Comparison of the numerical, analytic and ex- ex-perimental resultsex-perimental results

Figures 8.5a and 8.5b show the evolution of f₁computed with the numerical and analytic model respectively for w_f  1000 kg and wf  2000 kg for different values of be. For w_f  1000 kg it has been possible to measure clear wide oscillations only in a range of be between 3000 and 7500 mm while for wf  2000 kg that range is limited from 2000 to 4000 mm.

Table 8.4 reports the relative error (equation. 8.1) of the analytic and numeric model with respect to the experimental results. It is possible to note that the approximation of the numeric model is quite precise with a maximum relative error of 8,7% while the

analytic model tends to under-estimate the real oscillation frequency of δ.

r_e  f_1,model
f1,experimental

f_1,model (8.1)

w_f (kg) b_e (mm) r_e,numeric (%) r_e,analytic (%)

1000 3000 -6.3% -23.7%

1000 4000 -4.1% -16.7%

1000 5000 -0.2% -8.5%

1000 6000 1.3% -3.8%

1000 7500 8.7% 7.3%

2000 2000 -7.8% -36.7%

2000 3000 -2.1% -23.5%

2000 4000 4.8% -10.6%

Table 8.4: Relative errors of the numeric and analytic models with respect to the experimental results

3000 4000 5000 6000 7000 be (mm)

0.4 0.5 0.6 0.7 0.8 0.9 1 1.1

frequency (Hz)

experimental numerical analytic

(a) w_f  1000 kg

2000 2500 3000 3500 4000 be (mm)

0.4 0.5 0.6 0.7 0.8 0.9

frequency (Hz)

experimental numerical analitic

(b) w_f  2000 kg

Figure 8.5: Comparison of the numeric, analytic and experimental results

Final considerations

The current document is the result of a collaboration with Movimatica srl, lasted more than six months, during which it was possible to understand the typical dynamics of an innovative and constantly expanding workplace.

The first part of this document has showed the potentiality that a CAN based teleme-try system offers also in non-automotive applications. In particular in the first chapter describes how a CAN network works and how the CAN frames can be easily read and used for applications like a data logger. The ’MERLO VisuaLogger ’ GUI is an innova-tive instrument that can be used in case of accident of the machine. In fact it provides an easy method to visualize the geometric configuration of the machine during the accident. A great advantage of this instrument is its versatility because the database containing the informations about each model of the Merlo machine can be easily up-dated in case of production of new models. This GUI can also be used to read and convert the ASCII log files directly recorded from the CAN bus. This function could be used, during the final test that each machine undergoes, to easily test the proper functioning of the sensors related to geometric configuration of the machine. In fact if the virtual animation of the machine shows the same operations that the machine has done during the record of the log file, it means that the sensors returns the expected measures.

On the other hand the second part of this activity has demonstrated how an IMU can be used to detect the dynamic behaviour of a telescopic handler. The complementary filter, used to extrapolate the pitch and roll angle from the IMU, was tuned in such a way to use almost exclusively the data of the accelerometer (c_f  0.98). The analy-sis of some test (not reported in this document) performed making the machine pass over some bumps has required, on the rebound, to take more into account the data of the gyroscope because of the spikes in the accelerometer data. The test at the head-quarter of Merlo have showed the poor reliability of the on board inclination sensor on the chassis and have highlighted the possible positions where to install the IMU in

order to minimize the noise produced by the engine and the hydraulic pumps. The comparison between γ and δ θ has confirmed that an IMU can provide a reliable measure of the inclination angle of the boom and, unlike the on-board rotary encoder, it can measure also the oscillations of the boom during the CDC/operator blocks of the boom movement. The Fourier analysis of the boom’ s oscillations has shown a certain proportionality between the oscillation frequency of δ and the boom extension. The solution of the eigenproblem of the analytic and numerical model has revealed that the first mode of both the models replicate the behaviour of the machine during the oscillations induced by the block of the boom lowering. Since the stiffness of the front and rear axle (k₁and k₂) and of the boom (k_b) were unknown, a parametric analysis has been performed to make the resonance frequency of δ match with the first resonance frequency (f1) of the two models tuning the value of k1,k2 and kb. This analysis has revealed revealed the non-linearity of k₁,k₂ and k_b. The scarcity of data has forced us to consider the boom as a wedged beam with k_b  k0b{l and to charge the non linear effect to the stiffness of the front and rear axle. With some iterative simulation it was possible to find a plausible value to k_0b and to k₁ and k₂ for w_f  1000 kg and wf  2000. Even if those results derive from some strong approximations they can provide important informations for the initial tuning of the new control system. In particular the numeric model has revealed to well emulate the dynamic behaviour of the real machine. The advantage of those two models is that they can predict the behaviour of any model of frontal telescopic handler just modifying the geometric and mass properties. The reli-ability of those models could be much improved with more precise informations about the stiffness of the wheels and of the boom.

Bibliography

[1] Bs en 15000: Rough-terrain trucks - safety requirements and verification part 8:

Variable-reach tractors. Standard, British Standard, 2008.

[2] Gulf Coast Data Concepts. Human Activity Monitor (HAM) User manual.

[3] Steve Corrigan HPL. Introduction to the controller area network (can).

[4] ISO 22915-10: Industrial trucks — Verification of stability Part 10: Additional stability test for trucks operating in the special condition of stacking with load laterally displaced by powered devices. Standard, International Standard Organi-sation, 2008.

[5] ISO 22915-14: Industrial trucks — Verification of stability Part 14: Rough-terrain variable-reach trucks. Standard, International Standard Organisation, 2010.

[6] ISO 22915-20: Industrial trucks — Verification of stability Part 20: Trucks oper-ating with offset load, offset determined by utilisation — Stability tests. Standard, International Standard Organisation, 2008.

[7] Markus Junger. Introduction to j1939. Vector, version, 1:1–11, 2010.

[8] PD CEN/TS 1459-8: Rough-terrain trucks - Safety requirements and verification Part 8: Variable-reach tractors. Standard, Comit´e Europ´een de Normalisation, 2018.

[9] Singapore Government. Data loggers for mobile cranes, 2015.

[10] W. Voss. A Comprehensible Guide to Controller Area Network. Copperhill Tech-nologies Corporation, 2008.

[11] Wilfried Voss. A comprehensible guide to J1939. Copperhill Technologies Corpo-ration, 2008.

[12] Wikipedia contributors. High-pass filter — Wikipedia, the free encyclopedia, 2019.

[13] Wikipedia contributors. Inertial measurement unit — Wikipedia, the free ency-clopedia, 2019.

[14] Wikipedia contributors. Low-pass filter — Wikipedia, the free encyclopedia, 2019.

[15] Wikipedia contributors. Telescopic handler — Wikipedia, the free encyclopedia, 2019.

Acknowledgements

Finally, I would like to thank Prof. Aurelio Som`a to have supported me during the realisation of this document and for the patience that he has always showed to me.

I would also like to thank Ing. Federico Fraccarollo, reference point of Movimatica, that has always helped me both during the intern-ship and the period of realisation of this document. He had a key role in the completion of this work. They steered me in the right direction whenever they thought I needed it.

I can’t forget to thank Ing. Stefano Sivo, researcher of Politecnico, who demonstrated an infinite availability to help me during the different phases of this work.

I am also grateful to all the staff of Movimatica, starting from the general manager Ing.

Marco Mattioli, who allowed me to do the intern-ship in its company, Giorgio Ponza and Claudio Bertan who have helped me with IT problems.

Last but not the least, I would like to thank my parents Maria Angela and Corrado, my sister Silvia and my grandparents for supporting me with wise advice and for always being by my side.

List of Figures

1.1 Number of millions CAN nodes used over time . . . 3

1.2 Simplified scheme of a passenger car CAN . . . 4

1.3 Standard CAN frame: 11 bit identifier [3] . . . 5

1.4 Extended CAN frame: 29 bit identifier . . . 6

1.5 Bus topology . . . 7

1.6 CAN bus voltage level . . . 8

1.7 Complete CAN frame . . . 8

1.8 D-sub 9 pin connector . . . 9

1.9 Example of j1939 applications . . . 10

1.10 Description of PGN 65262 in SAE J1939/71 . . . 12

1.11 Description of SPN 110 in SAE J1939/71 . . . 12

1.12 Description of SPN 563 in SAE J1939/71 . . . 12

1.13 SPN and PGN . . . 13

1.14 PEAK USB interface . . . 14

1.15 PCAN View . . . 14

1.16 CAN data decoded with DBC file . . . 14

2.1 Merlo frontal telescopic handler . . . 16

2.2 Load chart on stabilizers (left) and on tyres (right) with forks . . . 17

3.1 Some frames extracted from an animation . . . 22

3.2 VRML file containing a cube . . . 23

3.3 Different possible modification to the file in Figure 3.2 . . . 24

3.4 (1) turret base - (2) first section of the boom - (3) cab - (4) second section of the boom (5) third section of the boom (6) support arm -(7) raft - (8) chassis - (9) stabilizers support - (10) stabilizer extension (11) stabilizer piston (12) stabilizer foot (13) stabilizers cylinder -(14) engine - (15) tyre - (16) rim . . . 25

3.5 Different models of Roto created adapting the same .wrl file . . . 25

3.6 Parametrisation for all non rotating telescopic handlers . . . 26

3.7 Parametrisation for all rotating telescopic handlers . . . 27

3.8 ’file selection’ window . . . 29

3.9 ’analysis’ window . . . 30

3.10 ’log conversion’ window . . . 31

4.1 Rough terrain variable reach tractor . . . 33

4.2 Parameters for the designation of the actual capacity of the telescopic handler with fork . . . 36

4.3 Tilt table . . . 37

4.4 Representation of different axles . . . 38

4.5 Special operating condition . . . 43

4.6 Special operating condition . . . 44

4.7 Execution phases of the test . . . 47

5.1 Degrees of freedom of a body in the space . . . 50

5.2 Different kind of IMUs . . . 51

5.3 Angles derived from accelleration . . . 52

5.4 Schematic representation of the complementary filter . . . 53

5.5 A simple RC circuit . . . 54

5.6 Bode diagram of a low-pass filter . . . 55

5.7 A simple RC circuit . . . 56

5.8 Bode diagram of an high pass filter . . . 58

5.9 Selected model for the test . . . 61

5.10 IMU reference frame . . . 61

5.11 Geometric scheme of measured angles . . . 62

5.12 Evolution of θ during some different tests . . . 64

5.13 Comparison of θ measured by different IMUs . . . 64

5.14 Comparison of the second oscillation of Test 6 . . . 65

5.15 δ γ from IMU 1 and IMU 2 records . . . 66

5.16 Different phases of Test 7 . . . 66

5.17 Comparison between γ and δ θ . . . 67

5.18 Condition δ θ ¡ γ . . . 68

5.19 Second oscillation of Test 12 . . . 69

5.20 Second oscillation of Test 12 . . . 69

5.21 Influence of b_e and w_f on f_δ . . . 70

5.22 Linear approximation of f_δ for different w_f values . . . 71

5.23 Influence of b_e and w_f on f_θ,1 . . . 71

5.24 Influence of b_e and w_f on f_θ,2 . . . 72

6.1 Geometric scheme of the boom . . . 74

6.2 Simplified 3 dof model . . . 75

6.3 Free body diagram of the machine in static condition . . . 77

6.4 Mode shapes . . . 81

7.1 Model’s bodies . . . 83

7.2 Axis of the revolute joint . . . 85

7.3 Springs on the front and rear axles . . . 86

7.4 Mode shapes . . . 88

8.1 Combination of k₁ and k_b that satisfy the condition in table 8.1 . . . . 91

8.2 Hollow rectangular section . . . 92

8.3 Combination of k₁ and k₂ that satisfy the condition in table 8.1 . . . . 94

8.4 Comparison of the numerical and experimental results . . . 95

8.5 Comparison of the numeric, analytic and experimental results . . . 96