The monolithic accelerometer with C-to-D circuit has been implemented by TSMC 0.18um 1P6M CMOS mixed-signal process and APM MEMS process in T18-101B. The layout of the accelerometer with C-to-D circuit on a single chip is shown in Figure 5.3 and its size is 1343um*1419um. The accelerometer takes an area of 793um*812.5um. The die photo of the integrated chip by optical microscope is shown in Figure 5.4. The chip connects to the circuit board through bonding wires as shown in Figure 5.5.
Accelerometer
C-to-D
Figure 5.3: The layout of the integrated chip
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MEMS motion analyzer (MMA) of CIC is used to test the movement and resonant frequency of sensors as shown in Figure 5.6, and the setting of the measurement is set to sweep from 1kHz to 4kHz. The measurement results of the Chip1, 2, and 6 are 2.5kHz as shown in Figure 5.7 compared with 2.19kHz of the simulation.
Measuring instruments used in the measurement include a shaker with vibration control system, a reference accelerometer, power supplies, a function generator, a
Accelerometer
C-to-D circuit
Figure 5.4: The die photo of the chip
Bonding
Figure 5.5: Photos of bonding board and bonding wire
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Figure 5.6: MEMS Motion Analyzer
logic analyzer, and other supporting instruments. The function of the reference accelerometer is used to detect the current force value. The reference accelerometer PCB 352C44 is fixed on the shaker with a sensitivity of 100mV/g. The sinusoidal reference acceleration input, with 100Hz and 1-gravity to 5-gravity, are shown in Figure 5.8 to 5.12. The logic analyzer is used to catch the data of 9bits counter in the range of 0 to 25m second about four periods, and the bits number is related to the gravity of the moment when the reference sinusoidal acceleration is at the peak value.
Then the bits number of the peak value is averaged in the peak of four periods.
The chip under test is wire bonded on the package and mounted on the experimental circuit board for measurement. LDS shaker generates the input acceleration to test the initial capacitance and the capacitance sensitivity. The major instruments used in the measurement are summarized in Table 5.1. The setup of the
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measurement environment is shown in Figure 5.13 for testing the chip. There are two single-axis accelerometers on LDS shaker. One is the reference accelerometer with orange clay for fix the reference one, and the other is the designed accelerometer on the test board. With supply voltage VDD=1.8V, it dissipates a 428.9uA of current and results in a 772uW of static power consumption.
Table 5.1: Instruments used in the measurement
Instrument Model Key Features
Shaker LDS 406-PA100E
Input acceleration range:
±10g Frequency range:
5Hz-9kHz Vibration control
system LDS Laser USB Signal analysis
Spectrum analysis Reference
accelerometer PCB 352C44 Acceleration:±5g
Sensitivity: 100mV/g
Power supply Agilent E3632A Output: 15V/7A
Function generator Tabor Electronics
WW2572A Square wave:50MHz
Logic analyzer Agilent 16902A 4 pods, 16channels/pod Fixture Local customization Length x Width x Height:
11x6.5x9.5
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Figure 5.7: The measurement results of resonant frequency of the accelerometer
0 0.004 0.008 0.012 0.016 0.020 0.024 0.028 0.032 0.036 0.040
0
Figure 5.8: 1G, 100Hz sinusoidal reference acceleration input
0
0 0.004 0.008 0.012 0.016 0.020 0.024 0.028 0.032 0.036 0.040
Figure 5.9: 2G, 100Hz sinusoidal reference acceleration input
0
1000 1500 2000 2500 3000 3500 4000
Chip1
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0 0.004 0.008 0.012 0.016 0.020 0.024 0.028 0.032 0.036 0.040
Figure 5.10: 3G, 100Hz sinusoidal reference acceleration input
0
0 0.004 0.008 0.012 0.016 0.020 0.024 0.028 0.032 0.036 0.040
Figure 5.11: 4G, 100Hz sinusoidal reference acceleration input
0
0 0.004 0.008 0.012 0.016 0.020 0.024 0.028 0.032 0.036 0.040
Figure 5.12: 5G, 100Hz sinusoidal reference acceleration input
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Power Supply Function Generator
Logic Analyzer
Reference Sensor
Chip on board
LDS Shaker LDS Power Amplifier
Board
Chip Fixture
Figure 5.13: Photos of instruments
The chip5 is destroyed due to the bonding. With -5 to 5 acceleration of gravity of input from LDS shaker, the measurement results of gravity to Time (g to T) of other chips are shown in Figure 5.14, and it shows that chip1, 2, and 6 are close to increase linearly and more linear than chip3 and 4. Chip1, 2, and 6 are averaged to form the AVG curve as shown in Figure 5.14. The measurement results compared with the simulation are shown in Figure 5.15. The results are divided into two parts, gravity to capacitance (g to C) and g to T. The part of g to T is measured from the testing environment, and the other part of g to C is derivate from both g to T of measurement and capacitance to time (C to T) of the simulation. It shows higher capacitance sensitivity and lower linear characteristic compared with the simulation. The measurement results show that the capacitance range is 640fF to 890fF with -5 to 5 gravity and the capacitance sensitivity of the black linear trend line is 23.02fF/g. All chips of the measurement results are shown in Table 5.2 compared with the simulation.
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Because the curves of measurement results show the non-linear feature, the sensitivity of capacitance and g to T are simplified from linear trend line of each chip. Obviously, the sensitivity and dynamic range of the measurement results are bigger than the simulation. The possible reasons are that the parasitic capacitance and offset of circuits are made to enlarge the pulse-width and digital bits. The overall conversion relation is given as
g → C → PW → D (5.2) where g is gravity, C is the measured capacitance, PW is pulse-width, and D is the digital bit. There is some capacitance offset in C-to-PW circuit, but the sensitivity is accurate from the measurement results of T18-101A. The measured D values are directly transferred to PW values. Therefore, there are two possible reasons. One is the accuracy of the co-simulation model from MEMS+, and the other is the added D values due to the noise. The resolution of PW could be introduced the noise, but the design is based on one bit for one gravity from MEMS+ because the capacitance range between simulation and measurement is still verified.
Comparing with [7], the sensing capacitance range of this design is smaller 10 times as shown in Table 5.3. The sensor with circuits on single chip and fully digital output signal of the features are over than others. The circuit is designed to use the 9bits counter and 50MHz sampling rate to readout the fully digital, so the power
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consumption is over than others.
Figure 5.14: The measurement results of g to T of chips
Figure 5.15: The comparison between simulation and measurement
7
Linear trend line of g to C (measurement)
g
T (us)
Simulation v.s Measurement
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Table 5.2: The summary of simulation and measurement results
Simulation Chip1 Chip2 Chip3 Chip4 Chip5 Chip6
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Topology Quasi-digital Quasi-digital Quasi-digital Digital Power &
0.8 with sensor & circuits
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Chapter 6 Conclusions and Future Work 6.1 Conclusions
In the measurement, the capacitance sensitivity under the situation of linear trend line is 23fF/g compared with 2.88fF/g of the simulation in -5 to 5 gravity. The initial capacitance of measurement result is about 730fF compared with 455.6fF of the simulation.
In the future, the improvement will be focused on both reading capacitance and resistance on a single chip. We will add offset cancellation to readout practical capacitance, and temperature compensation of circuits for compensating the sensors.
6.2 Future Work
Sensor fusion is the combining of sensory data or data derived from sensory data from disparate sources such that the resulting information is in some sense better than would be possible when these sources were used individually. The term better in this case can mean more accurate, more complete, or more dependable, or refer to the result of an emerging view, such as stereoscopic vision (calculation of depth information by combining two-dimensional images from two cameras at slightly different viewpoints).The data sources for a fusion process are not specified to originate from identical sensors. One can distinguish direct fusion, indirect fusion and fusion of the outputs of the former two. Direct fusion is the fusion of sensor data from
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a set of heterogeneous or homogeneous sensors, soft sensors, and history values of sensor data, while indirect fusion uses information sources like a priori knowledge about the environment and human input. Sensor fusion is also known as (multi-sensor) Data fusion and is a subset of information fusion.
Beyond figuring out the basics for how a Windows 8 system might use sensors, we also needed to think about how apps might use sensors. We looked at a variety of examples of sensor-enabled apps including games, commercial applications, tools, and utilities, to help us determine which scenarios to support as shown in Figure 6.1.
First on the list was the ability for apps to understand motion and screen rotation. This requires an accelerometer, a device that can be used to measure the force due to gravity, and the motion of the device itself. But most scenarios require more than just an understanding of motion and gravity. Orientation is also an important requirement for many applications. To enable a PC to understand orientation, we needed to integrate the functionality of a compass. A 3D accelerometer and a 3D magnetometer are required. This combination of sensors is called a 6-axis motion and orientation sensing system, and can support a basic tilt-compensated compass, screen rotation, and certain casual game apps like a labyrinth style game. Recently, a new type of sensor has started to emerge on phone platforms, the gyro sensor. Gyro sensors measure angular speed, typically along 3 axes. We can also use the data from gyro
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sensors to increase the responsiveness and accuracy of 3D motion-sensing systems. A gyro sensor is very sensitive. Now let’s take a look at sensor fusion in action from the above sensors.
Figure 6.1: Freescale Microsoft® Windows® 8 Sensor Fusion Data Flow
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Vita
姓名 : 王竣傑 性別 : 男
出生地 : 台中市
生日 : 民國七十六年七月十八日
地址 : 台中市南區南和路八十八巷十三號一樓
學歷 : 國立交通大學電子工程研究所碩士班 2010/07~2012/09
國立彰化師範大學機電工程學系 2005/09~2009/07
英文論文題目 :
Capacitive Accelerometer with Capacitance to Digital Interface Circuit Design
中文論文題目 :
電容式加速度計暨電容轉數位介面電路設計