Energy-saving dynamic control method for a pulping machine in a straw pulping process

Abstract

The present invention belongs to the technical field of data processing, and proposes a method for energy-saving dynamic control of a pulper in a straw pulping process, specifically: crushing and cutting straw to form straw fragments, inputting the straw fragments into a pulper at a uniform speed, and grinding the straw fragments into pulp by a pulping blade; wherein in the process of grinding the straw fragments into pulp by the pulping blade, energy-saving dynamic control is implemented on the rotor that controls the pulping blade. The energy consumption analysis value calculated when identifying whether the energy consumption is abnormal through shear force data is obtained by analyzing the shear force, so it can effectively quantify the abnormal power consumption caused by excessive rotor power in an unstable load working environment during the straw pulping process, thereby reducing the friction energy consumption loss caused by the fixed power rotor driving the pulping blade when the load fluctuates greatly, and achieving energy saving effect by reducing the risk of unnecessary energy consumption caused by reducing friction loss, which greatly improves the unnecessary energy waste of the pulper in large-scale production.

Description

Technical Field

[0001] The invention belongs to the technical field of automatic control and energy-saving control, and in particular relates to an energy-saving dynamic control method for a pulping machine in a straw pulping process. Background Art

[0002] The physical properties of straw itself include high moisture content, fragile fiber structure and high impurity content, especially the presence of silicon and wax layers, which pose challenges to the operation of mechanical equipment. Compared with wood pulping, straw fibers are shorter and more brittle, and are easily broken or blocked during mechanical operation. Traditional crushing and pulping equipment is often designed for wood, so it is not completely suitable for straw. In order to adapt to the characteristics of straw short fibers, the current solution to this problem is generally to equip the straw pulping system with a crusher, and use the crusher to process the straw into straw fragments. However, straw fibers are shorter and contain more non-fibrous matter, which means that the equipment needs to consume more energy to break up the fibers during the pulping process, which makes the pulping equipment tend to work in a high-energy consumption mode for process efficiency and quality. The high-energy consumption working mode often means that a large amount of unnecessary friction and heat are generated during pulping. The existing pulping machine process often uses a fixed speed to input straw fragments for pulping, which makes the energy consumption fluctuate with the pulping load and further deepens the friction and heat loss. On the one hand, this is because the moisture content of the straw fragments often changes dynamically, unless additional moisture treatment is performed, but this will undoubtedly increase the redundancy and efficiency of the pulping process; therefore, when the load is large, the fixed speed will cause the equipment to overwork and generate excess friction and heat; when the load is small, the energy is not fully utilized, resulting in an increase in the idling rate, resulting in energy waste, especially when the load fluctuates greatly, pulping at a fixed speed will cause friction far exceeding the required level. Because pulping equipment has priority in production for process efficiency and quality requirements, dynamically allocating shear force and load level can provide an opportunity to save energy in the straw pulping process. Summary of the invention

[0003] The purpose of the present invention is to propose an energy-saving dynamic control method for a pulper in a straw pulping process to solve one or more technical problems existing in the prior art and at least provide a beneficial choice or create conditions.

[0004] In order to achieve the above object, according to one aspect of the present invention, a method for energy-saving dynamic control of a pulping machine in a straw pulping process is provided, the method comprising the following steps:

[0005] The straw is crushed and cut into straw fragments, and the straw fragments are uniformly fed into a pulping machine, and the straw fragments are ground into pulp by pulping blades;

[0006] During the process of grinding the straw fragments into pulp by the beating blades, energy-saving dynamic control is implemented on the rotor that controls the beating blades. The specific method includes: obtaining shear force data from the shear force sensor of the pulper, identifying whether the energy consumption is abnormal through the shear force data, and reducing the output power of the rotor when the energy consumption is abnormal, so that the energy consumption returns to normal levels.

[0007] Furthermore, the method of uniformly feeding the straw fragments into the pulping machine is as follows: the length of the straw fragments ranges from 2 to 3 cm, and the speed of feeding the straw fragments into the pulping machine is 5 kg / s to 10 kg / s.

[0008] Furthermore, the method of grinding the straw fragments into pulp by the pulping blade is: controlling the rotation speed of the pulping blade to range from 800 RPM to 1500 RPM.

[0009] Furthermore, the method for obtaining shear force data from the shear force sensor of the beater is: the shear force sensor is installed at the fixed bracket or bearing seat position of the beater blade, the shear force reading is obtained every 0.5 seconds to 5 seconds through the shear force sensor, and the shear force obtained at each moment is saved as shear force data.

[0010] The principle of using shear force to identify whether energy consumption is abnormal is that there is friction between the pulping blade and the fiber and pulp, especially when the shear force is large, this friction will convert part of the mechanical energy into heat energy and generate friction heat. When the shear force is too large, the friction will also increase and cause more heat to be generated. Therefore, excessive shear force will cause the temperature inside the equipment to rise, especially when there is more friction heat generated in the contact area between the blade and the pulp. Excessive temperature will accelerate the wear of the pulper, shorten the service life of the blade, and increase the maintenance cost of the equipment. When the load is large, the fixed speed will cause the equipment to overwork and generate excess friction and heat; when the load is small, the energy is not fully utilized, resulting in an increase in the idling rate, resulting in energy waste. Especially when the load fluctuates greatly, beating at a fixed speed will cause the friction force to far exceed the required level.

[0011] Furthermore, the method for identifying whether the energy consumption is abnormal through shear force data is as follows: set a time period as the monitoring period RETM, RETM∈[10,15] minutes; record the obtained shear force as Hefrc, and all shear forces in the monitoring period constitute the first time series; calculate the autocorrelation coefficient PHOS of each element of the first time series to form a lagged correlation factor sequence, obtain the time corresponding to the first autocorrelation coefficient in the lagged correlation factor sequence whose autocorrelation coefficient is less than 0.3, and set its serial number value in all monitoring moments as the first lagged value TEmn;

[0012] According to the autocorrelation coefficient and shear force data, a shear force autoregressive model is constructed to obtain the updated shear force. Specifically, for any moment Te, the updated shear force HefrcTe =PHOS(1)×Hefrc Te-1 +PHOS(2)×Hefrc Te-2 +…+PHOS(TEmn)×Hefrc Te-TEmn +EPsi t ;

[0013] Where PHOS(1), PHOS(2), and PHOS(TEmn) are the autocorrelation coefficients corresponding to the first, second, and TEmnth moments in the monitoring period, respectively. Te-1 、Hefrc Te-2 、Hefrc Te-TEmn are the shear forces before the first, second, and TEmn at the current moment Te, EPsi t is white noise that follows a standard normal distribution and is randomly generated by the rnorm() function in the R software;

[0014] The reason for the calculation of the shear force autoregressive model is that by studying the memory of the real-time shear force values ​​of the time series data and the past monitoring moments, the theoretical shear force values ​​that change with time under normal circumstances at the current monitoring moment are predicted, so that the obtained real-time shear force values ​​have strong robustness, so as to accurately calculate the residuals between the actual observed values ​​and the predicted values.

[0015] All updated shear forces constitute the second time series. For any monitoring moment, the absolute value of the corresponding shear force difference between the first time series and the second time series is calculated, which is recorded as the reconstructed shear force error SIoce. All reconstructed shear force errors constitute the third time series. All data of the third time series are fitted by polynomial regression. The average value and the average value of all the maximum values ​​and the minimum values ​​of the obtained polynomial regression fitting curve are recorded as the first maximum value FS_max and the first minimum value FS_min, respectively. The interval [FS_min, FS_max] is recorded as the confidence safety analysis domain. All reconstructed shear force errors corresponding to TEmn monitoring moments in the reverse time direction at any moment constitute the fourth time series. The average value and standard deviation of all data in the fourth time series are calculated and recorded as SIave and SIsyd, respectively. The shear force decision factor at that moment is recorded as ;

[0016] The calculation principle of the confidence safety analysis region is to use the shear force value training model of the time series data of historical moments, smooth the reconstructed shear force error data, extract the characteristics of extreme fluctuations of abnormal values, and provide a reference for the thresholds required to be set during monitoring.

[0017] The shear force at the current moment is predicted by the shear force autoregressive model, and its reconstructed shear force error is calculated. If the corresponding reconstructed shear force error does not belong to the confidence safety analysis region and the absolute value of its shear force decision factor is greater than 2, the energy consumption at the current moment is judged to be abnormal.

[0018] Since the above-mentioned shear force autoregressive model is obtained by accurately calculating the autocorrelation coefficient of the shear force data, and the autocorrelation coefficient accurately shows the correlation of the shear force data under different time lags, the real-time shear force data can be effectively predicted based on the historical shear force data; however, in data scenarios that require rapid response to process changes, the prediction model constructed using only the autocorrelation coefficient is difficult to use other key features for prediction, so that in the process of determining energy consumption anomalies, there are too few factors to consider and it is impossible to consider them from a global perspective, making the misjudgment problem particularly obvious. In order to improve the accuracy of the shear force autoregressive model prediction, the present invention proposes a more preferred solution;

[0019] Furthermore, the method of identifying whether the energy consumption is abnormal through shear force data is as follows: set a time period as the monitoring period TCF, TCF∈[15,20] minutes, obtain the shear force data of all moments in the TCF time period and write them into a sequence recorded as the shear force reference sequence Srs; record the moment where each maximum value element in the shear force reference sequence is located as the high consumption moment; the period between any high consumption moment and the first high consumption moment in the reverse time direction constitutes a characteristic interval; in the elements of the sequence Srs corresponding to any characteristic interval, each element greater than the median value of the characteristic interval and each element less than or greater than the median value of the characteristic interval constitutes a sequence, which are recorded as the first energy consumption sequence and the second energy consumption sequence respectively; the ratio of the average value of each element in the first energy consumption sequence to the average value of each element in the second energy consumption sequence is recorded as the overflow index Cqe;

[0020] Define the range of the elements in the characteristic interval as the range index Raqe; divide the length of the shear force reference sequence by the number of characteristic intervals, round down the obtained value and record it as DF; starting from the first element of the shear force reference sequence, divide an interval every DF elements and record it as the evaluation interval; calculate the average value of all elements in each evaluation interval, and normalize the calculated average values, and the value obtained after processing is recorded as the balance factor Bgy of the corresponding evaluation interval;

[0021] The principle of obtaining the balance factor here is actually to amplify the values ​​of the shear force average values ​​in each evaluation interval that are biased towards the maximum value, thereby increasing the weight of the data of the shear force average value biased towards the maximum value and reducing the weight of the smaller values. In the process of mathematical analysis, it can be understood as achieving a classification effect based on the bias of the maximum and minimum values ​​in the set. This enables it to dynamically and effectively reflect the shear force state of the beater at the monitoring time, thereby providing mathematical support for the application of the balance factor in time series analysis to observe the adjustment effect.

[0022] The first difference component and the second difference component at any moment are defined as the difference between the corresponding shear force at that moment and the average value of the first characteristic interval and the first evaluation interval searched in the reverse time direction. The maximum value of the absolute values ​​corresponding to the first difference component and the second difference component is recorded as the energy consumption difference component Fcdor at that moment. The energy consumption analysis value ENLY is calculated based on the overflow index and the balance factor:

[0023] ;

[0024] Where i1 and i2 are accumulated variables, exp() is an exponential function with the natural constant e as the base, FBT and FAT are the number of feature intervals and evaluation intervals respectively, and Cqe i1 and Raqe i1 Represent the overflow index and range index of the i1th characteristic interval respectively; Bgy i2 Represents the equilibrium factor of the i2th evaluation interval.

[0025] The benchmark reference set is composed of a pair of moments and their corresponding energy consumption analysis values. Any moment is taken as the current moment. The Pearson correlation coefficient of the benchmark reference set at two consecutive moments is calculated in the reverse time direction from the current moment. If the obtained Pearson correlation coefficient is less than 0.5, it indicates that the energy consumption at that moment is abnormal.

[0026] Beneficial effects: Usually, this type of monitoring method for excessive energy release uses a moving average and a preset threshold method for control. However, in the problem of identifying abnormal energy consumption of the beater rotor, the shear force fluctuation is a reflection of the local contact between the fiber and the blade, and its change is affected by factors such as different materials, local fiber distribution and instantaneous friction. The moving average ignores these sudden abnormal signals, thereby reducing the energy-saving release opportunities and reducing the energy-saving effect. The combination of the moving average and the preset threshold lacks a hierarchical understanding of short-term abnormal shear force fluctuations, and cannot achieve multi-level energy-saving opportunity release, making the dynamic control effect lack timeliness and efficiency.

[0027] Since the energy consumption analysis value calculated when the shear force data is used to identify whether the energy consumption is abnormal is obtained by analyzing the time series data of the shear force, it can effectively quantify the abnormal power consumption caused by excessive rotor power in an unstable load working environment during the straw pulping process, thereby reducing the friction energy consumption loss caused by the fixed power rotor driving the pulping blade when the load fluctuates greatly, and achieving energy saving effect by reducing the risk of unnecessary energy consumption caused by friction loss.

[0028] Furthermore, when energy consumption is abnormal, the output power of the rotor is reduced to restore the energy consumption to a normal level. If the energy consumption is judged to be abnormal at a certain moment, the power of the rotor of the beating blade is reduced by 5%-15% until it is judged that the energy consumption is not abnormal.

[0029] Preferably, all undefined variables in the present invention, if not clearly defined, can be manually set thresholds.

[0030] The present invention also provides an energy-saving dynamic control system for a pulper in a straw pulping process, the energy-saving dynamic control system for a pulper in a straw pulping process comprises: a processor, a memory, and a computer program stored in the memory and executable on the processor, the processor implements the steps in the energy-saving dynamic control method for a pulper in a straw pulping process when executing the computer program, the energy-saving dynamic control system for a pulper in a straw pulping process can be run in computing devices such as desktop computers, laptop computers, PDAs, and cloud data centers, the executable system may include, but is not limited to, a processor, a memory, and a server cluster, the processor executes the computer program and runs in the following system units:

[0031] A shear force data acquisition unit, used for acquiring shear force data from a shear force sensor of a beater;

[0032] An energy consumption abnormality judgment unit is used to identify whether the energy consumption is abnormal through shear force data;

[0033] The dynamic control unit is used to reduce the output power of the rotor when abnormal energy consumption occurs, so that the energy consumption returns to normal levels.

[0034] The beneficial effects of the present invention are as follows: the present invention provides an energy-saving dynamic control method for a pulper in a straw pulping process. In the method, the energy consumption analysis value calculated when identifying whether the energy consumption is abnormal through shear force data is obtained by analyzing the time series data of the shear force. Therefore, it can effectively quantify the abnormal power consumption phenomenon caused by excessive rotor power in an unstable load working environment during the straw pulping process, thereby reducing the friction energy consumption loss caused by the fixed power rotor driving the pulping blade when the load fluctuates greatly. The energy-saving effect is achieved by reducing the risk of unnecessary energy consumption caused by friction loss, which greatly improves the unnecessary energy waste of the pulper in large-scale production, improves the utilization rate of production materials, and also has a guarantee significance for the service life and cycle of the pulping blade. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The above and other features of the present invention will become more obvious by describing in detail the embodiments shown in the accompanying drawings. The same reference numerals in the accompanying drawings of the present invention represent the same or similar elements. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other accompanying drawings can be obtained based on these accompanying drawings without creative work. In the accompanying drawings:

[0036] Figure 1 The figure shows a flow chart of a method for energy-saving dynamic control of a pulping machine in a straw pulping process;

[0037] Figure 2 Shown is a structural diagram of an energy-saving dynamic control system for a pulping machine in a straw pulping process. DETAILED DESCRIPTION

[0038] The following will be combined with the embodiments and drawings to clearly and completely describe the concept, specific structure and technical effects of the present invention, so as to fully understand the purpose, scheme and effect of the present invention. It should be noted that the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0039] like Figure 1 The figure shows a flow chart of a straw pulping process energy-saving dynamic control method for a pulping machine. Figure 1 The following describes a method for energy-saving dynamic control of a pulping machine in a straw pulping process according to an embodiment of the present invention, the method comprising the following steps:

[0040] Example 1

[0041] The straw is crushed and cut into straw fragments, and the straw fragments are uniformly fed into a pulping machine, and the straw fragments are ground into pulp by pulping blades;

[0042] During the process of grinding the straw fragments into pulp by the beating blades, energy-saving dynamic control is implemented on the rotor that controls the beating blades. The specific method includes: obtaining shear force data from the shear force sensor of the pulper, identifying whether the energy consumption is abnormal through the shear force data, and reducing the output power of the rotor when the energy consumption is abnormal, so that the energy consumption returns to normal levels.

[0043] Furthermore, the method of uniformly feeding the straw fragments into the pulping machine is as follows: the length of the straw fragments ranges from 2 to 3 cm, and the speed of feeding the straw fragments into the pulping machine is 5 kg / s.

[0044] Further, the method of grinding the straw fragments into pulp by the pulping blade is: controlling the rotation speed range of the pulping blade to be 800 RPM.

[0045] Furthermore, the method for obtaining shear force data from the shear force sensor of the beater is: the shear force sensor is installed at the fixed bracket or bearing seat position of the beater blade, the shear force reading is obtained every 0.5 seconds through the shear force sensor, and the shear force obtained at each moment is saved as shear force data.

[0046] Furthermore, the method for identifying whether the energy consumption is abnormal through shear force data is as follows: set a time period as the monitoring period RETM=10 minutes; record the obtained shear force as Hefrc, and all shear forces in the monitoring period constitute the first time series; calculate the autocorrelation coefficient PHOS of each element of the first time series to form a lagged correlation factor sequence, obtain the time corresponding to the first autocorrelation coefficient in the lagged correlation factor sequence whose autocorrelation coefficient is less than 0.3, and use its serial number value in all monitoring moments as the first lagged value TEmn;

[0047] According to the autocorrelation coefficient and shear force data, a shear force autoregressive model is constructed to obtain the updated shear force. Specifically, for any moment Te, the updated shear force Hefrc Te =PHOS(1)×Hefrc Te-1 +PHOS(2)×Hefrc Te-2 +…+PHOS(TEmn)×Hefrc Te-TEmn +EPsi t ;

[0048] All updated shear forces constitute the second time series. For any monitoring moment, the absolute value of the corresponding shear force difference between the first time series and the second time series is calculated, which is recorded as the reconstructed shear force error SIoce. All reconstructed shear force errors constitute the third time series. All data of the third time series are fitted by polynomial regression. The average value and the average value of all the maximum values ​​and the minimum values ​​of the obtained polynomial regression fitting curve are recorded as the first maximum value FS_max and the first minimum value FS_min, respectively. The interval [FS_min, FS_max] is recorded as the confidence safety analysis domain. All reconstructed shear force errors corresponding to TEmn monitoring moments in the reverse time direction at any moment constitute the fourth time series. The average value and standard deviation of all data in the fourth time series are calculated and recorded as SIave and SIsyd, respectively. The shear force decision factor at that moment is recorded as ;

[0049] The shear force at the current moment is predicted by the shear force autoregressive model, and its reconstructed shear force error is calculated. If the corresponding reconstructed shear force error does not belong to the confidence safety analysis region and the absolute value of its shear force decision factor is greater than 2, the energy consumption at the current moment is judged to be abnormal.

[0050] Furthermore, when energy consumption is abnormal, the output power of the rotor is reduced to restore the energy consumption to a normal level. If the energy consumption is judged to be abnormal at a certain moment, the power of the rotor of the beating blade is reduced by 5%-15% until it is judged that the energy consumption is not abnormal.

[0051] Example 2

[0052] Example 2 adopts the same control method as Example 1, the difference being that the method of identifying whether energy consumption is abnormal through shear force data is replaced by: assuming a time period as a monitoring period TCF=15 minutes, obtaining the shear force data at all moments in the TCF time period and writing them into a sequence recorded as a shear force reference sequence Srs; recording the moments where each maximum value element in the shear force reference sequence is located as a high-consumption moment; the period between any high-consumption moment and the first high-consumption moment in the reverse time direction constitutes a characteristic interval; in the elements of the sequence Srs corresponding to any characteristic interval, each element greater than the median value of the characteristic interval and each element less than or greater than the median value of the characteristic interval constitutes a sequence, which are recorded as the first energy consumption sequence and the second energy consumption sequence respectively; the ratio of the average value of each element in the first energy consumption sequence to the average value of each element in the second energy consumption sequence is recorded as the overflow index Cqe;

[0053] Define the range of the elements in the characteristic interval as the range index Raqe; divide the length of the shear force reference sequence by the number of characteristic intervals, round down the obtained value and record it as DF; starting from the first element of the shear force reference sequence, divide an interval every DF elements and record it as the evaluation interval; calculate the average value of all elements in each evaluation interval, and normalize the calculated average values, and the value obtained after processing is recorded as the balance factor Bgy of the corresponding evaluation interval;

[0054] The first difference component and the second difference component at any moment are defined as the difference between the corresponding shear force at that moment and the average value of the first characteristic interval and the first evaluation interval searched in the reverse time direction. The maximum value of the absolute values ​​corresponding to the first difference component and the second difference component is recorded as the energy consumption difference component Fcdor at that moment. The energy consumption analysis value ENLY is calculated based on the overflow index and the balance factor:

[0055] ;

[0056] Where i1 and i2 are accumulated variables, exp() is an exponential function with the natural constant e as the base, FBT and FAT are the number of feature intervals and evaluation intervals respectively, and Cqe i1 and Raqe i1 Represent the overflow index and range index of the i1th characteristic interval respectively; Bgy i2 Represents the equilibrium factor of the i2th evaluation interval.

[0057] The benchmark reference set is composed of a pair of moments and their corresponding energy consumption analysis values. Any moment is taken as the current moment. The Pearson correlation coefficient of the benchmark reference set at two consecutive moments is calculated in the reverse time direction from the current moment. If the obtained Pearson correlation coefficient is less than 0.5, it indicates that the energy consumption at that moment is abnormal.

[0058] The embodiment of the present invention provides an energy-saving dynamic control system for a straw pulping machine, such as Figure 2 Shown is a structural diagram of an energy-saving dynamic control system for a pulper in a straw pulping process of the present invention. The energy-saving dynamic control system for a pulper in a straw pulping process of this embodiment 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, the steps in the embodiment of the energy-saving dynamic control method for a pulper in a straw pulping process are implemented.

[0059] The system comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to run in the following units of the system:

[0060] A shear force data acquisition unit, used for acquiring shear force data from a shear force sensor of a beater;

[0061] An energy consumption abnormality judgment unit is used to identify whether the energy consumption is abnormal through shear force data;

[0062] The dynamic control unit is used to reduce the output power of the rotor when abnormal energy consumption occurs, so that the energy consumption returns to normal levels.

[0063] The energy-saving dynamic control system for a pulper in a straw pulping process can be run on computing devices such as desktop computers, laptop computers, PDAs, and cloud servers. The energy-saving dynamic control system for a pulper in a straw pulping process can be operated on systems including, but not limited to, processors and memories. Those skilled in the art can understand that the example is merely an example of an energy-saving dynamic control system for a pulper in a straw pulping process, and does not constitute a limitation on an energy-saving dynamic control system for a pulper in a straw pulping process. It can include more or fewer components than the example, or a combination of certain components, or different components. For example, the energy-saving dynamic control system for a pulper in a straw pulping process can also include input and output devices, network access devices, buses, etc.

[0064] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the energy-saving dynamic control system operating system of the straw pulping process beater, and various interfaces and lines are used to connect the various parts of the energy-saving dynamic control system operating system of the straw pulping process beater.

[0065] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the energy-saving dynamic control system of the pulping machine of the straw pulping process by running or executing the computer program and / or module stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0066] Although the description of the present invention has been quite detailed and has been described in particular with respect to several described embodiments, it is not intended to be limited to any of these details or embodiments or any particular embodiment, so as to effectively cover the intended scope of the present invention. In addition, the present invention is described above with the embodiments foreseeable by the inventors, and its purpose is to provide a useful description, and those non-substantial changes to the present invention that are not currently foreseen may still represent equivalent changes of the present invention.

Claims

1. A method for energy-saving dynamic control of a straw pulping machine, characterized in that: The method comprises the following steps: The straw is crushed and cut to form straw fragments, and the straw fragments are uniformly fed into a pulping machine, and the straw fragments are ground into pulp by a pulping blade; in the process of grinding the straw fragments into pulp by the pulping blade, energy-saving dynamic control is implemented on the rotor controlling the pulping blade, and the specific method includes: obtaining shear force data from the shear force sensor of the pulping machine, identifying whether the energy consumption is abnormal through the shear force data, and reducing the output power of the rotor when the energy consumption is abnormal, so that the energy consumption returns to a normal level; wherein the method of identifying whether the energy consumption is abnormal through the shear force data is: setting a time period as a monitoring period RETM, RETM∈[10,15] minutes; the obtained shear force is recorded as Hefrc, and all shear forces in the monitoring period constitute a first time series; Calculate the autocorrelation coefficient PHOS of each element of the first time series to form a lagged correlation factor sequence, obtain the time corresponding to the first autocorrelation coefficient with an autocorrelation coefficient less than 0.3 in the lagged correlation factor sequence, and set its serial number value in all monitoring moments as the first lagged value TEmn; construct a shear force autoregressive model based on the autocorrelation coefficient and shear force data and obtain the updated shear force, specifically: for any moment Te, the updated shear force Hefrc Te =PHOS(1)×Hefrc Te-1 +PHOS(2)×Hefrc Te-2 +…+PHOS(TEmn)×Hefrc Te-TEmn +EPsi t ; Where PHOS(1), PHOS(2), and PHOS(TEmn) are the autocorrelation coefficients corresponding to the first, second, and TEmnth moments in the monitoring period, respectively. Te-1 、Hefrc Te-2 、Hefrc Te-TEmn are the shear forces before the first, second, and TEmn at the current moment Te, EPsi t is white noise that follows a standard normal distribution and is randomly generated by the rnorm() function in the R software; All updated shear forces constitute the second time series. For any monitoring moment, the absolute value of the corresponding shear force difference between the first time series and the second time series is calculated, which is recorded as the reconstructed shear force error SIoce. All reconstructed shear force errors constitute the third time series. All data of the third time series are fitted by polynomial regression. The average value and the average value of all the maximum values ​​and the minimum values ​​of the obtained polynomial regression fitting curve are recorded as the first maximum value FS_max and the first minimum value FS_min, respectively. The interval [FS_min, FS_max] is recorded as the confidence safety analysis domain. All reconstructed shear force errors corresponding to TEmn monitoring moments in the reverse time direction at any moment constitute the fourth time series. The average value and standard deviation of all data in the fourth time series are calculated and recorded as SIave and SIsyd, respectively. The shear force decision factor at that moment is recorded as ; The shear force at the current moment is predicted by the shear force autoregressive model and its reconstructed shear force error is calculated. If the corresponding reconstructed shear force error does not belong to the confidence safety analysis region and the absolute value of its shear force decision factor is greater than 2, the energy consumption at the current moment is determined to be abnormal.

2. The energy-saving dynamic control method for a pulping machine in a straw pulping process according to claim 1 is characterized in that: The method of uniformly feeding the straw fragments into the pulping machine is as follows: the length of the straw fragments ranges from 2 to 3 cm, and the speed at which the straw fragments are fed into the pulping machine is 5 kg / s to 10 kg / s.

3. The energy-saving dynamic control method for a pulping machine in a straw pulping process according to claim 1 is characterized in that: The method for grinding the straw fragments into pulp by the pulping blade is: controlling the rotation speed range of the pulping blade to be 800 RPM-1500 RPM.

4. The energy-saving dynamic control method for a pulping machine in a straw pulping process according to claim 1 is characterized in that: The method for obtaining shear force data from the shear force sensor of the beater is: the shear force sensor is installed on the fixed bracket or bearing seat of the beater blade, the shear force reading is obtained every 0.5 seconds to 5 seconds through the shear force sensor, and the shear force obtained at each moment is saved as shear force data.

5. The energy-saving dynamic control method for a pulping machine in a straw pulping process according to claim 1, characterized in that: The method of identifying whether the energy consumption is abnormal through shear force data is as follows: set a time period as the monitoring period TCF, TCF∈[15,20] minutes, obtain the shear force data of all moments in the TCF time period and write them into a sequence recorded as the shear force reference sequence Srs; record the moment where each maximum value element in the shear force reference sequence is located as the high consumption moment; the period between any high consumption moment and the first high consumption moment in the reverse time direction constitutes a characteristic interval; in the elements of the sequence Srs corresponding to any characteristic interval, the elements greater than the median value of the characteristic interval and less than or greater than the median value of the characteristic interval are respectively composed of sequences, which are respectively recorded as the first energy consumption sequence and the second energy consumption sequence; the ratio of the average value of each element in the first energy consumption sequence to the average value of each element in the second energy consumption sequence is recorded as the overflow index Cqe; Define the range of the elements in the characteristic interval as the range index Raqe; divide the length of the shear force reference sequence by the number of characteristic intervals, round down the obtained value and record it as DF; starting from the first element of the shear force reference sequence, divide an interval every DF elements and record it as the evaluation interval; calculate the average value of all elements in each evaluation interval, and normalize the calculated average values, and the value obtained after processing is recorded as the balance factor Bgy of the corresponding evaluation interval; The first difference component and the second difference component at any moment are defined as the difference between the corresponding shear force at that moment and the average value of the first characteristic interval and the first evaluation interval searched in the reverse time direction. The maximum value of the absolute values ​​corresponding to the first difference component and the second difference component is recorded as the energy consumption difference component Fcdor at that moment. The energy consumption analysis value ENLY is calculated based on the overflow index and the balance factor: ； Where i1 and i2 are accumulated variables, exp() is an exponential function with the natural constant e as the base, FBT and FAT are the number of feature intervals and evaluation intervals respectively, and Cqe i1 and Raqe i1 Represent the overflow index and range index of the i1th characteristic interval respectively; Bgy i2 represents the equilibrium factor of the i2th evaluation interval; The benchmark reference set is composed of a pair of moments and their corresponding energy consumption analysis values. Any moment is taken as the current moment. The Pearson correlation coefficient of the benchmark reference set at two consecutive moments is calculated in the reverse time direction from the current moment. If the obtained Pearson correlation coefficient is less than 0.5, it indicates that the energy consumption at that moment is abnormal.

6. The energy-saving dynamic control method for a pulping machine in a straw pulping process according to claim 1, characterized in that: When energy consumption is abnormal, the output power of the rotor is reduced. The method to restore the energy consumption to normal levels is: if the energy consumption is judged to be abnormal at a certain moment, the power of the rotor of the beating blade is reduced by 5%-15% until it is judged that the energy consumption is not abnormal.

7. A straw pulping process energy-saving dynamic control system for a pulping machine, characterized in that: The energy-saving dynamic control system for a pulper in a straw pulping process comprises: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the energy-saving dynamic control method for a pulper in a straw pulping process described in any one of claims 1 to 6 are implemented. The energy-saving dynamic control system for a pulper in a straw pulping process runs on a desktop computer, a laptop computer, a PDA, and a computing device in a cloud data center.

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