CN203198644U - Novel automobile tire pressure wireless monitoring system - Google Patents
Novel automobile tire pressure wireless monitoring system Download PDFInfo
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- CN203198644U CN203198644U CN 201320026187 CN201320026187U CN203198644U CN 203198644 U CN203198644 U CN 203198644U CN 201320026187 CN201320026187 CN 201320026187 CN 201320026187 U CN201320026187 U CN 201320026187U CN 203198644 U CN203198644 U CN 203198644U
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- vehicle tire
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Abstract
The utility model discloses a novel automobile tire pressure wireless monitoring system which consists of multiple SAW (surface acoustic wave) sensors 1, a wireless transmit receive switch 2, a wireless transmitter 3, a wireless receiver 4, an ADSP 5, an antenna 6, a display device 7, an alarm device 8 and the like. The system disclosed by the utility model realizes passivity of the sensors, and the service life is completely not limited by a battery; greater miniaturization of the sensors can be realized, and the influence on the dynamic balance of wheels can be ignored; a wireless transceiving system adopts a single-chip application circuit, thus a transceiving device has a small volume and is convenient to mount; and weak signal processing is realized on an ADSP chip, thus the reliability of the whole monitoring system is improved.
Description
Technical field
Air pressure of automobile tire monitoring system (TPMS) be mainly used in real-time tire pressure automatically monitoring with report to the police, make chaufeur can take appropriate measures to avoid the generation of accident, guarantee the safe driving of automobile.The utility model relates to a kind of novel motor tire wireless monitor system.
Background technology
Existing TPMS is by the direct measured pressure signal of the tyre pressure sensor on the wheel, by microprocessor processes, sends to receiving end in operator's compartment by radio frequency chip, thereby the result is shown, and gives the navigating mate reference.But this mode will be installed lithium cell in tire, and as the power supply of wireless transmitter module, so not only the kinetic balance to tire impacts, and battery life is limited, changes very inconvenient in inside tires.
The utility model content
The purpose of this utility model is to overcome weak point of the prior art, and a kind of passive mode is provided.By being installed in the pressure that wheel surface acoustic wave (SAW) sensor detects tire, overcome the deficiencies in the prior art, take full advantage of the advantage of ADSP treater aspect the signal processing simultaneously, the small signal that receives is handled with neural network algorithm, improve precision and the reliability of system.
The utility model is realized by following scheme.
A kind of novel vehicle tire pressure wireless monitor system of the utility model as shown in Figure 1.Its composition and annexation: be installed in several SAW sensors (1) on the wheel, wireless receiving and dispatching change-over swith (2), wireless launcher (3), wireless receiver (4), ADSP (5), antenna (6), read out instrument (7), warning device (8); By the pressure that is installed in several SAW sensors (1) detection tires on the wheel; Microprocessor ADSP (5) control wireless receiving and dispatching change-over swith (2), wireless launcher (3) and wireless receiver (4) are realized the wireless and passive of tire pressure is read; ADSP (5) is connected with telltale (7), annunciator (8), realizes that the change curve of vehicle tire pressure shows and abnormal alarm in real time.
1.SAW the composition of sensor 1 as shown in Figure 2, interdigital transducer (9), matrix (10), coding reflecting grating (11), reading reflecting grating (12), reed capsule (13), encoder magnet (14).
2. wireless launcher (3) is used the monolithic radio transmitter as shown in Figure 3, selects MAX7044 for use, and 300-450MHz ASK transmission circuit, MAX7044 are based on the VHF/UHF transmitting chip of crystal oscillator PLL.
3. wireless transceiver (4) is used the monolithic wireless receiving circuit, as shown in Figure 4.Select for use the MAX7044 among MAX7033 and Fig. 3 to constitute wireless data transceiving system.MAX7033 is a kind of CMOS superheterodyne receiver chip of low-power consumption, and receive frequency range is at the ASK of 300-450MHz signal.
The utility model compared with prior art has following advantage:
1. realize passiveization of sensor itself, its life-span is not subjected to the restriction of battery fully, avoids changing the trouble of battery disassembly and assembly tire.
2. can realize the micro-miniaturisation more of sensor, can ignore fully to the kinetic balance influence of wheel.
3. wireless transceiver system adopts the monolithic application circuit, makes the transmit receive unit volume little, easy for installation.
4. realize that at the ADSP chip neural network algorithm to the processing of small signal, improves the reliability of whole monitoring system.
Description of drawings
A kind of novel motor tire wireless monitor system composition diagram of Fig. 1.
Fig. 2 SAW sensor construction figure.
Fig. 3 wireless transmitter circuits schematic diagram.
Fig. 4 wireless receiver circuits schematic diagram.
Fig. 5 multilayer forward direction BP neural network structure figure
Fig. 6 is based on the sef-adapting filter functional block diagram of neural network
Wherein: SAW sensor (1), wireless receiving and dispatching change-over swith (2), wireless launcher (3), wireless receiver (4), ADSP (5), antenna (6), read out instrument (7), warning device (8), interdigital transducer (9), matrix (10), coding reflecting grating (11), reading reflecting grating (12), reed capsule (13), encoder magnet (14) etc.
The specific embodiment
Below in conjunction with accompanying drawing the utility model is further described:
1.SAW the principle of sensor 1
Interdigital transducer as shown in Figure 2 is used for excitation and the detection of surface acoustic wave, and it is converted to SAW to the electric wave signal that antenna receives, and the SAW of detection of reflected is converted to electromagnetic wave simultaneously, launches through antenna.The RF pulse signal central frequency of emission is 433MHz.Bandwidth-the 3dB of frequency-response function.Adopt split-finger transducer as reflecting grating.
2. the principle of work of wireless launcher 3
As shown in Figure 3, MAX7044 launches the OOK/ASK data in the 300-450MHz frequency limit, and data rate reaches 100Kb/s, and horsepower output is+13dBm (50 Ω load) that power line voltage is+2.1-+3.6V.Current draw only is 7.7mA when 2.7V, and the consumption of standby electric current and voltage is 130nA, clock output frequency f
XTAL=16Hz, working temperature range-40 ℃-+125 ℃.MAX7044 application circuit schematic diagram as shown in Figure 3.C31, C32, C36, L31, L33, Y31 have different numerical value for the different operating frequency in Fig. 3.
3. the principle of work of wireless receiver 4
As shown in Figure 4, MAX7033 chip receiver radio frequency input reference signal is-120--114dBm, maximum data is 86Kb/s, operating voltage is 3.3V or 5.0V, 250us run up time, current draw is 6.88mA, low-power consumption mode current draw＜3.5uA, during f (RF)=433MHz, crystal oscillator frequency is 4.7547MHz.In Fig. 4, C49, L41, L42 have different numerical value with Y41 for the different operating frequency.
4.ADSP the selection of chip
ADSP5 selects a kind of in the ADSP21XX family chip, and concrete technical parameter is example with ADSP2181.The same with other dsp chip of ADI company, ADSP2181 is based on Harvard structure equally, just based on the parallel organization of the parallel bus that separates, this structure is owing to adopt instruction bus and the data bus that separates, make fetch instruction and fetch data and the operation of arithmetical logic can be finished simultaneously, therefore, it can finish multiply-add operation one time in the monocycle.ADSP2181 is 16 fixed-point dsps of High Performance that Analog Devices company released the second half year in 1994.It has the high-speed cruising ability of 33MIPS (version that 40MIPS is arranged now) and flexible user interface, is one of state-of-the-art fixed DSP product in the world today.
ADSP2181 performance figure: sheet internal program and the data bus structure of Fen Liing---Harvard structure (Harvard Architecture) fully, the one-cycle instruction system of 33MIPS, the one-cycle instruction redirect, multifunction instructions (Multifunction Instructions) is supported the on-chip memory (On-chip Memory) of 80k, comprising the program store of 16k x24bit and the data memory of 16k*16bit, program store not only can be used for the storage program but also can be used for storing data, the ALU (ALU) that separates, multiplication/accumulator/accum (MAC), tubbiness shifter B arrel Shifter), two covers are data access address generator (DAG) fully independently, 16 internal clockings of programmable, 16 inside DMA port (IDMA) is supported on-chip memory visit at a high speed, the memory address space of the separation of gating able to programme and I/O address space, the programmable wait state, 6 external interrupt, 13 zone bits able to programme can be used for signal indication flexibly and data communication.Use neural network algorithm simultaneously and carry out the small signal processing, for details, see the appendix.
5. the working process of monitoring system
When running into the impedance noncontinuous surface, surface acoustic wave will produce reflection.Therefore utilize many coding reflecting gratings (9) can be made into wireless SAW short range, the low power passive sensor of single port mode of operation.The antenna (6) of radio-frequency queries pulse on SAW device of wireless launcher (3) emission receives, and the interdigital transducer (7) that is connected with antenna (6) is converted to surface acoustic wave (SAW) to electric signal.Be positioned at the reflecting grating meeting part reflective sound wave on the track, the echo of reflection is launched through antenna (6) after the conversion of IDT piezoelectricity again.Coding reflecting grating (12) is normal different with degree of reflection (reflectance coefficient) to sound wave under the abnormal state at tire pressure, just comprises the modulation signal of showing tool numerical value like this in the echoed signal.Wireless receiver (4) receives signal, just realizes the wireless and passive of pressure of tire is read, and telltale (8) shows the change curve of tire pressure in real time simultaneously, if unusually except telltale (8) demonstration, while annunciator (9) sends acousto-optic.
Appendix
The method for detecting weak signals of neural network
Neural network refer to simulate biological neuromechanism with and a kind of algorithm of calculating of the mode of process information.The neural network that is used for Detection of Weak Signals mainly contains BP neural network, RBF neural network and GRNN neural network.
The BP neural network has advantages such as massive parallelism, self study, self adaptation, Nonlinear Mapping because of it, for adaptive nonlinear filtering provides a kind of new method.Multi-layer BP Neural Network adopts the Sigmoid function as its activation function, can realize that nonlinear function approaches with arbitrary accuracy, can detect the small signal that is flooded by noise so form the nonlinear adaptive filter with the BP neural network.
1 adaptive noise cancellation principle
Adaptive filtering theory is a kind of optimal filtering method that grows up on linear filtering bases such as Wiener filtering, Kalman filterings.The adaptive noise cancellation principle does not need to know in advance the statistical property of interference noise, and it can adjust to optimum regime with self working state in the process of successive iteration, and is all effective to suppressing broadband noise and narrow-band noise.The characteristics of adaptive filtering are that the transfer function of filter often changes with the variation of incoming signal, namely are the characteristic of Nonlinear Mapping between the input and output of filter.Compare many deficiencies and the restriction of linear filter, adaptive filtering can obtain than linear process more performance in a lot of occasions.
The core of adaptive noise cancellation is sef-adapting filter.Adaptive filtering is to adjust filter parameter with adaptive algorithm to make filter output approach noise superimposed in sensor 1 output signal, so just makes the output of neutralizer approach measured signal.Adaptive filtering can adopt minimum mean square error criterion as its optiaml ciriterion, and namely the mean square value of the output e (k) of neutralizer reaches minimum.Below this is analyzed, neutralizer is output as:
e(k)＝y(k)-z(k)＝s(k)+n(k)-z(k)
Its mean square value is
E[e
2(k)]＝E[(s(k)+n(k)-z(k))
2]
＝E[s
2(k)+n
2(k)+z
2(k)-2n(k)z(k)+2s(k)n(k)-2s(k)z(k)]
＝E[s
2(k)]+E[(n(k)-z(k))
2]+2E[s(k)n(k)]-2E[s(k)z(k)]
If interference noise n (k) is uncorrelated with measured signal s (k), then the output x (k) of sensor 2 is also uncorrelated with s (k), also is mutually uncorrelated through the output z (k) that filter obtains with s (k) by x (k), then has:
E[s(k)n(k)]＝0
E[s(k)z(k)]＝0
Carry it into following formula, obtain:
E[e
2(k)]＝E[s
2(k)]+E[(n(k)-z(k))
2]
＝R
s(0)+E[(n(k)-z(k))
2]
R in the formula
s(0) be the average power of signal, as can be seen, when z (k) trends towards n (k), E[e
2(k)] reach minimum value, namely can from noise, extract useful signal this moment.
The 2 sef-adapting filter designs based on the BP neural network
Artificial neural net (ANN) (Artificial Neural Network, ANN) be the human neural network that can realize certain function to manual construction on the basis of cerebral nerve network understanding understanding, it is the human brain neural network's that theorizes math modeling, is based on imitation cerebral nerve network architecture and function and a kind of information handling system of setting up.Artificial neural net (ANN) connects into complicated network by a large amount of simple components, has the non-linear of height, can carry out the system of complicated logical operation operation and realization nonlinear relationship.Fig. 5 is typical BP neural network structure figure.
The learning process of BP neural network is made up of two parts, i.e. forward propagation and reverse propagation.During forward propagation, input information via hidden layer is handled the back and is passed to output layer, and the neuronic state of each layer only influences the neuronic state of one deck down.If the output result of output layer with exceed desired range of values, then change reverse propagation over to, error information is returned along original neuron connecting path.In return course, revise the neuronic connection weights of each layer one by one.The continuous iteration of this process makes signal errors reach within the scope of permission at last.
Fig. 6 is the sef-adapting filter functional block diagram based on neural network.Usually sef-adapting filter is made up of two parts, i.e. filter segment and adaptive algorithm part, and adaptive algorithm partly is used for adjusting the parameter of filtering.Be filter segment in the frame of broken lines of Fig. 6, the process of adaptive filtering is exactly constantly to adjust the parameter of filter by neural network algorithm, reaches optimum filter effect.
Claims (5)
1. a novel vehicle tire pressure wireless monitor system is characterized in that: by the pressure that is installed in several SAW sensors (1) detection tires on the wheel; Microprocessor ADSP (5) control wireless receiving and dispatching change-over swith (2), wireless launcher (3) and wireless receiver (4) are realized the wireless and passive of tire pressure is read; ADSP (5) is connected with telltale (7), annunciator (8), realizes that the change curve of vehicle tire pressure shows and abnormal alarm in real time.
2. vehicle tire pressure wireless monitor system according to claim 1, it is characterized in that: described passive SAW sensor (2) comprises interdigital transducer (9), matrix (10), coding reflecting grating (11), reading reflecting grating (12), reed capsule (13), encoder magnet (14).
3. vehicle tire pressure wireless monitor system according to claim 1, it is characterized in that: described wireless launcher (3) comprises MAX7044 radiofrequency launcher chip and interface circuit thereof.
4. vehicle tire pressure wireless monitor system according to claim 1, it is characterized in that: described wireless receiver (4) comprises MAX7033 radio frequency receiver chip and interface circuit thereof.
5. vehicle tire pressure wireless monitor system according to claim 1 is characterized in that: the core microprocessors employing ADSP2181 chip of described ADSP (5).
Priority Applications (1)
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|---|---|---|---|
| CN 201320026187 CN203198644U (en) | 2013-01-18 | 2013-01-18 | Novel automobile tire pressure wireless monitoring system |
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|---|---|---|---|
| CN 201320026187 CN203198644U (en) | 2013-01-18 | 2013-01-18 | Novel automobile tire pressure wireless monitoring system |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103512600A (en) * | 2013-10-18 | 2014-01-15 | 重庆邮电大学 | Multifunctional safety monitoring device |
| CN103832225A (en) * | 2014-03-07 | 2014-06-04 | 厦门领夏智能科技有限公司 | Device for monitoring pressure temperature of battery-free tire |
| CN107379897A (en) * | 2017-07-07 | 2017-11-24 | 淮阴工学院 | A kind of vehicle tyre safety condition intelligent detection means |
| CN107379898A (en) * | 2017-07-07 | 2017-11-24 | 淮阴工学院 | A kind of Intelligent Sensing System for Car Tire Safety |
| CN108725104A (en) * | 2018-04-27 | 2018-11-02 | 深圳惠福芯科技有限公司 | A kind of device, method, tire and automobile reading tire information based on SAW-RFID |
| US20220196501A1 (en) * | 2020-12-23 | 2022-06-23 | Goodrich Corporation | Pressure monitoring systems and methods for monitoring pressure of evacuation assembly charge cylinders |
| EP4019404A1 (en) * | 2020-12-23 | 2022-06-29 | Goodrich Corporation | Pressure monitoring systems and methods for monitoring pressure of evacuation assembly charge cylinders |
-
2013
- 2013-01-18 CN CN 201320026187 patent/CN203198644U/en not_active Expired - Fee Related
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103512600A (en) * | 2013-10-18 | 2014-01-15 | 重庆邮电大学 | Multifunctional safety monitoring device |
| CN103512600B (en) * | 2013-10-18 | 2017-01-11 | 重庆邮电大学 | Multifunctional safety monitoring device |
| CN103832225A (en) * | 2014-03-07 | 2014-06-04 | 厦门领夏智能科技有限公司 | Device for monitoring pressure temperature of battery-free tire |
| CN107379897A (en) * | 2017-07-07 | 2017-11-24 | 淮阴工学院 | A kind of vehicle tyre safety condition intelligent detection means |
| CN107379898A (en) * | 2017-07-07 | 2017-11-24 | 淮阴工学院 | A kind of Intelligent Sensing System for Car Tire Safety |
| CN107379897B (en) * | 2017-07-07 | 2019-03-26 | 淮阴工学院 | A kind of vehicle tyre safety condition intelligent detection device |
| CN107379898B (en) * | 2017-07-07 | 2019-03-26 | 淮阴工学院 | A kind of Intelligent Sensing System for Car Tire Safety |
| CN108725104A (en) * | 2018-04-27 | 2018-11-02 | 深圳惠福芯科技有限公司 | A kind of device, method, tire and automobile reading tire information based on SAW-RFID |
| US20220196501A1 (en) * | 2020-12-23 | 2022-06-23 | Goodrich Corporation | Pressure monitoring systems and methods for monitoring pressure of evacuation assembly charge cylinders |
| EP4019404A1 (en) * | 2020-12-23 | 2022-06-29 | Goodrich Corporation | Pressure monitoring systems and methods for monitoring pressure of evacuation assembly charge cylinders |
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|---|---|---|---|
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20130918 Termination date: 20160118 |
|
| EXPY | Termination of patent right or utility model |