An adaptive nitrogen rate regulation method for the preparation of fermented silkworm excrement biochar

Abstract

This invention belongs to the field of automation control and proposes an adaptive nitrogen rate adjustment method for the preparation of fermented silkworm excrement biochar. Specifically, the method involves: firstly, arranging a carbon and oxygen gas concentration detection device in a tubular furnace to measure the real-time concentration of carbon and oxygen compounds; then, determining a favorable competitive state based on the real-time concentration measurement; and finally, adjusting the nitrogen rate using the result of the favorable competitive state determination. Based on real-time measured tail gas data, the method assesses the decreasing degree of volatile matter decomposition and increasing degree of small molecule hydrocarbon repolymerization under high-temperature steam, effectively preventing the accumulation of volatile matter caused by repolymerization, improving the volatile matter treatment efficiency of steam activation, and ensuring that the volatile matter content of the produced fermented silkworm excrement biochar meets manufacturing requirements, thereby enhancing the microbial adhesion ability of the finished product.

Description

Technical Field

[0001] This invention belongs to the field of automation control, specifically relating to an adaptive method for adjusting the nitrogen rate in the preparation of fermented silkworm excrement biochar. Background Technology

[0002] Biochar prepared from fermented silkworm excrement is a type of biochar with a superior microbial attachment advantage. Compared to ordinary biochar, fermented silkworm excrement biochar is richer in residual bioactive substances. These bioactive substances include humic substances and small-molecule organic acids produced by microbial decomposition of cellulose during fermentation. These small-molecule organic acids provide additional carbon sources for microbial growth, thus providing more abundant growth conditions. Simultaneously, the bioactive substances also include B vitamins in fermented silkworm excrement biochar, which can significantly shorten the microbial adaptation period and increase the growth rate. However, this microbial attachment advantage is usually unstable during the preparation of fermented silkworm excrement biochar. One reason is that volatile substances with uncertain content in the fermented silkworm excrement can inhibit microbial growth. Among these volatile substances, tar is the most significant. Currently, the common solution to this problem is steam activation treatment, which promotes the decomposition of volatile substances through high-temperature steam. Furthermore, it can also form a richer porous structure, enhancing the microbial attachment ability. However, silkworm excrement contains a significant amount of hemicellulose, lignin, and protein degradation products, which easily generate volatile substances at high temperatures, leading to volatile substance redeposition. This dynamic competition between volatile substance decomposition and redeposition under high-temperature steam requires the introduction of inert nitrogen gas to mitigate the problem. On one hand, this slows down the volatile substance decomposition rate to prevent excessive decomposition and subsequent repolymerization of small-molecule volatile substances. On the other hand, it reduces the oxygen content to inhibit the repolymerization of small-molecule hydrocarbons caused by oxidative decomposition. However, in practice, nitrogen injection has limitations in its effectiveness on steam activation. The resulting fermented silkworm excrement biochar still suffers from insufficient decomposition efficiency. This is because the nitrogen injection rate is typically controlled using a stable rate increase method. This ensures that in the early stages of steam activation, low-speed nitrogen with sufficient water and oxygen facilitates thorough decomposition, while in the later stages, high-speed nitrogen prevents redeposition. Linear rate regulation inevitably overlooks the frequent occurrence of instantaneous peaks in small-molecule hydrocarbons, preventing the true realization of benign competition. This means that rate regulation intervention occurs too early, leading to a higher nitrogen flow rate that dilutes water vapor and reduces the activation atmosphere intensity, prematurely inhibiting the pyrolysis process. This premature inhibition persists until the steam activation process is complete. The mechanisms of these instantaneous peaks in small-molecule hydrocarbons mainly include two types: one is that some gaseous products are temporarily trapped in the micropores of the carbon body due to density or high humidity during the initial activation phase, and then rapidly open or connect within a certain temperature range, resulting in a concentrated release and causing a local concentration peak; the other is that during activation, tar is not completely pyrolyzed into small-molecule acids but forms more unstable hydrocarbon precursors, which are then rapidly pyrolyzed into small-molecule hydrocarbons by a new thermal peak, forming a new instantaneous peak. In summary, the lack of benign competition results in insufficient volatile matter pyrolysis efficiency, increases the chance of volatile matter accumulation that inhibits microbial growth, and affects the microbial adhesion advantage of fermented silkworm excrement biochar, leading to unstable product quality. Therefore, an adaptive nitrogen rate regulation method is urgently needed for the preparation of fermented silkworm excrement biochar. Summary of the Invention

[0003] The purpose of this invention is to propose an adaptive nitrogen rate adjustment method for the preparation of fermented silkworm excrement biochar, so as to solve one or more technical problems existing in the prior art, and at least provide a beneficial option or create conditions.

[0004] To achieve the above objectives, according to one aspect of the present invention, a method for adaptively adjusting the nitrogen rate in the preparation of fermented silkworm excrement biochar is provided, the method comprising the following steps: S100, carbon and oxygen gas concentration detection equipment is installed in the tubular furnace; S200 obtains carbon and oxygen concentration by measuring the real-time concentration of carbon and oxygen compounds using a concentration detection device. S300, based on real-time concentration measurement, determines the state of competition; S400 uses the results of benign competitive determination to regulate the nitrogen rate.

[0005] Further, in step S100, the method for arranging the carbon and oxygen gas concentration detection device in the tubular furnace is as follows: the carbon and oxygen gas concentration detection device is an NDIR infrared sensor or a GC-FID online gas chromatograph; if an NDIR infrared sensor is selected, it is arranged between the tail gas emission end of the tubular furnace and the cooling zone; if a GC-FID online gas chromatograph is selected, it is arranged in the cooling zone.

[0006] In this method, the carbon and oxygen gas concentration detection device is referred to as the concentration detection device. The carbon and oxygen gas concentration detection device is used to measure the concentration of carbon and oxygen compounds in the exhaust gas of a tubular furnace. Carbon and oxygen compounds include carbon monoxide and carbon dioxide. The carbon and oxygen gas concentration detection device measures and records data in real time.

[0007] Tubular furnaces are used for steam activation of fermented silkworm excrement biochar. The purpose is to promote the decomposition of volatile substances through high-temperature steam, and to prevent the volatile substances from hindering the adhesion of microorganisms to fermented silkworm excrement biochar during application.

[0008] Among them, NDIR infrared sensors have engineering features such as fast response speed and good repeatability, making them more suitable for industrial preparation scenarios where real-time concentration trend monitoring and control feedback are required. GC-FID, on the other hand, is often used for material trend judgment and is more suitable for research scenarios involving changes in carbon and oxygen content in pyrolysis reaction pathways.

[0009] Further, in step S200, the method for obtaining the carbon oxide concentration by measuring the real-time concentration of carbon oxides using a concentration detection device is as follows: the carbon oxides include at least one of carbon monoxide and carbon dioxide, and the concentration value of gaseous carbon oxides in the tail gas of the tubular furnace is obtained in real time using a carbon oxide concentration detection device and recorded as the carbon oxide concentration; the carbon oxide concentration monitoring frequency is 10-20 times per minute.

[0010] When both carbon monoxide and carbon dioxide are included, the sum of their concentrations is taken as the carbon-oxygen concentration.

[0011] The sampling system includes a high-temperature sampling tube and a filtration device, so the sampling process inevitably introduces a certain gas lag time, usually within 2 seconds; monitoring every 3-6 seconds is to dynamically reflect the actual reaction situation and reduce lag identification, while effectively ensuring that the data changes between sampling points have a sufficiently large chance.

[0012] The principle of carbon and oxygen concentration in this method is that the concentration of carbon monoxide and carbon dioxide released during the raw material pyrolysis process is usually expressed as the total carbon and oxygen content in the gas phase. During the high-temperature steam activation process of fermented silkworm excrement, when the pyrolysis reaction is fully carried out, the release rate of carbon and oxygen gases is stable or continuously increasing, and the carbon and oxygen concentration is maintained at a high level. However, if the nitrogen rate increases too early, resulting in a decrease in the partial pressure of water vapor or dilution of the pyrolysis atmosphere, the activation reaction intensity decreases and the pyrolysis process is inhibited. At that time, the chance of the instantaneous peak of small molecule hydrocarbons is significantly reduced. Therefore, it is necessary to abstract a characteristic quantity reflecting the fit between the current nitrogen input rate and the actual pyrolysis reaction process through the change of carbon oxide content, which is the basis for competitive determination.

[0013] Further, in step S300, the method for determining the benign competitive state based on the real-time concentration measurement is as follows: the time point of concentration measurement is recorded as the measurement point; a time period is set as the backtesting period Tept, Tept∈[5,10] minutes; the difference between the carbon and oxygen concentrations of any measurement point and its previous measurement point is recorded as the instantaneous concentration difference; wherein the instantaneous concentration difference of the first measurement point is ignored.

[0014] If the instantaneous concentration difference at any measurement point is less than 0 and is less than the average of the instantaneous concentration differences in the sub-test period, then the good state competition of that measurement point is judged as a bad state; otherwise, the good state competition is judged as a good state. Let the instantaneous concentration difference of a measurement point being greater than that of its predecessor be the first good state condition. The proportion of measurement points that meet the first good state condition in the corresponding test period of any measurement point is the good state base value. The difference rate between any measurement point and the good state base value of its predecessor is the base value deviation rate. If the base value deviation rate in the test period is not less than 0.25, then the measurement point is judged to meet the second good state condition. The second benign condition uses the increase in the concentration transient at the current measuring point compared to the concentration transient in the historical sequence as the criterion. It is used to determine whether a measuring point is in a continuous cracking enhancement trend in its reverse time direction, thereby reflecting the matching of the current nitrogen input rate with the cracking process and demonstrating the dynamic continuity and trend stability of the reaction process. When the second benign condition is met, it indicates that the current carbon and oxygen concentration fluctuation amplitude has a clear upward trend relative to the history. The larger the base value offset rate, the faster the fluctuation enhancement rate. The more significant the trend, the more helpful it is to identify the highly compatible range between the nitrogen rate and the cracking process. It is a benign condition determination mechanism with trend-driven characteristics in the carbon and oxygen concentration change sequence.

[0015] The ratio of the instantaneous concentration difference to the carbon and oxygen concentration is the carbon and oxygen volatility, and the average carbon and oxygen volatility during the backtesting period is the carbon and oxygen volatility factor. The carbon-oxygen fluctuation factor, calculated by averaging the ratio of the instantaneous concentration difference at each measuring point to the corresponding carbon-oxygen concentration within a certain time window, reflects the relative intensity and stability of carbon-oxygen concentration fluctuations during the pyrolysis process. This factor eliminates the influence of absolute concentration, allowing it to more objectively reflect the relative trend of concentration fluctuations and embody the dynamic consistency of reactivity. A lower carbon-oxygen fluctuation factor indicates relatively stable concentration changes during that period, reflecting a stable reaction process without drastic disturbances; while a higher fluctuation factor indicates significant fluctuations in the reaction state, possibly accompanied by instability or a turning point in reactivity. The carbon-oxygen fluctuation factor can effectively assist in determining the benign competitive nature of the system.

[0016] The empirical fluctuation factor is calculated based on the good state determination. If the carbon-oxygen fluctuation factor during the backtesting period is less than the empirical fluctuation factor, the measurement point is determined to meet the third good state condition. The process of calculating the empirical fluctuation factor based on the good state determination is as follows: the preset empirical value is k1, and k1 is defaulted to 1 / 4 of the number of measurement points during the backtesting period. All measurement points determined to be good state in the first k1 measurement points form a fluctuation reference sequence. The carbon-oxygen fluctuation factor of the fluctuation reference sequence is recorded as the empirical fluctuation factor. If the number of measurement points in the first k1 measurement points that are in good state is less than 2, the measurement points determined to be in good state are adopted in the reverse time direction until the number of measurement points in good state in the fluctuation reference sequence is greater than or equal to 2. If the current measuring point satisfies the first good-state condition, the second good-state condition, and the third good-state condition, then the good-state competition of the measuring point is determined to be a good state; otherwise, it is a bad state. Since the determination of the benign state at each measuring point requires extraction of the concentration transient characteristics during the backtesting period, it can effectively quantify and identify the dynamic adaptability of the nitrogen rate to the pyrolysis reaction process, thereby effectively reducing the risk of premature rate regulation intervention, higher nitrogen flow rates diluting water vapor, and reducing the intensity of the activation atmosphere. However, current concentration trend analysis methods still have constraints in initial measuring point setting, trend slope quantification, and reference fluctuation construction. Especially in the early stage of the reaction or when historical window samples are insufficient, the initialization of the carbon-oxygen fluctuation factor is easily unstable, leading to amplified errors in benign state determination. This causes the system regulation feedback to deviate from the actual active state, making the problem more prominent. However, existing technologies cannot effectively compensate for the misjudgment caused by the lack of trend determination. To eliminate this influence, this invention proposes a better solution as follows: Furthermore, in step S300, the method for determining benign competition based on real-time concentration measurements is as follows: The time point at which the concentration was measured is recorded as the measurement point; a time period is defined as the retest period Tept, where Tept∈[10,20] minutes; During the backtesting period, the carbon and oxygen concentrations at each measuring point constituted a concentration sequence CO.Ls; In the CO.Ls sequence, the difference between the carbon and oxygen concentrations at any measurement point and the previous measurement point is recorded as the first instantaneous difference. The first instantaneous difference at the end point is the difference between the maximum and minimum carbon and oxygen concentrations in the corresponding CO.Ls sequence. The end point refers to the measuring point that is furthest from the current measuring point in time.

[0017] Calculate the sum of the average value and standard deviation of the first instantaneous difference of all measuring points in the reverse time direction for any measuring point, and record it as the concentration step value of that measuring point; if the first instantaneous difference of any measuring point is greater than its concentration step value, then the measuring point is marked as a change point, otherwise it is marked as a non-change point; The absolute value of the difference between the first instantaneous difference of any measuring point and the first instantaneous difference of the previous measuring point is denoted as the second instantaneous difference ILoc; For non-mutation points, if the second transient difference of any non-mutation point is less than the lower quartile, then the benign state competition of that non-mutation point is determined to be a benign state; otherwise, it is a dominant state. Here, the lower quartile is obtained by only counting the set of second transient differences of non-mutation points. The second transient difference is used to reflect the local stability of the carbon and oxygen concentration change trend. Its formation principle is equivalent to the absolute value of the second difference of the carbon and oxygen concentration, reflecting the strength of the trend reversal of the concentration change. The smaller the value, the more consistent the current concentration change trend is with the previous stage, and the more stable the system operation is. If the pyrolysis reaction of fermented silkworm excrement under high-temperature steam is stable, the carbon and oxygen concentration change curve over time should show an approximately linear increase or a slow increasing trend, and its second difference should be close to zero. However, if there is a disturbance in nitrogen input, a fluctuation in vapor pressure, or an interruption in the pyrolysis reaction, it is easy to cause a sudden change in the concentration trend, at which time the second transient difference increases significantly. Therefore, using the second transient difference as a criterion for determining the benign competitive state of non-abrupt point can effectively identify whether the carbon and oxygen release process is in a stable reaction state.

[0018] The concentration offset is calculated using the first instantaneous difference. The method for obtaining the concentration offset is as follows: in the CO.Ls sequence corresponding to any measurement point, calculate the difference between the first instantaneous error and the standard deviation of that measurement point, and the ratio of the obtained difference to the mean of the CO.Ls sequence is the concentration offset. The sub-benign state evaluation interval is obtained based on the non-mutation points, and the number of mutation points in the sub-benign state evaluation interval is denoted as NPP; The specific process of obtaining the sub-good state evaluation interval is to search in reverse time from any non-mutation point, locate the first non-continuous non-mutation point as the reference position, and ensure that there is at least one mutation point between the obtained reference position and the non-mutation point. The various measurement points between the non-mutation point and the obtained reference position constitute a sub-good state evaluation interval. The sub-good-state evaluation interval is used to construct a local reference structure for mutation points to support the relative evaluation system for determining their good-state competitiveness. This interval defines a time-continuous and relatively consistent window region, so that mutation points appearing within this time window have similar background conditions, which can be used to compare the degree of local disturbance of the current mutation point. If the location of a mutation point shows a greater trend reversal or concentration shift relative to other points in the interval, it can be regarded as showing a competitive disadvantage under the current pyrolysis atmosphere. By constructing the sub-good-state evaluation interval, the dynamic ranking and fine judgment of the relative stability of mutation points can be realized.

[0019] Calculate the benign critical estimate Kscv for the current mutation point based on the second transient and concentration offset: ; where i1 is the cumulative variable, ILoc i1 ILoc_ct represents the second transient measure of the i1th mutation point in the sub-good state assessment interval corresponding to the current mutation point, and ILoc_ct is the ratio of the maximum value to the average value of all second transient measures in the CO.Ls sequence corresponding to the current mutation point. GNPP i1is the number of mutation points in the sub-good state evaluation interval corresponding to the current mutation point that are smaller than the second transient of the current mutation point or the i1th mutation point; COF is the ordinal number of the concentration offset of the current mutation point in the CO.Ls sequence when the concentration offsets of each mutation point are arranged from smallest to largest; exp() is an exponential function with the natural constant e as the base; where the smaller the value of i1, the closer it is to the current time.

[0020] The preset monitoring quantity k2 is used. If the current monitoring point and the k2 preceding monitoring points are all abrupt change points, and the critical value of the current monitoring point is greater than the average critical value of the current abrupt change points during the backtesting period, then the current monitoring point is judged to be a good state; otherwise, it is a bad state. The value range of k2 is [1,5], and the default value is set to 1. When the benign competitive state is determined to be a poor performer, it indicates that in the current high-temperature steam activation process, the nitrogen input rate exhibits a mismatch in the cracking process. Insufficient activation atmosphere intensity suppresses the instantaneous peak of small molecule hydrocarbons, leading to a high risk of small molecule hydrocarbon redeposition.

[0021] Beneficial effects: Since the benign competition determination is based on the real-time judgment of the correctness of the occurrence of sudden increases in carbon and oxygen concentration at different levels, it can effectively quantify whether the chance of the instantaneous peak of small molecule hydrocarbons that often occurs during high-temperature steam activation exceeds the benign competition state that is conducive to promoting cracking and inhibiting redeposition after the nitrogen rate is increased or intervention is performed; thus, the obtained benign competition determination is actually a judgment that the degree of cracking of volatile substances under high-temperature steam is decreasing while the degree of repolymerization of small molecule hydrocarbons is increasing.

[0022] Further, in step S400, the method for adjusting the nitrogen rate using the good-state competition determination result is as follows: the adjustment time interval of the nitrogen rate is recorded as the speed regulation cycle length, and the starting time of the speed regulation cycle corresponding to the current time is the speed regulation starting point. If the current time is within the first half of the speed regulation cycle and the good-state competition determination is a bad state, then the nitrogen rate is restored to the previous nitrogen rate; if the current time is within the second half of the speed regulation cycle and the good-state competition determination is a bad state, then the speed regulation cycle length of the current nitrogen rate is increased.

[0023] The first half of the speed regulation cycle is the period of (BOTemp, BOTemp + 0.5 × TOAcc); the second half of the speed regulation cycle is the period of (BOTemp + 0.5 × TOAcc, BOTemp + 1 × TOAcc); TOAcc is the speed regulation cycle length, and BOTemp is the starting point of the speed regulation; when increasing the speed regulation cycle length of the current nitrogen rate, the increase in cycle length is between 0.1 × TOAcc and 0.5 × TOAcc, with a default value of 0.1 × TOAcc.

[0024] The adjustment interval is the time interval set for the nitrogen input rate to increase progressively during the steam activation process; that is, how often the nitrogen input rate is increased to counteract redeposition during the process. The speed regulation cycle is a time period of time after each update of the nitrogen input rate. The current speed regulation cycle is searched for its corresponding speed regulation cycle and its starting point based on its assigned speed regulation cycle length. Both the speed regulation starting point and the current moment are essentially time scales, displayed as time in computer programming. The previous nitrogen rate refers to the nitrogen input rate of the speed regulation cycle preceding the current speed regulation starting point, with each speed regulation cycle allowed to resume from the previous nitrogen rate at most once. There is a default one-to-one correspondence between nitrogen rate and speed regulation cycle.

[0025] Preferably, all undefined variables in this invention, if not explicitly defined, can be manually set thresholds.

[0026] This invention also provides an adaptive nitrogen rate regulation system for the preparation of fermented silkworm excrement biochar. The system includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the adaptive nitrogen rate regulation method for the preparation of fermented silkworm excrement biochar. This system can run on computing devices such as desktop computers, laptops, handheld computers, and cloud data centers. The runnable system may include, but is not limited to, processors, memory, and server clusters. The processor executes the computer program within the following system units: A detection equipment arrangement unit is used to arrange carbon and oxygen gas concentration detection equipment in a tubular furnace; The real-time content determination unit is used to measure the real-time concentration of carbon oxides using a concentration detection device to obtain the carbon oxide concentration. A benign competition determination unit is used to determine benign competition based on real-time concentration measurements. The nitrogen input rate regulation unit is used to regulate the nitrogen rate using the results of the benign competitive determination.

[0027] The beneficial effects of this invention are as follows: This invention provides an adaptive nitrogen rate adjustment method for the preparation of fermented silkworm excrement biochar. It makes real-time judgments based on the correctness of sudden increases in carbon and oxygen concentrations at different levels, effectively quantifying whether the chance of instantaneous peaks in small-molecule hydrocarbons, which often occur during high-temperature steam activation, exceeds the favorable competitive state that promotes pyrolysis and inhibits redeposition after nitrogen rate increase or intervention. Therefore, the obtained favorable competitive state judgment is actually a judgment that the degree of pyrolysis of volatile substances under high-temperature steam is decreasing while the degree of repolymerization of small-molecule hydrocarbons is increasing. Especially in the middle and later stages of high-temperature steam activation, the chance of instantaneous peaks in small-molecule hydrocarbons increases, and the favorable competitive state is more likely to be inhibited. By timely detecting premature entry of nitrogen rate increases in the favorable competitive state, the nitrogen rate is maintained at a level that ensures the favorable competitive state, thereby improving the pyrolysis efficiency of fermented silkworm excrement biochar and ensuring its microbial attachment advantage. Attached Figure Description

[0028] The above and other features of the present invention will become more apparent from the detailed description of the embodiments shown in conjunction with the accompanying drawings. In the accompanying drawings, the same reference numerals denote the same or similar elements. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort. In the drawings: Figure 1 The diagram shows a flowchart of an adaptive nitrogen rate adjustment method for the preparation of fermented silkworm excrement biochar. Figure 2 The diagram shows the structure of an adaptive nitrogen rate regulation system for the preparation of fermented silkworm excrement biochar. Detailed Implementation

[0029] The following will provide a clear and complete description of the concept, specific structure, and technical effects of the present invention in conjunction with the embodiments and accompanying drawings, so as to fully understand the purpose, solution, and effects of the present invention. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. Example

[0030] like Figure 1 The diagram shows a flowchart of an adaptive nitrogen rate control method for the preparation of fermented silkworm excrement biochar. The following section will combine... Figure 1 This invention describes an adaptive nitrogen rate adjustment method for preparing fermented silkworm excrement biochar according to an embodiment of the present invention, the method comprising the following steps: S100, carbon and oxygen gas concentration detection equipment is installed in the tubular furnace; S200 obtains carbon and oxygen concentration by measuring the real-time concentration of carbon and oxygen compounds using a concentration detection device. S300, based on real-time concentration measurement, determines the state of competition; S400 uses the results of benign competitive determination to regulate the nitrogen rate.

[0031] Furthermore, in step S100, the method for arranging the carbon and oxygen gas concentration detection device in the tubular furnace is as follows: the carbon and oxygen gas concentration detection device is an NDIR infrared sensor; if an NDIR infrared sensor is selected, it is arranged between the exhaust gas emission end of the tubular furnace and the cooling zone.

[0032] In this method, the carbon and oxygen gas concentration detection device is referred to as the concentration detection device. The carbon and oxygen gas concentration detection device is used to measure the concentration of carbon and oxygen compounds in the exhaust gas of a tubular furnace. Carbon and oxygen compounds include carbon monoxide and carbon dioxide. The carbon and oxygen gas concentration detection device measures and records data in real time.

[0033] Tubular furnaces are used for steam activation of fermented silkworm excrement biochar. The purpose is to promote the decomposition of volatile substances through high-temperature steam, and to prevent the volatile substances from hindering the adhesion of microorganisms to fermented silkworm excrement biochar during application.

[0034] Further, in step S200, the method for obtaining the carbon oxide concentration by measuring the real-time concentration of carbon oxides using a concentration detection device is as follows: the carbon oxides include carbon monoxide and carbon dioxide, and the concentration value of gaseous carbon oxides in the tail gas of the tubular furnace is obtained in real time using a carbon oxide concentration detection device and recorded as the carbon oxide concentration; the carbon oxide concentration monitoring frequency is 20 times per minute.

[0035] When both carbon monoxide and carbon dioxide are included, the sum of their concentrations is taken as the carbon-oxygen concentration.

[0036] The sampling system includes a high-temperature sampling tube and a filtration device, so the sampling process inevitably introduces a certain gas lag time, usually within 2 seconds; monitoring every 3 seconds is to dynamically reflect the actual reaction situation and reduce lag identification, while effectively ensuring that the data changes between sampling points have a sufficiently large chance.

[0037] Further, in step S300, the method for determining the benign competitive state based on the real-time concentration measurement is as follows: the time point of concentration measurement is recorded as the measurement point; a time period is set as the backtesting period Tept, with a value of 10 minutes; the difference between the carbon and oxygen concentrations of any measurement point and its previous measurement point is recorded as the instantaneous concentration difference; wherein the instantaneous concentration difference of the first measurement point is ignored.

[0038] If the instantaneous concentration difference at any measurement point is less than 0 and is less than the average of the instantaneous concentration differences in the sub-test period, then the good state competition of that measurement point is judged as a bad state; otherwise, the good state competition is judged as a good state. Let the instantaneous concentration difference of a measurement point being greater than that of its predecessor be the first good state condition. The proportion of measurement points that meet the first good state condition in the corresponding test period of any measurement point is the good state base value. The difference rate between any measurement point and the good state base value of its predecessor is the base value deviation rate. If the base value deviation rate in the test period is not less than 0.25, then the measurement point is judged to meet the second good state condition. The ratio of the instantaneous concentration difference to the carbon and oxygen concentration is the carbon and oxygen volatility, and the average carbon and oxygen volatility during the backtesting period is the carbon and oxygen volatility factor. The empirical fluctuation factor is calculated based on the good state determination. If the carbon-oxygen fluctuation factor during the backtesting period is less than the empirical fluctuation factor, the measurement point is determined to meet the third good state condition. The process of calculating the empirical fluctuation factor based on the good state determination is as follows: the preset empirical value is k1, and k1 is defaulted to 1 / 4 of the number of measurement points during the backtesting period. All measurement points determined to be good state in the first k1 measurement points form a fluctuation reference sequence. The carbon-oxygen fluctuation factor of the fluctuation reference sequence is recorded as the empirical fluctuation factor. If the number of measurement points in the first k1 measurement points that are in good state is less than 2, the measurement points determined to be in good state are adopted in the reverse time direction until the number of measurement points in good state in the fluctuation reference sequence is greater than or equal to 2. If the current measuring point satisfies the first good-state condition, the second good-state condition, and the third good-state condition, then the good-state competition of the measuring point is determined to be a good state; otherwise, it is a bad state. Further, in step S400, the method for adjusting the nitrogen rate using the good-state competition determination result is as follows: the adjustment time interval of the nitrogen rate is recorded as the speed regulation cycle length, and the starting time of the speed regulation cycle corresponding to the current time is the speed regulation starting point. If the current time is within the first half of the speed regulation cycle and the good-state competition determination is a bad state, then the nitrogen rate is restored to the previous nitrogen rate; if the current time is within the second half of the speed regulation cycle and the good-state competition determination is a bad state, then the speed regulation cycle length of the current nitrogen rate is increased.

[0039] The first half of the speed regulation cycle is the period of (BOTemp, BOTemp + 0.5 × TOAcc); the second half of the speed regulation cycle is the period of (BOTemp + 0.5 × TOAcc, BOTemp + 1 × TOAcc); TOAcc is the speed regulation cycle length, and BOTemp is the starting point of the speed regulation; when increasing the speed regulation cycle length of the current nitrogen rate, the increase in cycle length is 0.1 × TOAcc. Example

[0040] Example 2 employs the same nitrogen rate adaptive adjustment method as Example 1, the difference being that in step S300, the method for determining benign competition based on real-time concentration measurements is as follows: The time point at which the concentration was measured is recorded as the measurement point; a time period is set as the retest period Tept, which is 10 minutes; within the retest period, the carbon and oxygen concentrations of each measurement point constitute the concentration sequence CO.Ls; in the CO.Ls sequence, the difference between the carbon and oxygen concentrations of any measurement point and the previous measurement point is recorded as the first instantaneous difference; The first instantaneous difference at the end point is the difference between the maximum and minimum carbon and oxygen concentrations in the corresponding CO.Ls sequence. The end point refers to the measuring point that is furthest from the current measuring point in time.

[0041] Calculate the sum of the average value and standard deviation of the first instantaneous difference of all measuring points in the reverse time direction for any measuring point, and record it as the concentration step value of that measuring point; if the first instantaneous difference of any measuring point is greater than its concentration step value, then the measuring point is marked as a change point, otherwise it is marked as a non-change point; The absolute value of the difference between the first instantaneous difference of any measuring point and the first instantaneous difference of the previous measuring point is denoted as the second instantaneous difference ILoc; For non-mutation points, if the second transient difference of any non-mutation point is less than the lower quartile, then the benign state competition of that non-mutation point is determined to be a benign state; otherwise, it is a dominant state. Here, the lower quartile is obtained by only counting the set of second transient differences of non-mutation points. The concentration offset is calculated using the first instantaneous difference. The method for obtaining the concentration offset is as follows: in the CO.Ls sequence corresponding to any measurement point, calculate the difference between the first instantaneous error and the standard deviation of that measurement point, and the ratio of the obtained difference to the mean of the CO.Ls sequence is the concentration offset. The sub-benign state evaluation interval is obtained based on the non-mutation points, and the number of mutation points in the sub-benign state evaluation interval is denoted as NPP; The specific process of obtaining the sub-good state evaluation interval is to search in reverse time from any non-mutation point, locate the first non-continuous non-mutation point as the reference position, and ensure that there is at least one mutation point between the obtained reference position and the non-mutation point. The various measurement points between the non-mutation point and the obtained reference position constitute a sub-good state evaluation interval. Calculate the benign critical estimate Kscv for the current mutation point based on the second transient and concentration offset: ; where i1 is the cumulative variable, ILoc i1 ILoc_ct represents the second transient measure of the i1th mutation point in the sub-good state assessment interval corresponding to the current mutation point, and ILoc_ct is the ratio of the maximum value to the average value of all second transient measures in the CO.Ls sequence corresponding to the current mutation point. GNPP i1, is the number of mutation points in the sub-good state evaluation interval corresponding to the current mutation point that are smaller than the second transient difference of the current mutation point, i.e., the i1th mutation point; COF is the ordinal number of the concentration offset of the current mutation point in the CO.Ls sequence when the concentration offsets of each mutation point are arranged from smallest to largest; exp() is an exponential function with the natural constant e as the base. The preset monitoring quantity k2 is used. If the current monitoring point and the k2 preceding monitoring points are all abrupt change points, and the critical value of the current monitoring point is greater than the average critical value of the current monitoring point in the abrupt change point in the backtesting period, then the current monitoring point is judged to be in a good state; otherwise, it is in a bad state. k2 is set to 1. To verify the technical effects of the nitrogen rate adaptive adjustment method based on carbon and oxygen concentration surge recognition described in this invention in suppressing redeposition, improving pyrolysis efficiency, and enhancing microbial adhesion performance, the following experiment was designed. Three control groups were constructed using Example 1, Example 2, and a comparative example. Dried silkworm excrement treated with the same batch of fermentation was used, with a moisture content controlled at 8%. The temperature control accuracy of the tubular electric furnace was ±2°C. During the pyrolysis process, the tubular electric furnace was heated to 600°C and held at that temperature for 60 minutes, with a steam flow rate set at 120 mL / min. The specific surface area after steam activation treatment was determined using the nitrogen adsorption method with Micromeritics ASAP2460. The microbial adhesion test was performed by inoculating Bacillus using the static culture method. After 24 hours of culture, the adsorption rate per unit mass of the fermented silkworm excrement biochar was measured. The redeposition residue ratio in the fermented silkworm excrement biochar after steam activation treatment was calculated using the TGA thermogravimetric analysis method. The nitrogen rate was linearly increased from 40 to 160 mL / min, with a rate adjustment cycle of 2 minutes, meaning a minimum of 30 rate adjustments, each increasing the nitrogen rate by 4 mL / min. The difference between the comparative example and Examples 1 and 2 is that no additional nitrogen rate adjustment is performed using the benign competitive determination results.

[0042] Table 1. Comparison of High-Temperature Steam Activation Effects of Fermented Silkworm Excrement Biochar in Different Control Groups Peak average carbon and oxygen concentration (ppm) 455 478 467 Carbon and oxygen concentration fluctuation (CV%) 12.84% 18.32% 17.58% Residual redeposition weight (%) 15.36 8.91 7.63 BET specific surface area (m² / g) 328 376 370 Microbial adsorption rate increased (%) 16.3 18.2 21.7 Table 1 shows a comparison of the high-temperature steam activation effects of fermented silkworm excrement biochar in different control groups. In Examples 1 and 2, nitrogen rate regulation can better identify and coordinate with the instantaneous release of small molecule hydrocarbons. The gas generation rate during pyrolysis is highly synchronized with the atmosphere regulation, thus maintaining the system in the release advantage period, resulting in high reaction efficiency.

[0043] An embodiment of the present invention provides a nitrogen rate adaptive regulation system for the preparation of fermented silkworm excrement biochar, such as... Figure 2The diagram shows a structural diagram of an adaptive nitrogen rate regulation system for preparing fermented silkworm excrement biochar according to the present invention. This embodiment of the adaptive nitrogen rate regulation system for preparing fermented silkworm excrement biochar includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the above embodiment of the adaptive nitrogen rate regulation method for preparing fermented silkworm excrement biochar.

[0044] The system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program in units of the following system: A detection equipment arrangement unit is used to arrange carbon and oxygen gas concentration detection equipment in a tubular furnace; The real-time content determination unit is used to measure the real-time concentration of carbon oxides using a concentration detection device to obtain the carbon oxide concentration. A benign competition determination unit is used to determine benign competition based on real-time concentration measurements. The nitrogen input rate regulation unit is used to regulate the nitrogen rate using the results of the benign competitive determination.

[0045] The nitrogen rate adaptive regulation system for preparing fermented silkworm excrement biochar can run on computing devices such as desktop computers, laptops, handheld computers, and cloud servers. The system that can run on this nitrogen rate adaptive regulation system for preparing fermented silkworm excrement biochar may include, but is not limited to, processors and memory. Those skilled in the art will understand that the example described is merely an illustration of a nitrogen rate adaptive regulation system for preparing fermented silkworm excrement biochar and does not constitute a limitation on such a system. It may include more or fewer components, or a combination of certain components, or different components. For example, the nitrogen rate adaptive regulation system for preparing fermented silkworm excrement biochar may also include input / output devices, network access devices, buses, etc.

[0046] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the nitrogen rate adaptive regulation system for the preparation of fermented silkworm excrement biochar, connecting various parts of the system via various interfaces and lines.

[0047] The memory can be used to store the computer program and / or modules. The processor, by running or executing the computer program and / or modules stored in the memory and calling the data stored in the memory, realizes various functions of the nitrogen rate adaptive regulation system for preparing fermented silkworm excrement biochar. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0048] Although the invention has been described in considerable detail and particularly with regard to several of the described embodiments, it is not intended to limit itself to any of these details or embodiments or any particular embodiment, thereby effectively covering the intended scope of the invention. Furthermore, the invention has been described above with respect to embodiments foreseeable by the inventors in order to provide a useful description, and non-substantial modifications to the invention that have not yet been foreseen may still represent equivalent modifications.

Claims

1. A method for adaptively adjusting the nitrogen gas rate in the preparation of fermented silkworm excrement biochar, characterized in that, The method includes the following steps: S100, carbon and oxygen gas concentration detection equipment is installed in the tubular furnace; S200 obtains carbon and oxygen concentration by measuring the real-time concentration of carbon and oxygen compounds using a concentration detection device. S300, based on real-time concentration measurement, determines the state of competition; S400 uses the results of benign competition determination to regulate the nitrogen rate; In step S300, the method for determining the benign competitive state based on real-time concentration measurement is as follows: the time point of concentration measurement is recorded as the measurement point; a time period is set as the backtesting period Tept, and the difference between the carbon and oxygen concentrations of any measurement point and its previous measurement point is recorded as the instantaneous concentration difference. If the instantaneous concentration difference at any measurement point is less than 0 and is less than the average of the instantaneous concentration differences during the backtesting period, then the good state competition of that measurement point is judged as a bad state; otherwise, the good state competition is judged as a good state. Let the instantaneous concentration difference of a measurement point being greater than that of its predecessor be the first good state condition. The proportion of measurement points that meet the first good state condition during the backtesting period corresponding to any measurement point is the good state base value. The difference rate between any measurement point and the good state base value of its predecessor is the base value deviation rate. If the base value deviation rate during the backtesting period is not less than 0.25, then the measurement point is judged to meet the second good state condition. The ratio of the instantaneous concentration difference to the carbon and oxygen concentration is the carbon and oxygen volatility rate. The average carbon and oxygen volatility rate during the backtesting period is recorded as the carbon and oxygen volatility factor. The empirical volatility factor is calculated based on the good state determination. If the carbon and oxygen volatility factor during the backtesting period is less than the empirical volatility factor, the measurement point is determined to meet the third good state condition. If the current measurement point meets the first good state condition, the second good state condition, and the third good state condition, the good state competition of the measurement point is determined to be a good state; otherwise, it is a bad state.

2. The method for adaptively adjusting the nitrogen rate in the preparation of fermented silkworm excrement biochar according to claim 1, characterized in that, In step S100, the method for arranging a carbon and oxygen gas concentration detection device in the tubular furnace is as follows: the carbon and oxygen gas concentration detection device is an NDIR infrared sensor; the NDIR infrared sensor is used to extract and detect the exhaust gas between the exhaust gas emission end of the tubular furnace and the cooling zone.

3. The method for adaptively adjusting the nitrogen rate in the preparation of fermented silkworm excrement biochar according to claim 1, characterized in that, In step S200, the method for obtaining the carbon and oxygen concentration by measuring the real-time concentration of carbon and oxygen compounds using a concentration detection device is as follows: the carbon and oxygen compounds include at least one of carbon monoxide and carbon dioxide, and the concentration value of gaseous carbon oxides in the tail gas of the tubular furnace is obtained in real time using a carbon and oxygen compound concentration detection device and recorded as the carbon and oxygen concentration; the carbon and oxygen concentration monitoring frequency is 10-20 times per minute.

4. The method for adaptively adjusting the nitrogen rate in the preparation of fermented silkworm excrement biochar according to claim 1, characterized in that, In step S400, the method for adjusting the nitrogen rate using the good-state competition determination result is as follows: the time interval between two adjacent nitrogen rate updates is recorded as the speed regulation cycle length, and the starting time of the current speed regulation cycle is the speed regulation starting point. If the current time is within the first half of the speed regulation cycle and the good-state competition determination is a bad state, the nitrogen rate is restored to the previous nitrogen rate; if the current time is within the second half of the speed regulation cycle and the good-state competition determination is a bad state, the speed regulation cycle length of the current nitrogen rate is increased.

5. A nitrogen rate adaptive regulation system for the preparation of fermented silkworm excrement biochar, characterized in that, The nitrogen rate adaptive regulation system for preparing fermented silkworm excrement biochar includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the nitrogen rate adaptive regulation method for preparing fermented silkworm excrement biochar as described in any one of claims 1-4. The nitrogen rate adaptive regulation system for preparing fermented silkworm excrement biochar operates on computing devices such as desktop computers, laptops, handheld computers, and cloud data centers.

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