CN112082599A - Multi-source sensor data fusion system and method for intelligent greenhouse control - Google Patents
Multi-source sensor data fusion system and method for intelligent greenhouse control Download PDFInfo
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Abstract
The invention discloses a multi-source sensor data fusion system and method for controlling an intelligent greenhouse, wherein the preprocessing system comprises a first data preprocessing unit, a second data preprocessing unit and a third data preprocessing unit, the first data preprocessing unit, the second data preprocessing unit and the third data preprocessing unit respectively comprise a data receiving module, a local fusion algorithm module and a data output module, and the output end of the data receiving module is electrically connected with the input end of the local fusion algorithm module. The multisource sensor data fusion system and the multisource sensor data fusion method for controlling the intelligent greenhouse solve the problems that a plurality of temperature, humidity and illumination sensors are arranged in the existing intelligent greenhouse to detect numerical values, but the numerical values of the sensors have deviation between the numerical values when being detected, and accurate numerical value extraction cannot be carried out.
Description
Technical Field
The invention relates to the technical field of multi-sensor data fusion, in particular to a multi-source sensor data fusion system and method for intelligent greenhouse control.
Background
The multi-sensor information fusion is an information processing process which is carried out by automatically analyzing and integrating information and data from multiple sensors or multiple sources under certain criteria by using a computer technology to complete needed decision and estimation. With the development and maturity of sensor application technology, data processing technology, computer software and hardware technology and industrial control technology, the multi-sensor information fusion technology has formed a popular emerging subject and technology. The research of the multi-sensor information fusion technology in China is already applied to information positioning, identification and the like in engineering. And it is believed that with scientific progress, the multi-sensor information fusion technology becomes a special technology for comprehensive processing and research of intelligentized and refined data information images and the like, and the basic principle of the multi-sensor information fusion technology is like the process of comprehensively processing information by human brains, so that various sensors are subjected to multi-level and multi-space information complementation and optimized combination processing, and finally, the consistent explanation of the observation environment is generated. In the process, multi-source data is fully utilized for reasonable administration and use, and the final goal of information fusion is to derive more useful information by multi-level and multi-aspect combination of information based on the separated observation information obtained by each sensor. Not only is the advantage of mutual cooperation of a plurality of sensors utilized, but also the data of other information sources are comprehensively processed to improve the intelligence of the whole sensor system.
The existing intelligent greenhouse control system is provided with a plurality of temperature, humidity and illumination sensors for detecting numerical values, but the numerical values of the sensors have deviation between the numerical values when being detected, so that accurate numerical value extraction cannot be carried out.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a multi-source sensor data fusion system and method for intelligent greenhouse control, and solves the problems that a plurality of temperature, humidity and illumination sensors are arranged in the existing intelligent greenhouse control to detect numerical values, but the numerical values of the sensors have deviation among the numerical values during detection, so that accurate numerical value extraction cannot be carried out.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme: a multisource sensor data fusion system for control of intelligent warmhouse booth, including actuating system, sensor group, preprocessing system, data extraction system, fusion computing system and fusion numerical value result system, actuating system's output and sensor group's input electric connection, sensor group's output and preprocessing system's input electric connection, preprocessing system's output and data extraction system's input electric connection, data extraction system's output and fusion computing system's input electric connection, fusion computing system's output and fusion numerical value result system's input electric connection.
The preprocessing system comprises a first data preprocessing unit, a second data preprocessing unit and a third data preprocessing unit, wherein the output end of the first data preprocessing unit is electrically connected with the input ends of the first data preprocessing unit, the second data preprocessing unit and the third data preprocessing unit, the first data preprocessing unit, the second data preprocessing unit and the third data preprocessing unit respectively comprise a data receiving module, a local fusion algorithm module and a data output module, the output end of the data receiving module is electrically connected with the input end of the local fusion algorithm module, and the output end of the local fusion algorithm module is electrically connected with the input end of the data output module.
Preferably, the local fusion algorithm module comprises a failure data module for calculating based on the fusion matrix.
The failure data module based on the fusion matrix comprises a temperature value module, a humidity value module and a illuminance module, the output end of the failure data module based on the fusion matrix is electrically connected with the input end of the temperature value module, the output end of the failure data module based on the fusion matrix is electrically connected with the input end of the humidity value module, and the output end of the failure data module based on the fusion matrix is electrically connected with the input end of the illuminance module.
Preferably, the sensor group includes temperature sensor group, humidity sensor group and illumination sensor group, the output of sensor group and the input electric connection of temperature sensor group, the output of sensor group and the input electric connection of humidity sensor group, the output of sensor group and the input electric connection of illumination sensor group.
Preferably, the data extraction system includes a first data extraction unit, a second data extraction unit and a third data extraction unit, an output end of the data extraction system is electrically connected to an input end of the first data extraction unit, an output end of the data extraction system is electrically connected to an input end of the second data extraction unit, and an output end of the data extraction system is electrically connected to an input end of the third data extraction unit.
Preferably, the fusion calculation system comprises a D-S algorithm unit for overall calculation, and the output end of the D-S algorithm unit is electrically connected with the input end of the fusion numerical result system.
Preferably, the output end of the temperature sensor group is electrically connected with the input end of the first data preprocessing unit, the output end of the humidity sensor group is electrically connected with the input end of the second data preprocessing unit, and the output end of the illumination sensor group is electrically connected with the input end of the third data preprocessing unit.
Preferably, the output end of the temperature value module is electrically connected with the input end of the first data extraction unit, the output end of the humidity value module is electrically connected with the input end of the second data extraction unit, and the output end of the illuminance module is electrically connected with the input end of the third data extraction unit.
Preferably, the output ends of the first data extraction unit, the second data extraction unit and the third data extraction unit are electrically connected with the input end of the D-S algorithm unit.
The invention also discloses a multi-source sensor data fusion system for controlling the intelligent greenhouse, and the fusion method comprises the following steps:
s1, detecting numerical values, namely, starting a temperature sensor group, a humidity sensor group and an illumination sensor group in the sensor groups through a driving system, starting the numerical values in the intelligent greenhouse, wherein the numerical values are displayed by the temperature sensor group, the humidity sensor group and the illumination sensor group through a data receiving module in a time period from the start to the calculation, and after the numerical values are received, local fusion calculation can be carried out through a local fusion algorithm module.
S2, fusing numerical values locally, defining that dj corresponds to a temperature sensor group, a humidity sensor group and an illumination sensor group when a plurality of homogeneous sensors measure the same target, and calculating the dj by the following steps:
sensor and instrument
Where a is proper, i.e. temperature, 20-30 ℃, 60% -85%, i.e. illuminance, Qi is the mean square error of the data measured by the ith sensor, and the smaller the value of dj, the closer the observed values of the two sensors are i j. Otherwise, the larger the deviation is, when a plurality of sensors are used for measuring the same target parameter, the bounded line value beta i j of the dj is given according to experience or results of a plurality of experiments, and a matrix Rm is set to be called a multi-sensor fusion matrix, 400-600W/m 2;
b is low temperature, C is low temperature and high temperature, D is low temperature and insufficient illuminance, E is low temperature, high humidity and insufficient illuminance;
data fusion processing and experimental results;
taking a group of greenhouse parameters at 16:20:00 pm, if dj is 0, the side considers that the ith sensor and the jth sensor are poor in compatibility or mutually unsupported, if the ith sensor and the jth sensor are good in compatibility, the ith sensor and the jth sensor are called mutual support, if one sensor is supported by only a few sensors, the data of the sensor is invalid data, the data is required to be removed, and the rest sensors are valid sensors.
And S3, integrally fusing effective numerical values, extracting the numerical values of the effective temperature sensor group, the effective humidity sensor group and the effective illumination sensor group through the corresponding first data extraction unit, the corresponding second data extraction unit and the corresponding third data extraction unit, calculating through a D-S algorithm unit in the fusion calculation system, and presenting the final basic numerical value through a fusion numerical value result system.
(III) advantageous effects
The invention provides a multi-source sensor data fusion system and method for intelligent greenhouse control. Compared with the prior art, the method has the following beneficial effects:
1. the multi-source sensor data fusion system and method for controlling the intelligent greenhouse comprises a first data preprocessing unit, a second data preprocessing unit and a third data preprocessing unit, wherein the output end of the first data preprocessing unit is electrically connected with the input ends of the first data preprocessing unit, the second data preprocessing unit and the third data preprocessing unit, the first data preprocessing unit, the second data preprocessing unit and the third data preprocessing unit respectively comprise a data receiving module, a local fusion algorithm module and a data output module, the output end of the data receiving module is electrically connected with the input end of the local fusion algorithm module, the output end of the local fusion algorithm module is electrically connected with the input end of the data output module, the local fusion algorithm module comprises a failure data module based on a phase fusion matrix for calculation, the utility model discloses a greenhouse control system, including intelligent greenhouse control system, failure data module based on fuse matrix, temperature value module, humidity value module and illuminance module, the output of failure data module based on fuse matrix and the input electric connection of temperature value module, the output of failure data module based on fuse matrix and the input electric connection of humidity value module, carry out effective numerical value's extraction with the numerical value of temperature sensor group, humidity sensor group and illuminance module, be provided with a plurality of temperature, humidity and illuminance sensor in solving current intelligent greenhouse control and carry out the measuring of numerical value, but because the numerical value of a plurality of sensors can have the deviation between the numerical value when detecting, can't carry out the problem of the extraction of accurate numerical value.
2. According to the multisource sensor data fusion system and method for controlling the intelligent greenhouse, the extracted numerical values of the temperature sensor group, the humidity sensor group and the illumination sensor group are subjected to centralized fusion production through a D-S algorithm, unstable data are solved, the accuracy of data signal synthesis is improved, the synthesis efficiency is improved, and the reasonability and effectiveness of a conflict evidence synthesis result are ensured.
Drawings
FIG. 1 is a system diagram of the present invention;
FIG. 2 is a system diagram of a sensor pack of the present invention;
FIG. 3 is a diagram of a pre-processing system according to the present invention;
FIG. 4 is a diagram of a first data preprocessing system according to the present invention;
FIG. 5 is a system diagram of a local fusion algorithm of the present invention;
FIG. 6 is a system diagram of a failure data system based on a fusion matrix according to the present invention;
FIG. 7 is a diagram of a data preprocessing system of the present invention;
FIG. 8 is a diagram of a converged computing system of the present invention;
FIG. 9 is a flow diagram of the present invention;
FIG. 10 is a flow chart of the method of the present invention.
In the figure: 1. a drive system; 2. a sensor group; 21. a group of temperature sensors; 22. a humidity sensor group; 23. an illumination sensor group; 3. a pre-treatment system; 31. a first data preprocessing unit; 311. a data receiving module; 312. a local fusion algorithm module; 3121. a failure data module based on the fusion matrix; 31211. a temperature value module; 31212. a humidity value module; 31213. a light intensity module; 313. a data output module; 32. a second data preprocessing unit; 33. a third data preprocessing unit; 4. a data extraction system; 41. a first data extraction unit; 42. a second data extraction unit; 43. a third data extraction unit; 5. fusing the computing systems; 51. a D-S algorithm unit; 6. and (4) fusing a numerical result system.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an embodiment of the present invention provides a technical solution: a multisource sensor data fusion system for control of intelligent warmhouse booth, including actuating system 1, sensor group 2, preprocessing system 3, data extraction system 4, fuse computing system 5 and fuse numerical value result system 6, actuating system 1's output and sensor group 2's input electric connection, sensor group 2's output and preprocessing system 3's input electric connection, preprocessing system 3's output and data extraction system 4's input electric connection, data extraction system 4's output and fuse computing system 5's input electric connection, fuse computing system 5's output and fuse numerical value result system 6's input electric connection.
Referring to fig. 2, the sensor group 2 includes a temperature sensor group 21, a humidity sensor group 22 and an illumination sensor group 23, an output end of the sensor group 2 is electrically connected to an input end of the temperature sensor group 21, an output end of the sensor group 2 is electrically connected to an input end of the humidity sensor group 22, an output end of the sensor group 2 is electrically connected to an input end of the illumination sensor group 23, an output end of the temperature sensor group 21 is electrically connected to an input end of the first data preprocessing unit 31, an output end of the humidity sensor group 22 is electrically connected to an input end of the second data preprocessing unit 32, and an output end of the illumination sensor group 23 is electrically connected to an input end of the third data preprocessing unit 33.
Referring to fig. 3-6, the preprocessing system 3 includes a first data preprocessing unit 31, a second data preprocessing unit 32, and a third data preprocessing unit 33, wherein the output terminal of the first data preprocessing unit 31 is electrically connected to the input terminals of the first data preprocessing unit 31, the second data preprocessing unit 32, and the third data preprocessing unit 33, the first data preprocessing unit 31, the second data preprocessing unit 32, and the third data preprocessing unit 33 each include a data receiving module 311, a local fusion algorithm module 312, and a data output module 313, the output terminal of the data receiving module 311 is electrically connected to the input terminal of the local fusion algorithm module 312, the output terminal of the local fusion algorithm module 312 is electrically connected to the input terminal of the data output module 313, the local fusion algorithm module 312 includes a failure data module 3121 for calculating based on a fusion matrix, the failure data module 3121 based on the merged matrix includes a temperature value module 31211, a humidity value module 31212, and a light intensity module 31213, an output end of the failure data module 3121 based on the merged matrix is electrically connected to an input end of the temperature value module 31211, an output end of the failure data module 3121 based on the merged matrix is electrically connected to an input end of the humidity value module 31212, an output end of the failure data module 3121 based on the merged matrix is electrically connected to an input end of the light intensity module 31213, an output end of the temperature value module 31211 is electrically connected to an input end of the first data extraction unit 41, an output end of the humidity value module 31212 is electrically connected to an input end of the second data extraction unit 42, and an output end of the light intensity module 31213 is electrically connected to an input end of the third data extraction unit 43.
Referring to fig. 7, the data extraction system 4 includes a first data extraction unit 41, a second data extraction unit 42, and a third data extraction unit 43, an output end of the data extraction system 4 is electrically connected to an input end of the first data extraction unit 41, an output end of the data extraction system 4 is electrically connected to an input end of the second data extraction unit 42, an output end of the data extraction system 4 is electrically connected to an input end of the third data extraction unit 43, and output ends of the first data extraction unit 41, the second data extraction unit 42, and the third data extraction unit 43 are electrically connected to an input end of the D-S algorithm unit 51.
Referring to fig. 8, the fusion calculation system 5 includes a D-S algorithm unit 51 for overall calculation, and an output terminal of the D-S algorithm unit 51 is electrically connected to an input terminal of the fusion numerical result system 6.
Referring to fig. 10, the invention also discloses a multi-source sensor data fusion system for controlling the intelligent greenhouse, and the fusion method comprises the following steps:
s1, detecting numerical values, namely, starting the temperature sensor group 21, the humidity sensor group 22 and the illumination sensor group 23 in the sensor group 2 through the driving system 1, starting the numerical values in the intelligent greenhouse, wherein the numerical values are displayed by the temperature sensor group 21, the humidity sensor group 22 and the illumination sensor group 23 through the data receiving module 311 in a time period from the start to the time period required for calculation, and after the numerical values are received, local fusion calculation can be performed through the local fusion algorithm module 312.
S2, fusing numerical values locally, defining that dj corresponds to the temperature sensor group 21, the humidity sensor group 22 and the illumination sensor group 23 when a plurality of homogeneous sensors measure the same target, and calculating the dj by the following steps:
sensor and instrument
Wherein, a ═ is (suitably, i.e. temperature, 20-30 ℃, 60% -85%, i.e. illuminance, Qi is the mean square error of data measured by the ith sensor, the smaller the value of dj is, the closer the observed values of i j two sensors are, otherwise, the larger the deviation is, when the same target parameter is measured by a plurality of sensors, the bounded line value β i j of dj is given according to experience or the results of a plurality of experiments, and a matrix Rm is set to be called a multi-sensor fusion matrix, 400-;
b (low temperature), C (low temperature, high temperature), D (low temperature, insufficient illuminance), and E (low temperature, high humidity, insufficient illuminance);
data fusion processing and experimental results;
taking a set of greenhouse parameters (temperature is 20.5 ℃, humidity is 83%, and illuminance is 140W/m2) at 16:20:00 PM, if dj is 0, the side considers that the ith sensor and the jth sensor are poor in compatibility or mutually unsupported, if the ith sensor and the jth sensor are good in compatibility, the ith sensor and the jth sensor are mutually supported, if one sensor is supported by only a few sensors, the data of the sensor is failure data, the data is to be rejected, and the rest sensors are effective sensors.
And S3, integrally fusing effective numerical values, extracting the numerical values of the effective temperature sensor group 21, the effective humidity sensor group 22 and the effective illumination sensor group 23 through the corresponding first data extraction unit 41, the second data extraction unit 42 and the third data extraction unit 43, calculating through the D-S algorithm unit 51 in the fusion calculation system 5, and presenting the final basic numerical value through the fusion numerical value result system 6.
And those not described in detail in this specification are well within the skill of those in the art.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. A multisource sensor data fusion system for control of intelligent warmhouse booth, including actuating system (1), sensor group (2), preprocessing system (3), data extraction system (4), fuse computing system (5) and fuse numerical value result system (6), its characterized in that: the output end of the driving system (1) is electrically connected with the input end of the sensor group (2), the output end of the sensor group (2) is electrically connected with the input end of the preprocessing system (3), the output end of the preprocessing system (3) is electrically connected with the input end of the data extraction system (4), the output end of the data extraction system (4) is electrically connected with the input end of the fusion computing system (5), and the output end of the fusion computing system (5) is electrically connected with the input end of the fusion numerical value result system (6);
the pre-processing system (3) comprises a first data pre-processing unit (31), a second data pre-processing unit (32) and a third data pre-processing unit (33), the output end of the first data preprocessing unit (31) is electrically connected with the input ends of the first data preprocessing unit (31), the second data preprocessing unit (32) and the third data preprocessing unit (33), the first data preprocessing unit (31), the second data preprocessing unit (32) and the third data preprocessing unit (33) respectively comprise a data receiving module (311), a local fusion algorithm module (312) and a data output module (313), the output end of the data receiving module (311) is electrically connected with the input end of the local fusion algorithm module (312), the output end of the local fusion algorithm module (312) is electrically connected with the input end of the data output module (313).
2. The multi-source sensor data fusion system for intelligent greenhouse booth control of claim 1, wherein: the local fusion algorithm module (312) includes a fusion matrix based failure data module (3121) for computing;
the failure data module (3121) based on the fusion matrix comprises a temperature value module (31211), a humidity value module (31212) and a light intensity module (31213), an output end of the failure data module (3121) based on the fusion matrix is electrically connected to an input end of the temperature value module (31211), an output end of the failure data module (3121) based on the fusion matrix is electrically connected to an input end of the humidity value module (31212), and an output end of the failure data module (3121) based on the fusion matrix is electrically connected to an input end of the light intensity module (31213).
3. The multi-source sensor data fusion system for intelligent greenhouse booth control of claim 1, wherein: the sensor group (2) comprises a temperature sensor group (21), a humidity sensor group (22) and an illumination sensor group (23), the output end of the sensor group (2) is electrically connected with the input end of the temperature sensor group (21), the output end of the sensor group (2) is electrically connected with the input end of the humidity sensor group (22), and the output end of the sensor group (2) is electrically connected with the input end of the illumination sensor group (23).
4. The multi-source sensor data fusion system for intelligent greenhouse booth control of claim 1, wherein: the data extraction system (4) comprises a first data extraction unit (41), a second data extraction unit (42) and a third data extraction unit (43), the output end of the data extraction system (4) is electrically connected with the input end of the first data extraction unit (41), the output end of the data extraction system (4) is electrically connected with the input end of the second data extraction unit (42), and the output end of the data extraction system (4) is electrically connected with the input end of the third data extraction unit (43).
5. The multi-source sensor data fusion system for intelligent greenhouse booth control of claim 1, wherein: the fusion calculation system (5) comprises a D-S algorithm unit (51) used for overall calculation, and the output end of the D-S algorithm unit (51) is electrically connected with the input end of the fusion numerical result system (6).
6. The multi-source sensor data fusion system for intelligent greenhouse booth control of claim 3, wherein: the output end of the temperature sensor group (21) is electrically connected with the input end of the first data preprocessing unit (31), the output end of the humidity sensor group (22) is electrically connected with the input end of the second data preprocessing unit (32), and the output end of the illumination sensor group (23) is electrically connected with the input end of the third data preprocessing unit (33).
7. The multi-source sensor data fusion system for intelligent greenhouse booth control of claim 2, wherein: the output end of the temperature value module (31211) is electrically connected to the input end of the first data extraction unit (41), the output end of the humidity value module (31212) is electrically connected to the input end of the second data extraction unit (42), and the output end of the illuminance module (31213) is electrically connected to the input end of the third data extraction unit (43).
8. The multi-source sensor data fusion system for intelligent greenhouse booth control of claim 4, wherein: the output ends of the first data extraction unit (41), the second data extraction unit (42) and the third data extraction unit (43) are electrically connected with the input end of the D-S algorithm unit (51).
9. The multi-source sensor data fusion system for the intelligent greenhouse control according to any one of claims 1 to 8, wherein the fusion method comprises the following steps:
s1, detecting numerical values, namely starting a temperature sensor group (21), a humidity sensor group (22) and an illumination sensor group (23) in a sensor group (2) through a driving system (1), starting the numerical values in the intelligent greenhouse, receiving the numerical values displayed by the temperature sensor group (21), the humidity sensor group (22) and the illumination sensor group (23) through a data receiving module (311) in a time period from the start to the calculation, and performing local fusion calculation through a local fusion algorithm module (312) after the numerical values are received.
S2, fusing numerical values locally, and defining dj to correspond to a temperature sensor group (21), a humidity sensor group (22) and an illumination sensor group (23) when a plurality of homogeneous sensors measure the same target, wherein the dj is calculated by the following steps:
sensor and instrument
Where a is proper, i.e. temperature, 20-30 ℃, 60% -85%, i.e. illuminance, Qi is the mean square error of the data measured by the ith sensor, and the smaller the value of dj, the closer the observed values of the two sensors are i j. Otherwise, the larger the deviation is, when a plurality of sensors are used for measuring the same target parameter, the bounded line value beta ij of dij is given according to experience or the results of a plurality of experiments, and a matrix Rm is set to be called a multi-sensor fusion matrix, 400-600W/m 2;
b is low temperature, C is low temperature and high temperature, D is low temperature and insufficient illuminance, E is low temperature, high humidity and insufficient illuminance;
data fusion processing and experimental results;
taking a set of greenhouse parameters of 16:20:00 pm, wherein the temperature is 20.5 ℃, the humidity is 83%, and the illuminance is 140W/m2, if dj is 0, the ith sensor and the jth sensor are considered to have poor compatibility or not to support each other, if the ith sensor and the jth sensor have good compatibility, the ith sensor and the jth sensor are called to support each other, if one sensor is supported by only a few sensors, the data of the sensor is invalid data, the data is to be removed, and the rest sensors are valid sensors.
S3, the effective numerical values are fused integrally, the numerical values of the effective temperature sensor group (21), the effective humidity sensor group (22) and the effective illumination sensor group (23) are extracted through the corresponding first data extraction unit (41), the second data extraction unit (42) and the third data extraction unit (43), the D-S algorithm unit (51) in the fusion calculation system (5) is used for calculating, and the final basic numerical value is displayed through the fusion numerical value result system (6).
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