機(jī)電外文文獻(xiàn)翻譯--采用Atmel 89S51微控制器的風(fēng)速風(fēng)向測(cè)量系統(tǒng)【中文4420字】【PDF+中文WORD】,中文4420字,PDF+中文WORD,機(jī)電外文文獻(xiàn)翻譯,采用Atmel,89S51微控制器的風(fēng)速風(fēng)向測(cè)量系統(tǒng)【中文4420字】【PDF+中文WORD】,機(jī)電,外文,文獻(xiàn),翻譯,采用,Atmel,89 Wind Speed and Direction Measurement System Using Atmel 89S51 Microcontroller Eunice Sophia K T Department of Physics, Sri Krishnadevaraya University, Anantapuramu -515003, A.P., India. Email: eunice.sophia@gmail.com  Raghavendra Rao Kanchi Professor, VLSI & Embedded System Laboratory, Department of Physics and Principal, College of Engineering and Technology, SK University, Anantapuramu – 515003, A.P., India. Email: kanchiraghavendrarao@gmail.com Abstract—This paper presents a simple instrumentation design built around one of the 8051 family microcontroller to measure instantaneous wind speed and wind direction. This system includes an improved, yet an inexpensive cup anemometer: Davis Instruments 6410 to sense the above said two wind parameters. The accuracy of the processing system is estimated prior to the interfacing the system with the wind sensor. The software is developed in C language and the data is displayed on 16x2 LCD for every three seconds. The collected data is then plotted in circular histogram for analysis. The system designed has the potential to be further developed and be used for in applications for the reason of its effective measurement which correlated well with the standard readings. Keywords—AT89S51; Anemometer; LCD; Compass points; Friction coefficient; I. INTRODUCTION Even as the technology improves day by day and the devices get smarter, 8051 microcontroller and its derivatives still hold the promise of being a sufficient one in finding applications in various application fields. The present work concerns the measurement of two of the primary meteorological variables [1] namely wind speed and direction which is important in many applications like meteorology, wind resource assessment studies, air and water navigation, mining and agriculture. As per the statistics on March 2011, only 29% of the total gross potential for wind power development was installed in India of which 32% alone is technically usable [2]. Since the government targets for to enhance the wind power production to 60GW by 2022, it’s clear that India is more focused to produce electricity using renewable sources towards clean energy technology. The study therefore presents a design which could possibly provide a potential to be used in wind resource assessments. Wind is commonly measured and analyzed with its scalar components separately; wind speed with anemometer and wind direction with wind vane or weather vane. The annual nature of the system of air circulation in the troposphere, affects both the wind speed and direction at a location [3]. Due to their linearity and accuracy, rotational anemometers of cup and propeller type are commonly used for wind speed measurements. Though the measurements taken are usually of mean wind data, instantaneous wind measurement is also important. Instantaneous wind speed and direction data assist in analyzing the build of the turbine and tower whereas the mean wind speed data predicts wind power generation [4]. Minor differences in the wind speed measurement affects the power generation greatly since the power is proportional to the cube power of the wind speed [5]. So accurate wind speed measurements helps in calculating good feasibility studies for installing wind turbines. Among the different mechanisms [1] used to convert the rate of rotations to an appropriate electrical signal for recording the wind speed, four of them are commonly used which employ transducers of type DC generator, AC generator, the electrical contact and the interrupted light beam. . II. LITERATURE SURVEY Previous works relating to interfacing the cup anemometer and the vane for the wind speed and direction measurement are considered as follows: Ivan Simeonov et al [6] developed an embedded system for short-term weather forecast in which the wind speed transducer gave square wave pulses whose wind speed readings needed correction for every 1 kilometer increase in altitude. Michael Cosgrove et al [7] designed an ultra-low cost logging anemometer intended for feasibility surveys of wind power generation. In this case, although the magnetic reed switch produced one pulse for single switch closure per revolution of the cups, an algorithm for debouncing was developed. Haci Can and Vedat M. Karsh [8] work in the development of a data logger using 8051 based microcontroller to measure wind speed and direction, also saw the need for signal conditioning circuitry. Yahya S.H. Khraisat [9] in his work of developing a low- cost automated system that continuously measured weather parameters the terminal voltage from DC generator type, saw the need of signal conditioning before interfacing with the microcontroller. Fouad Sh. Tahir et al [10] designed a data acquisition system based on personal computer to measure temperature, wind speed and direction parameters. Even when the wind speed transducer produced one switch closure cycle for a single rotation of the cups, a DAC was added in the circuitry for the calculation of wind speed output. David Wekesa et al [11] developed an automated, low-cost system of wind speed and direction data logger using Atmel Atmega 32 microcontroller which used optoelectronics-based system that give higher pulse rates per revolution i.e. 6 to 44 [12]. Mehedi Al Emram et al [13] also developed a system for measuring wind speed and direction based on optoelectronics. The production of more than one pulse for a single revolution of the wind cups of the anemometer needed signal conditioning circuitry. From the above works taken into consideration, the transducers that produce the sinusoidal wave needed an additional circuit for signal conditioning or a square wave with a de bounce circuit. But this system doesn’t need signal conditioning and the sensor is easily interfaced even without any de bounce circuit or de bounce algorithm or use of a DAC. The correction in the altitude is carried out by extrapolating the values of wind speed from a lower height using friction coefficient. time. The device is not powered but sends out a pulse when the reed switch makes a contact on influence of the magnet. The reed switch is mounted so that it makes a single closure per revolution of the cups. The sensor includes sealed bearings for long life and can stand up to hurricane force winds although being sensitive to a light breeze with low starting threshold. Specifications of the sensor state that the range and accuracy were verified in the wind tunnel tests. The material of the cups is of light weight, versatile and eco-efficient with its operating range from less than 1 mph to over 200 miles per hour (mph). The rate of rotation of the cups is proportional to the wind blow. The weather vane that comes attached with the anemometer is flexible and has quick response to align itself pointing to the direction in which the wind blows. The vane is fitted inside with a 20k potentiometer. The vane’s direction corresponding voltage is recognized and direction is displayed accordingly on the LCD. The resistance from the wiper to the terminal is completely linear with azimuth. The directions are in accordance with the meteorological wind direction. The vane pointing north starts with 0 degrees and moves clockwise through 16 points on compass rose. TABLE I. COMPASS DIRECTIONS Compass points Degree N 348.75 – 11.25 NNE 11.25 – 33.75 NE 33.75 – 56.25 ENE 56.25 – 78.75 E 78.75 – 101.25 ESE 101.25 – 123.75 SE 123.75 – 146.25 SSE 146.25 – 168.75 S 168.75 – 191.25 SSW 191.25 – 213.75 SW 213.75 – 236.25 WSW 236.25 – 258.75 W 258.75 – 281.25 WNW 281.25 – 303.75 NW 303.75 – 326.25 NNW 326.25 – 348.75 III. HARDWARE A. Description of the Hardware The hardware primarily consists of the AT89S51 microcontroller, wind sensor or anemometer and LCD. AT89S51 is a high performing low-cost microcontroller. It is an 8-bit microcontroller with 4K bytes of In-system programmable flash memory. The on-chip flash enables the program memory to be reprogrammed either in-system or by conventional nonvolatile memory programmer. The other salient features of AT89S51 are: 128 bytes of RAM, 32 I/O lines and two 16bit timers/counters [14]. The anemometer [15] used has a 3 hemispherical cups symmetrically held on to the vertical shaft. This design of mechanical type anemometer exerts uniform torque during revolutions. It is a passive transducer of electrical contact type that calculates the amount of air blowing in an interval of  B. Hardware design The design employs the sensor unit followed by the processing unit and the display unit. Fig. 1. Design of the system The processing unit consists of an ADC and AT89S51 microcontroller along with the 5V power supply circuit. The display unit has a LCD that updates the wind speed and direction information every 3 seconds. The hardware designed was estimated for wind speed calculation accuracy by using a similar output as of the wind sensor i.e. a TTL compatible square wave, from a function generator. The results are shown in the table below. TABLE II. COMPARISON OF FREQUENCY INPUT AND DISPLAYED OUTPUT Frequency given (Hz) Calculated value for 2.25 sec LCD read for 2.25 sec 3 6.75 7 5 11.25 11 10 22.5 23 20 45 45 30 67.5 67 40 90 89 65 146.25 145 78 175.5 174 85 191.25 190 98 220.5 219 100 225 224 106 238.5 237 The results compared above shows that the output from the processing unit relates well with the frequency given. The speed pulse sent by the sensor was directly interfaced with the microcontroller without the need for signal conditioning. A pull-up resistor used in the circuit ensures the signal detected by the microcontroller is always high except when the sensor pulls it low. The mechanism includes counting the pulses in a sampling period of 2.25seconds which is in accordance with the recommended sampling averaging times of 1-5 seconds for wind speed and wind direction measurements [1]. The wind direction output from the sensor is connected to the controller through ADC 0804 which is a 8-bit and single channeled. The microcontroller is programmed to send out the appropriate direction according to the value at ADC. The functional circuit diagram is as follows:  Fig. 2. Block diagram of the circuit The photograph of the circuit is shown below. Fig. 3. Circuit on board. The anemometer was fixed to a 2 foot pole and placed atop a 3-storey building for the open air measurements. The sensor was arranged at a location where there is free flow of air but could not meet the specific requirements like fixing it above 7 feet due to infrastructural constraints. However, there was an unavoidable concrete obstruction to the northeastern side of the placement. The picture below shows all the sides of the sensor. Fig. 4. Anemometer placed for open air readings. IV. SOFTWARE Hr Standard WS10m (m/s) Observed WS16m(m/s) Standard WDir10m Observed WDir16m (Compass points) 16.5 1.5267 1.69875 68.5148 (ENE) ENE 17.0 1.8173 2.01168 76.0462 (ENE) ENE 17.5 1.8193 2.06756 92.9933 (E) E The software was developed in C language using Keil μVision5 Integrated Development Environment (IDE) [16]. The hex file of the software was loaded on to the microcontroller by USB powered conventional 8051 memory programmer. The flowchart of the software is as follows: TABLE III. STANDARD AND OBSERVED VALUES OF WIND SPEED AND DIRECTION Include suitable header files Define ports Initialize LCD Set Timer 1 to count 8-bit value Start counting pulses for the sampling period and stop the counter Display the wind run on LCD Read the wind direction digital output from ADC Select the wind direction according to the analog voltage and display on LCD Do it for ever Start Wind Rose graphs plotted using Oriana 4 software are shown below: Fig. 6. Wind direction resultant mean at ENE for 16:00 to 16:30. Fig. 5. Wind speed and direction measurement algorithm. V. RESULTS AND DISCUSSIONS Wind measurement of speed is recorded in mph and direction by the abbreviation of the compass direction on LCD. The sensor’s response to the instant weather conditions appear to be flexible and accurate. The vane heeded well to any slight change in the wind direction by pointing itself into the direction of the wind. The cup anemometer moved in accordance with the wind flow. The observations were taken for three half-an-hours during the day. The readings noted for every 2 minutes were averaged to half an hour and compared with the standard values of the sonic anemometer readings from the Aerosol and Atmospheric Research Laboratory (AARL) lab set up by ISRO at Sri Krishnadevaraya University (SKU). The standard readings at 10m height as well as the observed values at 16m height are tabulated below:  Fig. 7. Wind direction resultant mean at ENE during 16:30 to 17:00. Grasslands (ground level) 0.15 Tall crops, hedges and shrubs 0.20 Heavily forested land 0.25 Small town with some trees and shrubs 0.30 City areas with high rise buildings 0.40 Fig. 8. Wind direction resultant mean at E during 17:00 to 17:30 A few points of the results are: · Easterly wind blew for most of the time during the half an hour between 16hr to 16hr 30 min forming 50% of the total while the resultant mean is towards East-North east. · During the 16:30 to 17:00 time period, higher wind speeds were observed along East-Northeast and East direction with high frequency wind blowing from the East even for next half an hour. · The obstruction on north-western side impacted little on the observations due to easterly wind blowing for most of the time and the wind direction readings coincided exactly with that of the standard readings. · The wind speeds as observed at 16m are higher as expected with the wind speed measured at 10m. · The dead band error is present from 0o to 5o and from 355o to 360o. But the latter part of the error was eliminated by programming. The standard values of wind speed at height of 10m are extrapolated to the height of 16m at which the observed values relate. For extrapolation the power law [17] proposed by Hellmann is used. The equation is v/v0 = (H/H0)α (1) Where v is the the speed at height H, v0 is the speed at height H0 (frequently referred to as a 10-meter height) and α is the friction coefficient or Hellmann exponent or wind shear coefficient [18]. This coefficient is a function of the particular topography at a site, and this parameter can vary by the hour of the day, time of the year and with atmospheric conditions such as air density. The table [17] shown below relates the friction coefficient α for a variety of landscapes. Landscape type Friction coefficient (α) Lakes, ocean and smooth hard ground 0.10 TABLE IV. FRICTION COEFFICIENT TABLE FOR DIFFERENT LANDSCAPES. The friction coefficient α is calculated by rewriting (1), as α = (ln(v) – ln(v0)) / (ln(H) – ln(H0)) (2) According to the standard wind data from 15Hrs to 15.5Hrs on 1st April, 2016 the wind speed (v) at 18m height is 1.4704m/s and at 10m height, the wind speed (v0) is 1.39m/s. From (2), the friction coefficient for these values is 0.1. But the observations were taken on the same day from 16Hr to 17Hr 30min which was toward evening when the temperature fall and the friction coefficient increase. So the next two friction coefficients i.e. 0.15 and 0.20 were taken into consideration for extrapolating the standard reading from 10m to 16m height. The results are tabulated as below. TABLE V. EXTRAPOLATED STANDARD VALUES AND OBSERVED WIND SPEED READINGS S.No Time of the day (Hrs) WS(m/s) α=0.15 WS(m/s) α=0.20 Observed WS (m/s) 1 16.5 1.6382 1.6771 1.69875 2 17 1.9499 1.9964 2.01168 3 17.5 1.9521 1.9986 2.06756 The extrapolated standard wind speed readings for both the friction coefficients of α equal to 0.15 and 0.20 strongly correlated with the observed values of wind speed. The correlation coefficients are 0.99091 and 0.99089 respectively. The easterly wind blowing for most of the time did not have any apparent obstructions as can be seen from Fig. 4. Moreover, a little higher observed wind speed values can be accounted for the wind speed acceleration that occurs over hills, buildings etc (when the wind encounters an obstruction) [17]. The power management however is relatively short for the use of long term observations of wind data. VI. CONCLUSION The system developed using AT89S51 microcontroller and Davis Anemometer 6410 to measure real-time wind speed and wind direction showed fairly accurate results which were corroborated by the standard values from the Aerosol and Atmospheric Research Laboratory at SKU, taken during the same hours on the same day. The strong correlation coefficients obtained showed that the system can be a reliable one. References [1] USA Environmental Protection Agency (EPA). “Meteorological Monitoring Guidance for Regulatory Modeling Applications”, February 2000. EPA-454/R-99-005. [2] http://www.infraline.com/reportdetails/112/Wind-Power-Outlook-in- India-2015.htm [3] http://green-power.com.pl/en/home/wiatr-i-jego-pomiar-w-energetyce- wiatrowej/ [4] http://www.homepower.com/articles/wind-power/design- installation/understanding-wind-speed [5] http://www.wwindea.org/technology/ch01/en/1_4.html [6] I. Simeonov, H. Kilifarev, R. Llarionov, “Embedded system for short- term weather forecasting”, Proceedings of International Conference on Computer Systems and Technologies ( CompSysTech’06), 2006. [7] M. Cosgrove, B. Rhodes, J. Scott, “Ultra-low-cost Logging Anemometer for Wind Power Generation Feasibility Surveys”, Research Gate, January 2007. [8] H. Can, V. M. Karsh, “Multipoint Wind speed and direction measurement and data logging by using 8051-based microcontroller”, American Journal of Science, 157:2482-2488, 2007. [9] Yahya S. H. Khraisat, “Design a Wireless Meteorological Station in Jordan”, Canadian Center of Science and Education, vol. 5, no.1, January 2012. [10] F. S. Tahir, A. M. Salman, J. K. Mohammed, W. K. Ahmed, “Data Acquisition System for Wind Speed, Direction and Temperature Measurements”, Journal of Engineering, vol. 18, no. 11, pp. 1229-1236, November 2012. [11] D.W Wekesa, J.N. Kamau, J.N. Mutuku, “Calibrated data logging instrumentation system for wind speed and direction measurements”, Basic Research Journal of Engineering Innovation, vol. 1(3), pp. 53-57, June 2013. [12] S. Pindado, J. Cubas, F. Sorribes-Palmer, “The Cup Anemometer, a Fundamental Meteorological Instrument for the Wind Energy Industry. Research at the IDR/UPM Institute”, Sensors, vol. 14, pp. 21428-21452, August 2014. [13] http://documents.mx/documents/a-microcontroller-based-system-for- determining-instantaneous-wind-speed-and.html [14] AT89S51 Datasheet.pdf. [15] Davis Anemometer 6410 Datasheet.pdf. [16] http://www.keil.com/c51/pk51kit.asp [17] F. Banuelos-Ruedas, C.A. Camacho, S. Rios-Marcuello. “Methodologies used in its impact in the Wind Energy Resource Assessment in a Region”. Available: www.intechopen.com [18] Firas A. Hadi, “Diagnosis of the Best Method for Wind Speed Extrapolation”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering. vol. 4, no. 10, October 2015.