CN108108889A - A kind of water monitoring data on-line processing method and device - Google Patents
A kind of water monitoring data on-line processing method and device Download PDFInfo
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- CN108108889A CN108108889A CN201711364017.5A CN201711364017A CN108108889A CN 108108889 A CN108108889 A CN 108108889A CN 201711364017 A CN201711364017 A CN 201711364017A CN 108108889 A CN108108889 A CN 108108889A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/148—Wavelet transforms
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2201/00—Features of devices classified in G01N21/00
- G01N2201/12—Circuits of general importance; Signal processing
- G01N2201/127—Calibration; base line adjustment; drift compensation
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
- Y02A20/152—Water filtration
Abstract
The present invention provides a kind of water monitoring data on-line processing method and device, the described method includes：Obtain the curve of spectrum of water quality to be detected, the setting standard water quality curve of spectrum is as reference, the relevant peaks distance of the water quality curve of spectrum and the standard water quality curve of spectrum to be measured is calculated using auto-correlation function, according to the relevant peaks distance and sampling interval, dynamic calibration is carried out to the curve of spectrum of water quality to be measured；And noise removal process is carried out using dual-tree complex wavelet transform, threshold denoising and dual-tree complex wavelet inverse transformation method to the curve of spectrum after dynamic calibration, filter out the interference of noise signal, the last spectral signal according to after the noise removal process, water quality parameter value is measured by spectrometer, it is achieved thereby that the spectral signal that repeatability is good can be obtained, and interference of the extraneous environmental noise to water quality detection is avoided, improves the accuracy of water quality detection.
Description
Technical field
The present invention relates to water quality safety technical field, more particularly, to a kind of water monitoring data on-line processing method
And device.
Background technology
It is exactly water quality that environmental problem, which has become one of the focal issue of social concerns, the environmental problem of people's extensive concern,
Safety problem.Water quality inspection technique is widely used in water quality monitoring and the water of drinking water, water head site, underground water and municipal wastewater
Matter safe early warning, these technologies can be mainly divided into electrochemical methods, chromatographic separation technology method, biosensor technique method and
Spectra methods etc..Wherein, the water quality inspection technique based on spectra methods is that one in current water quality inspection technique is important
Developing direction.
In spectra methods, the original spectrum signal graph that spectrum sensor obtains also needs to carry out a series of calibration behaviour
Make, can just obtain repeatability preferably spectrogram.But current spectroscopic calibration algorithm is easily subject to the shadow that environmental factor changes
It rings, stability is poor, can not obtain comparatively ideal result.On the other hand, in actual measurement process, many backgrounds can be subject to make an uproar
The interference of sound, these interference reduce the accuracy of water quality parameter detection.Therefore, only solve the problems, such as it is above-mentioned these, can just have
Effect improves the accuracy and precision of testing result, obtains preferable spectral signal figure.
The content of the invention
It is an object of the invention to provide a kind of water monitoring data on-line processing method and devices, it is therefore intended that solves existing
Some water quality testing data on-line processing methods cannot obtain the preferable spectral signal of repeatability and cannot filter out noise signal
The problem of interference.
To achieve the above object, the present invention provides a kind of water monitoring data on-line processing method, comprise the following steps：
The spectral signal of water quality to be detected is obtained, dynamic calibration is carried out to the spectral signal；
Denoising is carried out to the spectral signal after the dynamic calibration, filters out the interference of noise signal；
According to the spectral signal after the denoising, water quality parameter value is obtained.
Preferably, water monitoring data on-line processing method provided by the invention, further includes step：
Repeated acquisition presets the water quality sample data of quantity, obtains parameter value corresponding with water quality sample data and water quality
Comprehensive evaluation result；
Build water quality data parameter and the associated linear regression model (LRM) of Water Quality Evaluation result；
Using parameter value corresponding with water quality sample data and Water Quality Evaluation described in acquisition as a result, to the line
Property regression model be trained, the coefficient value of the linear regression model (LRM) is obtained, convenient for influence of the analysis parameters to water quality.
Preferably, the spectral signal for obtaining water quality to be detected carries out dynamic calibration, specific mistake to the spectral signal
Cheng Shi：
The curve of spectrum of water quality to be detected is obtained using spectrum sensor, standard spectral curves are set as reference, to institute
The curve of spectrum and the standard spectral curves for stating water quality to be detected are calculated using auto-correlation function, obtain autocorrelation calculation
As a result；
According to the autocorrelation calculation as a result, obtaining the curve of spectrum of the water quality to be detected and the standard spectral curves
The distance between relevant peaks；
According to the distance between sampling interval and the relevant peaks, curve of spectrum calibration is carried out.
Preferably, the spectral signal to after the dynamic calibration carries out denoising, filters out the interference of noise signal,
Detailed process is：
Dual-tree complex wavelet transform is carried out to the spectral signature data after the dynamic calibration, obtains Phase information coefficient；
Threshold denoising processing is carried out to the Phase information coefficient, obtains the Phase information coefficient after denoising；
Dual-tree complex wavelet inverse transformation is carried out to the Phase information coefficient after the denoising, obtains the spectral signal after denoising.
Preferably, the water quality parameter specifically includes turbidity, COD, biochemical oxygen demand (BOD), total organic carbon and total
Suspended solid particles.
The present invention also provides a kind of online processing unit of water monitoring data, including：
For obtaining the spectral signal of water quality to be detected, dynamic calibration is carried out to the spectral signal for dynamic calibration module；
Noise remove module for carrying out denoising to the spectral signal after the dynamic calibration, filters out noise signal
Interference；
Water quality parameter acquisition module, for according to the spectral signal after the denoising, obtaining water quality parameter value.
Preferably, the online processing unit of water monitoring data provided by the invention, further includes：
Sample parameter acquisition module presets the water quality sample data of quantity for repeated acquisition, obtains and water quality sample number
According to corresponding parameter value and Water Quality Evaluation result；
Model construction module, for building water quality data parameter and the associated linear regression mould of Water Quality Evaluation result
Type；
Model coefficient acquisition module, for utilizing parameter value corresponding with water quality sample data and water quality described in acquisition
Comprehensive evaluation result is trained the linear regression model (LRM), obtains the coefficient value of the linear regression model (LRM), convenient for analysis
Influence of the parameters to water quality.
Preferably, the dynamic calibration module specifically includes：
Autocorrelation calculation unit for obtaining the curve of spectrum of water quality to be detected using spectrum sensor, sets standard light
As reference, the curve of spectrum and the standard spectral curves to the water quality to be detected are carried out spectral curve using auto-correlation function
It calculates, is obtained from correlation calculation result；
Relevant peaks distance acquiring unit, for according to the autocorrelation calculation as a result, obtaining the light of the water quality to be detected
The distance between relevant peaks of spectral curve and the standard spectral curves；
Curve of spectrum alignment unit, for according to the distance between sampling interval and the relevant peaks, carrying out the curve of spectrum
Calibration.
Preferably, the noise remove module specifically includes：
Complex wavelet transform unit, for carrying out dual-tree complex wavelet transform to the spectral signature data after the dynamic calibration,
Obtain Phase information coefficient；
Phase information coefficient denoising unit, for carrying out threshold denoising processing to the Phase information coefficient, after obtaining denoising
Phase information coefficient；
Phase information inverse transformation block for carrying out dual-tree complex wavelet inverse transformation to the Phase information coefficient after the denoising, obtains
Obtain the spectral signal after denoising.
Preferably, the water quality parameter value that the water quality parameter acquisition module obtains specifically includes turbidity, COD, life
Change the value of oxygen demand, total organic carbon and total suspended solid particle.
Compared with prior art, the present invention haing the following advantages and high-lighting effect：
Water monitoring data on-line processing method provided by the present invention and device, realize to being obtained from spectrum sensor
Water quality to be detected spectral signal carry out dynamic calibration；Also, it to the curve of spectrum after dynamic calibration, carries out at denoising
Reason, filters out the interference of noise signal.The method and device obtain the spectral curve that repeatability is good, while avoid outer
The interference that boundary's environment brings water quality detection improves accuracy and the accuracy of water quality parameter detection.
Description of the drawings
It in order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention, for those of ordinary skill in the art, without creative efforts, can be with
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is a kind of flow chart of water monitoring data on-line processing method disclosed by the embodiments of the present invention；
Fig. 2 is to obtain water quality to be detected in a kind of water monitoring data on-line processing method disclosed by the embodiments of the present invention
Spectral signal carries out the spectral signal flow chart of the method for dynamic calibration；
Fig. 3 be a kind of water monitoring data on-line processing method disclosed by the embodiments of the present invention in the dynamic calibration after
Spectral signal carry out denoising, filter out the flow chart of the method for the interference of noise signal；
Fig. 4 is a kind of structure diagram of the online processing unit of water monitoring data disclosed by the embodiments of the present invention；
Fig. 5 is the knot of dynamic calibration module in a kind of online processing unit of water monitoring data disclosed by the embodiments of the present invention
Structure schematic diagram；
Fig. 6 is the knot of noise remove module in a kind of online processing unit of water monitoring data disclosed by the embodiments of the present invention
Structure schematic diagram.
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, it is right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
As shown in Figure 1, the embodiment of the invention discloses a kind of water monitoring data on-line processing method, including following step
Suddenly：
S101 obtains the spectral signal on water quality to be detected from spectrum sensor, and the spectrum of water quality to be detected is believed
Number utilize curve of spectrum dynamic calibration algorithm carry out dynamic calibration.
Wherein, the detailed process of dynamic calibration is carried out to the spectral signal of water quality to be detected as shown in Fig. 2, including：
The curve of spectrum of the water quality to be detected obtained from spectrum sensor is labeled as S by S201detect, will act as reference
Standard spectral curves are labeled as Sref, the sample point datas of wherein this two curves is one-dimension array, array length L.It utilizes
Auto-correlation function in Matlab functions is to the curve of spectrum S of the water quality to be detecteddetectWith the standard spectral curves Sref
It is calculated, obtains their autocorrelation calculation as a result, shown as the following formula：
P=AutoCorr (Sref,Sdetect)
Wherein, the autocorrelation calculation result of acquisition is also one-dimension array data.
S202, the position in autocorrelation calculation result where two maximum values are exactly the position of relevant peaks, are then utilized
The position of relevant peaks calculates the distance between the curve of spectrum of water quality to be detected and the relevant peaks of standard spectral curves Δ L.
S203 according to the distance between sampling interval and relevant peaks Δ L, carries out curve of spectrum calibration, obtains accurate light
Spectral curve.
S102 carries out the spectral signal after dynamic calibration the data de-noising processing based on dual-tree complex wavelet, filters out
The interference of noise signal improves parameter detecting accuracy.
Wherein, the specific of the data de-noising processing based on dual-tree complex wavelet is carried out to the spectral signal after dynamic calibration
Process as shown in figure 3, including：
S301, the spectral signal after dynamic calibration are one group of discrete datas, and dual-tree complex wavelet is carried out to this group of data
Conversion, i.e., using two parallel wavelet trees, that is, upper ripple tree and lower ripple tree, different scale is decomposed by this group of discrete data
Phase information coefficient Ci, i is Decomposition order, wherein i=3；This decompose has approximate translation invariance, and data redundancy is few, meter
Calculate the advantages of efficient.
S302, the Phase information coefficient C obtained to decompositioniNoise removal process, threshold value choosing are carried out using Threshold Denoising Method
It is taken asσ is the signal noise standard deviation of estimation processing, and N is signal length.For the decomposition coefficient of Phase information,
Coefficient more than the threshold value is all set to 0, and the coefficient less than the threshold value retains, and spectral signal effectively inhibits after treatment
With eliminate noise contribution, obtain the Phase information coefficient after removal noise
S303, to the Phase information coefficient after removal noiseDual-tree complex wavelet inverse transformation is carried out, after obtaining removal noise
Spectral signal Sdenoise, the interference of noise signal is efficiently solved, makes water monitoring data more accurate.
According to the spectral signal obtained after denoising, water quality parameter value is obtained by Raman spectrometer by S103, including：
Turbidity, COD, biochemical oxygen demand (BOD), the value of total organic carbon and total suspended solid particle.
S104,10 groups of water quality sample datas of repeated acquisition obtain the corresponding spectrum of sample data using spectrum sensor and believe
Number, then using S101 and S102 steps to measure the corresponding water quality parameter value of sample data, and these sample datas are detected
Obtain corresponding Water Quality Evaluation result.
S105 builds water quality data parameter and the associated linear regression model (LRM) of Water Quality Evaluation result, by measurement
Water quality data parameter is respectively defined as parameter M1、M2、M3、M4、M5, then linear regression model (LRM) be expressed as：
Y=α1M1+α2M2+α3M3+α4M4+α5M5+α6
Wherein, αi(i=1,2,3,4,5,6) is regression coefficient, and Y represents Water Quality Evaluation result.
S106 utilizes the 10 groups of water quality parameter values corresponding with water quality sample data and Water Quality Evaluation knot of acquisition
Fruit is trained the linear regression model (LRM) of structure, using least square method criterion, obtains the regression coefficient of linear regression model (LRM)
Value, convenient for influence of the analysis parameters to water quality；Because regression coefficient value illustrate measured each water quality parameter for
The degree of relevancy of Water Quality Evaluation result and weight size, if the weight of some parameter is larger, then can allow correlation
Water purification manufacturer so can be preferably instructed when water sample is filtered at this, paying close attention to the relevant filtration needs of the parameter emphatically
The amendment of parameter error model and the calibration of hardware instruments equipment.On the other hand, after getting regression coefficient, detection next time water
During matter, it is only necessary to which measuring five parameters of current water quality just can obtain current Water Quality Evaluation as a result, having provided to the user just
Profit.
Water monitoring data on-line processing method described in the present embodiment passes through the water quality light to being obtained from spectrum sensor
Spectrum signal carries out dynamic calibration, has obtained the spectrogram that repeatability is good, has improved the stability of spectroscopic calibration.Then to passing through
Spectral signal after dynamic calibration carries out denoising, can so filter out the interference that noise signal is brought, effectively avoid the external world
Influence of the environment to water quality measurement obtains more accurate water quality parameter data.
As shown in figure 4, the embodiment of the invention also discloses a kind of online processing unit of water monitoring data, including：
Dynamic calibration module 401, for obtaining the spectral signal on water quality to be detected from spectrum sensor, and to be checked
The spectral signal for surveying water quality carries out dynamic calibration using curve of spectrum dynamic calibration algorithm.
Noise remove module 402 for carrying out denoising to the spectral signal after the dynamic calibration, filters out noise letter
Number interference.
Water quality parameter acquisition module 403, for according to the spectral signal after the denoising, obtaining water quality parameter value,
It specifically includes：Turbidity, COD, biochemical oxygen demand (BOD), the value of total organic carbon and total suspended solid particle.
Sample parameter acquisition module 404 presets the water quality sample data of quantity for repeated acquisition, obtains and water quality sample
The corresponding parameter value of data and Water Quality Evaluation result.
Model construction module 405, for building water quality data parameter and Water Quality Evaluation result is associated linear returns
Return model.
Model coefficient acquisition module 406, for using obtain described in parameter value corresponding with water quality sample data and
Water Quality Evaluation obtains the coefficient value of the linear regression model (LRM), is convenient for as a result, be trained to the linear regression model (LRM)
Analyze influence of the parameters to water quality.
Further, in the present embodiment, as shown in figure 5, dynamic calibration module specifically includes：
Autocorrelation calculation unit 501 for obtaining the curve of spectrum of water quality to be detected using spectrum sensor, sets standard
The curve of spectrum as reference, the curve of spectrum and the standard spectral curves to the water quality to be detected using auto-correlation function into
Row calculates, and is obtained from correlation calculation result；
Relevant peaks distance acquiring unit 502, for according to the autocorrelation calculation as a result, obtaining the water quality to be detected
The distance between relevant peaks of the curve of spectrum and the standard spectral curves；
Curve of spectrum alignment unit 503, for according to the distance between sampling interval and the relevant peaks, it is bent to carry out spectrum
Line is calibrated.
Further, in the present embodiment, as shown in fig. 6, noise remove module specifically includes：
Complex wavelet transform unit 601, for carrying out dual-tree complex wavelet change to the spectral signature data after the dynamic calibration
It changes, obtains Phase information coefficient.
Phase information coefficient denoising unit 602, for carrying out threshold denoising processing to the Phase information coefficient, after obtaining denoising
Phase information coefficient.
Phase information inverse transformation block 603, for carrying out dual-tree complex wavelet inverse transformation to the Phase information coefficient after the denoising,
Obtain the spectral signal after denoising.
In device described in the present embodiment, dynamic calibration module can be to the water quality spectral signal that is obtained from spectrum sensor
Dynamic calibration is carried out, the spectrogram that repeatability is good has been obtained, has improved the stability of spectroscopic calibration；Noise remove module is to warp
It crosses the spectral signal after dynamic calibration and carries out denoising, can so filter out the interference that noise signal is brought, effectively avoid outer
Influence of boundary's environment to water quality measurement improves the accuracy of water quality parameter detection.
Particular embodiments described above has carried out the purpose of the present invention, technical solution and advantageous effect further in detail
It describes in detail bright, it should be understood that the above is only a specific embodiment of the present invention, is not intended to limit the invention, it is all
Within the principle of the present invention, any modification, equivalent substitution, improvement and etc. done should be included in protection scope of the present invention
Within.
Claims (10)
1. a kind of water monitoring data on-line processing method, which is characterized in that comprise the following steps：
The spectral signal of water quality to be detected is obtained, dynamic calibration is carried out to the spectral signal；
Denoising is carried out to the spectral signal after the dynamic calibration, filters out the interference of noise signal；
According to the spectral signal after the denoising, water quality parameter value is obtained.
2. a kind of water monitoring data on-line processing method as described in claim 1, which is characterized in that further include following step
Suddenly：
Repeated acquisition presets the water quality sample data of quantity, obtains parameter value corresponding with water quality sample data and water quality synthesis
Evaluation result；
Build water quality data parameter and the associated linear regression model (LRM) of Water Quality Evaluation result；
Using parameter value corresponding with water quality sample data and Water Quality Evaluation described in acquisition as a result, to described linear time
Model is returned to be trained, obtains the coefficient value of the linear regression model (LRM).
3. a kind of water monitoring data on-line processing method as described in claim 1, which is characterized in that the acquisition is to be detected
The spectral signal of water quality carries out dynamic calibration to the spectral signal, and detailed process is：
The curve of spectrum of water quality to be detected is obtained using spectrum sensor, standard spectral curves are set as reference, are treated to described
The curve of spectrum and the standard spectral curves for detecting water quality are calculated using auto-correlation function, obtain autocorrelation calculation knot
Fruit；
According to the autocorrelation calculation as a result, obtaining the curve of spectrum of the water quality to be detected and the phase of the standard spectral curves
The distance between Guan Feng；
According to the distance between sampling interval and the relevant peaks, curve of spectrum calibration is carried out.
4. a kind of water monitoring data on-line processing method as described in claim 1, which is characterized in that described to the dynamic
Spectral signal after calibration carries out denoising, filters out the interference of noise signal, detailed process is：
Dual-tree complex wavelet transform is carried out to the spectral signature data after the dynamic calibration, obtains Phase information coefficient；
Threshold denoising processing is carried out to the Phase information coefficient, obtains the Phase information coefficient after denoising；
Dual-tree complex wavelet inverse transformation is carried out to the Phase information coefficient after the denoising, obtains the spectral signal after denoising.
A kind of 5. water monitoring data on-line processing method as described in claim 1, which is characterized in that the water quality parameter tool
Body includes turbidity, COD, biochemical oxygen demand (BOD), total organic carbon and total suspended solid particle.
6. a kind of online processing unit of water monitoring data, which is characterized in that including：
For obtaining the spectral signal of water quality to be detected, dynamic calibration is carried out to the spectral signal for dynamic calibration module；
Noise remove module for carrying out denoising to the spectral signal after the dynamic calibration, filters out the dry of noise signal
It disturbs；
Water quality parameter acquisition module, for according to the spectral signal after the denoising, obtaining water quality parameter value.
7. a kind of online processing unit of water monitoring data as claimed in claim 6, which is characterized in that further include：
Sample parameter acquisition module presets the water quality sample data of quantity for repeated acquisition, obtains and water quality sample data pair
The parameter value and Water Quality Evaluation result answered；
Model construction module, for building water quality data parameter and the associated linear regression model (LRM) of Water Quality Evaluation result；
Model coefficient acquisition module, for being integrated using parameter value corresponding with water quality sample data described in acquisition and water quality
Evaluation result is trained the linear regression model (LRM), obtains the coefficient value of the linear regression model (LRM).
A kind of 8. online processing unit of water monitoring data as claimed in claim 6, which is characterized in that the dynamic calibration mould
Block specifically includes：
Autocorrelation calculation unit for obtaining the curve of spectrum of water quality to be detected using spectrum sensor, sets standard spectrum bent
As reference, the curve of spectrum and the standard spectral curves of the water quality to be detected are counted using auto-correlation function for line
It calculates, is obtained from correlation calculation result；
Relevant peaks distance acquiring unit, for according to the autocorrelation calculation as a result, the spectrum for obtaining the water quality to be detected is bent
The distance between relevant peaks of line and the standard spectral curves；
Curve of spectrum alignment unit, for according to the distance between sampling interval and the relevant peaks, carrying out curve of spectrum calibration.
A kind of 9. online processing unit of water monitoring data as claimed in claim 6, which is characterized in that the noise remove mould
Block specifically includes：
Complex wavelet transform unit for carrying out dual-tree complex wavelet transform to the spectral signature data after the dynamic calibration, obtains
Phase information coefficient；
Phase information coefficient denoising unit for carrying out threshold denoising processing to the Phase information coefficient, obtains multiple small after denoising
Wave system number；
Phase information inverse transformation block for carrying out dual-tree complex wavelet inverse transformation to the Phase information coefficient after the denoising, is gone
Spectral signal after making an uproar.
A kind of 10. online processing unit of water monitoring data as claimed in claim 6, which is characterized in that the water quality parameter
The water quality parameter value that acquisition module obtains specifically includes turbidity, COD, biochemical oxygen demand (BOD), total organic carbon and total suspension
The value of solid particle.
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| CN108872516A (en) * | 2018-07-31 | 2018-11-23 | 梧州市兴能农业科技有限公司 | A kind of water quality monitoring early warning system |
| CN109115697A (en) * | 2018-09-30 | 2019-01-01 | 杭州电子科技大学 | A kind of multi-parameter water-quality on-Line Monitor Device of aggregate optical probe |
| CN109459399A (en) * | 2018-12-26 | 2019-03-12 | 南京波思途智能科技股份有限公司 | A kind of spectral water quality COD, turbidity detection method |
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| CN115060666A (en) * | 2022-08-17 | 2022-09-16 | 北京英视睿达科技股份有限公司 | Calibration method of water quality parameter sensor and water quality parameter measuring method and device |
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| CN116842326A (en) * | 2023-08-30 | 2023-10-03 | 灌南县北陈集动物防疫检疫所 | Livestock-raising water quality monitoring system based on optical means |
| CN117349611A (en) * | 2023-12-06 | 2024-01-05 | 山东清控生态环境产业发展有限公司 | Water quality fluctuation instrument monitoring method based on big data analysis |
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