CN105045107A - Home environmental parameter acquisition method based on Kalman filtering - Google Patents

Abstract

The invention provides a home environmental parameter acquisition method based on Kalman filtering. The home environmental parameter acquisition method based on Kalman filtering comprises the steps: based on an upper and lower computer structure, acquiring data by using a reasonable sensor; transmitting the data to an upper computer through a ZigBee protocol; using KF (Kalman Filtering) to analyze and process the data, thus obtaining the optimal estimate value about the current indoor environment, wherein the system automatically closes or opens the corresponding door and window or curtain when the estimate value is lower than the minimum value in the setting range or greater than the maximum value in the setting range, thus finishing the field real time control; and at last, displaying the data on a monitoring system based on the development of Labview in real time to provide a friendly control interface for an employer. The home environmental parameter acquisition method based on Kalman filtering is provided with high control precision, high real-time performance and high practicality.

Description

A kind of domestic environment parameter collecting method based on Kalman filtering

Technical field

The invention belongs to technology of Internet of things field, particularly relate to a kind of domestic environment parameter collecting method based on Kalman filtering.

Background technology

Along with electronic technology development, the requirement of people to domestic environment (temperature, luminosity, humidity) is more and more higher, the indoor current environmental parameter of timely collection, the switch of automatic control curtain, door and window, the living environment of the most comfortable is provided to people, has become current research focus and caused the interest of domestic and international numerous scholars.Document ^[1]the design of a kind of intelligent homehousehold data acquisition system based on S3C2410 processor of middle proposition, realizes the intelligent management that water, electricity, gas three show one, does not monitor accordingly the environmental parameter of people's life.For solving the problem of data Real-Time Monitoring in domestic environment, Zheng Yi ^[2]deng the ultra-low power consumption intelligent household data acquisition system (DAS) devised in 2011 using CC2430 as control core, this system achieves accurate acquisition to indoor temperature, humidity, intensity of illumination and gas concentration lwevel and process, but does not relate to the automatic control and regulation to indoor environment.

Summary of the invention

The object of the present invention is to provide a kind of domestic environment parameter collecting method based on Kalman filtering, be intended to solve the weak point in above-mentioned background technology.

The present invention is achieved in that a kind of domestic environment parameter collecting method based on Kalman filtering, said method comprising the steps of:

Indoor environment parameter is gathered by sensor;

Described indoor environment parameter is sent to host computer by Zigbee protocol;

By Kalman filtering algorithm, analysis and treament is carried out to the indoor environment parameter that host computer receives, obtain the optimal estimation value of current indoor environmental parameter;

Described optimal estimation value is compared with preset range value;

When optimal estimation value lower than arrange scope minimum value or higher than when arranging the maximal value of scope, closed by clamping device or open corresponding door and window or curtain.

Preferably, described environmental parameter comprises the concentration of temperature, humidity, intensity of illumination and carbon dioxide.

Preferably, describedly described indoor environment parameter be sent to host computer by Zigbee protocol specifically comprise:

By the data that gather in each junction sensor 1s by two buffer accepts;

Each junction sensor just sends an image data to main frame in data acquisition to a half;

Just switch the reception packet of this node after main frame receives, when the state determination main frame represented by bag is receiving the packet of which node.

Preferably, perform described when optimal estimation value lower than arrange scope minimum value or higher than when arranging the maximal value of scope, also comprise closed or open the step of corresponding door and window or curtain by clamping device after:

Data are presented in real time on the control inerface based on the supervisory system of Labview exploitation.

Preferably, describedly carry out analysis and treament by Kalman filtering algorithm to the indoor environment parameter that host computer receives, the step obtaining the optimal estimation value of current indoor environmental parameter specifically comprises:

Setting Gaussian noise;

Obtain neighbourhood noise;

Obtain expectation and variance;

By Kalman filtering algorithm multi-sensor collection to data process.

For in current Smart Home to the degree of accuracy of environment parameter control and requirement of real-time, the present invention is based on upper and lower structure, adopt rational sensor image data, host computer is sent to by Zigbee protocol, and by KF, analysis and treament is carried out to data, obtain the optimal estimation value of current indoor environment, when this value lower than arrange scope minimum value or higher than when arranging the maximal value of scope, system is automatically closed or is opened corresponding door and window or curtain, complete on-the-spot control in real time, finally data are presented in real time in the supervisory system based on Labview exploitation, for owner provides friendly control inerface.The results show, this Systematical control precision is high, real-time, has very strong practicality.

Accompanying drawing explanation

Fig. 1 is the flow chart of steps of the domestic environment parameter collecting method that the present invention is based on Kalman filtering;

Fig. 2 is sensor location schematic diagram in the embodiment of the present invention;

Fig. 3 is environmental parameter Acquisition Circuit connection diagram in the embodiment of the present invention;

Fig. 4 is data transmission time sequence figure in the embodiment of the present invention;

Fig. 5 is the process flow diagram of Kalman filtering work in the embodiment of the present invention.

Embodiment

In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.

Based on a domestic environment parameter collecting method for Kalman filtering, as shown in Figure 1, said method comprising the steps of

Step S1, gather indoor environment parameter by sensor.

In step sl, indoor environment parameter mainly comprises the concentration of temperature, humidity, intensity of illumination and carbon dioxide.For providing a comfortable living environment to people, selected sensor technology index is as follows:

(1) measurement range: temperature-20 ~ 60 DEG C, humidity: 20% ~ 80%RH, illuminance: 1 ~ 1000Lux, carbon dioxide content: 700PPM ~ 10000PPM;

(2) measuring error: temperature≤0.2 DEG C, humidity :≤1%RH, illuminance :≤1Lux, carbon dioxide content :≤10PPM;

(3) output signal: wireless transmission, transmission range >=20m.

For ensureing Systematical control precision, intend employing 8 temperature sensors A M2302 integrated with humidity,

8 high-precision photoresistance MG41-21 and 2 carbon dioxide sensor C20 common composing environment parameter acquisition circuit, its distribution as shown in Figure 2.Wherein 2 MG811 are placed on the position of sensor 7 and sensor 8, and AM2302 and each place of photoresistance respectively place one.

In addition, in embodiments of the present invention, AM2302 sensor is the temperature/humidity sensor that a accurate digital signal of monolithic whole school with I2C bus interface exports.Its hardware interface only has 4 pins, realizes data communication in the mode of I2C interface, because CC2530 does not possess I2C bus interface, therefore use general purpose I/0 mouthful to carry out analogue I2C bus, come to be realize by setting high low level to SCK, wherein PI.2 mouth connects DATA pin, and P1.3 connects SCK pin.And C20 sensor realizes data communication in the mode of RS232 interface, system is connected by P1.0 and the P1.1 of MAX232 and CPU; Realize the collection to carbon dioxide content.Photoresistance MG41-21 dark resistance is more than or equal to 0.1M Ω, light resistance is less than or equal to 1k Ω, by R-V translation circuit, the magnitude of voltage that Acquisition Circuit is exported is directly proportional to illuminance, and output voltage exports with the form of analog quantity, and there are 20 universaling I/O ports CC2530 outside, wherein P0 mouth 8 pins all can directly be connected with external analog amount, utilize 14 inner high-speed ADC converters, illuminance Parameter Switch is become digital signal, and its hardware elementary diagram as shown in Figure 3.

As shown in Figure 3, parameter acquisition circuit and CC2530 have three kinds of interface modes: RS232 mode, the mode of I2C mode and analog input.Wherein simulating signal can directly be inputted by P0.5, utilizes the ADC converter carried to realize analog/digital conversion.

CC2530 has USART0 and USART1 dual serial communication interface, both can work in UART pattern, also can be operated in SPI pattern, and the U0CSR.MODE by serial ports control/status register sets its mode of operation.In addition, also can directly use protocol stack program to use its default configuration: P0_2 is RX end, P0_3 is TX end.The RX end passed through by RS232 is connected with the TX end of CC2530; The TX end of RS232 is connected with the RX end of CC2530 can realize RS232 communication function, and the present invention adopts first scheme.

For I2C interface communication, due to the hardware interface of CC2530 not with I2C communication, therefore, by 8051 embedded cores, serial data line SDA and serial time clock line SCL can only be simulated by P1.2 mouth and P1.3 mouth respectively.

Step S2, described indoor environment parameter is sent to host computer by Zigbee protocol.

In step s 2, due to environment parameter control system, to each semaphore request Real-time Collection, requirement of real-time when therefore transmitting data is higher, should ensure the sample frequency of signal, also will ensure that each node completes data transmission in 1S.Below for temperature, illuminance node, set forth the implementation method of environmental parameter wireless Real-time Collection, data transmission time sequence figure as shown in Figure 4.

As shown in Figure 4, the packet of two node transmissions is designated as Data1 and Data1 respectively, wherein CH0, CH1 represents that leader cluster node receives the data of respective nodes, wherein each node just sends an image data to main frame collecting a half, just switches the reception packet of this node after main frame receives.As can be seen from sequential chart, the state represented by bag just can determine that main frame is at the packet when receiving which node.Data wherein in each node 1s are by BUF0 and BUF1 two buffer accepts.

Step S3, by Kalman filtering algorithm, analysis and treament is carried out to the indoor environment parameter that host computer receives, obtain the optimal estimation value of current indoor environmental parameter.

In step s3, data processing is the core of environmental control system, sensor sends by the mode of wireless transmission the data gathered to host computer, due to factors such as multipath transmisstion, outside noise impacts, loss of data can be caused or produce very big error, cause control system degree of accuracy not high, the actual demand of people can not be met.Native system adopt KF (KalmanFilterAlgorithm) algorithm to multi-sensor collection to data process, thus improve Systematical control precision.

The course of work of Kalman filter is actually the recursive operation process obtaining Wei Na and separate ^[2].Separate from Wei Na the Kalman filter derived and be actually the situation reaching stable state after Kalman filtering process terminates, at this moment the result of KF is identical with WienerSolution ^[3].Its filtering essence is exactly carry out in the recursion mode repeatedly " do not predicted-revise " ^[4], first perform predictor calculation, then the fresh information obtained by observed reading and KF gain, predicted value is revised.Can be predicted by filter value ^[5], also can obtain filtering by predicted value, both interact, and do not require to store any observation data, have good real-time.

Kalman filter gives the formula of an application state variable concept.And be different from other regressive filter structure, it only needs the estimated result remembeing a step.Consider that the state model of process noise and measurement noises two stochastic variables is called random state model.The present invention adopts C language to programme and realizes KF, and its algorithm flow is as follows:

(1) pre-estimation $\widehat{X\left(k\right)}=F(k,k-1)*X(k-1);$

(2) pre-estimation covariance matrix is calculated:

$\widehat{C\left(k\right)}=F(k,k-1)*C\left(k\right)*F{(k,k-1)}^{\′}+T(k,k-1)*Q\left(k\right)*T{(k,k-1)}^{\′};$

Q(k)＝U(k)*U(k)′；

(3) kalman gain matrix is calculated:

$K\left(k\right)=\widehat{C\left(k\right)}*H{\left(k\right)}^{\′}*{[H\left(k\right)*\widehat{C\left(k\right)}*H{\left(k\right)}^{\′}+R\left(k\right)]}^{^}(-1);$

R(k)＝N(k)*N(k)′；

(4) more new estimation:

$\widetilde{X\left(k\right)}=\widehat{X\left(k\right)}+K\left(k\right)*[Y\left(k\right)-H\left(k\right)*\widehat{X\left(k\right)}];$

(5) covariance matrix is estimated after calculating renewal:

$\widehat{C\left(k\right)}=[I-K\left(k\right)*H\left(k\right)*\widehat{C\left(k\right)}*{[I-K\left(k\right)*H\left(k\right)]}^{\′}+K\left(k\right)*R\left(k\right)*K{\left(k\right)}^{\′};$

(6) $X(k+1)=\widetilde{X\left(k\right)}$

$C(k+1)=\widetilde{C\left(k\right)}.$

Repeat above step (1) ~ (6) and Kalman filter function can be realized.Wherein X (k) is the state vector in k moment; The observation vector that Y (k) is the k moment; F (k, k-1) is state transition matrix; U (k) is k moment dynamic noise; T (k, k-1) is Systematical control matrix; H (k) is k moment observation matrix; N (k) observes noise for the k moment.

In step s3, the flow process of Kalman filtering work, as shown in Figure 5, comprises the following steps:

Setting Gaussian noise;

Obtain neighbourhood noise;

Obtain expectation and variance;

By Kalman filtering algorithm multi-sensor collection to data process.

Step S4, described optimal estimation value to be compared with preset range value.

In step s 4 which, user can preset the value range of needed by human body indoor environment parameter in systems in which by the manual setting means of telepilot, comprise the value range of the concentration of temperature, humidity, intensity of illumination and carbon dioxide.

Step S5, when optimal estimation value lower than arrange scope minimum value or higher than when arranging the maximal value of scope, closed by clamping device or open corresponding door and window or curtain.

In step s 5, clamping device comprises motor, is arranged on door and window or curtain.Going out the current every indoor environment parameter value monitored lower than preset range value in system-computed, closing and opening corresponding door and window or curtain by controlling motor.

Step S6, to be presented at data in real time based on the supervisory system of Labview exploitation control inerface on.

In step s 6, being shown processing the optimal estimation value obtained on control inerface by host computer, obtaining corresponding information more intuitively to make user.

For further verification msg acquisition precision and transmission reliability, in embodiments of the present invention, test with temperature/humidity, comprise without test case during Kalman filtering, have a Kalman filtering time test case and data transmission credibility test; Temperature/hygrometer inside and outside the THG312 multifunctional room of standard device employing OREGONSCIENTIFIC.Test result is distinguished as shown in Table 1 and Table 2:

Table 1 is without test result during FK

Test result when table 2 has a FK

Contrast table 1 and table 2, during without FK filtering, relative error is larger, and the relative error change of each test result also comparatively greatly, and when having FK filtering, maximum temperature relative error is 0.16%, humidity maximum relative error is 0.58%, all can meet the requirement of smart home environment state modulator.

The reliability that wireless senser acquisition node communicates with host computer is mainly tested in the test of data transmission performance, sensing distribution schematic diagram shown in Fig. 2, selects sensor 1-5 to be tested object, and setting node collection period is 1min, length of testing speech is 15min, and test result is as shown in table 3:

The test of table 3 data transmission performance

Can be drawn by table 3, the transmission of all data is all accurately, the reliability of verification system communication.

In embodiments of the present invention, take CC2530 as master controller, Kalman filtering algorithm is dissolved in the Acquire and process of environmental parameter, improve Systematical control precision; Achieve the design of wireless intelligent house environmental parameter automatic control system simultaneously, in the application of Smart Home, there is positive role to promotion technology of Internet of things.

List of references:

[1] Zhou Weilong, Wu Guiqing. the intelligent homehousehold data acquisition system based on S3C2410 designs [J]. modern electronic technology 2010,33 (1): 38-43.

[2] Zheng Yi, Liu Runhua. based on the low power-consumption intelligent household data acquisition system (DAS) [J] of CC2430. electronic design engineering, 2011,19 (22): 178-186.

[3] what court. based on the Smart Home data acquisition control system [D] of ZigBee technology. Institutes Of Technology Of Taiyuan, 2011.

[4] Lu Shengli, LIU MEILING, Tian Yanyan. based on many temperature sensor data emerging system [J] of Kalman filtering. Modern Scientific Instruments, 2013,1 (2): 65-68.

[5]Crochiere，Rabiner.OptimumFIRDigitalFilterImplementationsforDecimation，Interpolation，andNarrow-bandFiltering[J]，IEEETrans.Acoustics，Speech，andSignalProcessing.2005，Vol.23，No.5，pp.444-456.

Compared to the shortcoming and defect of prior art, the present invention has following beneficial effect: Kalman filtering algorithm is dissolved in the Acquire and process of environmental parameter by the present invention, improves Systematical control precision; Achieve the design of wireless intelligent house environmental parameter automatic control system simultaneously, in the application of Smart Home, there is positive role to promotion technology of Internet of things.

The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, all any amendments done within the spirit and principles in the present invention, equivalent replacement and improvement etc., all should be included within protection scope of the present invention.

Claims (5)

1., based on a domestic environment parameter collecting method for Kalman filtering, it is characterized in that, said method comprising the steps of:

Indoor environment parameter is gathered by sensor;

Described indoor environment parameter is sent to host computer by Zigbee protocol;

By Kalman filtering algorithm, analysis and treament is carried out to the indoor environment parameter that host computer receives, obtain the optimal estimation value of current indoor environmental parameter;

Described optimal estimation value is compared with preset range value;

When optimal estimation value lower than arrange scope minimum value or higher than when arranging the maximal value of scope, closed by clamping device or open corresponding door and window or curtain.

2., as claimed in claim 1 based on the domestic environment parameter collecting method of Kalman filtering, it is characterized in that, described environmental parameter comprises the concentration of temperature, humidity, intensity of illumination and carbon dioxide.

3. as claimed in claim 2 based on the domestic environment parameter collecting method of Kalman filtering, it is characterized in that, describedly described indoor environment parameter is sent to host computer by Zigbee protocol specifically comprises:

By the data that gather in each junction sensor 1s by two buffer accepts;

Each junction sensor just sends an image data to main frame in data acquisition to a half;

Just switch the reception packet of this node after main frame receives, when the state determination main frame represented by bag is receiving the packet of which node.

4. as claimed in claim 3 based on the domestic environment parameter collecting method of Kalman filtering, it is characterized in that, perform described when optimal estimation value lower than arrange scope minimum value or higher than when arranging the maximal value of scope, also comprise closed or open the step of corresponding door and window or curtain by clamping device after:

Data are presented in real time on the control inerface based on the supervisory system of Labview exploitation.

5. as claimed in claim 1 based on the domestic environment parameter collecting method of Kalman filtering, it is characterized in that, describedly carry out analysis and treament by Kalman filtering algorithm to the indoor environment parameter that host computer receives, the step obtaining the optimal estimation value of current indoor environmental parameter specifically comprises:

Setting Gaussian noise;

Obtain neighbourhood noise;

Obtain expectation and variance;

By Kalman filtering algorithm multi-sensor collection to data process.