulling test<br />Uncertain factors: <br />	wind speed, <br />drag factor, <br />	curve extrapolation,..<br...
Paulownia tomentosa trees in the yard of city the hall Kecskemét, the city of Zoltan Kodály<br />
Kecskemét, city hall<br />
Mechanical model for tree stability evaluation<br />
Green wood material compression strength can be predicted by MOE. <br />A stress wave velocity in fiber direction, togethe...
Tree stiffness determination and strength prediction<br />MOE=V2<br />Higher velocity:<br />  higher MOE<br />  higher st...
6.  Ultrasonic seedling test<br />
Shear type sensor<br />
Sensor attached to seedling<br />
Sensor attached to seedling<br />
Testing oak seedling<br />
7.  Conclusions<br /><ul><li>Visual Tree Evaluation is the most common tree evaluation technique.
Recently acoustic test becoming a standard tree evaluation technique in Hungary.
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Instrument Supported Tree Evaluation in Hungary

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Instrument Supported Tree Evaluation in Hungary

  1. 1. Instrument supported tree evaluation in Hungary<br />Ferenc Divos<br />University of West Hungary<br />Jozsef Bodig wood NDT Laboratory<br />Beijing, <br />16th International Wood NDT Symposium<br />October 12-14, 2009<br />
  2. 2. Content<br />Visual tree evaluation<br />Acoustic test, single path<br />Acoustic tomography<br />Acoustic root detection<br />Pulling test<br />Seedling test<br />Conclusions<br />
  3. 3. Human case Tree case<br />1st step: visual investigation<br />2nd step can be:<br /> - X-ray<br /> - Ultrasonic<br /> - CT, or MR<br /> - ………………<br />Arborist and patient <br />2nd step: NDT<br /> - acoustic tomography<br /> - pulling test<br /> - root detection<br /> - tree mechanics<br />
  4. 4. 1. Visual tree evaluation<br />Goal: tree related risk reduction.<br />Requirement: well trained expert.<br />Expert focusing to...<br />
  5. 5. ... holes<br />
  6. 6. ... openings, truntcations<br />
  7. 7. ... fungi fruits, wounds<br />
  8. 8. ... crone structure, tree shape<br />
  9. 9. ... soil conditions, environment<br />
  10. 10. Failure type 1.<br />
  11. 11. Failure type 2.<br />
  12. 12. Accident in Budapest, 2008<br />
  13. 13.
  14. 14. 2. Acoustic defect detection<br />Single path (2 sensors)<br />
  15. 15. Principle of decay detection<br />Sound propagation in an intact and in a decayed tree.<br />
  16. 16. Principle of decay detection<br />
  17. 17. Principle of decay detection<br />
  18. 18. FAKOPP Microsecond Timer<br />Measurement perpendicular to the grain<br />
  19. 19.
  20. 20. Evaluation of measurement results<br />The relative velocity change (RVC) is a measure of the defect size. If RVC is lower than 90% of the velocity in an intact tree, the tree contains an internal defect.<br />
  21. 21. Sound propagation<br />Oak disk, grid size is 2 by 2 cm, time resolution is 20 s.<br />
  22. 22. The setup for wave mapping<br />
  23. 23.
  24. 24.
  25. 25.
  26. 26.
  27. 27.
  28. 28.
  29. 29.
  30. 30. 3. Acoustictomography<br />by using more sensors<br />
  31. 31. Intact poplar trunk<br />
  32. 32. Decayed poplar trunk<br />
  33. 33. FAKOPP 2D Acoustic Tomograph<br />
  34. 34.
  35. 35.
  36. 36.
  37. 37.
  38. 38.
  39. 39.
  40. 40.
  41. 41.
  42. 42.
  43. 43.
  44. 44.
  45. 45.
  46. 46.
  47. 47.
  48. 48. FAKOPP 2D<br />Acoustic Tomograph<br />
  49. 49. Linden and <br /> Nut tree<br />
  50. 50.
  51. 51.
  52. 52. 4. Acoustic Root Detection<br />
  53. 53. Signal attenuation in soil is high, high sensitivity sensor is required<br />Amplitude (mV)<br />Distance (m)‏<br />
  54. 54. P-vawe velocity in soil is 300 m/s<br />Distance (mm)‏<br />Propagation time (ms)‏<br />Velocity in root is 3000 m/s <br />
  55. 55. Theoretical wavefront around a tree<br />
  56. 56. Soil velocity depends on depth<br />
  57. 57. Setup for acoustic root detection<br />
  58. 58.
  59. 59. High sensitivity (10V/g) <br />soil sensors<br />
  60. 60.
  61. 61. Velocity distribution around a tree<br />
  62. 62.
  63. 63.
  64. 64.
  65. 65.
  66. 66. Root depth is measured by a steel bar.<br />
  67. 67.
  68. 68.
  69. 69.
  70. 70.
  71. 71. Limitation of acoustic root detection<br />Large rocks, fence, concrete roads guidesthe sound propagation.<br />Technique is working well in parks and forest, but limited in urban area. <br />
  72. 72. 5. Pulling test<br />
  73. 73. Generalized <br />Inclination -<br /> tipping load curve<br />From Koch, 1989<br />
  74. 74.
  75. 75. Inclination sensor<br />
  76. 76. Force sensor<br />
  77. 77. Force display<br />
  78. 78. Loading device<br />
  79. 79. Pulling test in progress<br />
  80. 80. Fitted curve and extrapolated maximum load<br />
  81. 81. Evaluation<br />Generalizedinclination curve:<br /> = 1/3 tan(p/73,85) +0,00005 p2- 0,0009 p<br />where: : inclination in degree<br />p: force in % of maximum load.<br />
  82. 82.
  83. 83. Inclination (degree)<br />Force (N)<br />
  84. 84. Inclination (degree)<br />Force (N)<br />
  85. 85. Results of pulling test<br />
  86. 86. Limitations of pulling test<br />Uncertain factors: <br /> wind speed, <br />drag factor, <br /> curve extrapolation,..<br />Load is not static, but dynamic.<br />Trees are falling down not only in storms, <br /> but sometimes in wind silent condition. <br />
  87. 87. Paulownia tomentosa trees in the yard of city the hall Kecskemét, the city of Zoltan Kodály<br />
  88. 88. Kecskemét, city hall<br />
  89. 89.
  90. 90.
  91. 91.
  92. 92.
  93. 93. Mechanical model for tree stability evaluation<br />
  94. 94.
  95. 95. Green wood material compression strength can be predicted by MOE. <br />A stress wave velocity in fiber direction, together with the nominal density of the tree, provides the dynamic MOE and compression strength.<br />
  96. 96. Tree stiffness determination and strength prediction<br />MOE=V2<br />Higher velocity:<br /> higher MOE<br /> higher strength<br /> longer fibers<br /> low microfibril angle<br />
  97. 97. 6. Ultrasonic seedling test<br />
  98. 98. Shear type sensor<br />
  99. 99. Sensor attached to seedling<br />
  100. 100. Sensor attached to seedling<br />
  101. 101. Testing oak seedling<br />
  102. 102. 7. Conclusions<br /><ul><li>Visual Tree Evaluation is the most common tree evaluation technique.
  103. 103. Recently acoustic test becoming a standard tree evaluation technique in Hungary.
  104. 104. Acoustic technique is a reliable tool for tree trunk evaluation.
  105. 105. Acoustic root detection technique is approved in the practice.
  106. 106. Instrument supported tree evaluation increases tree safety, reduces tree related risk.</li></li></ul><li>Thank you for <br />your attention!<br />

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