Method for on-line quantitative monitoring of oil stain content in water

Abstract

The invention discloses a method for quantitatively monitoring the content of oil stains in water on line, which comprises the following steps of: recording the oxygen content under the condition of no oil stains and the oxygen content after a probe wraps a hydrophobic material to adsorb the oil stains at a set temperature, and obtaining a corresponding oxygen concentration differential according to the oxygen content; analyzing the obtained oxygen concentration differential to obtain a quantitative relation curve among the peak height signal-to-noise ratio SNR, the quantitative response time and the oil contamination amount, changing the oil contamination type at the set temperature, and obtaining the quantitative relation curve among the peak height signal-to-noise ratio SNR, the quantitative response time and the oil contamination amount under the condition of different dosages of the oil contamination according to the method; and quantitative monitoring of the oil stains in the water is realized by verifying the accuracy of the quantitative relation curve. Measurement results can be obtained on site, long-term unmanned monitoring can be realized through a remote communication interface, and automatic acquisition and transportation of data are realized.

Description

Technical Field

[0001] The invention belongs to the technical field of water body monitoring, and specifically relates to a method for online quantitative monitoring of oil pollution content in water. Background Art

[0002] With the booming global economy, human living resources are scarce. Water is the resource we depend on for survival. In recent years, the discharge of oily wastewater has seriously polluted the waters and endangered human health. Common sources of oil pollution include industrial waste oil, food manufacturing industry, textile industry, marine oil spills, oil extraction and other industries. About 600-1100 tons of oily wastewater flow into the ocean every year. Therefore, it is of great significance to quickly and accurately monitor the quantitative monitoring of oil pollution to feedback the specific situation of the oil spill area, which can detect the oil pollution as early as possible and minimize the adverse effects of oil spills on the marine environment.

[0003] In existing research, the methods for oil pollution monitoring include: gravity / centrifugal separation, electrochemical method, flotation method, salting-out method, biochemical method, coalescence filtration method, etc. Although these monitoring methods have good results, they cannot achieve online quantitative monitoring. They all require the oily wastewater to be taken out for offline measurement. Failure to monitor oil pollution in time will lead to the spread of oil pollution and contamination of waters. There are also some methods that use spectral principles to monitor oil spills, such as visible light (VIS), infrared (NIR, MIR, TIR), ultraviolet (UV), fluorescence (LIF, 3D), multi-spectral / hyper-spectral / hyper-spectral, radar (SAR, SLAR), microwave radiometer, etc. In actual applications, the monitored oil spills may be affected by many factors. Therefore, in order to further obtain more accurate quantitative oil pollution monitoring results and to further improve oil spill monitoring technology, it is necessary to develop new marine oil spill online monitoring technologies.

[0004] There are few existing studies on monitoring oil pollution based on oxygen content, while oxygen sensors are economical and portable instruments with wide applications. Since the oxygen content of hydrophobic oil-absorbing materials after absorbing oil is related to the oil content and type, it is urgent to design a method for quantitative monitoring of oil pollution in water based on the combination of hydrophobic oil-absorbing materials and oxygen sensors. Summary of the invention

[0005] In order to solve the technical problems of the existing online quantitative monitoring of oil pollution that are not timely and accurate, the present invention provides a method for online quantitative monitoring of the oil pollution content in water, which uses oxygen sensors to quantitatively monitor the oil pollution and builds a monitoring system that can monitor the changes in the oil pollution content in hydrophobic oil absorbing materials in real time, providing more convenient and online information for nearshore monitoring of marine oil spills.

[0006] To achieve the above object, the present invention is implemented by the following technical solutions:

[0007] A method for online quantitative monitoring of oil content in water, wherein the method adopts an online oil monitoring device for online monitoring, wherein the online oil monitoring device comprises a signal acquisition device, a signal transmission device, and a signal processing device, wherein the signal acquisition device transmits a signal to the signal processing device via the signal transmission device, wherein the signal acquisition device comprises an oxygen sensor and a hydrophobic oil absorbing material, wherein the hydrophobic oil absorbing material is fixed on the probe of the oxygen sensor via a sealing film; wherein:

[0008] The method for online quantitative monitoring of oil content in water includes the following steps:

[0009] S1. At a set temperature, place an oxygen sensor probe wrapped with a hydrophobic oil-absorbing material above a water surface without oil pollution, record the oxygen content in the absence of oil pollution, obtain the corresponding oxygen concentration differential through the oxygen content, and draw a graph of the oxygen content and oxygen concentration differential over time;

[0010] S2, standard deviation of background noise σd of parameter values ​​before refueling;

[0011] S3. At a set temperature, place the oxygen sensor probe wrapped with a hydrophobic oil-absorbing material in water containing oil pollution, and record the oxygen content after the probe is wrapped with a hydrophobic material and absorbs the oil pollution, and obtain the corresponding oxygen concentration differential through the oxygen content, and draw a graph of the oxygen content and oxygen concentration differential changing with time;

[0012] S4, analyzing the oxygen concentration differential obtained in step S3 to obtain a peak height H of the oxygen concentration differential, thereby calculating a peak height signal-to-noise ratio SNR;

[0013] The calculation formula of peak height signal-to-noise ratio SNR is: Where H is the peak height of the differential oxygen concentration and σd is the standard deviation of the background noise in step 1.

[0014] S5, repeating steps S2 to S4, measuring the oxygen content of the same oil with different contents online through an oxygen sensor and drawing a curve;

[0015] S6. Define the time period from the time when the oxygen sensor probe is placed in the oil to the time when the peak height signal-to-noise ratio (SNR) reaches 3 as the quantitative response time, and obtain the quantitative relationship curve between the peak height signal-to-noise ratio (SNR), the quantitative response time and the amount of oil pollution, which is specifically expressed as:

[0016] With the peak height signal-to-noise ratio SNR as the horizontal axis and the oil content as the vertical axis, it is found that the peak height signal-to-noise ratio SNR and the oil content are in direct proportion. As the peak height signal-to-noise ratio SNR increases, the oil content value increases. The linear correlation equation is expressed as:

[0017] y=a1x1-c1 (1)

[0018] Linear correlation R12>0.90 (2)

[0019] Where y is the oil content, x1 is the peak height signal-to-noise ratio SNR, a1 and c1 are the measured calibration constants;

[0020] With the quantitative response time as the horizontal axis and the ln value of the oil content as the vertical axis, it is found that the quantitative response time and the ln value of the oil content are inversely proportional. As the quantitative response time increases, the ln value of the oil content decreases. The linear correlation equation is expressed as

[0021] y=a2x2+c2 (3)

[0022] Linear correlation R22>0.90 (4)

[0023] Where y is the oil content, x2 is the quantitative response time, a2 and c2 are the measured calibration constants;

[0024] S7. At a set temperature, the type of oil pollution is changed, and a quantitative relationship curve between the peak height signal-to-noise ratio (SNR), the quantitative response time and the amount of oil pollution under different dosage conditions is obtained according to the above method;

[0025] S8. Quantitative monitoring of oil pollution in water can be achieved by verifying the accuracy of the quantitative relationship curve.

[0026] Furthermore, the hydrophobic and oil-absorbing material is porous hydrophobic and oil-absorbing fiber, hydrophobic and oil-absorbing sponge or hydrophobic and oil-absorbing carbon felt.

[0027] Furthermore, the oxygen sensor fixes the oxygen sensor probe above the oil container through a fixing device and connects it to a power source through a wire; the oxygen sensor transmits the oxygen content value to the signal processing device through a signal transmission device.

[0028] Further, the oxygen sensor includes a host, a probe, a wire and a membrane cap, wherein:

[0029] The host comprises a housing and an electronic system disposed in the housing, wherein the electronic system comprises an I / U converter and an A / D converter;

[0030] The probe comprises a cathode and an anode, wherein the cathode is composed of a platinum electrode and the anode is composed of a silver electrode;

[0031] The membrane cap includes a plastic shell and an oxygen-permeable membrane at the bottom. The membrane cap contains potassium chloride electrolyte. The membrane cap, the probe, and the potassium chloride electrolyte are combined to form an electrolytic cell. When external oxygen molecules pass through the oxygen-permeable membrane at the bottom, an oxidation-reduction reaction occurs at the probe electrode and generates current. The reaction formula is as follows:

[0032] The cathode is reduced: O2+2H2O+4e→4OH-

[0033] Anode is oxidized: 4Cl-+4Ag+-4e→4AgCl

[0034] According to the current obtained by the reaction at the probe electrode, the current is converted into a voltage through an I / U converter, and then converted through an A / D converter to convert the input voltage into an oxygen digital signal, and the oxygen digital signal is output to the signal processing device through a signal transmission device.

[0035] Furthermore, the signal processing device calculates the oxygen concentration differential according to the obtained oxygen digital signal, and plots a graph showing the change of oxygen content and oxygen concentration differential over time; the calculation formula of the oxygen concentration differential is as follows:

[0036] Derivative=-(Ot+1-Ot) / 3 (5)

[0037] The unit of oxygen concentration differential is mg / L, Ot is the oxygen content measured at a certain moment, Ot+1 is the oxygen content measured at the next moment after Ot, and 3 is the measurement interval from Ot to Ot+1, which is 3s.

[0038] Furthermore, it also includes a vibrator, which is arranged below the oil container to provide vibration for the oil container to simulate sea water fluctuations.

[0039] Furthermore, the oxygen sensor is an optical oxygen sensor that does not consume oxygen, an electrochemical oxygen-consuming oxygen sensor or a portable oxygen sensor, an electrode-based oxygen sensor or a portable oxygen sensor.

[0040] Furthermore, the oxygen sensor is an electrode-based portable oxygen sensor for online real-time monitoring of the oxygen content inside the probe wrapping material, measuring once every three seconds for continuous measurement. Furthermore, the signal transmission device can be an optical fiber cable, a USB data cable, a wireless transceiver, a microwave transmitter or a satellite.

[0041] Furthermore, the power supply is a DC regulated power supply, which is used to provide power for the oxygen sensor probe, and the output voltage is 12 V. The wire is an alligator clip wire, and the signal transmission device adopts optical fiber transmission, one end of the optical fiber is connected to the host, and the other end is connected to the USB port and transmits the signal value to the signal processing device.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0043] 1. The monitoring method of the present invention verifies the accuracy of the quantitative relationship curve through actual examples, and finds that the accuracy of the oil pollution amount obtained by inserting the signal value obtained by actual monitoring into the quantitative relationship curve reaches more than 95%, thus successfully realizing the quantitative monitoring of oil pollution in water.

[0044] 2. The monitoring method of the present invention uses an oxygen sensor to monitor the changes in the oxygen content in the hydrophobic oil-absorbing material to perform online oil pollution monitoring and quantitative analysis. It is simple, convenient, fast, and has reliable data, and is suitable for on-site fixed-point online oil pollution monitoring.

[0045] 3. The present invention can obtain measurement results on-site, and can also realize long-term unmanned monitoring and automatic data collection and transportation through a remote communication interface.

[0046] 4. The monitoring method of the present invention is less affected by external factors such as the marine environment and weather, is not easily disturbed by false targets, and can quickly and accurately monitor the presence and amount of oil spills in oil spill accidents.

[0047] 5. The present invention can be applied to oil spill accident monitoring in various types of waters, and the sensor is easy to operate and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1a It is a schematic diagram of the quantitative oil pollution online monitoring device of the present invention;

[0049] Among them, 1-oxygen sensor, 2-conductor, 3-power supply, 4-signal transmission device, 5-signal processing device, 6-fixing device, 7-oil container, 8-hydrophobic oil absorbing material, 9-vibrator;

[0050] Figure 1b for Figure 1a Schematic diagram of the oxygen sensor composition;

[0051] Figure 1c Run the flow chart for the smart device platform; Figure 2 It is the monitoring diagram of the oxygen sensor probe in the air;

[0052] Figure 3 This is an oil spill monitoring chart with a soybean oil emulsified oil pollution level of 100ppm;

[0053] Figure 4 This is the oil spill monitoring chart with the amount of petroleum ether emulsified oil pollution being 100ppm;

[0054] Figure 5 This is the oil spill monitoring chart with soybean oil emulsified oil content of 75ppm;

[0055] Figure 6 This is an oil spill monitoring chart with a soybean oil emulsified oil content of 50ppm;

[0056] Figure 7 This is an oil spill monitoring chart with a soybean oil emulsified oil content of 25ppm;

[0057] Figure 8This is an oil spill monitoring chart with a soybean oil emulsified oil content of 10ppm;

[0058] Fig. 9 This is an oil spill monitoring chart with a soybean oil emulsified oil content of 5ppm;

[0059] Fig.10 It is a linear correlation diagram between the peak height signal-to-noise ratio and the amount of oil pollution;

[0060] Fig.11 It is a linear correlation diagram between the quantitative response time and the ln value of the oil pollution amount. DETAILED DESCRIPTION

[0061] The present invention is further described in conjunction with the following examples, but the protection scope of the present invention is not limited thereto. It should be understood that the following examples are only for specific illustration and do not limit the scope of the present invention, and obvious changes and modifications made by those skilled in the art according to the present invention are also included in the scope of the present invention.

[0062] refer to Figure 1a to Figure 1c The oil pollution online monitoring device includes a signal acquisition device, a signal transmission device 4, and a signal processing device 5. The signal acquisition device transmits the signal to the signal processing device 5 through the signal transmission device 4. The signal acquisition device includes an oxygen sensor 1 and a hydrophobic oil-absorbing material 8. The hydrophobic oil-absorbing material 8 is fixed on the probe of the oxygen sensor 1 through a sealing film. The oxygen sensor 1 fixes the oxygen sensor probe above the oil container 7 through a fixing device 6 and is connected to the power supply 3 through a wire 2; the oxygen sensor 1 transmits the oxygen content value to the signal processing device 5 through the signal transmission device 4. The vibrator 9 is arranged below the oil container 7 to provide vibration for the oil container 7 to simulate seawater fluctuations. The signal transmission device adopts optical fiber transmission, one end of the optical fiber is connected to the host, and the other end is connected to the USB port and transmits the signal value to the signal processing device.

[0063] Specifically, in the following embodiments of the present invention, the oil container 7 is a 1L beaker, and the hydrophobic oil-absorbing material 8 is a hydrophobic porous C-shaped PP non-woven fabric.

[0064] The oxygen sensor 1 includes a host 11, a probe 12, a wire 13 and a membrane cap 14, wherein:

[0065] The host 11 includes a housing and an electronic system 111 disposed in the housing, wherein the electronic system 111 includes an I / U converter and an A / D converter;

[0066] The probe 12 includes a cathode and an anode, wherein the cathode is composed of a platinum electrode and the anode is composed of a silver electrode;

[0067] The membrane cap 14 includes a plastic shell and an oxygen permeable membrane 141 at the bottom. The membrane cap 14 contains potassium chloride electrolyte. The membrane cap 14, the probe 12, and the potassium chloride electrolyte are combined to form an electrolytic cell. When external oxygen molecules pass through the oxygen permeable membrane at the bottom, an oxidation-reduction reaction occurs at the probe electrode and generates current. The reaction formula is as follows:

[0068] The cathode is reduced: O2+2H2O+4e→4OH-

[0069] Anode is oxidized: 4Cl-+4Ag+-4e→4AgCl

[0070] According to the current obtained by the reaction at the probe electrode, the current is converted into a voltage through an I / U converter, and then converted through an A / D converter to convert the input voltage into an oxygen digital signal, and the oxygen digital signal is output to the signal processing device through a signal transmission device.

[0071] The signal processing device 5 calculates the oxygen concentration differential according to the obtained oxygen digital signal, and plots a graph showing the change of oxygen content and oxygen concentration differential over time; the calculation formula of the oxygen concentration differential is as follows:

[0072] Derivative=-(Ot+1-Ot) / 3 (5)

[0073] The unit of oxygen concentration differential is mg / L, Ot is the oxygen content measured at a certain moment, Ot+1 is the oxygen content measured at the next moment after Ot, and 3 is the measurement interval from Ot to Ot+1, which is 3s.

[0074] The oxygen sensor is an electrode-based portable oxygen sensor, which is used to monitor the oxygen content inside the probe wrapping material online in real time, with measurements taken every three seconds and continuously.

[0075] The power supply is a DC regulated power supply, which is used to provide power for the oxygen sensor probe, and the output voltage is 12 V. The wire is an alligator clip wire.

[0076] The signal processing device processes the obtained digital electrical signal through the intelligent management platform of the oil suction device. After receiving the digital electrical signal, the intelligent management platform of the oil suction device is first initialized, and after no signal interruption, the oxygen content signal is collected. After the collection is completed, the data processing stage is carried out to obtain the final result. The operation flow chart of the intelligent management platform of the oil suction device is shown in the attached Figure 1c The intelligent management platform of the oil suction device mainly runs the following procedures according to the obtained oxygen digital signal: 1. Real-time recording of the oxygen content monitored by the probe, 2. Calculation of the oxygen concentration differential using the oxygen content according to the formula stored in the platform, 3. Plotting the graph of the oxygen content and oxygen concentration differential over time. The above three steps are carried out simultaneously on the intelligent management platform of the oil suction device.

[0077] In an embodiment of the present invention, a hydrophobic porous C-shaped PP nonwoven fabric is obtained by the following method: in the fiber preparation process, polypropylene (PP) is used as the fiber body, dibutyl phthalate (DBP) is used as the pore-forming agent, and the mass percentage of PP is 70% and DBP is 30%. Before spinning, PP and DBP are heated to 190°C in a nitrogen atmosphere until the PP particles are completely dissolved. Then, the material is poured into a tray, cooled and formed into particles. During the spunbonding process, the molten polymer is extruded through a spinneret at a speed of 30ml min-1 at 165°C, and then air-coagulated at a speed of 700r min-1 to form fibers and achieve phase separation. The fibers are then transported to a flower roller to obtain NWFs. The original fibers are extracted with isopropanol for 8h and air-dried at 60°C for 2h to obtain porous fiber NWFs.

[0078] Example 1

[0079] At 25°C, take 800mL of deionized water in a beaker, turn on the vibrator switch, fix a 4×4cm hydrophobic porous C-shaped PP non-woven fabric on the oxygen sensor probe, place the oxygen sensor probe on the water surface, obtain the oxygen content change value in the hydrophobic porous C-shaped PP non-woven fabric through the oxygen sensor and draw a change curve, see attached Figure 2 It can be observed that when there is no oil pollution, the oxygen concentration remains in a certain range, and the oxygen concentration differential peak height does not change significantly, indicating that when there is no oil pollution, there will be no large signal fluctuations.

[0080] Example 2

[0081] At 25°C, prepare soybean oil emulsified oil, take 50ml soybean oil, 50mg surfactant Span 80 (Span 80 surfactant: soybean oil = 1g: 1L) and stir to dissolve completely. Take 800mL of deionized water and pour it into an empty beaker, add 100ppm (1ppm = 1mg / L) soybean oil emulsified oil to the beaker, turn on the vibrator switch, and make the soybean oil emulsified oil and water form a mixed emulsion. Fix a 4×4cm hydrophobic porous C-shaped PP non-woven fabric on the oxygen sensor probe, place the oxygen sensor probe on the water surface, record the signal value of oxygen content changing with time, obtain the oxygen content change value in the hydrophobic porous C-shaped PP non-woven fabric through the oxygen sensor and draw a change curve. It can be clearly observed that after adsorbing soybean oil, the oxygen concentration has a significant downward trend, the peak height is obvious, and the peak shape is good, see attached Figure 3 This indicates that when the device is wrapped with hydrophobic oil-absorbing material and comes into contact with oil, a change in the signal value will occur, which can be used for subsequent quantitative monitoring.

[0082] Example 3

[0083] Using the device of Example 2, 28g of sodium chloride (NaCl) was added to 800mL of water at 25°C to dissolve and obtain simulated seawater; 100ppm of soybean oil emulsified oil was added to a beaker, and the vibration instrument switch was turned on to form a mixed emulsion between the soybean oil emulsified oil and water. A 4×4cm hydrophobic porous C-shaped PP non-woven fabric was fixed on the oxygen sensor probe, and the oxygen sensor probe was placed on the water surface. The signal value of oxygen content changing with time was recorded and plotted into a curve. The result was the same as that of Example 2, which shows that changing the type of water body has no effect on the response of the oxygen content signal value.

[0084] Example 4

[0085] Using the device of Example 2, 14g of sodium chloride (NaCl) was added to 800mL of water at 25°C to dissolve and obtain simulated seawater of dilute concentration; 100ppm soybean oil was added to the beaker to emulsify the oil pollution, and the experiment in Example 2 was repeated. The oxygen content value was monitored online by the oxygen sensor and a curve was drawn to perform quantitative analysis of the oil pollution. The results were the same as those in Example 2, and it was found that reducing the content of sodium chloride had no effect on the experimental monitoring results. This shows that changing the type of water body has no effect on the response of the oxygen content signal value.

[0086] Example 5

[0087] Example 5 is the same as Example 2, except that the type of oil pollution is changed to petroleum ether emulsified oil pollution, and petroleum ether emulsified oil pollution (surfactant Span 80: petroleum ether = 1g: 1L) is prepared, 100ppm of petroleum ether emulsified oil pollution is added to the beaker, and the oxygen content value is monitored online by an oxygen sensor and a curve is drawn. Figure 4 It can be seen that after the hydrophobic oil-absorbing material comes into contact with petroleum ether oil, the oxygen content decreases and the oxygen concentration differential curve also changes. This indicates that after the hydrophobic oil-absorbing material wrapped in the oxygen sensor probe absorbs oil, the signal value will change, and a quantitative relationship curve can be formulated based on its variable relationship.

[0088] Example 6

[0089] Example 6 is the same as Example 2, except that the amount of soybean oil pollution is changed to 75ppm, and the oxygen content value is monitored online by an oxygen sensor and plotted into a curve to perform quantitative analysis of the oil pollution. It is found that as the amount of oil pollution decreases, the quantitative response time increases, and the peak height signal-to-noise ratio and other data decrease. See attached Figure 5 . Afterwards, the changes in the oil content in the hydrophobic oil-absorbing material can be monitored by the oxygen sensor to achieve quantitative research on oil pollution in marine oil spill accidents. This shows that the quantitative analysis of oil pollution in marine oil spill accidents can be achieved by monitoring the changes in the oxygen content in the hydrophobic oil-absorbing material by the oxygen sensor.

[0090] Example 7

[0091] The method of Example 7 is the same as that of Example 2, except that the amount of soybean oil pollution is changed to 50ppm, and the oxygen content value is monitored online by an oxygen sensor and plotted into a curve to perform quantitative analysis of the oil pollution. It is found that the amount of oil pollution is reduced, the quantitative response time is increased, and the peak height signal-to-noise ratio and other data are reduced. See attached Figure 6 Afterwards, the changes in the oil content in the hydrophobic oil-absorbing material can be monitored by oxygen sensors to achieve quantitative research on oil pollution in marine oil spill accidents.

[0092] Example 8

[0093] Example 8 is the same as Example 2, except that the amount of soybean oil pollution is changed to 25ppm, and the oxygen content value is monitored online by an oxygen sensor and plotted into a curve to perform quantitative analysis of the oil pollution. It is found that the amount of oil pollution is reduced, the quantitative response time is increased, and the peak height signal-to-noise ratio and other data are reduced. See attached Figure 7 Afterwards, the changes in the oil content in the hydrophobic oil-absorbing material can be monitored by oxygen sensors to achieve quantitative research on oil pollution in marine oil spill accidents.

[0094] Example 9

[0095] Example 9 is the same as Example 2, except that the amount of soybean oil pollution is changed to 10ppm, and the oxygen content value is monitored online by an oxygen sensor and plotted into a curve to perform quantitative analysis of the oil pollution. It is found that the amount of oil pollution is reduced, the quantitative response time is increased, and the peak height signal-to-noise ratio and other data are reduced. See attached Figure 8 Afterwards, the changes in the oil content in the hydrophobic oil-absorbing material can be monitored by oxygen sensors to achieve quantitative research on oil pollution in marine oil spill accidents.

[0096] Example 10

[0097] The method of Example 10 is the same as that of Example 2, except that the amount of oil pollution is changed to 5ppm, and the oxygen content value is monitored online by an oxygen sensor and plotted into a curve to perform quantitative analysis of the oil pollution. It is found that the amount of oil pollution is reduced, the quantitative response time is increased, and the peak height signal-to-noise ratio and other data are reduced. See attached Fig. 9 Afterwards, the changes in the oil content in the hydrophobic oil-absorbing material can be monitored by oxygen sensors to achieve quantitative research on oil pollution in marine oil spill accidents.

[0098] The quantitative analysis data of Examples 2, 6 to 10 are plotted with the peak height signal-to-noise ratio as the abscissa and the soybean oil contamination amount as the ordinate. Fig.10 It is concluded that as the peak height signal-to-noise ratio increases, the value of soybean oil contamination content also increases, and the two are in direct proportion. The linear correlation equation is:

[0099] y=8.3063x1-20.8995 (1)

[0100] Linear correlation R1 2 =0.9868 (2)

[0101] Among them, y is the oil content and x1 is the peak height signal-to-noise ratio SNR.

[0102] The quantitative analysis data of Examples 2, 6 to 10 are plotted with the quantitative response time as the horizontal axis and the ln value of the soybean oil contamination amount as the vertical axis. Fig.11 It is concluded that as the quantitative response time increases, the ln value of soybean oil pollution decreases, and the two are inversely proportional. The linear correlation equation is:

[0103] y=-0.2695x2+6.3819 (3)

[0104] Linear correlation R2 2 =0.966 (4)

[0105] Among them, y is the oil content and x2 is the quantitative response time.

[0106] The quantitative analysis monitoring data of Examples 2 and 6 to 10 were analyzed, and the results are shown in Table 1.

[0107] Table 1

[0108]

[0109]

[0110] It can be seen from Table 1 that as the soybean oil content gradually decreases from 100ppm, 75ppm, 50ppm, 25ppm, 10ppm, and 5ppm, the quantitative response time increases, which are 6s, 8s, 10s, 12s, 14s, and 18s respectively; the peak height signal-to-noise ratio also decreases, which are 15dB, 11dB, 8dB, 6dB, 4dB, and 3dB respectively.

[0111] After analyzing and processing the data of Examples 2 and 6 to 10, two quantitative relationship curves were obtained, and three different soybean oil contamination contents were re-selected to verify the accuracy of the quantitative relationship curves.

[0112] Embodiment 11

[0113] Example 11 is the same as Example 2. N-hexane is used to emulsify the oil (surfactant Span 80: n-hexane = 1 g: 1 L). The experiment of Example 2 is repeated. The oil content is measured 4 times at 90 ppm, 65 ppm, 55 ppm, and 30 ppm. The actual peak height signal-to-noise ratio and response time measured by the oxygen sensor are compared with the oil content obtained by substituting into the linear equation to verify the accuracy of the linear equation.

[0114] Four different types of quantitative analysis monitoring data of oil pollution content were selected for analysis, and the results are shown in Table 2.

[0115] Table 2

[0116]

[0117] As shown in Table 2, the accuracy of the signal value actually measured by the device and the value calculated by the linear equation is as high as over 95%. The verification shows that the peak height signal-to-noise ratio and quantitative response time obtained by the online quantitative monitoring device can characterize the oil pollution content. The online monitoring method can accurately monitor the oil spill signal at the first time and provide timely feedback on the oil pollution content.

[0118] Example 12

[0119] Example 12 In order to verify the accuracy of the quantitative working curve, n-hexane emulsified oil was prepared (surfactant Span 80: n-hexane = 1g: 1L), and 90ppm, 65ppm, and 30ppm of the prepared oil were taken respectively, dissolved in water, and the oil-water emulsion was separated by the currently common membrane separation technology to separate the n-hexane emulsified oil (the membrane separation technology used here is: Wu Zhongjie, Liu Zeyan, Xie Lianke, et al. Hydrophilic modification of polyvinylidene fluoride membrane and its emulsion separation and heavy metal adsorption application [J]. Journal of Chemical Industry, 2021, 72 (S1): 421-429) disclosed in the method). The results of the separated oil amount are shown in Table 3.

[0120] Table 3

[0121]

[0122] The credibility of the quantitative working curves of response time and oil pollution amount, peak height signal-to-noise ratio and oil pollution amount was verified by membrane technology separation method, and it was found that the online quantitative monitoring method of oil pollution content in water of the present invention is true and effective, and can provide more accurate information for offshore oil spills and nearshore monitoring of marine oil spills.

Claims

1. A method for online quantitative monitoring of oil content in water, wherein the method adopts an online oil monitoring device for online monitoring, wherein the online oil monitoring device comprises a signal acquisition device, a signal transmission device, and a signal processing device, wherein the signal acquisition device transmits a signal to the signal processing device via the signal transmission device, wherein the signal acquisition device comprises an oxygen sensor and a hydrophobic oil absorbing material, wherein the hydrophobic oil absorbing material is fixed on the probe of the oxygen sensor via a sealing film; wherein The method for online quantitative monitoring of oil content in water includes the following steps: S1. At a set temperature, place an oxygen sensor probe wrapped with a hydrophobic oil-absorbing material above a water surface without oil pollution, record the oxygen content in the absence of oil pollution, obtain the corresponding oxygen concentration differential through the oxygen content, and draw a graph of the oxygen content and oxygen concentration differential over time; S2, standard deviation of background noise σd of the parameter value before refueling; S3. At a set temperature, place the oxygen sensor probe wrapped with a hydrophobic oil-absorbing material in water containing oil pollution, and record the oxygen content after the probe is wrapped with a hydrophobic material and absorbs the oil pollution, and obtain the corresponding oxygen concentration differential through the oxygen content, and draw a graph of the oxygen content and oxygen concentration differential changing with time; S4, analyzing the oxygen concentration differential obtained in step S3 to obtain a peak height H of the oxygen concentration differential, thereby calculating a peak height signal-to-noise ratio SNR; S5, repeating steps S2 to S4, measuring the oxygen content of the same oil with different contents online through an oxygen sensor and drawing a curve; S6. Define the time period from the time when the oxygen sensor probe is placed in the oil to the time when the peak height signal-to-noise ratio (SNR) reaches 3 as the quantitative response time, and obtain the quantitative relationship curve between the peak height signal-to-noise ratio (SNR), the quantitative response time and the amount of oil pollution, which is specifically expressed as: With the peak height signal-to-noise ratio SNR as the horizontal axis and the oil content as the vertical axis, it is found that the peak height signal-to-noise ratio SNR and the oil content are in direct proportion. As the peak height signal-to-noise ratio SNR increases, the oil content value increases. The linear correlation equation is expressed as: y=a1x1-c1 (1) Linear correlation R1 2 >0.90 (2) Where y is the oil content, x1 is the peak height signal-to-noise ratio SNR, a1 and c1 are the measured calibration constants; With the quantitative response time as the horizontal axis and the ln value of the oil content as the vertical axis, it is found that the quantitative response time and the ln value of the oil content are inversely proportional. As the quantitative response time increases, the ln value of the oil content decreases. The linear correlation equation is expressed as y=a2x2+c2(3) Linear correlation R2 2 >0.90 (4) Where y is the oil content, x2 is the quantitative response time, a2 and c2 are the measured calibration constants; S7. At a set temperature, the type of oil pollution is changed, and a quantitative relationship curve between the peak height signal-to-noise ratio (SNR), the quantitative response time and the amount of oil pollution under different dosage conditions is obtained according to the above method; S8. Quantitative monitoring of oil pollution in water can be achieved by verifying the accuracy of the quantitative relationship curve.

2. The method for online quantitative monitoring of oil content in water according to claim 1, characterized in that: The hydrophobic and oil-absorbing material is porous hydrophobic and oil-absorbing fiber, hydrophobic and oil-absorbing sponge or hydrophobic and oil-absorbing carbon felt.

3. The method for online quantitative monitoring of oil content in water according to claim 1, characterized in that: The oxygen sensor is fixed on the top of the oil container by a fixing device, and is connected to the power supply through a wire; the oxygen sensor transmits the oxygen content value to the signal processing device through the signal transmission device.

4. The method for online quantitative monitoring of oil content in water according to claim 1, characterized in that: The oxygen sensor comprises a host, a probe, a wire and a membrane cap, wherein: The host comprises a housing and an electronic system disposed in the housing, wherein the electronic system comprises an I / U converter and an A / D converter; The probe comprises a cathode and an anode, wherein the cathode is composed of a platinum electrode and the anode is composed of a silver electrode; The membrane cap includes a plastic shell and an oxygen-permeable membrane at the bottom. The membrane cap contains potassium chloride electrolyte. The membrane cap, the probe, and the potassium chloride electrolyte are combined to form an electrolytic cell. When external oxygen molecules pass through the oxygen-permeable membrane at the bottom, an oxidation-reduction reaction occurs at the probe electrode and generates current. The reaction formula is as follows: The cathode is reduced: O2+2H2O+4e→4OH - Anode is oxidized: 4Cl - +4Ag+-4e→4AgCl According to the current obtained by the reaction at the probe electrode, the current is converted into a voltage through an I / U converter, and then converted through an A / D converter to convert the input voltage into an oxygen digital signal, and the oxygen digital signal is output to the signal processing device through a signal transmission device.

5. The method for online quantitative monitoring of oil content in water according to claim 1, characterized in that: The signal processing device calculates the oxygen concentration differential according to the obtained oxygen digital signal, and plots a graph showing the change of oxygen content and oxygen concentration differential over time; the calculation formula of the oxygen concentration differential is as follows: Derivative=-(O t+1- O t ) / 3 (5) The unit of oxygen concentration differential is mg / L, O t is the oxygen content measured at a certain moment, O t+1 Yes t The oxygen content measured at the next moment is 3 for O t to t+1 The measurement interval is 3s.

6. The method for online quantitative monitoring of oil content in water according to claim 3, characterized in that: It also includes a vibrator, which is arranged below the oil container to provide vibration for the oil container to simulate seawater fluctuations.

7. The method for online quantitative monitoring of oil content in water according to claim 1, characterized in that: The oxygen sensor is an optical oxygen sensor of a non-oxygen-consuming type, an electrochemical oxygen-consuming type oxygen sensor or a portable oxygen sensor, an electrode method oxygen sensor or a portable oxygen sensor.

8. The method for online quantitative monitoring of oil content in water according to claim 1, characterized in that: The signal transmission device may be a fiber optic cable, a USB data cable, a wireless transceiver, a microwave transmitter or a satellite.

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