An improved method for detecting moisture distribution in biomass waste

Abstract

The present invention provides an improved method for detecting the moisture distribution of biomass waste, belonging to the technical field of detecting the moisture distribution of biomass waste. Specifically: a moisture meter is used to conduct a thermal drying experiment on a biomass waste sample, the sample is heated, and real-time sampling and monitoring are performed, thereby obtaining real-time quality data of the biomass waste sample; based on the real-time quality data of the sample, a water loss curve of the biomass waste is drawn with the ratio of the remaining sample amount to the total mass of the biomass waste sample at each sampling time point as the horizontal coordinate, and the mass change of the biomass waste sample within the sampling time interval as the vertical coordinate, and the water loss curve is accurately divided; finally, the ratio of the weight loss proportion of the corresponding section to the moisture content of the sample is used as the proportion of the first three types of moisture, and the proportion of bound water is calculated by subtracting the proportion of the first three types of moisture from the moisture content. The present invention can effectively solve the problem of difficulty in distinguishing the inflection point of the water loss curve.

Description

Technical Field

[0001] The present invention relates to the technical field of biomass waste moisture distribution detection, in particular to an improved biomass waste moisture distribution detection method, and more particularly to a method for dividing different forms of moisture volatilization stages of a thermal drying method water loss curve. Background Art

[0002] Biomass waste, such as anaerobic digestion residues and municipal sludge, not only contains rich organic components and nutrients but also has a high calorific value. With proper pretreatment, it can be used for dry or semi-dry anaerobic fermentation, soil improvement, incineration for power generation, and pyrolysis to produce biochar, making it a highly promising biomass resource. Dehydration pretreatment, as a crucial component of the biomass waste resource utilization system, is crucial for effectively reducing the volume of organic waste, facilitating subsequent transportation and disposal, increasing the calorific value of incineration, and controlling leachate generation.

[0003] Currently, the commonly used dehydration and conditioning methods for organic waste, such as physical methods such as microwave, ultrasound, and hydrothermal treatment, chemical methods such as acid / alkali pretreatment, advanced oxidation, coagulation / flocculation, and biological methods such as enzymatic hydrolysis, bioleaching, and bioflocculation, are mainly achieved by destroying the microbial cell structure and extracellular polymers in biomass waste, changing the hydrophilicity of extracellular polymers, or reducing their binding strength with water, so as to promote the conversion of bound water to surface adsorbed water, capillary water, and free water. Therefore, it can be seen that understanding the existence form and composition ratio of water is very important in the study of deep dehydration, and is the basis for improving the dehydration performance of biomass waste and the efficiency of solid-liquid separation.

[0004] Methods for measuring the moisture distribution of biomass waste include the freeze-thaw expansion method based on a low-temperature threshold, differential scanning calorimetry, mechanical methods such as filtration and centrifugation, thermal drying based on a "four-stage curve," and low-field nuclear magnetic resonance (LF-NMR). The first four methods only provide a rough classification of moisture into free and bound water. Furthermore, the selection of threshold temperature and mechanical strength is highly arbitrary, and the basis for their selection remains unresolved. Thermal drying and LF-NMR provide a more detailed classification of moisture content. LF-NMR is rapid, efficient, and non-destructive, allowing for repeated testing within the shelf life of the sample. However, its use is primarily limited by its high testing cost. Compared to thermal drying and LF-NMR, thermal drying has relatively low testing efficiency, with testing times of tens of minutes per sample. Furthermore, these methods suffer from ambiguity in identifying the inflection point of the dehydration curve and the lack of a unified standard for dehydration stage classification. However, the moisture analyzer used in these methods is low-cost, compact, and space-efficient in the laboratory. Despite limitations in testing efficiency, these methods remain widely used. Therefore, it is particularly important to use other efficient and accurate methods to correct the test results of the thermal drying method in order to accurately and quickly locate the inflection point of the water loss curve and to formulate a unified standard for the stage division of the water loss curve. Summary of the Invention

[0005] To address the long-standing technical issues in existing thermal drying methods, such as difficulty identifying inflection points and the lack of a unified standard for stage division, the present invention provides an improved method for detecting the moisture distribution of biomass waste. The purpose of the present invention is to construct a set of stage division criteria for characterizing the volatilization of various types of water based on the thermal dehydration curves of biomass waste, thereby calibrating the detection results of the thermal drying method and improving the thermal drying method. This stage division standard is based on the verification and comparison of the thermal drying method test results and the LF-NMR test results of dozens of samples, as well as the induction of the shape of the dehydration curves.

[0006] The object of the present invention is to provide an improved method for detecting the moisture distribution of biomass waste, comprising the following steps:

[0007] (1) Use a moisture meter to conduct a thermal drying experiment on the biomass waste sample, heat the biomass waste sample under constant temperature conditions until the quality no longer changes, and conduct real-time sampling and monitoring to obtain real-time quality data of the biomass waste sample;

[0008] (2) Based on the real-time mass data of the biomass waste sample obtained in step (1), a water loss curve of the biomass waste is drawn with the ratio of the remaining sample amount at each sampling time point to the total mass of the biomass waste sample as the horizontal axis and the mass change of the biomass waste sample within the sampling time interval as the vertical axis;

[0009] (3) According to the water loss curve obtained in step (2), the thermal water loss is divided into free water, capillary water, surface adsorbed water, and bound water; wherein, the water loss in the constant-rate evaporation section and before is regarded as free water, and the ratio of the weight loss ratio of the sample in this section to the sample moisture content is used as the free water ratio; the water loss in the arc section between the end of the constant-rate evaporation section and the beginning of the first linear decline section is regarded as capillary water, and the ratio of the weight loss ratio of the sample in this section to the sample moisture content is used as the capillary water ratio; the water loss in the first linear decline section is regarded as surface adsorbed water, and the ratio of the weight loss ratio of the sample in this section to the sample moisture content is used as the surface adsorbed water ratio; the water loss in the second linear decline section is regarded as bound water, and the bound water ratio is calculated by subtracting the ratio of the other three types of water from the sample moisture content, thereby realizing the detection of the moisture distribution of biomass waste;

[0010] In step (1), the biomass waste sample is tested in parallel for at least three times during the thermal drying experiment; the water content is divided into categories by superimposing multiple water loss curves obtained from multiple parallel experiments in step (2), determining the inflection point based on the overall trend of the multiple curves, and thereby dividing the water loss curves into different water volatilization stages.

[0011] In some embodiments of the present invention, in step (1), the temperature of heating the biomass waste sample is 60-80°C.

[0012] In some embodiments of the present invention, in step (1), the amount of biomass waste sampled in the thermal drying experiment is 2-4 g.

[0013] In some embodiments of the present invention, in step (1), glass fiber paper is used to measure moisture in the thermal drying experiment.

[0014] In some embodiments of the present invention, in step (1), the interval time of real-time sampling and monitoring of the thermal drying experiment is 20-30 s.

[0015] The above technical solution of the present invention has the following advantages over the prior art:

[0016] The present invention divides the dehydration curve into four stages based on the varying downward trends / slopes of each segment, representing different types of water volatilization. The classification criteria are relatively clear and well-defined, and a theoretical model of the biomass waste dehydration curve is developed accordingly to modify the traditional four-stage model. The method of superimposing three dehydration curves and determining inflection points based on the overall trend facilitates faster and more accurate location of inflection points, eliminating interference from abnormal trends. This invention effectively addresses the long-standing issues of thermal drying methods, such as difficulty identifying inflection points and the lack of a unified standard for stage division. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments of the present invention in conjunction with the accompanying drawings, wherein:

[0018] Figure 1 These are the water loss curves of the original samples of four kinds of biomass waste in the examples of the present invention.

[0019] Figure 2 These are the water loss curves of the original samples of four kinds of biomass waste in the examples of the present invention.

[0020] Figure 3 1 is the correspondence between the three types of moisture contents measured by the thermal drying method and the LF-NMR method in the embodiment of the present invention.

[0021] Figure 4 The slope statistics of the representative stages of the water loss curve of the thermal drying method in the embodiment of the present invention are shown, where AD-FW refers to the free water of anaerobic digestate; MS-FW refers to the free water of municipal sludge; AD-SW refers to the surface adsorbed water of anaerobic digestate; MS-SW refers to the surface adsorbed water of municipal sludge; AD-BW refers to the bound water of anaerobic digestate; and MS-BW refers to the bound water of municipal sludge.

[0022] Figure 5 This is a conceptual diagram of the water loss curve of the biomass waste thermal drying method in an embodiment of the present invention.

[0023] Figure 6 It is the traditional four-stage theoretical curve in the prior art. DETAILED DESCRIPTION

[0024] The present invention will be further described below with reference to the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it. However, the embodiments are not intended to limit the present invention.

[0025] Example:

[0026] The biomass waste samples included eight original samples (numbered 1–8), including five types of anaerobic digestion residues from three anaerobic digestion plants A, B, and C, two types of municipal sludge from two municipal sewage plants D and E, and industrial sludge from a sludge drying and incineration plant F, as well as 15 ultrasonically pretreated samples (numbered 9–23). Detailed information about the samples is shown in Table 1 .

[0027] Table 1 Sample information

[0028]

[0029] Note: AD is anaerobic digestate, MS is municipal sludge, and IS is industrial sludge; LG, LM, BJG, HQ, BLG, and YQ are plant names, namely anaerobic digestion plant A, anaerobic digestion plant B, anaerobic digestion plant C, municipal sewage plant E, and sludge incineration plant F, respectively, as shown in the fourth column of the table; US1 to US5 are five ultrasonic pretreatment conditions, as shown in the last column of the table; the absence of US in the sample name indicates that it is the original sample without ultrasonic treatment.

[0030] The present invention relates to a method for detecting moisture distribution in biomass waste, primarily based on an improved thermal drying method. The thermal drying experiments were conducted using a German Sartorius MA37 moisture meter and glass fiber paper manufactured by the China Precision Testing Equipment Center. The LF-NMR verification test was conducted using a Suzhou Newmai Company MesoMR23-060H-I low-field nuclear magnetic resonance imaging analyzer.

[0031] Biomass waste has poor uniformity, and moisture analyzers can only load a few to tens of grams. This makes them more suitable for biomass waste samples than thermogravimetric analyzers, which only load 10 to 15 mg. To limit the detection time, the sample load was chosen between 2 and 4 g. In this example, a 5 mL pipette was used to measure 3 mL of sample, with approximately 0.5 cm of the pipette tip cut off to ensure that the sample concentration remained unchanged.

[0032] Spread the sample evenly on the aluminum foil dish of the moisture analyzer, which is covered with glass fiber paper. Glass fiber paper has excellent water absorption properties and ensures that the sample has sufficient evaporation surface for even heating, thus ensuring accurate and reproducible test results.

[0033] Taking into account factors such as detection efficiency, inflection point recognition, and the absence of organic volatilization, thermal drying experiments were conducted at a constant temperature of 70°C and 60% humidity. The moisture meter was set to automatically record the sample mass every 20 seconds until the mass stopped changing, thereby obtaining real-time quality data for the biomass waste samples.

[0034] Under the above conditions of heating temperature and sample dosage, the single sample detection time is less than 30 min.

[0035] The water loss curve of biomass waste was drawn with the ratio of the remaining sample amount to the total sample mass at each sampling time point (%) as the horizontal axis and the change in sample mass within the sampling time interval (Δm, g / 20s) as the vertical axis to characterize the water loss process and water loss rate, respectively.

[0036] Here we only show the water loss curves of 8 raw samples of biomass waste to save space, e.g. Figures 1 and 2 As shown. Taking sample 1 (AD-LG-1) as an example, the water loss curve is divided into stages, as shown Figure 1 In (a), the water loss before the end of the constant-rate evaporation section (segments A to D) is considered free water, the water loss in the arc segment between the end of the constant-rate evaporation and the beginning of the first linear decline (segment DE) is considered capillary water, the water loss in the first linear decline segment (segment EF) is considered surface adsorbed water, and the water loss in the second linear decline segment (segment FG) is considered bound water. The ratio of the weight loss percentage in the corresponding segment to the sample moisture content is then used as the proportion of the first three types of water. The bound water percentage is calculated by subtracting the proportion of the first three types of water from the moisture content.

[0037] It's important to note that the endpoint of thermal drying is not equivalent to the endpoint of bound water volatilization. Bound water, which is intracellular water and in the late stages of volatilization, is significantly affected by the significant increase in the proportion of solid matter. This severely hinders mass and heat transfer in the system, causing a rapid decrease in the rate of water volatilization and causing sample mass changes to occur over 20 seconds. Therefore, water loss in the FG section is only a portion of the bound water, and its proportion needs to be calculated based on the difference.

[0038] Three parallel tests were performed on the same sample, and the three resulting water loss curves were superimposed. The inflection point was determined based on the overall trend, allowing for quick and accurate identification of the inflection point and eliminating interference from abnormal trends. The water loss curves of other samples were divided into stages based on the aforementioned criteria, and the moisture distribution results from the thermal drying method were calculated.

[0039] At the same time, the LF-NMR method was used to obtain the transverse spin-spin relaxation time (T2) distribution of these biomass waste samples, and the proportions of three types of water: moderately mobile water, mechanically bound water, and bound water were obtained.

[0040] The test results of the two methods are shown in Table 2. Pearson correlation analysis was performed on the various moisture content ratios measured by the two methods. It was found that the bound water, capillary water and free water ratios obtained by the thermal drying method were significantly positively correlated with the bound water, mechanically bound water and moderately mobile water ratios obtained by the LF-NMR method. The corresponding relationship diagram of the three groups of moisture contents was drawn with the detection value of the thermal drying method as the horizontal axis and the detection value of the LF-NMR method as the vertical axis, and a linear fit was performed, as shown in Figure 2. Figure 3 shown.

[0041] Depend on Figure 3 From (a), we can see that the bound water content data of sample No. 10, sample No. 22 and sample No. 23 are outliers. Figure 3 The capillary water content data of sample No. 22 and sample No. 23 in (b) are outliers. In addition, the detection results of the three types of water by the two methods all showed a good linear correlation, and the goodness of fit R 2Good. We speculate that the outliers are due to LF-NMR detection bias. The outlier samples have a high moisture content, and the content of moderately mobile water is much higher than that of bound water and mechanically bound water. This may be because the small peak signal is masked, causing detection errors. Figure 3 The data points in (c) are relatively scattered, which is related to the fact that free water accounts for a larger proportion than bound water and capillary water. In addition, in deep dehydration research, water content other than free water is often given greater attention.

[0042] In addition, by Figure 3 The boxplots in Figure 2 show that the ratios of the two methods for the three moisture content groups are distributed within relatively small ranges: 0.987-1.094, 0.063-0.488, and 1.18-1.23. Statistical analysis of the thermal drying method revealed that the percentages of bound water, surface adsorbed water + capillary water, and free water ranged from 0.53% to 4.51%, 16.30% to 23.68%, and 72.82% to 82.63%, respectively. These values ​​are consistent with the generally accepted ranges of bound water (less than 10%), free water (65% to 85%), and intermediate water (10% to 25%).

[0043] The above three data all show that referring to the results of LF-NMR detection is helpful to quickly and accurately locate the inflection point of the water loss curve of the thermal drying method; more importantly, it proves that the stage division method of the water loss curve provided by the present invention is reasonable and feasible.

[0044] The shapes of the water loss curves of municipal sludge and anaerobic digestate are slightly different. The arc section of anaerobic digestate is smoother, while the arc section of sludge sample is slightly angular. Therefore, the slopes of the representative stages of the water loss curves of anaerobic digestate and sludge are calculated separately. Figure 4 It can be seen that the slopes of their constant-rate evaporation sections are approximately zero; the slopes of the straight-line sections of the anaerobic digestate water loss curve representing the volatilization of surface adsorbed water are distributed in a relatively concentrated range of 0.308~0.589, and the slopes of the straight-line sections representing the surface adsorbed water of sludge are distributed in a relatively concentrated range of 0.247~0.747; while the slopes of the straight-line sections representing the volatilization of bound water are relatively dispersed. The data in the box of anaerobic digestate, that is, the middle 50% of the data are distributed in the range of 1.496~2.328, and the middle 50% of the data of sludge are distributed in the range of 0.975~1.492. It can be approximately considered that the slopes of the two straight-line sections of the two substances do not overlap statistically.

[0045] Although industrial sludge and municipal sludge are classified into one category when performing data statistics in this embodiment, in fact, the proportion of bound water in industrial sludge is relatively high, dehydration is more difficult, and there is no stratification or solid-liquid separation when standing. These characteristics are closer to anaerobic digestate. In addition, the shape of its water loss curve is also closer to that of anaerobic digestate, that is, the arc segment representing capillary water is smoother. Therefore, the water loss curves of different types of biomass waste may be slightly different, and the slopes of the two straight line segments representing the evaporation of surface adsorbed water and bound water may also be different. However, the thermal drying water loss curves of these biomass wastes can be summarized as follows. Figure 5 The conceptual model shown:

[0046] (1) Free water volatilization stage: The water volatilization rate first increases rapidly (AB segment), then experiences a short deceleration (BC segment), and then goes through a long constant evaporation stage (CD segment). The slope of the water loss curve is approximately zero, indicating that the water volatilization in this stage is almost unaffected by solid matter; this is defined as the "constant evaporation segment".

[0047] (2) Capillary water volatilization stage: The evaporation interface gradually penetrates from the surface of the material to the interior of the material. It is a process in which the water retained in the gaps between the biological flocs overcomes the capillary force and gradually evaporates. The water loss rate gradually slows down, the slope of the water loss curve gradually increases, and the shape is approximately an arc (DE segment); it is defined as the "arc segment".

[0048] (3) Surface adsorbed water volatilization stage: The water adsorbed on the solid surface begins to volatilize, and it needs to overcome the physical forces between molecules. Affected by the solid matter, the mass transfer and heat transfer resistance of the system increases, and the evaporation flux decreases, resulting in a significant decrease in the water loss rate. The water loss curve is approximately a straight line (EF segment); this is defined as the "first linear decline segment."

[0049] (4) Bound water volatilization stage: The water bound in the microbial cells begins to volatilize. This part of water is the most difficult to volatilize, and the water loss rate drops rapidly. The water loss curve is a straight and steep line (FG segment); it is defined as the "second linear decline segment".

[0050] The traditional "four-stage curve" is as follows Figure 6As shown in the figure, each stage is defined from the perspective of evaporation flux. The first stage is a short heating stage, the second stage is a constant speed stage, the third stage is a deceleration stage, and the fourth stage is a second deceleration stage. According to the bonding relationship between water and solid particles given therein, it is believed that the first and second stages belong to the free water volatilization stage; the third stage is the capillary water volatilization stage; the fourth stage is the surface adsorbed water volatilization stage; and the bound water volatilization stage is after the Weq (equilibrium moisture, chemically bound water, internal water or intracellular water) point, that is, the volatilization of bound water is not reflected on the water loss curve. In fact, according to the test results of this embodiment, as shown in FIG. Figures 1 and 2 As shown, the capillary water volatilization stage is not a straight line segment, and the Weq point changes with adjustments to the data recording interval. Therefore, simply summarizing the water loss curve into four distinct stages lacks rationality and provides limited guidance for the precise classification of water forms. The improved conceptual model of the water loss curve for thermal drying proposed in this paper more closely reflects the actual water loss process of biomass waste, revising and supplementing the "four-stage model."

[0051] Table 2 Water distribution test results of thermal drying method and LF-NMR method in the embodiment of the present invention

[0052]

[0053] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will appreciate that other variations or modifications can be made based on the above description. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. An improved method for detecting moisture distribution of biomass waste, characterized in that: The following steps are involved: (1) Use a moisture meter to conduct a thermal drying experiment on the biomass waste sample, heat the biomass waste sample under constant temperature conditions until the quality no longer changes, and conduct real-time sampling and monitoring to obtain real-time quality data of the biomass waste sample; (2) Based on the real-time mass data of the biomass waste sample obtained in step (1), a water loss curve of the biomass waste is drawn with the ratio of the remaining sample amount at each sampling time point to the total mass of the biomass waste sample as the horizontal axis and the mass change of the biomass waste sample within the sampling time interval as the vertical axis; (3) According to the water loss curve obtained in step (2), the thermal water loss is divided into free water, capillary water, surface adsorbed water, and bound water; wherein, the water loss in the constant-rate evaporation section and before is regarded as free water, and the ratio of the weight loss ratio of the sample in this section to the sample moisture content is used as the free water ratio; the water loss in the arc section between the end of the constant-rate evaporation section and the beginning of the first linear decline section is regarded as capillary water, and the ratio of the weight loss ratio of the sample in this section to the sample moisture content is used as the capillary water ratio; the water loss in the first linear decline section is regarded as surface adsorbed water, and the ratio of the weight loss ratio of the sample in this section to the sample moisture content is used as the surface adsorbed water ratio; the water loss in the second linear decline section is regarded as bound water, and the bound water ratio is calculated by subtracting the ratio of the other three types of water from the sample moisture content, thereby realizing the detection of the moisture distribution of biomass waste; In step (1), the biomass waste sample is tested in parallel for at least three times during the thermal drying experiment; the water content is divided into categories by superimposing multiple water loss curves obtained from multiple parallel experiments in step (2), determining the inflection point based on the overall trend of the multiple curves, and thereby dividing the water loss curves into different water volatilization stages.

2. The detection method according to claim 1, characterized in that In step (1), the temperature of heating the biomass waste sample is 60-80°C.

3. The detection method according to claim 1, wherein In step (1), the amount of biomass waste sampled for the thermal drying experiment was 2-4 g.

4. The detection method according to claim 1, wherein In step (1), glass fiber paper is used for moisture determination in the thermal drying experiment.

5. The detection method according to claim 1, wherein In step (1), the interval time of real-time sampling monitoring of the thermal drying experiment is 20~30 s.

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