Applied CAD and ANFIS to the Chinese Braille display optimization

Displays 24 (2003) 213–222 www.elsevier.com/locate/displa

Applied CAD and ANFIS to the Chinese Braille display optimization Fung-Huei Yeh, Huoy-Shyi Tsay, Shih-Hao Liang* Mechanical and Electro-Mechanical Engineering, Tamkang University, 151 Ying-chuan Road, Taipei County, Tamsui 251, Taiwan ROC Received 12 September 2003; revised 20 January 2004; accepted 20 January 2004

Abstract In this paper, a new type of Chinese Braille display (CBD) has been invented by the combined use of computer aided design (CAD) and adaptive-network-based fuzzy inference system (ANFIS). The new type of CBD can offer more powerful actuating force from 15 to 30 gw and lower power voltage from 6 to 4.5 V than the older type of CBD after the bunt mechanism and magnetic mechanism were redesigned. Not only did the study focus on the design process of the new CBD to establish system model using CAD, but also the physical design parameters were optimized by an inverse prediction technique using ANFIS. Besides, the study also solved the noise of fans and the thermal failure of Braille cells, and proved the new CBD could still work in safe even if the cooling system broke down by experiment. q 2004 Elsevier B.V. All rights reserved. Keywords: Chinese Braille display; Computer aided design; Adaptive-network-based fuzzy inference system; Optimization; Inverse prediction

1. Introduction The Chinese Braille display (CBD) is an assistant device to display Brailles, translated from English and Chinese texts on computer screen, for the Chinese visually impaired people. Usually, Brailles are assembled by pinheads on Braille cells. Each Braille cell may have six or eight pins, having two columns of three or four pins, respectively. Braille display is refreshable by moving the pins in each Braille cell up and down. Based on the actuators selected, the refreshable mechanisms may vary in different displays. The actuators generally used are solenoid, relay, piezoelectric beam, shape-memory alloy (SMA), and electrorheological (ER) fluid. The first commercialized tactile displays learned by most users were developed by Mr Schaefer and Mr Schonherr in Germany in the mid-1970’s. This display is actuated by tiny solenoids. However, solenoids are usually jammed by dust. Frisken Gibson et al. [1] also use solenoids to make a vertically two-dimensional tactile display in 1987. Sixtyfour solenoids (8 £ 8 pins) are used and evenly spread in two layers for translating a visual image to the four-level raised pins. In 1990, Sriskanthan and Subramanian [2] intended to use relays as actuators. In this study, a fully * Corresponding author. Tel.: þ886-2-2621-5656x2012; fax: þ 886-22620-9745. E-mail address: [email protected] (S.-H. Liang). 0141-9382/$ - see front matter q 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.displa.2004.01.008

functional 40-cell Braille display terminal was presented, and visually handicapped people can use it to access IBM PCs. Another commonly used display is mainly driven by piezoelectric material made cantilever beam for lifting every single pin [3]. Such a display has been improved and taken a large share on the market. Recently, Yobas et al. [4,5] went into the pneumatic actuated display using microelectro-mechanical systems (MEMS) and piezoelectric technology. Their research presents the actuation of one Braille pin and makes prediction on how to build an array of pins in a Braille cell. Alternative ways to drive the tactile display are SMA [6,7] and ER fluid [8]. The SMA wires are heated to shrink and to move the pins up or down depends on the mechanisms designed, but the system produces high heat generation rate and also needs well cooling systems. By using ER fluid with high voltage applied (Max. 10 kV per 20 mA), dots with compliant rubber surfaces can be actuated to configured shape. Owing to the high voltage applied, the safety should be carefully handled. Some research attempted to decrease the volume of Braille display and came up with creative ideas. For example, Braille cells are designed to locate on the rim of rotating wheel like the tread on tire [9]. The wheel can be software controlled to rotate far enough to display six pins Brailles. Inside the wheel, the upward or downward positions of pins are controlled only by three solenoids in row.

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Another creative design is that a single cell module is placed on the outer edge of a pantograph in place of cells of a Braille display [10]. When the cell module moves on the any location of the two-dimensional page, the single cell module presents the current Braille accordingly. These inventions were not popular due to the inconvenience for the visually impaired people brushing the finger across the pins on the surface of the Braille cell. Commonly, brushing is much more useful to identify the Brailles. Besides the above displays introduced, in Taiwan, the first relay actuated CBD was presented in 1995 and named golden Braille display (GBD). There are more than 1000 GBDs are in service. In the mean while, a new type of CBD named super Braille display (SBD) is under development. There are 45 Braille cells in a CBD and each Braille cell has eight pins. The pins are driven up and down by eight relays. In contrast to most of displays using piezoelectric actuators, we choose relay instead. The main thought is that relay is durable, reliable, and its actuations are more than one thousand million times in despite of its weight. The manufacturing technology of relay is welldeveloped, and a good quality of relay can be easily pursued. Among of all, the key reason is that it costs less and can be afford by most of the visually impaired people in Taiwan. Normally, the price of such a Braille cell is around 10 US dollars, and a piezoelectric type Braille cell may be raised to 35 US dollars. The relay of GBD is composed of iron core, copper coil, and lever mechanism. When the voltage is supplied to the coil, the relay pushes the pin up; when the power is off, the self-weight of lever mechanism lets the pin downward to its original position. After GBD works for a long time, the high temperature increases the resistance of relays to make actuating force of pins decrease. Especially the fans in GBD break down. Then, the components of overheated Braille cells are destroyed. Fig. 1 shows the picture of thermal defect of pins in a Braille cell of GBD after the fans in the display break down when the supply voltage is above 7 V. So, the practicability and comfortable touch of a relayactuated Braille display depend on the actuating force of pins in structural design, and the durability of a relayactuated Braille display depends on the voltage supplied on the coil in thermal design. The combination of different design parameters will make the working temperature of

Fig. 1. The picture of single Braille cell of GBD after thermal failure.

Fig. 2. The picture of single Braille cell of SBD.

Braille cells and the actuating force of pins act various behaviors, which will be optimized by applied CAD and ANFIS. After the optimal design is found and applied, the new type of CBD will be more reliable. Fig. 2 shows the picture of the prototype of a Braille cell of SBD, which is a well-designed module. In contrast to the previous GBD, SBD gets more powerful actuating force with low working temperature. Thus the Braille cells of SBD would not break down due to thermal effect. By redesigning the relay actuator for the bunt and magnetic mechanisms, the Braille pins become more sensitive to improve reading accuracy. With the power dissipation of SBD, only the fans of low RPM and airflow are needed to meet the end of thermal cooling. Therefore, the noise is reduced to make operators use SBD more comfortably. Besides, the Braille pin and the outer shape of SBD are specially designed and managed to decrease tiredness after long hour use through the Human Factor Engineering.

2. Design of mechanical structure of Braille display After near a decade service experience of GBD, common suggestions obtained from users are: the actuating force of pin decreases, the raised level of pin is uneven, the noise of fan is loud, and pin damaged by thermal loading. In order to eliminate deficiencies described above, the mechanical structure of a Braille display similar to GBD is re-designed and improved in this study. In the following sections, the design of actuator, Braille cell, and fabrication of SBD are described. 2.1. Design of actuator Figs. 3(a) and (b) show the structure of actuators of GBD and SBD, respectively. A relay type actuator is assembled of iron core and coil wound with enamel wire. When the current flows through the coil, the concentrated magnetism by adding the iron core will pull the input arm (armature). Moreover, the output arm pushes a pinhead upward based on the lever principle. GBD and SBD both follow the principles of relay and lever, but differ from their structures. The length ratio of input arm and output arm of GBD is approximately 1:3 on Fig. 3(a), and that of SBD is approximately 1:1 on Fig. 3(b). It means that the actuating

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Fig. 3. (a) The relay structure of GBD. (b) The relay structure of SBD.

force of SBD is larger than that of GBD at the same duty point to enable easier identification of Brailles and more comfortable sense of touch. 2.2. Design of Braille cell Differences between Braille cells of GBD and SBD can be found in Figs. 4(a) and (b). The height of cells in SBD is 41 mm and in GBD is 53 mm. The re-arrangement of relays in SBD causes its cell height less than that in GBD. The design also shortens the length of Braille pins in GBD to prevent thermal deflection in GBD. The tactile device in SBD is separable which is convenient for maintenance and repair of pins. In addition to stronger structure, PA46 þ 30% Fiber Glass, of polymer frame in SBD, the relative positions of printed circuit board (PCB), actuator, and pinhead become more precise and strong in order to prevent driven mechanism from jamming, which may take place by thermal effect. Finally, the system case of SBD can be thinner because of lower height of Braille cell. 2.3. Design of Braille display The fabrication structures inside GBD and SBD are shown in Figs. 5(a) and (b). Both displays have 45 Braille cells. In order to show the inside structure, only one cell is placed in the 23rd slot in Fig. 5. The communication interface basically designed between the Braille display and computer is Parallel Port. By switching the communication

Fig. 4. (a) The single cell structure of GBD. (b) The single cell structure of SBD.

module, the SBD is capable to transmit Braille signals through RS232 Port, USB Port, and Bluetooth. So the I/O interface can be widely supported. In the front of SBD case bottom, a row of vents is placed and two slow fans are located to the rear to help cooling. Besides, the 45 Braille cells of SBD are plugged into the slots and fixed by two beams, and every single Braille cell is hot-pluggable even if the power supply is working. Such design is convenient for maintenance of Braille cells. Also, SBD is superior to GBD over two aspects as following. The first is the improvement of the mechanism of actuator. It lowers the power consumption and therefore the low heat generation rate comes from actuator. There is no need to place fans with high airflow rate, which causes loud noise like that in GBD. SBD only needs a less noisy fan to

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Fig. 6. (a) The complete arrangement of relays in GBD. (b) The complete arrangement of relays in SBD.

governing equation is then defined as [11]:

rc

›T ›2 T ›2 T ðT 2 TP Þ q00 þ flux þ q_ G ¼ k 2 þ k 2 þ h1 1 L ›t L ›x ›y ð1Þ

Fig. 5. (a) The overall structure of GBD. (b) The overall structure of SBD.

meet the requirement and create a better user environment. Second, owing to the lower height of the cell module, the case of SBD can be made thinner. The arc-shaped upper cover suits the natural hand shape when using. This special design emerges from Human Factor Engineering to enable long-term use with tiresome-free brushing.

3. Numerical modeling In the numerical analysis of SBD, it focuses on heat transfer and electromagnetic theory. The advantages are to save time and speed up the design procedures. Moreover, the numerical results are prepared for the premise part of ANFIS to perform the inverse prediction of optimal design parameters. 3.1. Thermal modeling The heat source of single Braille cell is mainly generated from eight relay actuators. The complete arrangements of the actuators of GBD and SBD are shown in Figs. 6(a) and (b). According to the symmetry principle of system shape and boundary conditions, it only needs to analyze the 23rd Braille cell that is plugged on the approximate center of machine case. After simplifying the numerical model with correct boundary conditions, the compact heat transfer

where r is the density, c is the specific heat, and k is the conductivity. h1 and T1 ; respectively indicate the heat transfer coefficient and the ambient temperature of air. L is the thickness of PCB. t is time, and T is the temperature parameter. The two-dimensional control volume of finite difference method (FDM) is used, and the equation based on finite difference time domain (FDTD) [6] is:

rcP DxDyL nþ1 ðTP 2 TPn Þ Dt  kw DyL n ke DyL n n n ðTW 2 TP Þ þ ðTE 2 TP Þ ¼ Dx Dx   k DxL n k DxL n ðTN 2 TPn Þ þ s ðTS 2 TPn Þ þ n Dy Dy n n 00 þ ½h1 DxDyðT1 2 TP Þ þ qflux DxDy þ q_ G DxDyL

ð2Þ

In the system mentioned above, because the PCB does not generate any heat, the q_ G term equals zero. The eight actuators are supplied with voltage in order to generate the magnetic field which drives the Braille pins. It will generate heat across the PCB since copper coil still has internal resistance. It is worth noting that the resistance of the copper depends on the temperature, so the q00flux term also depends on it. The relationship between the resistance of copper coil and the temperature is: Rf ¼ Ri ð1 þ ðTf 2 Ti Þ=ð234:5 þ Ti ÞÞ

ð3Þ

Rf is the final resistance of the copper coil under a temperature of steady state, and Ri is the resistance of the copper coil at the initial temperature. Tf and Ti are the final steady state and the initial ambient temperature, respectively.

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The equation for the heat flux from the surface of relay to the PCB is: q00flux =L ¼ q00flux ðTf Þ=L ¼ V 2 =Rf

ð4Þ

3.2. Electromagnetic modeling The static magnetic theorem [12] is used to analyze the relay. Field intensity H and flux density B must obey Eqs. (5) and (6): 7£H ¼J

ð5Þ

7£B¼0

ð6Þ

According to the variant material properties, Eq. (7) shows the relationship of B and H : B ¼ mH

ð7Þ

Fig. 7. (a) The two dimensional magnetic flux field of the relay actuator of GBD. (b) The two dimensional magnetic flux field of the relay actuator of SBD.

If the material property is nonlinear, the permeability m is a function of B that can be expressed as:

m¼

B HðBÞ

ð8Þ

By the magnetic vector potential approach, flux density B resulted from the vector potential A yields Eq. (9): B¼7£A

ð9Þ

The definition of B in the Eq. (9) always obeys Eq. (6), so Eq. (6) can be rewritten as the following form:   1 7£ 7£A ð10Þ mðBÞ If the material is isotropic, Eq. (10) can be simplified as: 2m72 A ¼ J

ð11Þ

The definition of Maxwell stress tensor is that on a unit area, the net force is produced by the magnetic field across the surface of object. The differential form of force is: dF ¼

1 ðHðBnÞ þ BðHnÞ 2 HðBnÞÞ 2

3.3. Numerical results of thermal and electromagnetic model The heat generation from the relay is also decayed due to the increasing coil resistance resulting from the raising temperature. This is because the resistance of the copper coil depends on the change of temperature, in the state of fixed supply voltage; the coil current varies with the temperature. As what are mentioned above, it is necessary to use the transient thermal analysis to detect the dynamic equilibrium of the temperature and coil resistance. After the steady state reached, the actuating force of pin is estimated from electromagnetic analysis. Fig. 8 represents the total process of the numerical solutions. The original design actuator parameters of GBD are supply voltage, 6 V, coil resistance, 330 V, dimensions of the cooling fan, sized 60 £ 60 £ 25 mm, fan speed, 4000 RPM, and airflow, 18 CFM. Two fans are assembled in the back of the case shown in Fig. 5. There are two states of airflow; one condition is that

ð12Þ

Vector n denotes that the point normal to the surface at the point of interest. And the net force can be estimated by the integral equation that is the stress tensor over a specific surface. Fig. 7(a) shows the two dimensional magnetic flux field of the relay actuator of GBD, and Fig. 7(b) of SBD. The final coil current I ¼ V=Rf is found by using the resistance of relay, which is estimated by previous thermal analysis results, and then the actuating force is obtained by the electromagnetic finite element method (FEM) model.

Fig. 8. The total processes of numerical solution.

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Table 1 The numerical results of single Braille cell of GBD (330 V, 6 V)

Numerical model

Experiment

Convection state

The maximum temperature of solenoid (8C)

The actuating force of pinhead (gw)

With fan

43.61

16.21

Without fan

69.91

13.81

With fan Without fan

42.9 70.0

15.9 13.1

the fans are energized and the system is under the force convection, and the other is that the fans are powered off and the system is under the nature convection. Table 1 shows the numerical and experiment results of GBD at the room temperature 27 8C, and the relay resistance of the original design of GBD is 330 V at 6 V. It is clear that the maximum temperature of the GBD hardware almost reached the limited temperature 75 8C while the system did not contain fans. This is because of that 45 Braille cells are assembled together, high density of heat generation causes the airflow vents out of its cooling ability. The simple way to solve the thermal problem is to add the fans in the system inside the case. Apparently the actuating force of pin of GBD is also above 15 gw when the system is under the force convection. Noticeably, the superior structure design of SBD must make less influence of thermal effect over actuating force of pins. In other words, the study redesigns the duty point of SBD actuator to optimize the supply voltage and loops of copper coil; therefore, the temperature can be in the acceptable range and the force of Braille pinhead also must meet the requirement. Besides, it is also necessary to achieve the goal of making a lower noisy Braille display expected by the GBD users. However, the problem comes along with the cooling requirement. The key point is to balance the thermal generation, actuating force of pin, and fan noise.

4. Adaptive-network-based fuzzy inference system identification and errors The design of SBD must have the following specifications: First, for the reason of comfortable reading, the best actuating force is above 15 gw based on the tests from the visually impaired people. Next, the turns of the relay should be limited within the small space between the enclosure of two boards of Braille cell. Finally, and most importantly, the working temperature must be below 75 8C to avoid lowering actuating force and damaging pins and relays.

The traditional approach maybe find better design parameters by a trial-and-error method according to the above specifications, but it is not guaranteed that this solution is optimal. ANFIS is superior to the trial-anderror method, because ANFIS can build the inverse prediction model of system behaviors after the database obtained from numerical models. Then ANFIS predicts the optimal solutions in a short time. 4.1. ANFIS architecture and learning The structure of ANFIS [13,14] has five layers and it uses Sugeno fuzzy inference model to be the learning algorithm. For example, in the simplest structure of fuzzy inference system, there are two inputs, x and y; and one output f : In the first order of Sugeno fuzzy inference model, the typical fuzzy if-then rule can be expressed as: Rule 1: If (x is A1 ) and (y is B1 ) then f1 ¼ p1 x þ q1 y þ r1 Rule 2: If (x is A2 ) and (y is B2 ) then f2 ¼ p2 x þ q2 y þ r2 These parameters, p1 ; p2 ; q1 ; q2 ; r1 ; and r2 ; are linear, whereas A1 ; A2 ; B1 ; and B2 are nonlinear. The equivalent structure of ANFIS is shown in Fig. 9. The five layers in ANFIS are fuzzy, production, normalized, defuzzy, and total output layer in order. The following concepts are the input-and-output relationships of each layer. 4.1.1. Fuzzy layer Input x to A1 and A2 ; and y to B1 and B2 ; respectively. A1 ; A2 ; and B1 ; B2 are the linguistic expresses used to distinguish the membership functions (MFs). The relationships between the input –output and MFs are: O1;i ¼ mAi ðxÞ

ði ¼ 1; 2Þ

ð13Þ

O1;j ¼ mBj ðyÞ

ðj ¼ 1; 2Þ

ð14Þ

O1;i and O1;j denote the output functions of the first layer, mAi ðxÞ and mBj ðyÞ denote MFs. The generalized bell function can be used as the MFs. Also, any continuous and piecewise differentiable functions, such as trapezoidal or triangular-shaped MFs, can be used

Fig. 9. Equivalent ANFIS architecture.

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for node functions in this layer. Parameters in this layer are referred to as premise parameters. 4.1.2. Production layer Every node in this layer is marked as symbol P: The outputs are w1 and w2 ; the weight functions of the next layer. They can be shown as: O2;i ¼ wi ¼ mAi ðxÞmBi ðyÞ

ði ¼ 1; 2Þ

ð15Þ

O2;i is the output function of the second layer. 4.1.3. Normalized layer The node is marked as N, and it is used to normalize the weight functions. The function is: wi O3;i ¼ wi ¼ ði ¼ 1; 2Þ ð16Þ w1 þ w2 O3;i is the output function of the third layer. 4.1.4. Defuzzy layer Being an adaptive node, the linear parameter is also called consequent part. The relationship between input and output is: O4;i ¼ wi fi ¼ wi ðpi x þ qi y þ ri Þ

ð17Þ

O4;i is the output function of the fourth layer. Parameters in this layer will be referred to as consequent parameters. 4.1.5. Total output layer Its node is marked as S; the summation of all inputs. It can be expressed as: O5;i ¼ Si wi fi ¼

S i w i fi Si wi

ð18Þ

219

In order to have ANFIS learn more correctly, enough sets of training data computed from the numerical model are needed. Placing the 23rd single Braille cell under the specific ambient temperature, the values of the demanded voltage and the coil resistance are inputted. Each combination of the input parameters is mapped into the specific output of the maximum temperature and actuating force of pin in the numerical model. There are two types of the airflow condition in the numerical model, nature convection and force convection. The supply voltage varies from 3 to 6 V, and the increment in each step is 0.5 V; the coil resistance, from 260 to 360 V, and the increment in each step is 10 V. So, there are 77 data sets for ANFIS training. Fig. 10(a) shows the inverse learning of the ANFIS to fit the numerical data. The original input parts of the numerical models become the consequent parts of the adaptive neural networks, and it is clearly to see obviously that ANFIS suits for simulating consequent parts of the relay resistance and actuating force of pin. It deserves to be mentioned that if the traditional trialand-error method is used, there are not any chances to build the system model in a short time. It is important that ANFIS can select any parameter as its premise part, and the design parameters as the output part. It is not necessary to reuse the numerical model to find out the behaviors of the system responses and design parameters. Comparing Fig. 10(a) with Fig. 10(b), it is found the differences between the ANFIS and the numerical model: in the original design process, the numerical model must select the supply voltage and the relay resistance as its inputs, and the maximum temperature and actuating force of pin as its outputs. ANFIS has a better process to choose the actuating force of pin and the coil resistance as its premise part, and the maximum

O5;i is the output function f of the fifth layer. The ANFIS learning in this study is off-line. This method is to train all the data sets, and apply the gradient and least square method to ensure the neural-network parameters. The hidden layer is computed by the gradient method of the feedback structure. The final output is estimated by the least square method, so the computing speed of hybrid learning method mentioned above is faster than that of the gradient method only. 4.2. Selecting the design parameters and inverse prediction The original inputs of numerical forward models are the supply voltage and the resistance of the copper coil. The outputs are the maximum temperature of the relay and the actuating force of pinhead, which are computed by the thermal and electromagnetic numerical forward models. The feasible data sets establish the databases, which are trained in ANFIS for the prediction of the maximum temperature and the supply voltage. And then in some restrained conditions, the optimal design parameters can be predicted by ANFIS.

Fig. 10. (a) The learning procedure of ANFIS. (b) The reasoning system for Chinese Braille Display.

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F.-H. Yeh et al. / Displays 24 (2003) 213–222 Table 2 The thickness of relay to each coil resistance

Fig. 11. RMSE and epoch number for working temperature and supply voltage.

temperature and demanded voltage as the consequent part. The objective of such inverse learning is to simplify the design procedure, and it is the significant function of the fully trained ANFIS. 4.3. Results of ANFIS inverse prediction and experiment There are only two MFs of the bell function type for each input in ANFIS, the outputs are the temperature and supply voltage, respectively. Fig. 11 shows the root mean squared error (RMSE), and the epoch number. Full-trained ANFIS re-presents the system behaviors much faster than the numerical model does and it takes short time to calculate, too. The inverse way of utilizing ANFIS to find the design parameters was mentioned in Section 4.2. In order to find the optimal design, it is necessary to add control variables to select the preferable design parameters. Following steps demonstrate how this can be done: First, the pinhead is the main care point after the visually impaired people have tested the comfortable touching in

Thickness of relay (mm)

Coil resistance (V)

4.49 4.55 4.61 4.66 4.72 4.77 4.83 4.88 4.94 4.99 5.04

260 270 280 290 300 310 320 330 340 350 360

reading the Brailles. Based on the experiences and habits, the actuating force of pin must be above 15 gw. Second, because of the space limitation between the PCB boards of two Braille cells, the turns of the copper coil on the relay must be limited. The safest space of the relay is below 5 mm. The schematic structure of the relay is shown in Fig. 12. The thickness of the copper coil is calculated by Eq. (19): hn ¼ 2R½1 þ ðn 2 1Þcos 308

n ¼ 1; 2; 3…

ð19Þ

R is the diameter of the copper coil that is 0.05 mm, and n is the layers of the copper coil looped on the iron core. The total thickness of the relay is: H ¼ 2ðRcore þ hn Þ

ð20Þ

The thickness of the relay corresponded to each resistance is shown in Table 2. The more turns of the loops it has, the stronger magnetism it occurs; nevertheless, 320 V is chosen as the maximum because of the space limitation when actuator’s surface is covered with 0.1 mm thick insulated tape for the purpose of protection. Third, that the system temperature must be lower than 75 8C is the most important step concerning with the stability of electronic system. Meanwhile, the widely use of polymer material causes the PCB and pinhead to be below Table 3 The design solutions of SBD

Fig. 12. The schematic structure of relay.

The actuating force of pinhead (gw)

Coil resistance (V)

Maximum temperature of relay (8C)

Supply voltage (V)

29.5 29.6 29.7 29.8 29.9 30 30.1 30.2 30.3 30.4 30.5

320 320 320 320 320 320 320 320 320 320 320

50.18 50.39 50.6 50.82 51.03 51.25 51.47 51.69 51.92 52.14 52.37

4.46 4.48 4.5 4.52 4.54 4.56 4.58 4.6 4.62 4.65 4.67

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5. Conclusion

Table 4 Specification of fans used in GBD and SBD Model

Size (mm)

Speed (RPM)

Air flow (CFM)

Noise (dBA)

Original fan for GBD New fan for SBD

60 £ 60 £ 25 40 £ 40 £ 6

4000 6000

18 5.5

31 28

its qualitative change temperature for the consideration of lightweight. When the temperature exceeds that the polymer can bear, the pinhead will be burned out and then jam in the cell base. Now, the critical design of the nature convection is emphasized, and then the better sets of the design parameters are found. The detail parameters and result values are shown in Table 3. The optimized outcomes fit our limitation. To make lower inner system temperature, proper cooling by fans toward Braille cells and power supply module is chosen. Besides, noise produced by fans in GBD still needs to be improved. The specifications of fans of the old ones for GBD and new chosen ones for SBD are listed in Table 4. A new fan is smaller in size and a 3 dBA decrease in noise level. However, if the noises of two fans are phase correlated, there can be up to a 6 dBA increase in sound pressure level (SPL). So, the maximum noise level of two fans in GBD may be a sound level of 37 dBA, and the two fans in SBD may be in 34 dBA. After that, 29.7 gw as the parameter of the maximum actuating force of pin in nature convection is selected, and the numerical model is reused to prove the precision of ANFIS. Last, the k-type thermocouple sensors are glued to the surface of the relay in order to measure the temperature. After the SBD reaches the steady state, the final relay temperature of the nature convection states can be measured while the power of fans is off. At that time, the force meter can be used to measure the actuating force of pin. The comparison between the numerical model, ANFIS, and the experimental results of SBD are shown in Table 5 when the ambient temperature is 27 8C.

Table 5 The comparison between the numerical model, ANFIS, and the experimental results of SBD Comparison of results at 4.5 V, 320 V Maximum temperature (8C)

Actuating force (g)

Numerical model ANFIS prediction Errors (%)

53.56 50.60 5.52

29.70 29.70 0.00

Experiment

52

29

In this study, a new type of CBD is successfully redesigned and optimized by CAD and ANFIS. Two design parameters that have the major influence on the actuating force and maximum temperature, including supply voltage and coil resistance, were analyzed by the thermal FDM and electromagnetic FEM numerical models and established the basic databases for ANFIS. Using these databases, the optimal design of SBD can be inversely predicted by ANFIS. As verification, the maximum temperature and the actuating force for the optimal supply voltage predicted inversely by ANFIS were compared with the experimental data. The comparison indicates that the maximum temperature and the actuating force of both natural and force convection models achieved very satisfactory accuracy. ANFIS is a rule-based system; it requires suitable amounts of training data and MFs. In this study, two bell-shape MFs and 77 sets of data are used enough to perform a very accurate prediction. The accuracy of maximum temperature reached is as high as 94.41%, and the best accuracy of the actuating force for the inversely predicted supply voltage of ANFIS reached is as high as 100.00%. After optimization, the working temperature of SBD is 52 8C without fans. SBD can still work safely at this working temperature without thermal failure. In the previous design of GBD, there are two fans used for cooling. The maximum noise level measured is 37 dBA. Since the SBD is a well-designed Braille display even without fans, two low noise fans are still added to improve the durability of SBD. The noise resulted is lower than the half of it in GBD. SBD successfully becomes a new type of stable and durable CBD.

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