CN109060611B - Suspended sand mass concentration data processing method based on laser particle analyzer - Google Patents
Suspended sand mass concentration data processing method based on laser particle analyzer Download PDFInfo
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- CN109060611B CN109060611B CN201810747307.6A CN201810747307A CN109060611B CN 109060611 B CN109060611 B CN 109060611B CN 201810747307 A CN201810747307 A CN 201810747307A CN 109060611 B CN109060611 B CN 109060611B
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- 239000002245 particle Substances 0.000 title claims abstract description 43
- 239000004576 sand Substances 0.000 title claims abstract description 26
- 238000003672 processing method Methods 0.000 title claims abstract description 10
- 238000000034 method Methods 0.000 claims abstract description 19
- 239000000126 substance Substances 0.000 claims abstract description 8
- 238000005303 weighing Methods 0.000 claims abstract description 6
- 238000003908 quality control method Methods 0.000 claims abstract description 4
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 9
- 239000013535 sea water Substances 0.000 claims description 8
- 238000012545 processing Methods 0.000 claims description 7
- 238000012421 spiking Methods 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000000967 suction filtration Methods 0.000 description 1
- 239000000725 suspension Substances 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/02—Investigating particle size or size distribution
- G01N15/0205—Investigating particle size or size distribution by optical means
- G01N15/0211—Investigating a scatter or diffraction pattern
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
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Abstract
The invention relates to a suspended sand mass concentration data processing method based on a laser particle analyzer, which mainly comprises the following steps: acquiring the volume concentration of suspended particulate matters with different particle sizes at each station in an observation sea area by using a laser particle sizer; performing quality control on the obtained original data of the volume concentration of the suspended particulate matters with different particle sizes; performing linear fitting by using a least square method according to the mass concentration of the suspended sand measured by a partial site chemical weighing method and the total volume concentration of the suspended particulate matters at corresponding positions to obtain a fitting coefficient and a correlation coefficient; and fitting the total volume concentration of suspended matters of each station in the survey sea area to the mass concentration of suspended sand of each station by using a fitting relation obtained by linear fitting.
Description
Technical Field
The invention relates to the field of marine sedimentary dynamics, in particular to a suspended sand mass concentration data processing method based on a laser particle analyzer.
Background
In recent years, the marine pollution is more serious due to human activities, industrial production and the like, the mass concentration of suspended sand is an important parameter for detecting water quality, and the pollution degree of the effluent environment can be directly judged according to the concentration of the suspended sand. The process of directly sampling and filtering in site and obtaining the mass concentration of the suspended sand by using a chemical weighing method is complicated, the workload is large, and time and labor are wasted. The laser particle analyzer can obtain a high-frequency suspended particle volume concentration sequence or profile through accurate correction by utilizing a laser forward scattering technology, and the mass concentration of suspended sand obtained through fitting is more accurate after data in a temperature jump layer is removed through calculating buoyancy frequency.
Disclosure of Invention
In view of the above, the present invention provides a suspended sand mass concentration data method based on a laser particle analyzer, which aims to more accurately obtain a suspended sand mass concentration sequence or profile in an investigation sea area, and provide a higher frequency and accurate data basis for the research of marine science, and the technical scheme is as follows:
a suspended sand mass concentration data processing method based on a laser particle analyzer mainly comprises the following steps:
1) acquiring the volume concentration of suspended particulate matters with different particle sizes at each station in an observation sea area by using a laser particle sizer;
2) the quality control is carried out on the obtained original data of the volume concentration of the suspended particulate matters with different particle sizes, and the method comprises the following steps:
a. sorting all data according to water depth, eliminating data with obvious errors, and eliminating data with observed particle size of 0 more than 5;
b. performing de-spiking processing on the data based on multiples of the standard deviation;
c. carrying out moving average processing on adjacent data;
d. summing the different particle sizes processed in the steps to obtain the total volume concentration of the suspended particulate matters and taking the precision;
e. according to the temperature, salinity and pressure of each station in the observed sea area, the seawater density of the corresponding station is obtained, so that the Brent-Vesella frequency N of each station is obtained, and according to logN2>-3, determining the position of the temperature jump layer in the seawater, and eliminating the data measured by the chemical method and the data measured by the laser particle analyzer at the temperature jump layer in consideration of the response time of the laser particle analyzer;
3) performing linear fitting by using a least square method according to the mass concentration of the suspended sand measured by a partial site chemical weighing method and the total volume concentration of the suspended particulate matters at corresponding positions to obtain a fitting coefficient and a correlation coefficient;
4) and fitting the total volume concentration of suspended matters of each station in the survey sea area to the mass concentration of suspended sand of each station by using a fitting relation obtained by linear fitting.
The suspended sand mass concentration data processing method based on the laser particle analyzer accurately measures the concentration distribution of 36-grain-size particles in seawater in real time on the basis of a laser forward scattering technology, and then fits the suspended sand mass concentration. Compared with the on-site direct sampling and suction filtration, the invention has the advantages of more convenience, rapidness, time saving and labor saving; compared with acoustic observation, the invention can obtain data of different water depths in real time based on the arrangement of field instruments, has high vertical resolution, is not limited by the water depth, and does not need to consider the problems of signal attenuation and the like; compared with the conventional data processing method, the method comprehensively considers the instrument response problem and the influence of plankton at the temperature jump layer, eliminates the false data, and can accurately fit the mass concentration of the suspended sand on the site.
Drawings
FIG. 1 is a schematic diagram of a suspended sand mass concentration data processing method based on a laser particle analyzer;
FIG. 2 is a schematic diagram of a least squares principle;
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention are described in further detail below.
The embodiment of the invention introduces a suspended sand mass concentration data processing method based on a laser particle analyzer, aiming at accurately realizing the suspended sand mass concentration with high space-time resolution, and the specific implementation steps are as follows:
1. data acquisition: the laser particle size analyzer is placed and recovered at a fixed point of an investigation sea area site by using a ship-borne winch for field measurement, the volume concentration of suspended particles with 36 particle sizes is measured in real time by a laser forward scattering technology, and the sampling frequency is 1 Hz. The process of arranging the instrument ensures that the side of the arranging ship is windward and evenly put down so as to ensure the stability of the measurement of the instrument.
2. Initial processing of data: the quality control is carried out on the obtained raw data, and the process is as follows:
(21) sorting all data according to water depth, physically removing obvious error data, and removing data with more 0 (generally more than 5) particle size;
(22) and performing de-peaking processing on the data based on the multiple of the standard deviation, wherein the de-peaking principle is as follows:
where i a data sequence of a certain site, ziIs the depth of water, x, of the corresponding positioniFor raw data of the corresponding position measured by the laser granulometer, DiAnd s is the standard deviation of the data of the station corresponding to the first derivative of the water depth. So that | DiAnd l is less than or equal to lim multiplied by s, wherein lim is variable, namely, data which is lower than a certain multiple of the standard deviation s is reserved, data which is higher than the standard is deleted, and meanwhile, the data at the deleted part is supplemented by averaging similar data.
(23) Carrying out 5-element moving average processing on data between adjacent data; and summing the processed 36 types of particle sizes to obtain the total volume concentration of the suspended particulate matters and obtaining the precision.
(24) According to the temperature, salinity and pressure of each station in the observation sea area measured by the CTD, the seawater density of the corresponding station is obtained according to the formula:
the Brent-Vesella frequency (also called buoyancy frequency) of each station is obtained. In the formula c0Is the speed of sound. Rho is the density of the seawater, z is the depth of the water, and g is the acceleration of gravity.One is of a very small order and negligible. According to logN2>-3 to determine the location of the thermocline in the sea water. Considering the response time of the laser particle analyzer, in order to increase the accuracy of fitting, the data measured by the chemical method and the data measured by the laser particle analyzer at the temperature jump layer are removed。
3. Correction and fitting of data: and performing unary linear fitting on the remaining non-jump layer data and the total volume concentration data of the suspended particles at the corresponding positions observed by the laser particle sizer by using a least square method. As shown in fig. 2, let n points correspond to each other, and select a regression line y ═ ax + b to be closest to the n points, including
Wherein y isiRepresenting the mass concentration data, x, of the suspended sand measured by a chemical weighing methodiRepresenting the total volume concentration data of the suspended particles observed at the corresponding position of the laser particle analyzer,is the average of all the mass concentrations,is the average of all suspension volume concentrations. Correspond toIs xiAt a point on the regression line,the smaller the regression line, the better the fit to the scatter. Finally, a correlation coefficient R-square with the fitting coefficient a, b and the confidence coefficient of 95% is obtained, and the correlation coefficient can provide quantitative persuasion for the correlation of the fitting coefficient a and the fitting coefficient b.
4. Fitting of data: and fitting according to the fitting coefficients a and b obtained in the previous step and a formula y ═ ax + b to obtain the suspended sand mass concentration at all positions. In the formula, x is the total volume concentration data of all suspended particles measured by the laser particle analyzer, and y is the mass concentration data of all suspended sands obtained by fitting.
Claims (1)
1. A suspended sand mass concentration data processing method based on a laser particle analyzer mainly comprises the following steps:
1) acquiring the volume concentration of suspended particulate matters with different particle sizes at each station in an observation sea area by using a laser particle sizer;
2) performing quality control on the obtained original data of the volume concentration of the suspended particulate matters with different particle sizes; the method comprises the following steps:
a. sorting all data according to water depth, eliminating data with obvious errors, and eliminating data with observed particle size of 0 more than 5;
b. performing de-spiking processing on the data based on multiples of the standard deviation;
c. carrying out moving average processing on adjacent data;
d. summing the different particle sizes processed in the steps to obtain the total volume concentration of the suspended particulate matters and taking the precision;
e. according to the temperature, salinity and pressure of each station in the observed sea area, the seawater density of the corresponding station is obtained, so that the Brent-Vesella frequency N of each station is obtained, and according to logN2>-3, determining the position of the temperature jump layer in the seawater, and eliminating the data measured by the chemical weighing method and the data measured by the laser particle analyzer at the temperature jump layer in consideration of the response time of the laser particle analyzer;
3) performing linear fitting by using a least square method according to the mass concentration of the suspended sand measured by a partial site chemical weighing method and the total volume concentration of the suspended particulate matters at corresponding positions to obtain a fitting coefficient and a correlation coefficient;
4) and fitting the total volume concentration of suspended matters of each station in the survey sea area to the mass concentration of suspended sand of each station by using a fitting relation obtained by linear fitting.
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CN110057990B (en) * | 2019-03-08 | 2021-09-14 | 天津大学 | PH correction method of multi-parameter water quality profiler |
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CN101893540A (en) * | 2010-07-09 | 2010-11-24 | 青岛海洋地质研究所 | Eight neighborhood algorithm-based method for estimating scale error of suspended sediment inverse model |
CN102081033A (en) * | 2009-11-26 | 2011-06-01 | 上海海洋大学 | Suspended sand concentration calculating method based on coastal zone imager |
CN105092436A (en) * | 2015-07-31 | 2015-11-25 | 中国石油天然气股份有限公司 | Sediment particle size spectral analysis method and device |
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CN102081033A (en) * | 2009-11-26 | 2011-06-01 | 上海海洋大学 | Suspended sand concentration calculating method based on coastal zone imager |
CN101893540A (en) * | 2010-07-09 | 2010-11-24 | 青岛海洋地质研究所 | Eight neighborhood algorithm-based method for estimating scale error of suspended sediment inverse model |
CN105092436A (en) * | 2015-07-31 | 2015-11-25 | 中国石油天然气股份有限公司 | Sediment particle size spectral analysis method and device |
CN105259086A (en) * | 2015-10-29 | 2016-01-20 | 广东美的制冷设备有限公司 | Detection method and system of dust concentration |
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