CN109189927A - gas turbidity data automatic clustering method, device and server - Google Patents
gas turbidity data automatic clustering method, device and server Download PDFInfo
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- CN109189927A CN109189927A CN201810992667.2A CN201810992667A CN109189927A CN 109189927 A CN109189927 A CN 109189927A CN 201810992667 A CN201810992667 A CN 201810992667A CN 109189927 A CN109189927 A CN 109189927A
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Abstract
The present invention provides gas turbidity data automatic clustering method, device and server, and the method includes obtaining n gas turbidity to handle node PiThe gas turbidity sample vector x of transmissioniConstitute sample set；The dissimilarity between two samples is calculated, and obtains dissimilarity matrixInitialize classification ω；Each sample is obtained for the degree of membership of classification；Each sample is obtained for the contribution degree of classification；Export the cluster result indicated based on the degree of membership and contribution degree.The gas turbidity data processing system that distributed gas turbidity processing node and server are constituted is provided in the present invention, the system can be realized the automatic control acquisition of gas turbidity data, the distributed gas turbidity processing automatic monitoring alarm of node, gas turbidity data sensibility and clustering processing, it is clear that the automatic cluster of gas turbidity provides a kind of reliable index for the pollution control of subsequent gases turbidity.
Description
Technical field
The present invention relates to environment protection field more particularly to gas turbidity data automatic clustering methods, device and server.
Background technique
In Environmental Studies, smoke contamination is important a ring, and in smoke contamination with submicron particles pollute for
Human injury is most obvious, therefore, it is necessary to be monitored analysis for submicron particles pollution.However in the prior art lack pair
In the relevant programme for monitoring and automatically analyzing automatically of submicron particles pollution.
Further, since the hysteresis quality of sensing element so that obtained detection data can not fast reaction smoke content change
Change, therefore, it is necessary to sensibility processing be carried out for data, so that obtained testing result reaction is rapider.
Cluster is carried out for the pollution level of submicron particles to be conducive to carry out subsequent pollution control according to cluster result,
And in the prior art also without providing the scheme of automatic cluster.
Summary of the invention
In order to solve the above technical problem, the present invention provides gas turbidity data automatic clustering method, device and servers.
The present invention is realized with following technical solution:
Gas turbidity data automatic clustering method, which comprises
It obtains n gas turbidity and handles node PiThe gas turbidity sample vector x of transmissioniConstitute sample set；
The dissimilarity between two samples is calculated, and obtains dissimilarity matrix R={ rij}n*n；
Initialize classification ω；
Each sample is obtained for the degree of membership of classification；
Each sample is obtained for the contribution degree of classification；
Export the cluster result indicated based on the degree of membership and contribution degree；
The detection device of gas turbidity includes by first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and third gas
Body Turbidity measurement instrument gas turbidity detection module in series and gas nephelometer calculate module, the first gas Turbidity measurement
Instrument, second gas Turbidity measurement instrument and third gas Turbidity measurement instrument pass through change of the perception light in instrument internal transmission process
Change and carrys out detection gas turbidity；The first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and third gas Turbidity measurement
Instrument has identical structure；It includes light source that it is internal, is additionally provided with photoelectric sensor on light source outgoing optical propagation direction；It is described
The output end of photoelectric sensor is connect with high-gain amplifier, the high-gain amplifier with for converting electrical signals to gas turbidity
Converter connection, the converter connect with the gas turbidity computing module.
Further, the degree of membership is indicated with u, uikIndicate sample vector xiTo classification ωkDegree of membership, the contribution
Spending is indicated with v, vkjIndicate sample vector xjTo classification ωkContribution weight；
Degree of membership is according to formula；It calculates, contribution degree is according to formulaIt calculates, φ and β are constant related with clustering precision.
A kind of gas turbidity data automatic cluster device, comprising:
Sample set obtains module, for obtaining n gas turbidity processing node PiThe gas turbidity sample vector x of transmissioni
Constitute sample set；
Dissimilarity computing module for calculating the dissimilarity between two samples, and obtains dissimilarity matrix；
Initialization module, for initializing classification；
Degree of membership computing module, for obtaining each sample for the degree of membership of classification；
Contribution degree computing module, for obtaining each sample for the contribution degree of classification；
Cluster result output module, for exporting the cluster result based on the degree of membership and contribution degree expression；
The detection device of gas turbidity includes by first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and third gas
Body Turbidity measurement instrument gas turbidity detection module in series and gas nephelometer calculate module, the first gas Turbidity measurement
Instrument, second gas Turbidity measurement instrument and third gas Turbidity measurement instrument pass through change of the perception light in instrument internal transmission process
Change and carrys out detection gas turbidity；The first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and third gas Turbidity measurement
Instrument has identical structure；It includes light source that it is internal, is additionally provided with photoelectric sensor on light source outgoing optical propagation direction；It is described
The output end of photoelectric sensor is connect with high-gain amplifier, the high-gain amplifier with for converting electrical signals to gas turbidity
Converter connection, the converter connect with the gas turbidity computing module.
A kind of server, the server include a kind of above-mentioned gas turbidity data automatic cluster device.
In the description of the invention, it is to be understood that term " center ", " longitudinal direction ", " transverse direction ", "upper", "lower",
The orientation or positional relationship of the instructions such as "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outside" is
It is based on the orientation or positional relationship shown in the drawings, is merely for convenience of description the invention and simplifies description, rather than indicate
Or imply that signified device or element must have a particular orientation, be constructed and operated in a specific orientation, therefore cannot understand
For the limitation to the invention.In addition, term " first ", " second " etc. are used for description purposes only, and should not be understood as indicating
Or it implies relative importance or implicitly indicates the quantity of indicated technical characteristic." first ", " second " etc. are defined as a result,
Feature can explicitly or implicitly include one or more of the features.In the description of the invention, unless separately
It is described, the meaning of " plurality " is two or more.
In the description of the invention, it should be noted that unless otherwise clearly defined and limited, term " peace
Dress ", " connected ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or integrally
Connection；It can be mechanical connection, be also possible to be electrically connected；Can be directly connected, can also indirectly connected through an intermediary,
It can be the connection inside two elements.For the ordinary skill in the art, on being understood by concrete condition
State concrete meaning of the term in the invention.
The beneficial effects of the present invention are:
The gas turbidity data processing system that distributed gas turbidity processing node and server are constituted is provided in the present invention
System, the system can be realized the automatic prison of the automatic control acquisition of gas turbidity data, distributed gas turbidity processing node
Control the sensibility and clustering processing of alarm, gas turbidity data, it is clear that the automatic cluster of gas turbidity is subsequent gases turbidity
Pollution control provides a kind of reliable index.
Detailed description of the invention
Fig. 1 is gas turbidity data preprocessing module processing method flow chart provided in this embodiment；
Fig. 2 is gas turbidity data acquisition module block diagram provided in this embodiment；
Fig. 3 is gas turbidity computing module block diagram provided in this embodiment；
Fig. 4 is gas turbidity data automatic clustering method flow chart provided in this embodiment；
Fig. 5 is gas turbidity data automatic cluster device block diagram provided in this embodiment；
Fig. 6 is server architecture schematic diagram provided in this embodiment.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, the present invention will be made below further detailed
Description.
The embodiment of the present invention provides a kind of turbidity data processing system, and the turbidity data processing system is by distributed gas
Turbidity handles node and server is constituted, the distributed gas turbidity processing node and the server communication.Each gas is turbid
Degree processing node obtains gas turbidity data in response to the instruction of the server, carries out gas turbidity data prediction and by gas
Body turbidity data pre-processed results are transmitted to server, and the server is used for according to obtained gas turbidity data prediction knot
Fruit carries out the processing of gas turbidity data clusters.
The gas turbidity processing node includes gas turbidity data acquisition module and gas turbidity data preprocessing module；
The gas turbidity data acquisition module is for obtaining gas turbidity data；The gas turbidity data are according to acquisition
Time sequencing sequentially recorded；
The gas turbidity data preprocessing module is used to carry out the sensibility processing of gas turbidity data；The sensibility
It is excessively slow to handle data variation caused by hysteresis quality for reducing data collecting module collected gas turbidity data, and make via
Sensibility treated data being capable of more sensitive reaction gas turbidity variation.
The gas turbidity data preprocessing module executes following treatment processes, as shown in Figure 1:
S101. key message extraction is carried out to gas turbidity data.
The key message, which is extracted, realizes P using following formula1(n)=P1(n-1)×(1-θ)+P(n)× θ, wherein P(n)It is
The gas turbidity data of n-th of sampling instant, P1(n-1)It is that the corresponding key message of (n-1)th sampling instant extracts as a result, P1(n)
It is that the corresponding key message of n-th of sampling instant extracts as a result, θ is to extract operator, is in specific information extraction process
Constant, specific value can be set according to the actual situation.
S102. result is extracted to key message and carries out sensitive process.
The pretreatment realizes P using following formula2(n)=P '(n-1)×(1-κ)+[χ×(1+Γ)×P1(n)-χ×
P1(n-1)] × κ, wherein P2(n)It is that the corresponding susceptibility correction of n-th of sampling instant extracts as a result, P '(n-1)It is (n-1)th sampling
The final output at moment, κ, χ, Γ are susceptibility processing coefficients, and specific value can be set according to the actual situation
It is fixed.
S103. arrangement output is carried out to sensitive process result.
The arrangement output realizes P ' using following formula(n)=P(n)×(1-|P2(n)-P(n)|)+P2(n)×|P2(n)-P(n)
|, wherein P '(n)It is the final output of n-th of sampling instant.
Certainly, in n=1, P '(n)=P(n)=P1(n)=P2(n)。
Specifically, the gas turbidity data acquisition module is as shown in Fig. 2, turbid including gas turbidity detection module, gas
Spend computing module, memory and comparator.
The gas turbidity detection module is by first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and third gas
Turbidity measurement instrument is in series, the first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and the inspection of third gas turbidity
Variation of the instrument by perception light in instrument internal transmission process is surveyed come detection gas turbidity.If gas turbidity increases, light
The light that source issues just will increase by the absorption of the submicron particles in gas and refraction, the light of the photodetector sensing of instrument internal
Flux is reduced.
Specifically, the first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and third gas Turbidity measurement instrument
Has identical structure.It includes light source that it is internal, is additionally provided with photoelectric sensor on light source outgoing optical propagation direction.The light
The output end of electric transducer is connect with high-gain amplifier, the high-gain amplifier with for converting electrical signals to gas turbidity
Converter connection, the converter are connect with the gas turbidity computing module.The first gas Turbidity measurement instrument, the second gas
Body Turbidity measurement instrument is different with the optical source wavelength in third gas Turbidity measurement instrument, in a feasible embodiment, respectively
450nm, 500nm, 550nm, photoelectric sensor are 400-600nm to the response range of spectrum.In the embodiment of the present invention for
The selection principle of optical source wavelength is: avoiding vapor and titanium dioxide as far as possible in the colleague for finding out gas sub-micron granule density
The influence that carbon decays for light source.
The gas turbidity computing module is as shown in Figure 3, comprising:
Gas turbidity acquiring unit, the first concentration ρ measured for obtaining first gas Turbidity measurement instrument1, second gas
The first concentration ρ that Turbidity measurement instrument measures2, the first concentration ρ that third gas Turbidity measurement instrument measures3。
Cluster centre computing unit, for calculating the first concentration ρ1, the second concentration ρ2With third concentration ρ3Cluster centre
ρ0.The calculation method of cluster centre can refer to the prior art.
Weight calculation unit, for calculating the first concentration ρ1Corresponding weighted value σ1, the second concentration ρ2Corresponding weighted value σ2
With third concentration ρ3Corresponding weighted value σ3.The acquisition function of weight isWherein | ρ0-ρi| marker concentration and poly-
The Euclidean distance at class center.
Calculated result output unit is used for output gas concentration calculation result.The calculated result uses weighted mean method
It obtainsIf | ρ0-ρi|, then directly by its corresponding ρiCalculated result as gas turbidity computing unit.
Number of the gas turbidity calculated result that calculated result output unit obtains as the gas turbidity data of step S101
According to source.
The memory is for storing all previous gas turbidity calculated result, and the comparator for calculating more recently
The gas turbidity between gas turbidity twice arrived is poor.If the gas turbidity absolute value of the difference is greater than preset first threshold,
Cluster driving request then is issued to server, if the gas turbidity absolute value of the difference is greater than preset second threshold, to clothes
Business device issues alarm command.
Specifically, the first threshold is less than the second threshold, presets if the gas turbidity absolute value of the difference is greater than
First threshold, then cause server and gas turbidity at each gas turbidity monitoring point resurveyed and gathers again
Class；The gas turbidity monitoring point is prompted nearby to occur if the gas turbidity absolute value of the difference is greater than preset second threshold
It is abnormal, alarm command is issued to server.
During interacting with server, the gas that the gas turbidity monitoring point is issued in response to server is turbid
Acquisition instructions are spent, the acquisition for carrying out gas turbidity is started.
Specifically, the gas turbidity acquisition instructions include between gas turbidity times of collection and gas turbidity acquisition time
Every.In response to the gas turbidity acquisition instructions, the gas turbidity monitoring point generates a counter, a timer, institute
It states counter and acquires gas turbidity for recording the number of acquisition gas turbidity, gas turbidity monitoring point described in timer driver.
After obtaining gas turbidity each time, gas turbidity value is pressed into gas turbidity queue and carries out sensibility processing, to sensibility
After the completion of processing, the gas turbidity sample vector being made of sensitive process result is obtained, and by the gas turbidity sample vector
It is transmitted to server.
The server carries out gas turbidity data automatic cluster, as shown in Figure 4, comprising:
S201. it obtains n gas turbidity and handles node PiThe gas turbidity sample vector x of transmissioniConstitute sample set.
S202. the dissimilarity between two samples is calculated, and obtains dissimilarity matrix R={ rij}n*n。
S203. classification ω is initialized.
Specifically, three classifications are initialized in the embodiment of the present invention, for initializing class in other feasible embodiments
Not without limitation.Classification number is indicated using c in embodiments of the present invention.
S204. each sample is obtained for the degree of membership of classification.
S205. each sample is obtained for the contribution degree of classification.
S206. the cluster result based on the degree of membership and contribution degree expression is exported.
Specifically, the degree of membership is indicated with u, uikIndicate sample vector xiTo classification ωkDegree of membership, the contribution degree
It is indicated with v, vkjIndicate sample vector xjTo classification ωkContribution weight.
Degree of membership is according to formula (one):It calculates, contribution degree is according to formula (two):As it can be seen that being input with sample vector, calculating is iterated according to formula (one) and formula (two),
To obtain each sample vector for the degree of membership and contribution degree of classification.Formula (one) and φ in formula (two) and β be with
The related constant of clustering precision.
The embodiment of the invention also discloses a kind of gas turbidity data automatic cluster devices, as shown in Figure 5, comprising:
Sample set obtains module, for obtaining n gas turbidity processing node PiThe gas turbidity sample vector x of transmissioni
Constitute sample set.
Dissimilarity computing module for calculating the dissimilarity between two samples, and obtains dissimilarity matrix.
Initialization module, for initializing classification.
Degree of membership computing module, for obtaining each sample for the degree of membership of classification.
Contribution degree computing module, for obtaining each sample for the contribution degree of classification.
Cluster result output module, for exporting the cluster result based on the degree of membership and contribution degree expression.
In the device of the invention embodiment with embodiment of the method be based in the same manner as inventive concept.
The embodiments of the present invention also provide a kind of storage medium, the storage medium can be used for saving for realizing implementation
The program code for needing to use in example.Optionally, in the present embodiment, above-mentioned storage medium can be located at computer network
At least one network equipment in multiple network equipments.Optionally, in the present embodiment, above-mentioned storage medium may include but not
It is limited to: USB flash disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access
Memory), the various media that can store program code such as mobile hard disk, magnetic or disk.
Specifically, Fig. 6 is a kind of server architecture schematic diagram provided in an embodiment of the present invention, and the server architecture can be with
For running gas turbidity data automatic cluster device.The server 800 can generate bigger because of configuration or performance difference
Difference, may include one or more central processing units (central processing units, CPU) 822 (for example,
One or more processors) and memory 832, the storage of one or more storage application programs 842 or data 844
Medium 830 (such as one or more mass memory units).Wherein, memory 832 and storage medium 830 can be of short duration
Storage or persistent storage.The program for being stored in storage medium 830 may include one or more modules (diagram is not shown),
Each module may include to the series of instructions operation in server.Further, central processing unit 822 can be set to
It is communicated with storage medium 830, the series of instructions operation in storage medium 830 is executed on server 800.Server 800 is also
It may include one or more power supplys 826, one or more wired or wireless network interfaces 850, one or one
The above input/output interface 858, and/or, one or more operating systems 841, such as Windows ServerTM, Mac
OS XTM, UnixTM, LinuxTM, FreeBSDTM etc..Step performed by above method embodiment can be shown based on the Fig. 6
Server architecture.
In the above embodiment of the invention, it all emphasizes particularly on different fields to the description of each embodiment, does not have in some embodiment
The part of detailed description, reference can be made to the related descriptions of other embodiments.
In several embodiments provided herein, it should be understood that disclosed terminal, it can be by another way
It realizes.Wherein, system embodiment described above is only schematical, such as the division of the unit, only a kind of
Logical function partition, there may be another division manner in actual implementation, such as multiple units or components can combine or can
To be integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Coupling, direct-coupling or communication connection can be through some interfaces, the indirect coupling or communication connection of unit or module,
It can be electrical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
It should be understood that the sequencing of the embodiments of the present invention is for illustration only, the excellent of embodiment is not represented
It is bad.
Those of ordinary skill in the art will appreciate that realizing that all or part of the steps of above-described embodiment can pass through hardware
It completes, relevant hardware can also be instructed to complete by program, the program can store in a kind of computer-readable
In storage medium, storage medium mentioned above can be read-only memory, disk or CD etc..
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (4)
1. gas turbidity data automatic clustering method, which is characterized in that the described method includes:
It obtains n gas turbidity and handles node PiThe gas turbidity sample vector x of transmissioniConstitute sample set；
The dissimilarity between two samples is calculated, and obtains dissimilarity matrix R={ rij}n*n；
Initialize classification ω；
Each sample is obtained for the degree of membership of classification；
Each sample is obtained for the contribution degree of classification；
Export the cluster result indicated based on the degree of membership and contribution degree；
The detection device of gas turbidity includes turbid by first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and third gas
Degree detector gas turbidity detection module in series and gas nephelometer calculation module, the first gas Turbidity measurement instrument,
Second gas Turbidity measurement instrument and third gas Turbidity measurement instrument pass through variation of the perception light in instrument internal transmission process
Carry out detection gas turbidity；The first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and third gas Turbidity measurement instrument
Has identical structure；It includes light source that it is internal, is additionally provided with photoelectric sensor on light source outgoing optical propagation direction；The light
The output end of electric transducer is connect with high-gain amplifier, the high-gain amplifier with for converting electrical signals to gas turbidity
Converter connection, the converter are connect with the gas turbidity computing module.
2. gas turbidity data automatic clustering method according to claim 1, it is characterised in that:
The degree of membership indicates with u, uikIndicate sample vector xiTo classification ωkDegree of membership, the contribution degree indicates with v, vkj
Indicate sample vector xjTo classification ωkContribution weight；
Degree of membership is according to formula；It calculates, contribution degree is according to formulaMeter
It calculates, φ and β are constant related with clustering precision.
3. a kind of gas turbidity data automatic cluster device characterized by comprising
Sample set obtains module, for obtaining n gas turbidity processing node PiThe gas turbidity sample vector x of transmissioniIt constitutes
Sample set；
Dissimilarity computing module for calculating the dissimilarity between two samples, and obtains dissimilarity matrix；
Initialization module, for initializing classification；
Degree of membership computing module, for obtaining each sample for the degree of membership of classification；
Contribution degree computing module, for obtaining each sample for the contribution degree of classification；
Cluster result output module, for exporting the cluster result based on the degree of membership and contribution degree expression；
The detection device of gas turbidity includes turbid by first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and third gas
Degree detector gas turbidity detection module in series and gas nephelometer calculation module, the first gas Turbidity measurement instrument,
Second gas Turbidity measurement instrument and third gas Turbidity measurement instrument pass through variation of the perception light in instrument internal transmission process
Carry out detection gas turbidity；The first gas Turbidity measurement instrument, second gas Turbidity measurement instrument and third gas Turbidity measurement instrument
Has identical structure；It includes light source that it is internal, is additionally provided with photoelectric sensor on light source outgoing optical propagation direction；The light
The output end of electric transducer is connect with high-gain amplifier, the high-gain amplifier with for converting electrical signals to gas turbidity
Converter connection, the converter are connect with the gas turbidity computing module.
4. a kind of server characterized by comprising including a kind of gas turbidity data automatic cluster as claimed in claim 3
Device.
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