A method for detecting cellulose content in methylcellulose production wastewater

Abstract

The present invention belongs to the technical field of cellulose content detection, and specifically relates to a method for detecting cellulose content in methyl cellulose production wastewater. The method comprises the following steps: extracting a sample from the wastewater generated in the methyl cellulose production process, pre-treating the sample and evenly dividing the sample into a plurality of wastewater samples; conducting adsorption experiments on the wastewater samples at different adsorption temperatures, and determining the effective adsorption temperature by monitoring the results of the adsorption capacity and the wastewater state stability. In this way, the adsorption capacity and the wastewater state stability can be maximized at the effective adsorption temperature, which can not only reduce the influence of impurities in the wastewater on the cellulose quality, thereby ensuring that the extracted cellulose has high purity and quality, but also avoid the fluctuation interference on the adsorption efficiency, thereby improving the overall effect of the adsorption process.

Description

Technical Field

[0001] The invention belongs to the technical field of cellulose content detection, and particularly relates to a method for detecting cellulose content in methyl cellulose production wastewater. Background Art

[0002] As a water-soluble cellulose ether, methylcellulose is widely used as an ideal additive in the pharmaceutical, food and construction industries because of its excellent water solubility, film-forming, adhesive, emulsifying and thickening properties.

[0003] In the production process of methyl cellulose, wastewater is inevitably generated due to chemical reactions and material processing. The wastewater may contain incompletely converted cellulose materials. Therefore, the cellulose content of the wastewater generated during the production process is usually tested. The test results can be used to evaluate whether there is material loss or process defects in the production process, thereby helping companies improve production processes, reduce raw material losses, and improve product quality and output.

[0004] Due to the complex composition of wastewater, in addition to methylcellulose, it may also contain other organic or inorganic substances, and these impurities may interfere with the detection of cellulose. In order to avoid the interference of these complex components on the detection of methylcellulose, the commonly used method is to use a specific solvent or resin to selectively adsorb methylcellulose to achieve its enrichment. Subsequently, the adsorbed methylcellulose is eluted from the solvent and purified to achieve the purpose of accurately detecting its content.

[0005] In the process of extracting methyl cellulose from wastewater using selective adsorption technology, temperature is a crucial parameter because it affects the adsorption capacity of the adsorbent. Generally speaking, an increase in the adsorption temperature may enhance the activity of the adsorbent, thereby improving the adsorption efficiency. However, in existing adsorption operations, too much emphasis is often placed on the positive effect of the adsorption temperature on the adsorption capacity, while the effect of the adsorption temperature on the stability of the wastewater state is ignored. In fact, the increase in the adsorption temperature may destroy the original composition and structure of the wastewater, causing the wastewater state to become unstable. It can be seen that the adsorption temperature has a positive effect on the adsorption capacity, but has a negative effect on the stability of the wastewater state. Therefore, if only the effect of the adsorption temperature on the adsorption capacity is paid attention to, cellulose adsorption may be carried out when the wastewater state is unstable. On the one hand, it is easy to cause a decrease in the quality of cellulose; on the other hand, the adsorption efficiency may fluctuate greatly, thereby reducing the recovery rate of cellulose, so that the adsorption effect cannot achieve the expected goal. Summary of the invention

[0006] In view of this, the present invention aims to propose a method for detecting the cellulose content in methyl cellulose production wastewater. The effective adsorption temperature is determined by balancing the influence of the adsorption temperature on the adsorption capacity and the stability of the wastewater state, thereby realizing the optimization of the cellulose selective adsorption process in the process of detecting the cellulose content in methyl cellulose production wastewater, and effectively solving the problems mentioned in the background technology.

[0007] The purpose of the present invention can be achieved by the following technical scheme: A method for detecting the cellulose content in methylcellulose production wastewater, comprising the following steps: S1, extracting sample wastewater from the wastewater generated by methylcellulose production, and evenly dividing it into several wastewater samples after pretreatment.

[0008] S2. Conduct physical and chemical characteristic tests on each wastewater sample and select suitable adsorbents accordingly.

[0009] S3. Determine the appropriate adsorption temperature range for the adapted adsorbent, and assign an adsorption temperature to each wastewater sample accordingly.

[0010] S4. Adjust the temperature of each wastewater sample to the assigned adsorption temperature.

[0011] S5. Perform an adsorption experiment on each wastewater sample using an adapted adsorbent at the adjusted adsorption temperature, and monitor the adsorption capacity and wastewater state stability in real time.

[0012] S6. Determine the effective adsorption temperature based on the adsorption capacity detected during the adsorption process and the stability of the wastewater state.

[0013] S7. Perform a large-scale adsorption operation on the remaining wastewater using an adapted adsorbent and a determined effective adsorption temperature to adsorb cellulose in the wastewater.

[0014] S8. The adsorbent adsorbed with cellulose is eluted to recover the cellulose.

[0015] S9. Purify the eluted cellulose and test the content of the purified cellulose to determine the cellulose content in the wastewater.

[0016] In combination with all the above technical solutions, the positive effects of the present invention are as follows: the present invention extracts samples from the wastewater generated in the methyl cellulose production process, and evenly divides the samples into several wastewater samples after pretreatment, conducts adsorption experiments on the wastewater samples at different adsorption temperatures, and determines the effective adsorption temperature by monitoring the results of the adsorption capacity and the wastewater state stability. In this way, the adsorption capacity and the wastewater state stability can be maximized at the effective adsorption temperature. It can not only reduce the influence of impurities in the wastewater on the quality of cellulose, thereby ensuring that the extracted cellulose has high purity and quality, but also avoid the fluctuation interference on the adsorption efficiency, thereby improving the overall effect of the adsorption process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0018] Figure 1 It is a diagram of the steps for implementing the method of the present invention.

[0019] Figure 2 The figure is a process flow chart of methylcellulose adsorption extraction in the present invention.

[0020] Figure 3 It is a schematic diagram of the implementation steps of determining the effective adsorption temperature in the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] See also Figure 1 As shown, the present invention proposes a method for detecting the cellulose content in methyl cellulose production wastewater, comprising the following steps: S1, extracting sample wastewater from the wastewater generated by methyl cellulose production, and evenly dividing the sample wastewater into a plurality of wastewater samples after pretreatment.

[0023] It should be pointed out that by evenly dividing the sample wastewater into several wastewater samples, it can be ensured that the capacity of each wastewater sample is the same. Carrying out subsequent adsorption experiments under such conditions means that all samples have the same initial conditions at the beginning of the experiment, which makes the experimental results comparable. This can eliminate the experimental bias caused by differences in sample capacity and ensure the authenticity and reliability of the experimental results.

[0024] S2. Conduct physical and chemical characteristic tests on each wastewater sample and select suitable adsorbents accordingly.

[0025] It should be added that currently commonly used adsorbents include activated carbon, ion exchange resins, polymer adsorbents, diatomaceous earth, etc.

[0026] Applied to the above scheme, the physicochemical characteristics of the wastewater sample include pH value, metal ion concentration, organic matter content, hardness, etc. The reason for using these characteristics as physicochemical characteristics is that these characteristics have a great influence on the selection of suitable adsorbents, as follows: The pH value of the wastewater will affect the surface charge state of the adsorbent and the charge state of the target pollutant. Select a suitable adsorbent according to the pH value, such as alkaline adsorbents can be selected when the pH is acidic, and alkaline adsorbents can be selected when the pH is alkaline.

[0027] The concentration of metal ions in wastewater is also a factor to be considered when selecting adsorbents. Different adsorbents have different adsorption capacities for metal ions. For example, ion exchange resins are particularly suitable for removing heavy metal ions.

[0028] The organic content of the wastewater determines whether the adsorbent is suitable for treating this type of pollutant. High organic content may require an adsorbent with stronger adsorption capacity, such as activated carbon or polymer adsorbents.

[0029] The hardness of wastewater may affect the adsorption efficiency of the adsorbent. Wastewater with too high hardness may require the selection of an adsorbent that is not affected by hardness.

[0030] In the specific operation of the above scheme, the selection of an adapted adsorbent is implemented as follows: performing statistical difference analysis on the detection data corresponding to similar physicochemical characteristics of the physicochemical characteristics detected in each wastewater sample to identify stable physicochemical characteristics.

[0031] It should be understood that since the extracted sample wastewater is divided into several wastewater samples, the selection of suitable adsorbents based on the physical and chemical characteristics of the wastewater cannot rely solely on the physical and chemical characteristics of a single wastewater sample as the basis for selection. This is because multiple samples may have different physical and chemical characteristics. Comprehensive consideration of the physical and chemical characteristics of all samples can ensure the applicability and effectiveness of the adsorbent.

[0032] What needs to be further explained is that by performing statistical analysis on the difference of the test data of the same physical and chemical characteristics in different wastewater samples, the statistical difference can be standard deviation, coefficient of variation, range, etc. The coefficient of variation is the ratio of the standard deviation to the mean value, indicating the relative degree of variation, and the range is a statistic that measures the difference between the maximum and minimum values ​​in the data set, thereby identifying stable physical and chemical characteristics. The identified stable physical and chemical characteristics mean that these characteristics vary less in different wastewater samples, and then select the appropriate adsorbent based on the stable physical and chemical characteristics. By identifying the physical and chemical characteristics that are stable in different wastewater samples, the adsorbent selected based on these characteristics can show consistent adsorption effects in different samples, thereby improving the reliability of the adsorption effect. This helps to select an adsorbent that can work in different environments and improve the wide applicability of the adsorbent.

[0033] In the preferred operation of the above scheme, the identification of stable physical and chemical characteristics is achieved as follows: various difference statistics of the same type of physical and chemical characteristics are comprehensively calculated to obtain comprehensive difference data of various types of physical and chemical characteristics.

[0034] Specifically, the comprehensive difference data can be obtained by removing the dimension of each difference statistic of the same physical and chemical characteristics and then accumulating them. The dimension difference between different physical and chemical characteristics can be eliminated by removing the dimension, ensuring that each difference statistic is compared on the same scale, thereby avoiding the deviation caused by different dimensions. Under this scheme, the standard deviation and the difference between the maximum and minimum values ​​are both dimensional and cannot be directly accumulated. The comprehensive difference data obtained can reflect the overall degree of change of physical and chemical characteristics in different wastewater samples, thereby providing a comprehensive evaluation index.

[0035] The comprehensive difference data of various physical and chemical characteristics are compared with the configured allowable difference data, and the physical and chemical characteristics that are less than or equal to the allowable difference data are identified as stable physical and chemical characteristics.

[0036] It is important to understand that by comparing the comprehensive difference data with the pre-configured allowable difference data, it is possible to identify those physical and chemical characteristics whose variation range is within the allowable range, and to screen out truly stable physical and chemical characteristics, thereby improving the reliability of the results. This method reduces the influence of subjective judgment and makes the results more objective and credible.

[0037] The number of stable physical and chemical characteristics is counted, and adsorbents meeting the corresponding characteristics are selected based on the stable physical and chemical characteristics.

[0038] In the above operation example, it is assumed that the stable physical and chemical characteristics identified are pH value, metal ion concentration and organic matter content, wherein the adsorbent selected within the pH value range is activated carbon, the adsorbent selected at the metal ion concentration is a polymer adsorbent, and the adsorbent selected at the organic matter content is an ion exchange resin.

[0039] The adsorbents meeting various stable physical and chemical characteristics are compared to identify whether there are overlapping adsorbents. If there are overlapping adsorbents, the adsorbent is used as a compatible adsorbent. Otherwise, the adsorbents meeting various stable physical and chemical characteristics are listed as candidate adsorbents.

[0040] It should be noted that overlapping adsorbents are adsorbents that are consistent with the adsorbents under various stable physical and chemical characteristics. Obviously, in the above examples, the adsorbents that meet the pH value, metal ion concentration and organic matter content are different. Activated carbon, polymer adsorbent and ion exchange resin are all taken as candidate adsorbents.

[0041] The historical adsorption records of the candidate adsorbents are retrieved respectively, and the historical adsorption records that meet the stable physical and chemical characteristics are selected as reference adsorption records based on the physical and chemical characteristics of the wastewater recorded in the historical adsorption records.

[0042] The adsorption effect data recorded is extracted from the reference adsorption records corresponding to each candidate adsorbent, wherein the adsorption effect data may be adsorption efficiency, adsorption capacity, etc., and then the candidate adsorbent corresponding to the best adsorption effect is screened out as the matching adsorbent.

[0043] The present invention compares and overlaps adsorbents that meet stable physical and chemical characteristics in wastewater samples, and further optimizes the selection using historical adsorption records when there is no overlap. The selected compatible adsorbent is more scientific and reasonable and has higher reliability and applicability.

[0044] S3. Determine the appropriate adsorption temperature range for the adapted adsorbent, and assign an adsorption temperature to each wastewater sample accordingly.

[0045] In the manner in which the above scheme can be implemented, the suitable adsorption temperature range of the adapted adsorbent can be extracted from the instructions for use of the adapted adsorbent, which usually provide the optimal operating temperature range of the adsorbent. The purpose is to provide a temperature selection within a certain range for subsequent adsorption experiments, thereby narrowing the adsorption temperature selection range, avoiding experiments at inappropriate temperatures, and reducing invalid attempts. In addition, narrowing the temperature selection range can reduce the number of experiments and shorten the experimental cycle, thereby saving time and human resources.

[0046] In a further achievable manner, the process of assigning the adsorption temperature to each wastewater sample is as follows: statistics are performed on all wastewater samples to determine the total number of samples.

[0047] The suitable adsorption temperature range is divided into equal parts according to the number of wastewater samples to obtain the interval temperature of each range.

[0048] Starting from the lower limit temperature of the suitable adsorption temperature range, the temperature is increased in intervals to obtain several temperature nodes.

[0049] In the above implementation example, assume that there are 10 wastewater samples, the suitable adsorption temperature range is 20°C to 40°C, and 20°C to 40°C is divided into 10 equal parts, and the obtained interval temperature is 2°C, where the lower limit temperature is 20°C, and it increases every 2°C from 20°C, and the following temperature nodes are obtained: 20°C, 22°C, 24°C, 26°C, 28°C, 30°C, 32°C, 34°C, 36°C, 38°C, 40°C.

[0050] Each wastewater sample is mapped to a temperature node to obtain the adsorption temperature assigned to each wastewater sample.

[0051] S4. Adjust the temperature of each wastewater sample to the assigned adsorption temperature.

[0052] It should be added that when adjusting the temperature of wastewater samples, it is necessary to ensure that the environmental conditions of all wastewater samples are consistent except for temperature, in order to comply with the single variable principle, ensure that the only variable in the experiment is temperature, reduce the impact of other variables on the experimental results, and make the experimental results more accurate and reliable.

[0053] S5. Perform an adsorption experiment on each wastewater sample using an adapted adsorbent at the adjusted adsorption temperature, and monitor the adsorption capacity and wastewater state stability in real time.

[0054] It should be added that when using adapted adsorbents to adsorb each wastewater sample, it is indeed necessary to first weigh a certain amount of adsorbent according to the capacity of the wastewater sample to ensure that the amount of adsorbent used is sufficient to avoid incomplete adsorption caused by using too little adsorbent, thereby affecting the effect of the adsorption experiment.

[0055] In the optimization implementation of the above scheme, the adsorption capacity includes adsorption rate and adsorption capacity, wherein the adsorption rate refers to the speed at which the adsorbent adsorbs pollutants per unit time. It reflects the speed of the adsorption process. Specifically, the adsorption rate monitoring is as follows: each wastewater sample is combined with a cellulose fluorescent dye to form a labeled wastewater sample.

[0056] It should be noted that the monitoring of the adsorption rate in the present invention adopts a fluorescent labeling method. Fluorescent labeling refers to labeling the adsorbate with a fluorescent dye so that the adsorbate can generate a fluorescent signal on the surface of the adsorbent during the adsorption process. By monitoring the change of the fluorescent signal, the adsorption rate can be indirectly reflected. This method can provide real-time, visual monitoring results, and the dynamic changes in the adsorption process can be intuitively observed.

[0057] It is further important to know that when using fluorescent labeling to monitor the adsorption rate, one must first select a fluorescent dye suitable for cellulose and ensure that the labeled cellulose does not fall off or quench during the adsorption process. At the same time, the labeling efficiency must be high so that it can be clearly seen during subsequent image acquisition.

[0058] In the specific implementation of the above scheme, cellulose is a natural polysaccharide that usually does not carry fluorescent groups. This means that it is difficult to directly fluorescently label cellulose. In addition, chemical modification of cellulose may change its physical and chemical properties and affect its adsorption performance. In this case, fluorescently labeled cellulose derivatives can be used, which are easier to fluorescently label.

[0059] As another example, cellulose can be labeled with fluorescent probes, which are molecules that can bind to specific substances and emit fluorescence. For example, small molecule probes labeled with fluorescent dyes can be used, which can bind to cellulose and emit fluorescent signals.

[0060] In another example, fluorescently labeled auxiliary molecules can be used to label cellulose, which can bind to cellulose during adsorption and emit fluorescent signals. For example, fluorescently labeled proteins or other small molecules can be used, which can form complexes with cellulose and emit fluorescent signals during adsorption.

[0061] The marked wastewater sample is brought into contact with the adsorbent in a container so that the adsorbent and the adsorbate are in full contact. A high-definition imager is used to collect contact state images in real time during the contact process. A viscometer is used to synchronously detect the viscosity of the wastewater in the container to obtain the contact state images and wastewater viscosity at each collection moment.

[0062] The high-definition imager mentioned above may be a fluorescence imager, which can visually capture the fluorescence distribution state.

[0063] The above-mentioned real-time collection can record the initial contact moment as the initial adsorption moment, and then collect at set time intervals to obtain a number of collection moments.

[0064] The use of a high-definition imager in the above process can capture images during the contact process in real time and provide intuitive visual information.

[0065] In another optimized implementation of the above operation, the reason for monitoring the viscosity of the wastewater is that during the adsorption of cellulose in the methylcellulose production wastewater, the physical state of the wastewater will change, such as viscosity change, which is specifically reflected in that the cellulose in the wastewater will increase the viscosity of the wastewater, because the cellulose molecular chain is long and it is easy to form a network structure, resulting in an increase in the viscosity of the solution. When the cellulose is adsorbed by the adsorbent, the cellulose content in the wastewater decreases, and the original network structure is destroyed, resulting in a decrease in the viscosity of the wastewater. Therefore, by monitoring the changes in the viscosity of the wastewater during the adsorption process, the adsorption efficiency can be reflected to a certain extent.

[0066] In the example of viscosity monitoring, a capillary viscometer can be used to quickly monitor the viscosity of wastewater. The specific operation is to first install the capillary viscometer, ensure that the capillary is clean and unblocked, record the time required for the sample to flow through the capillary, and then use the formula The wastewater viscosity η is calculated, k represents the constant of the capillary viscometer, t represents the time required for the sample to flow through the capillary, and A represents the correction value.

[0067] The contact state image at each acquisition moment is focused on the fluorescence accumulation area, and then the boundary contour of the fluorescence accumulation area is extracted to obtain the fluorescence accumulation range.

[0068] In the above operation example, the fluorescence collection range may be a fluorescence collection area.

[0069] The fluorescence aggregation range at each collection moment is compared with the fluorescence aggregation range at the previous collection moment to calculate the fluorescence aggregation gain at each collection moment. The fluorescence aggregation gain calculation can obtain the fluorescence aggregation gain by taking the difference between the fluorescence aggregation range at each collection moment and the fluorescence aggregation range at the previous collection moment and dividing the difference by the fluorescence aggregation range at the previous collection moment. It should be noted that since the initial adsorption moment does not exist at the previous collection moment, the initial adsorption moment does not participate in the calculation of the fluorescence aggregation gain.

[0070] It is important to note that when using fluorescent labeling for adsorption monitoring, cellulose will gradually accumulate around the adsorbent as the adsorption progresses, causing the fluorescence aggregation range to continue to increase.

[0071] The fluorescence aggregation increase at each collection moment is compared with the set critical increase. For example, the critical increase is 0.2. If the fluorescence aggregation increase at a certain collection moment is less than or equal to the critical increase, it means that the fluorescence aggregation range will no longer increase. At this time, it can be considered that the adsorption process is basically completed, and the collection moment is regarded as the end of adsorption.

[0072] The first adsorption rate of the wastewater sample is calculated by comparing the fluorescence aggregation range of the marked wastewater sample and the adsorbent at the initial adsorption moment with the fluorescence aggregation range at the end of adsorption. The specific calculation method is to subtract the fluorescence aggregation range at the end of adsorption from the fluorescence aggregation range at the initial adsorption moment, and divide the difference by the time between the end of adsorption and the initial adsorption moment.

[0073] The second adsorption rate of the wastewater sample is calculated by comparing the wastewater viscosity at the initial adsorption moment of the marked wastewater sample and the wastewater viscosity at the end of the adsorption moment. The specific calculation method is to subtract the wastewater viscosity at the initial adsorption moment from the wastewater viscosity at the end of the adsorption moment, and divide the difference by the time between the end of the adsorption moment and the initial adsorption moment.

[0074] The adsorption rate of the wastewater sample is obtained by performing weighted average calculation on the first adsorption rate and the second adsorption rate of the wastewater sample.

[0075] It should be added that, when determining the weight factors of the first adsorption rate and the second adsorption rate, it is taken into account that the first adsorption rate is calculated based on fluorescence aggregation and can more directly reflect the adsorption rate, while the second adsorption efficiency is calculated based on wastewater viscosity, which is an indirect reflection. Therefore, a slightly larger weight factor is given to the first adsorption rate. By way of example, the weight factors of the first adsorption rate and the second adsorption rate are 0.6 and 0.4, respectively.

[0076] The present invention combines fluorescent labeling and dual monitoring of wastewater viscosity to perform adsorption rate analysis, which not only provides intuitive visual information on the adsorption rate, but also reflects the changes in physical state during the adsorption process through changes in viscosity, thereby more comprehensively evaluating the adsorption rate.

[0077] In further optimization implementation of the above scheme, the adsorption capacity is monitored as follows: the fluorescence aggregation range in the contact state image corresponding to the adsorption completion moment in the wastewater sample is taken as the adsorption capacity.

[0078] It is important to know that adsorption capacity refers to the maximum amount of pollutants that an adsorbent can adsorb under certain conditions. It reflects the maximum adsorption capacity of the adsorbent. The moment of adsorption completion means that the fluorescence aggregation range no longer increases. The fluorescence aggregation range at this moment reflects the maximum adsorption capacity of the adsorbent.

[0079] The present invention can comprehensively evaluate the performance of the adsorbent in wastewater treatment by comprehensively considering the adsorption rate and the adsorption capacity.

[0080] In another optimized implementation of the above scheme, the wastewater state stability is monitored in the following process: during the adsorption process of each wastewater sample, the density and surface tension of the wastewater are detected in real time to obtain the wastewater density and wastewater surface tension at each collection moment.

[0081] It is important to understand that the state of wastewater will undergo a series of changes during the adsorption process. The reason why the changes in wastewater density and surface tension are used as representations here is that the changes in these two parameters can directly or indirectly reflect the physical and chemical changes in the adsorption process. Specifically, as the adsorbent continues to adsorb pollutants in the wastewater, the solid matter content in the wastewater changes, resulting in changes in wastewater density; changes in solute concentration in the wastewater will affect the surface tension. After the adsorbent adsorbs the solutes in the wastewater, the surface tension will change accordingly. At the same time, these two parameters have high measurability and sensitivity.

[0082] The wastewater density and wastewater surface tension at the initial adsorption moment were compared with the wastewater density and wastewater surface tension at the end of adsorption to obtain the wastewater density change difference and wastewater surface tension change difference.

[0083] It should be pointed out that the above-mentioned wastewater density variation difference and wastewater surface tension variation difference are the variation differences after taking the absolute values.

[0084] The wastewater density variation difference and the wastewater surface tension variation difference are divided by the wastewater density and the wastewater surface tension at the initial adsorption time to obtain the wastewater density variation degree and the wastewater surface tension variation degree.

[0085] The wastewater density stability and wastewater surface tension stability are obtained by subtracting the wastewater density variation and wastewater surface tension variation from the value 1.

[0086] The wastewater density stability and wastewater surface tension stability of the wastewater sample are weighted averaged to obtain the wastewater state stability of the wastewater sample.

[0087] The weight factors corresponding to the wastewater density stability and wastewater surface tension stability mentioned above can be determined according to actual needs.

[0088] The present invention realizes multi-dimensional analysis of wastewater state stability by combining changes in wastewater density and changes in wastewater surface tension, which is beneficial to improving the reliability of analysis results.

[0089] S6. Determine the effective adsorption temperature based on the adsorption capacity detected during the adsorption process and the stability of the wastewater state, see Figure 3 As shown, the specific implementation is as follows: a coordinate system is constructed with the assigned adsorption temperature as the horizontal axis and the adsorption rate, adsorption capacity and wastewater state stability as the vertical axes, and the correlation curves of the adsorption rate, adsorption capacity and wastewater state stability with the adsorption temperature, adsorption rate, adsorption capacity and wastewater state stability of each wastewater sample are drawn.

[0090] Identify whether there is an intersection between the correlation curves of adsorption rate, adsorption capacity, wastewater state stability and adsorption temperature. If there is an intersection, take the adsorption temperature corresponding to the intersection as the effective adsorption temperature. If there is no intersection, extract the adsorption temperature corresponding to the maximum adsorption rate, maximum adsorption capacity and maximum wastewater state stability from the drawn correlation curves, and record them as the optimal rate adsorption temperature, optimal capacity adsorption temperature and optimal stable adsorption temperature, respectively.

[0091] It should be understood that if the three correlation curves intersect at a certain temperature, this usually means that at this temperature, a relative equilibrium state is reached between the various factors, and this temperature can be considered as the effective adsorption temperature.

[0092] Analyze whether there is a difference between the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature. If there is no difference, take the average of the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature to obtain the effective adsorption temperature. If there is a difference, extract the adsorption rate, adsorption capacity and wastewater state stability corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature from the correlation curve of adsorption rate, adsorption capacity and wastewater state stability with adsorption temperature to form the adsorption data set corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature.

[0093] In the above, the following process is used to analyze whether there is a difference between the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature: the highest temperature and the lowest temperature are extracted from the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature, and the temperature difference between the highest temperature and the lowest temperature is obtained.

[0094] The temperature difference is compared with the preset temperature difference with which there is a difference. If the temperature difference reaches the temperature difference with which there is a difference, then the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature are analyzed to be different.

[0095] The adsorption value is evaluated using the adsorption data sets corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature. The specific evaluation is as follows: the adsorption rate, adsorption capacity and wastewater state stability in the adsorption data sets corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature are introduced into the evaluation formula The adsorption values ​​corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature are obtained, where x1, x2 and x3 represent the adsorption rate, adsorption capacity and wastewater state stability, respectively. They represent the weight factors of adsorption rate, adsorption capacity and wastewater state stability respectively, and f1, f2 and f3 represent the functions corresponding to adsorption rate, adsorption capacity and wastewater state stability respectively.

[0096] In the above implementation description, the functions corresponding to the adsorption rate, adsorption capacity, and wastewater state stability can be selected according to needs. For example, a nonlinear function, such as an exponential function, can be selected. This is because in actual situations, the relationship between the adsorption rate, adsorption capacity, wastewater state stability and adsorption value may be nonlinear, which can more accurately reflect the actual situation.

[0097] The adsorption values ​​corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature are compared, and the adsorption temperature corresponding to the maximum adsorption value is extracted as the effective adsorption temperature.

[0098] When determining the effective absorption temperature according to the constructed association curve, the present invention first identifies whether the association curve has an intersection, and then determines the effective absorption temperature according to different situations, so that the determination result is more scientific and reasonable.

[0099] S7. Perform a large-scale adsorption operation on the remaining wastewater using an adapted adsorbent and a determined effective adsorption temperature to adsorb cellulose in the wastewater.

[0100] S8. The adsorbent adsorbed with cellulose is eluted to recover the cellulose.

[0101] S9. Purify the eluted cellulose and test the content of the purified cellulose to determine the cellulose content in the wastewater.

[0102] The methylcellulose adsorption extraction process mentioned above is Figure 2 shown.

[0103] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A method for detecting cellulose content in methylcellulose production wastewater, characterized in that: The steps include: S1. Extract sample wastewater from wastewater generated by methylcellulose production, and evenly divide it into several wastewater samples after pretreatment; S2. Conduct physical and chemical characteristic tests on each wastewater sample, and select suitable adsorbents; S3, determining a suitable adsorption temperature range for the adapted adsorbent, and assigning an adsorption temperature to each wastewater sample accordingly; S4, adjusting the temperature of each wastewater sample to the assigned adsorption temperature; S5. Conduct an adsorption experiment on each wastewater sample using an adapted adsorbent at the adjusted adsorption temperature, and monitor the adsorption capacity and wastewater state stability in real time; S6. determining the effective adsorption temperature based on the adsorption capacity detected during the adsorption process and the stability of the wastewater state; S7, performing a large-scale adsorption operation on the remaining wastewater using an adapted adsorbent and a determined effective adsorption temperature to adsorb cellulose in the wastewater; S8, eluting the adsorbent adsorbed with cellulose to recover the cellulose; S9. Purify the eluted cellulose and test the content of the purified cellulose to determine the cellulose content in the wastewater.

2. The method for detecting cellulose content in methylcellulose production wastewater according to claim 1, characterized in that: The selection of an adapted adsorbent is implemented as follows: Perform statistical difference analysis on the test data corresponding to the same type of physical and chemical characteristics of each wastewater sample to identify stable physical and chemical characteristics; Count the number of stable physical and chemical characteristics, and select adsorbents that meet the corresponding characteristics based on the stable physical and chemical characteristics; Compare the adsorbents that meet the various stable physical and chemical characteristics to identify whether there are overlapping adsorbents. If there are overlapping adsorbents, the adsorbent is used as a compatible adsorbent. Otherwise, the adsorbents that meet the various stable physical and chemical characteristics are listed as candidate adsorbents. Retrieving historical adsorption records of candidate adsorbents respectively, and selecting historical adsorption records that meet stable physical and chemical characteristics as reference adsorption records based on the physical and chemical characteristics of wastewater recorded in the historical adsorption records; The adsorption effect data recorded are extracted from the reference adsorption records corresponding to each candidate adsorbent, and then the candidate adsorbent corresponding to the best adsorption effect is screened out as the matching adsorbent.

3. The method for detecting cellulose content in methylcellulose production wastewater according to claim 2, characterized in that: The identification of stable physicochemical characteristics is achieved as follows: Comprehensively calculate the difference statistics of the same type of physical and chemical characteristics to obtain the comprehensive difference data of various physical and chemical characteristics; The comprehensive difference data of various physical and chemical characteristics are compared with the configured allowable difference data, and the physical and chemical characteristics that are less than or equal to the allowable difference data are identified as stable physical and chemical characteristics.

4. The method for detecting cellulose content in methylcellulose production wastewater according to claim 1, characterized in that: The process of assigning adsorption temperature to each wastewater sample is as follows: Conduct a statistical analysis of all wastewater samples to determine the total number of samples; According to the number of wastewater samples, the suitable adsorption temperature interval is equally divided to obtain the interval temperature of each interval; Starting from the lower limit temperature of the suitable adsorption temperature range, the temperature is increased in sequence according to the interval temperature to obtain several temperature nodes; Each wastewater sample is mapped to a temperature node to obtain the adsorption temperature assigned to each wastewater sample.

5. The method for detecting cellulose content in methylcellulose production wastewater according to claim 1, characterized in that: The adsorption capacity includes adsorption rate and adsorption capacity, wherein the adsorption rate is monitored as follows: combining each wastewater sample with a cellulose fluorescent dye to form a labeled wastewater sample; The marked wastewater sample is brought into contact with the adsorbent phase in a container, and a high-definition imager is used to collect a contact state image in real time during the contact process, and a viscometer is used to synchronously detect the viscosity of the wastewater in the container, so as to obtain the contact state image and wastewater viscosity at each collection time; Focus the contact state image at each acquisition moment on the fluorescence gathering area, and then extract the boundary contour of the fluorescence gathering area to obtain the fluorescence gathering range; The fluorescence aggregation range at each acquisition moment is compared with the fluorescence aggregation range at the previous acquisition moment to calculate the fluorescence aggregation increase at each acquisition moment; Compare the fluorescence aggregation increase at each collection time with the set critical increase. If there is a collection time at which the fluorescence aggregation increase is less than or equal to the critical increase, then the collection time is taken as the adsorption completion time. Compare the fluorescence aggregation range of the marked wastewater sample and the adsorbent at the initial adsorption time with the fluorescence aggregation range at the end of adsorption to calculate the first adsorption rate of the wastewater sample; Compare the wastewater viscosity at the initial adsorption moment of the marked wastewater sample and the adsorbent with the wastewater viscosity at the end of adsorption to calculate the second adsorption rate of the wastewater sample; The adsorption rate of the wastewater sample is obtained by performing weighted average calculation on the first adsorption rate and the second adsorption rate of the wastewater sample.

6. The method for detecting cellulose content in methylcellulose production wastewater according to claim 5, characterized in that: The adsorption capacity is monitored as follows: The fluorescence aggregation range in the contact state image corresponding to the completion moment of adsorption in the wastewater sample is taken as the adsorption capacity.

7. The method for detecting cellulose content in methylcellulose production wastewater according to claim 5, characterized in that: The wastewater state stability is monitored as follows: During the adsorption process of each wastewater sample, the density and surface tension of the wastewater are detected in real time to obtain the density and surface tension of the wastewater at each collection moment; The wastewater density and wastewater surface tension at the initial adsorption moment are compared with the wastewater density and wastewater surface tension at the end of adsorption to obtain the wastewater density variation difference and wastewater surface tension variation difference; Divide the wastewater density variation difference and wastewater surface tension variation difference by the wastewater density and wastewater surface tension at the initial adsorption time to obtain the wastewater density variation degree and wastewater surface tension variation degree; Subtract the wastewater density fluctuation degree and wastewater surface tension fluctuation degree from the value 1 to obtain the wastewater density stability and wastewater surface tension stability; The wastewater density stability and wastewater surface tension stability of the wastewater sample are weighted averaged to obtain the wastewater state stability of the wastewater sample.

8. The method for detecting cellulose content in methylcellulose production wastewater according to claim 1, characterized in that: The effective adsorption temperature is determined by referring to the following process: A coordinate system is constructed with the assigned adsorption temperature as the horizontal axis and the adsorption rate, adsorption capacity and wastewater state stability as the vertical axis, and a correlation curve between the adsorption rate, adsorption capacity and wastewater state stability and the adsorption temperature is drawn for the adsorption temperature, adsorption rate, adsorption capacity and wastewater state stability of each wastewater sample; Identify whether there is an intersection between the correlation curves of adsorption rate, adsorption capacity, wastewater state stability and adsorption temperature. If there is an intersection, take the adsorption temperature corresponding to the intersection as the effective adsorption temperature. If there is no intersection, extract the adsorption temperature corresponding to the maximum adsorption rate, the maximum adsorption capacity and the maximum wastewater state stability from the drawn correlation curves, and record them as the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature, respectively. Analyze whether there is a difference between the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature. If there is no difference, the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature are averaged to obtain the effective adsorption temperature. If there is a difference, the adsorption rate, adsorption capacity and wastewater state stability corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature are respectively extracted from the correlation curve of adsorption rate, adsorption capacity and wastewater state stability with adsorption temperature to form the adsorption data set corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature; Adsorption value evaluation was performed using the adsorption data sets corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature, and the optimal stable adsorption temperature; The adsorption values ​​corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature are compared, and the adsorption temperature corresponding to the maximum adsorption value is extracted as the effective adsorption temperature.

9. The method for detecting cellulose content in methylcellulose production wastewater according to claim 8, characterized in that: The process of analyzing whether there is a difference between the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature is as follows: Extracting the highest temperature and the lowest temperature from the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature, and obtaining the temperature difference between the highest temperature and the lowest temperature; The temperature difference is compared with the preset temperature difference with which there is a difference. If the temperature difference reaches the temperature difference with which there is a difference, then the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature are analyzed to be different.

10. The method for detecting cellulose content in methyl cellulose production wastewater according to claim 8, characterized in that: The adsorption value evaluation is implemented as follows: The optimal rate adsorption temperature, optimal capacity adsorption temperature and optimal stable adsorption temperature correspond to the adsorption rate, adsorption capacity and wastewater state stability in the adsorption data set and are introduced into the evaluation formula The adsorption values ​​corresponding to the optimal rate adsorption temperature, the optimal capacity adsorption temperature and the optimal stable adsorption temperature are obtained, where x1, x2 and x3 represent the adsorption rate, adsorption capacity and wastewater state stability, respectively. They represent the weight factors of adsorption rate, adsorption capacity and wastewater state stability respectively, and f1, f2 and f3 represent the functions corresponding to adsorption rate, adsorption capacity and wastewater state stability respectively.

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