Dynamic stress regulation and control method in biological fertilizer crushing process

Abstract

The invention relates to the technical field of crushing and crushing, and discloses a dynamic stress regulation and control method in a biological fertilizer crushing process, which comprises the following steps: injecting detection pulse airflow into a crushing cavity and collecting an acoustic reverberation signal of the detection pulse airflow; calculating an energy attenuation rate characteristic value from the signal, and dynamically adjusting an analysis frequency band and a regulation and control threshold value of the signal in combination with a material humidity and rotating speed signal obtained in real time; and finally, according to a comparison result of the characteristic value and a dynamic regulation and control threshold value, carrying out closed-loop regulation and control on operation parameters of the crusher. According to the method, a regulation and control mode for directly monitoring and regulating and controlling the energy utilization efficiency in the crushing cavity is constructed, the problem of hidden energy waste caused by excessive interaction or wall surface retention of the materials is avoided, the method can actively adapt to changes of the humidity of the materials and the rotating speed of equipment, and the regulation and control accuracy is guaranteed.

Description

Technical Field

[0001] The invention relates to a dynamic stress control method in a biofertilizer pulverization process, and belongs to the technical field of crushing and pulverization. Background Art

[0002] In the field of biofertilizer crushing technology, there is a common technical difficulty in obtaining energy utilization efficiency directly and in real time. The existing control method usually relies on monitoring the operating current of the crusher's main motor to judge the load.

[0003] However, the complex composition and variable moisture content of biofertilizers mean that the motor current signal cannot accurately reflect the actual fluidization state and energy efficiency of the materials in the cavity. This indirect state perception often causes the pulverization process to suffer from energy waste without being noticed. This manifests itself in the form of ineffective beating of fully crushed materials in the cavity due to failure to be discharged in time, or sticky materials adhering to the cavity wall, destroying the ideal circulation flow state. These processes result in continuous energy waste and a decline in material quality, and the improvement idea of ​​simply increasing the input power is of no help. Therefore, how to establish a method that can online quantify the pulverization cavity process, the fluidization state and energy efficiency of the materials inside it, and use this as a basis for closed-loop control of operating parameters such as feed rate, has become a technical issue to be solved in this field. Summary of the Invention

[0004] The present invention provides a method for dynamic stress control in the pulverization process of biological fertilizers, the main purpose of which is to solve the problem that the existing technology cannot directly perceive the energy utilization efficiency in the pulverization chamber and is difficult to perform adaptive closed-loop control of the pulverization process to avoid energy waste.

[0005] To achieve the above object, the present invention provides a method for dynamic stress control during a biofertilizer pulverization process, comprising the following steps: Step a, injecting a detection pulse airflow into the running pulverizing chamber at a fixed period; Step b, while injecting the detection pulse airflow, collecting the acoustic echo signal within a predetermined time length, and obtaining a humidity signal representing the moisture content of the bio-fertilizer to be crushed and a speed signal representing the operating state of the crusher rotor; Step c, determining an analysis frequency band of the acoustic echo signal according to the humidity signal, and determining the analysis frequency band to be a low frequency range when the humidity signal indicates that the moisture content is higher than a humidity threshold; otherwise, determining the analysis frequency band to be a wide frequency range; Step d, calculating the energy decay rate characteristic value of the acoustic echo signal within the determined analysis frequency band; Step e: adjusting a reference threshold range according to the speed signal to obtain a dynamic control threshold range; Step f: comparing the decay rate characteristic value calculated in step d with the dynamic control threshold range obtained in step e, and adjusting the feed speed of the pulverizer according to the comparison result.

[0006] Preferably, the calculation of the energy decay rate characteristic value in step d is achieved by the following method: dividing the predetermined time length into two consecutive time windows A and time window B on the time axis; calculating the total signal energy in time window A respectively and the total signal energy in time window B Then, the energy decay rate characteristic value is calculated by the following relationship: , , where the total signal energy is obtained by summing the squares of the signal amplitude values ​​of all sampling points in the corresponding time window.

[0007] Preferably, the adjustment of the feed speed in step f specifically includes: when the characteristic value of the energy decay rate is lower than the lower limit of the dynamic control threshold range, reducing the feed speed; when the characteristic value of the energy decay rate is higher than the upper limit of the dynamic control threshold range, increasing the feed speed.

[0008] Preferably, after reducing the feed rate, the method further comprises the step of injecting a cleaning pulse airflow into the pulverizing chamber, wherein the pressure of the cleaning pulse airflow is higher than the pressure of the detection pulse airflow.

[0009] Preferably, the adjustment of the speed signal in step e is specifically as follows: extracting the fundamental frequency of the wind whistle sound generated by the interaction between the detection pulse airflow and the pulverizer rotor from the initial segment of the acoustic echo signal; comparing the fundamental frequency of the wind whistle sound with the reference fundamental frequency corresponding to the rated speed of the pulverizer to obtain a frequency deviation; and adjusting the upper and lower limits of the reference threshold range according to a predetermined ratio based on the size and direction of the frequency deviation to obtain the dynamic control threshold range.

[0010] Preferably, before step a, a material type identification step is also included, which includes: at the initial stage of starting the pulverizer, injecting a sequence airflow consisting of at least two pulses with a predetermined time interval into the material to be tested entering the pulverizing chamber; collecting the acoustic response signal generated by the sequence airflow, and extracting the peak intensity ratio and ringing duration of the response signal as an acoustic fingerprint; comparing the acoustic fingerprint with a database containing acoustic fingerprints of multiple known materials to determine the type of the material to be tested; and based on the determined material type, calling the corresponding fixed period and the reference threshold range from the parameter library.

[0011] Preferably, it also includes a crushing medium wear status diagnosis step, which includes: when the crusher is running at no load, by injecting pulse airflow and analyzing its acoustic echo signal, obtaining and storing the reference resonant frequency characterizing the crushing medium; during the operation of the crusher, performing spectral analysis on the collected acoustic echo signal at predetermined time intervals to obtain the current resonant frequency; when the deviation of the current resonant frequency from the reference resonant frequency exceeds the wear frequency threshold, outputting a crushing medium wear warning signal.

[0012] Preferably, while outputting the pulverizing medium wear warning signal, the upper and lower limits of the dynamic control threshold range are also increased according to the size of the deviation.

[0013] Preferably, a state diagnosis step of a detection pulse airflow injection device is also included, which step includes: recording the initial sonic boom peak intensity of the acoustic echo signal collected each time the detection pulse airflow is injected; calculating the change rate of the initial sonic boom peak intensity in multiple consecutive injection cycles; when the absolute value of the change rate is higher than the device state change rate threshold, outputting an injection device maintenance warning signal.

[0014] Preferably, the method further includes the step of obtaining the operating current signal of the main motor of the crusher; and the adjustment of the feed speed in step f is performed based on a comprehensive consideration of the comparison result and the operating current signal.

[0015] Compared to existing technologies, the present invention offers the following advantages: It establishes an operational control method that directly provides insight into the energy utilization efficiency within the pulverizing chamber. This method no longer relies on the indirect and often delayed main motor current signal. Instead, it injects a probe pulse airflow into the chamber and analyzes the energy decay rate of its acoustic reverberation, obtaining a physical characteristic quantity that directly characterizes the fluidization state and energy transfer efficiency of the material within the chamber. This method enables the control system to shift from monitoring energy input to sensing energy efficiency, thereby avoiding the problem of hidden energy loss caused by excessive material interaction or wall retention. This establishes a closer connection between energy consumption and actual crushing work during the pulverizing process, and provides the ability to adapt to changes in critical operating conditions. By acquiring both the humidity signal of the pulverized material and the pulverizer speed signal in conjunction with the acoustic reverberation signal, the method can proactively address two of the most common types of interference. When changes in the material moisture content cause changes in the acoustic propagation characteristics, the method proactively avoids signal distortion by adjusting the analysis frequency band, ensuring the validity of the decay rate characteristic value. When the speed deviates due to factors such as power grid fluctuations, the method adjusts the reference threshold range to calibrate the control scale in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a timing diagram of the control process of the present invention; Figure 2 This is a comparison chart of the acoustic fingerprints of different materials in the present invention; Figure 3 This is a block diagram of the overall architecture of the system of the present invention.

[0017] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0018] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings. However, it should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] An embodiment of the present application provides a method for dynamic stress control in a bio-fertilizer pulverization process. The system consists of a detection pulse airflow injection device, an acoustic sensor, an auxiliary state sensor, and a control core. The operation mode is as follows: the control core drives the injection device to inject airflow into the pulverization chamber at a preset period, and simultaneously collects the signals fed back by the acoustic sensor and the auxiliary state sensor. By analyzing the characteristics of the energy dissipation rate in the acoustic signal and adjusting the analysis model and control target in combination with the real-time working conditions, the control instructions for the pulverizer operating parameters are generated, thereby forming a closed-loop control.

[0020] In the crushing and pulverizing operation of biofertilizers, a common technical problem in the existing technology is that the control system has difficulty in directly obtaining the actual fluidization state of the material in the crushing chamber. In particular, when processing materials with uneven components or moisture content, the control system relies on monitoring the operating current of the crusher's main motor. Due to the indirect nature of the signal response, it is often unable to effectively identify the excessive interaction state of the material retained in the chamber due to excessive crushing, or the wall retention state caused by sticky materials adhering to the chamber wall. Both states lead to energy consumption and deterioration of material quality. To directly quantify the dynamic behavior of the material in the chamber, the present method is configured to inject a detection pulse airflow into the operating chamber through an electromagnetic pneumatic valve provided on the crushing chamber at a fixed period. At the same time, an acoustic echo signal within a predetermined time length is collected through an acoustic sensor installed on the outer wall of the chamber. The energy decay rate of the acoustic echo signal can reflect the concentration of suspended particulate matter in the chamber and the smoothness of material circulation, thereby providing a physical observation for evaluating energy utilization efficiency.

[0021] In order to calculate the energy decay rate of the acoustic echo signal, the control core divides the collected acoustic signal of a predetermined time length into two consecutive time windows A and B on the time axis. By summing the squares of the signal amplitude values ​​of all sampling points in each time window, the total signal energy in time window A is obtained. and the total signal energy in time window B , and then according to the relationship Calculate the energy decay rate characteristic value ; The characteristic value Characterizes the speed of energy decay. When its value is high, it corresponds to a state where the amount of suspended material in the cavity is small, the flow is smooth, and the energy decays quickly. When its value is low, it corresponds to an excessive interactive state where the broken fine particles in the cavity are suspended and aggregated, forming an acoustic damping medium and the energy decay slows down. By comparing the value with the dynamic control threshold range, the feed speed of the crusher can be controlled in a closed loop; considering that the moisture content of the biofertilizer to be crushed is a variable that affects the propagation characteristics of sound waves, this method not only collects the acoustic echo signal, but also obtains the humidity signal that characterizes the moisture content of the material through the humidity sensor; before calculating the characteristic value of the energy decay rate, the control core determines the analysis frequency band based on the humidity signal, and its procedure is: compare the humidity signal with the preset humidity threshold, when the humidity signal indicates that the moisture content is lower than the threshold, determine the analysis frequency band to be a wide frequency range, when the humidity signal indicates that the moisture content is higher than the humidity threshold, switch the analysis frequency band to the low frequency range with weaker moisture absorption effect, this way of avoiding high-frequency signal distortion ensures the calculated The effectiveness of the value under different material humidity conditions; similarly, in order to avoid the interference of the crusher speed fluctuation on the control benchmark, this method also extracts the fundamental frequency of the wind whistle generated by the interaction of the detection pulse airflow and the rotor from the initial segment of the acoustic echo signal. The control core compares the real-time fundamental frequency with the reference fundamental frequency that is pre-calibrated to correspond to the rated speed of the crusher to obtain the frequency deviation, and adjusts the upper and lower limits of the benchmark threshold range according to the predetermined relationship based on the size and direction of the deviation to obtain a dynamic control threshold range that matches the actual speed. This procedure realizes the online calibration of the control model without increasing the hardware cost.

[0022] In obtaining the effective energy decay rate characteristic value After the adaptively adjusted dynamic control threshold range, the control core executes the control steps, and its logic is: when When the value is lower than the lower limit of the dynamic control threshold range, it indicates that the energy utilization efficiency in the cavity has decreased. At this time, the output instruction reduces the feed rate of the pulverizer. In some embodiments, a cleaning pulse airflow with a pressure higher than the detection pulse airflow can be injected to disturb and promote the discharge of retained materials. When the value is higher than the upper limit of the dynamic control threshold range, it indicates that the material supply in the cavity is insufficient, and at this time, an instruction is output to increase the feed speed; in some embodiments, in order to enhance the reliability of the system operation, the control core will also comprehensively consider the operating current signal of the main motor of the crusher when making decisions, forming a composite judgment basis; in order to cope with the differences in physical properties of different batches of materials, the method may also include a material type identification step. In this step, at the initial start-up of the crusher, a preset sequence airflow is injected into a small amount of material to be tested entering the cavity, and its acoustic response signal is collected, and the peak intensity ratio and ringing duration of the response signal are extracted as an acoustic fingerprint. The acoustic fingerprint is compared with a database containing acoustic fingerprints of multiple known materials pre-set in the control core to determine the type of material to be tested, and based on the determined type, the corresponding fixed period and reference threshold range are called from the parameter library.

[0023] In addition, this method can also be applied to the health status diagnosis of key components of the equipment. The first step is to diagnose the wear status of the crushing medium. This step obtains and stores the reference resonant frequency representing the initial state of the crushing medium by injecting a pulsed airflow and analyzing the spectrum of its acoustic echo signal when the crusher is unloaded. During the operation of the equipment, the collected acoustic echo signal is spectrally analyzed at predetermined time intervals to obtain the current resonant frequency. When the deviation of the current resonant frequency from the reference resonant frequency exceeds the wear frequency threshold, a crushing medium wear warning signal is output. At the same time, the dynamic control threshold range can be increased accordingly based on the size of the deviation to compensate for the change in crushing efficiency caused by medium wear. The second step is to diagnose the status of the pulsed airflow injection device. This step records and calculates the change rate of the initial sonic boom peak intensity of the acoustic echo signal in multiple consecutive injection cycles. When the absolute value of the change rate exceeds the device status change rate threshold, an injection device maintenance warning signal is output.

[0024] Example 1: In a bio-organic fertilizer production facility, a hammer mill on its production line is used to process fermented straw-based fertilizer. Due to storage and transportation reasons, the internal moisture content of this batch of materials is unevenly distributed. Most of the materials are dry materials with a moisture content of less than 30%, mixed with high-humidity and high-toughness fiber agglomerates with a moisture content of more than 45%. If a feedback control method relying on the operating current of the main motor is adopted, in order to avoid blockage caused by high-humidity agglomerates, the feed rate usually needs to be set to a low conservative value, thereby limiting the overall production efficiency.

[0025] In order to cope with this working condition, the dynamic stress control method disclosed in the above specific embodiment is deployed in the pulverizer. In the initial stage of processing dry materials, the system operates stably, and the acoustic echo signal collected by the acoustic sensor decays rapidly. The energy decay rate characteristic value calculated based on this is Maintained near the upper limit of the dynamic control threshold range, the control core accordingly maintains the crusher feed speed at a high level; when the high-humidity and high-tenacity fiber agglomerates enter the crushing chamber, the agglomerates are not immediately crushed but suspended and rolled in the chamber, causing the concentration of crushed particles in the chamber to increase. At this time, the main motor operating current does not immediately show an increase that can be used as a clear basis for judgment, but the acoustic environment has changed, and the attenuation process of the acoustic echo signal has slowed down. The control core calculates the The value has fallen below the lower limit of the dynamic control threshold range; at this time, two parallel responses occur in the system. One is based on The value is lower than the lower limit, and the control core immediately outputs a command to reduce the feed speed to provide time and space for the crushing chamber to decompose the current high-toughness material; secondly, the humidity sensor deployed at the feed inlet detects that the moisture content of the material exceeds the preset threshold. The humidity signal triggers the control core to switch the acoustic analysis frequency band from the wide frequency range to the low frequency range. This eliminates the interference of the high humidity environment on the propagation of sound waves and ensures The effectiveness of the value as a judgment basis is determined. Since the feed speed is adjusted early based on the effective acoustic state assessment, the crushing medium is able to gradually process the high-humidity fiber agglomerates before the material is excessively accumulated. During this process, the operating current of the main motor increases slightly, but does not reach the overload shutdown threshold.

[0026] After the high-humidity agglomerate is processed, the subsequent incoming material returns to a dry state, the fluidization state in the cavity returns to smooth, and the energy decay rate characteristic value calculated by the control core is It then returned to the dynamic control threshold range. Based on this, the system judged that the load capacity in the cavity had recovered and automatically increased the feed speed to the original higher level. No human intervention or shutdown interruption occurred in the entire crushing process, and under the condition of fluctuations in material properties, it maintained stable operation close to the rated capacity of the equipment.

[0027] Example 2: In order to quantitatively verify the actual operating effect of the above-mentioned dynamic stress control method, a test platform for comparative testing was built in this embodiment. The platform is based on an SFSP series hammer mill. Its feed is controlled by a screw feeder with adjustable speed. The test material is a batch of straw-based bio-fertilizer with an average moisture content of 15%. During the test, the same batch of materials with a moisture content of 35% after humidification treatment are added to it at predetermined time points to simulate the working conditions of material property fluctuations in industrial production. The test sets up a control group and a test group. The control group uses a PID controller to control the feed according to the operating current signal of the main motor of the crusher. The experimental group adopted the dynamic stress control method disclosed in the present invention; in this experiment, the injection period of the detection pulse airflow was set to 3 seconds. The setting of this parameter is intended to balance the real-time control and operating costs. Considering that the average residence time of the material in the selected model of crusher cavity is about 15 to 20 seconds, the 3-second injection period can sample and evaluate the fluidization state at least 5 times before the material completes a cycle, providing time resolution for control decisions. At the same time, the pressure of the injected airflow is set to 0.2MPa. The disturbance energy generated by this pressure can be ignored relative to the total energy input of the crusher main motor, thereby reducing the systematic impact of the detection behavior on the test results.

[0028] After the test, both groups first ran stably for 15 minutes. At the 16th minute, the same mass of high-humidity material was mixed into the feed synchronously and continued for 3 minutes. The response patterns of the two systems showed differences. In the control group, after the high-humidity material entered, the main motor current produced a hysteresis and a sharp rise, reaching a peak of 88.3A at the 17th minute. In order to avoid the risk of overload, its PID controller significantly reduced the feed speed to 80.2kg / min, causing significant oscillation in the system operation. In comparison, the energy decay rate characteristic value of the experimental group was At the beginning of the disturbance, it dropped rapidly from a stable value of 0.82 to 0.55. Its response time was earlier than the significant change of the motor current. Based on this, the system first adjusted the feeding speed down to 120.6 kg / min. At the same disturbance peak at the 17th minute, the main motor current was only 64.5 A, and the feeding speed was still maintained at 115.3 kg / min. If the feeding speed of the two groups is compared with time, it can be observed that the speed curve of the control group shows a sharp deep V-shaped drop after the disturbance occurs, while the speed curve of the test group shows a shallow dish shape with a gentle change, indicating that the feeding speed of the control group is 0.82. It shows that the control process of the latter is more stable. After the entire test cycle, the total processed material volume and total energy consumption of the two groups were calculated. The data showed that when encountering the same operating disturbance, the peak current of the test group was about 27% lower than that of the control group, and the fluctuation range of the feed rate was reduced by about 40%. Its final average unit energy consumption was 20.8kWh / t, which was about 4.6% lower than that of the control group's 21.8kWh / t. This shows that the method of regulating by monitoring the characteristic value of the energy decay rate can help maintain the system's operating stability and improve energy utilization efficiency when responding to fluctuations in material characteristics.

[0029] Example 3: This example combines Figures 1 to 3 , the dynamic stress control method in the biofertilizer crushing process is explained. Figure 1 As shown, the diagram is executed in a fixed time cycle. In this embodiment, it is set to be executed every 3 seconds. At the beginning of the cycle, the control core first sends a pulse injection instruction to the injection device, and the injection device then injects a detection pulse airflow into the crushing chamber. The airflow generates an acoustic echo in the cavity. The acoustic sensor is responsible for collecting this acoustic echo signal and transmitting it back to the control core; at the same time, the humidity sensor also collects the current material humidity signal and sends it to the control core. After receiving the two signals, the control core first determines the frequency band used for subsequent analysis based on the humidity signal, and then calculates the energy decay rate characteristic value of the acoustic echo signal. , and compare the characteristic value with a dynamic control threshold range, and enter an alt selection branch structure according to the comparison result: If the value is lower than the preset lower limit, it is judged that there is too much material in the cavity or the flow is not smooth, and the control core sends a command to the feed controller to reduce the feed speed; if If the value is higher than the preset upper limit, it is judged that the load in the cavity is insufficient, and the control core will issue a command to increase the feed speed; if If the value is within the threshold range, the system is judged to be operating in an ideal state, and the control core instructs the feed controller to maintain the current speed.

[0030] like Figure 2 As shown, the horizontal axis of the graph represents frequency in kilohertz ( ), the vertical axis represents the normalized amplitude. The figure contains three different curves, which correspond to the spectrum characteristics of the acoustic response signals generated by three different materials, straw-based fertilizer, fungus residue-based fertilizer and mixed fertilizer, when they are excited by the same pulse airflow. It can be clearly observed from the figure that the peak frequency of the response of straw-based fertilizer appears at about The peak frequencies of the response of the fungus residue-based fertilizer and the mixed fertilizer both appeared at about However, there is an obvious difference in the peak amplitude of the latter two. This acoustic feature that is significantly separable in the frequency domain due to the differences in the physical properties of the materials themselves, such as density, particle size, fiber content, etc., constitutes their respective unique acoustic fingerprints. When the production task is switched, the control system can automatically identify the material type and accurately call the corresponding control parameters by comparing the acoustic fingerprint collected at the initial startup with the known fingerprints in the database.

[0031] like Figure 3 As shown in the figure, the biofertilizer to be crushed first enters the pulverizer through a screw feeder, where the rotor inside the pulverizer crushes it, and the processed material becomes the finished product. During this process, the intelligent control core serves as the system's hub, receiving real-time signals from the acoustic sensor, humidity sensor, and main motor through the sensor signal stream. The intelligent control core integrates four major functional modules: a data analysis and decision engine for calculating attenuation rates, comparing thresholds, and generating decisions; a working condition adaptation module for adjusting analysis models and control targets based on humidity or speed signals; an equipment health diagnosis module for online diagnosis of pulverizing medium wear and injection device status; and a material type identification module for identifying the material's acoustic fingerprint and automatically matching parameters during initial startup. Based on the results of the comprehensive analysis and decision-making, the intelligent control core issues commands to the pulse airflow injection device and feed rate controller through the control command flow, respectively regulating the injection of the detection airflow and the feed rate of the screw feeder. This constructs a closed-loop control system that includes material processing, state perception, intelligent decision-making, and precise execution.

[0032] Example 4: In a biofertilizer production line where the aforementioned dynamic stress control method has been deployed, when the production task is switched and a new material with different physical properties from the original material, a high-density fungus residue-based fertilizer, needs to be processed, in order to adapt the control system to this new material, an offline engineering calibration procedure needs to be performed to determine its corresponding energy decay rate characteristic value working range and construct its acoustic fingerprint; when the calibration procedure is started, the fungus residue-based fertilizer is used as the material to be crushed and fed into the crusher through a screw feeder. During the operation of the crusher, the feed speed of the feeder is adjusted in a step-by-step manner to gradually increase it from a lower initial value. At each feed speed setting point, the operation is maintained until the current of the main motor of the crusher is consistent with the current calculated by the system. The values ​​all reach a stable state. Under this stable state, samples are taken at the discharge port and the particle size distribution of the finished powder is analyzed by sieving method. The average operating current of the main motor under the feeding speed and Stable readings.

[0033] By analyzing the data collected during the continuous adjustment process, the following corresponding relationship can be obtained: when the feed rate is in a lower range, the system calculates The value is above 0.75, at this time the finished product particle size is too fine and the unit energy consumption is high; with the increase of feed speed, when the main motor current does not increase significantly and the finished product particle size distribution meets the technical requirements, the corresponding The values ​​are distributed in a range of 0.5 to 0.7; if the feed rate is further increased, the particle size of the finished product begins to become coarser and exceeds the quality acceptance range. The value drops below 0.5, indicating that an excessive interaction state has occurred in the cavity. Based on this set of data, the energy decay rate characteristic value working range of the fungus residue-based fertilizer is determined to be 0.5 to 0.7, and the benchmark threshold range of the material is set as the lower limit. Equal to 0.5, upper limit Equal to 0.7.

[0034] After determining the baseline threshold range of the fungus residue-based fertilizer, the archiving step of its acoustic fingerprint is executed, the crushing chamber is emptied, and 500 grams of the material is fed into the crusher through the feeder when the crusher is running at no load, and the material type recognition step of the control system is started. The system automatically injects a sequence of airflow containing three short pulses into the cavity, and collects the acoustic response signal generated by its interaction with the material. The control core extracts the peak intensity ratio and ringing duration from the response signal as the time domain feature, and uses this set of feature vectors as the acoustic fingerprint of the fungus residue-based fertilizer, and compares it with the lower limit of 0.5. and an upper limit of 0.7 The parameters are associated and stored in the parameter library inside the control core. When the subsequent production task switches to this material, the system can automatically call this set of calibrated control parameters through acoustic fingerprint comparison at the initial startup.

[0035] Example 5: In this embodiment, in order to enable the dynamic stress control method to have the ability to perform online diagnosis of the wear state of the pulverizing medium, a reference resonant frequency calibration procedure needs to be executed each time the pulverizer is replaced with a new pulverizing medium. This procedure allows the pulverizer rotor to run at rated speed and no-load under the condition that the pulverizer stops feeding and the cavity is empty. At this time, the control system injects a set of ten detection pulse airflows and performs spectrum analysis on the acoustic echo signal generated by each pulse to extract the resonance peak frequency with the highest amplitude and the most stable in the preset frequency band of 3kHz to 5kHz. By calculating the average value of this group of frequencies, a reference resonant frequency that can characterize the inherent vibration characteristics of this set of new pulverizing media is obtained. And store it in the control core.

[0036] After the pulverizer enters regular production operation, the control system automatically performs an online wear diagnosis every 100 working hours based on the cumulative operating time. At this diagnostic moment, the system uses the acoustic echo signal collected by a regular detection pulse airflow to perform spectrum analysis and obtain the current resonant frequency. The system then compares the current resonant frequency with the stored reference resonant frequency. Compare, its judgment logic is to calculate the frequency deviation percentage The deviation value is compared with the preset wear frequency threshold of 5%, which is pre-set based on the wear mechanism analysis of the crushing media of this model. When it is higher than 5%, the system will output a crushing medium wear warning signal. At the same time, the system will also make compensatory adjustments to the dynamic control threshold range based on the size of the deviation, that is, multiply the upper and lower limits of the original benchmark threshold range by a coefficient. , moderately increase the threshold to cope with the changes in crushing efficiency caused by media wear, and maintain the stability of finished product quality before the media is replaced.

[0037] Example 6: In order to enable the dynamic stress control method to adapt online to the deviation of the actual rotor speed of the pulverizer caused by grid voltage fluctuations or changes in the load characteristics of the motor itself, it is necessary to perform a reference fundamental frequency calibration procedure for speed monitoring when the system is first deployed. After confirming that the pulverizer is running stably at its rated speed under rated voltage, the control system injects a set of 20 detection pulse airflows and performs a fast Fourier transform on the initial 50 milliseconds of the acoustic echo signal collected each time to determine the fundamental frequency of the wind whistle generated by the interaction between the airflow and the rotor. By calculating the average value of the set of fundamental frequency readings, a reference fundamental frequency corresponding to the rated speed is obtained. And store it in the control core.

[0038] During normal production operation, the control core calculates the energy decay rate characteristic value of each cycle At the same time, the initial segment of the periodic acoustic echo signal is also analyzed to obtain the real-time fundamental frequency of the wind whistle. , in the Before comparing with the dynamic control threshold range, the system will first adjust the lower limit of the threshold range according to the deviation of the speed. Compensatory adjustment is made. The inherent logic of the adjustment is that the reduction of the rotation speed will lead to a decrease in crushing efficiency. Therefore, it is necessary to moderately relax the restriction on the concentration of suspended materials in the cavity, that is, to reduce The value of , its adjustment relationship is defined as ,in, is the uncompensated reference lower limit, and It is the actual lower limit value obtained after real-time speed compensation.

[0039] When a system that has completed this calibration and configuration encounters a grid voltage drop during operation, causing its actual speed to drop by 3% compared to the rated speed, the system will be notified of this state in real time through the proportional decrease in the fundamental frequency of the whistle sound. In each subsequent control cycle, the system will automatically apply the aforementioned adjustment relationship to adjust the lower threshold value by 3%. The corresponding adjustment is reduced by 3%. This fine-tuning enables the control system to correctly interpret the slight changes in the fluidization state of the material in the cavity caused by the natural reduction in speed, avoiding unnecessary reduction in the feed rate due to excessive interaction caused by misjudging this state as impending blockage. As a result, the entire control method achieves closed-loop self-calibration of its own core operating parameters without adding external speed sensors, maintaining control accuracy under different operating conditions.

[0040] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for dynamic stress control in a biofertilizer pulverization process, characterized in that: The following steps are involved: Step a, injecting a detection pulse airflow into the running pulverizing chamber at a fixed period; Step b, while injecting the detection pulse airflow, collecting the acoustic echo signal within a predetermined time length, and obtaining a humidity signal representing the moisture content of the bio-fertilizer to be crushed and a speed signal representing the operating state of the crusher rotor; Step c, determining an analysis frequency band of the acoustic echo signal according to the humidity signal, and determining the analysis frequency band to be a low frequency range when the humidity signal indicates that the moisture content is higher than a humidity threshold; otherwise, determining the analysis frequency band to be a wide frequency range; Step d, calculating the energy decay rate characteristic value of the acoustic echo signal within the determined analysis frequency band; Step e: adjusting a reference threshold range according to the speed signal to obtain a dynamic control threshold range; Step f: comparing the decay rate characteristic value calculated in step d with the dynamic control threshold range obtained in step e, and adjusting the feed speed of the pulverizer according to the comparison result.

2. The method for dynamic stress control in a biofertilizer crushing process according to claim 1, characterized in that: The calculation of the energy decay rate characteristic value in step d is achieved by dividing the predetermined time length into two consecutive time windows A and time window B on the time axis; calculating the total signal energy in time window A and time window B respectively. and the total signal energy in time window B Then, the energy decay rate characteristic value is calculated by the following relationship: , , where the total signal energy is obtained by summing the squares of the signal amplitude values ​​of all sampling points in the corresponding time window.

3. The method for dynamic stress control in a biofertilizer crushing process according to claim 1, characterized in that: The adjustment of the feed speed in step f specifically includes: when the characteristic value of the energy decay rate is lower than the lower limit of the dynamic control threshold range, reducing the feed speed; when the characteristic value of the energy decay rate is higher than the upper limit of the dynamic control threshold range, increasing the feed speed.

4. The method for dynamic stress control during the pulverization process of biological fertilizer according to claim 3, characterized in that: After reducing the feeding speed, the method further includes the step of injecting a cleaning pulse airflow into the pulverizing chamber, wherein the pressure of the cleaning pulse airflow is higher than the pressure of the detection pulse airflow.

5. The method for dynamic stress control in a biofertilizer crushing process according to claim 1, characterized in that: The adjustment of the speed signal in step e is specifically as follows: extracting the fundamental frequency of the wind whistle sound generated by the interaction between the detection pulse airflow and the pulverizer rotor from the initial segment of the acoustic echo signal; comparing the fundamental frequency of the wind whistle sound with the reference fundamental frequency corresponding to the rated speed of the pulverizer to obtain a frequency deviation; and adjusting the upper and lower limits of the reference threshold range according to a predetermined ratio based on the size and direction of the frequency deviation to obtain the dynamic control threshold range.

6. The method for dynamic stress control during the biofertilizer crushing process according to claim 1, characterized in that: Before step a, a material type identification step is also included, which includes: at the initial stage of the pulverizer startup, injecting a sequence airflow consisting of at least two pulses with a predetermined time interval into the material to be tested entering the pulverizing chamber; collecting the acoustic response signal generated by the sequence airflow, and extracting the peak intensity ratio and ringing duration of the response signal as an acoustic fingerprint; comparing the acoustic fingerprint with a database containing acoustic fingerprints of multiple known materials to determine the type of the material to be tested; and based on the determined material type, calling the corresponding fixed period and the reference threshold range from the parameter library.

7. The method for dynamic stress control in a biofertilizer pulverization process according to claim 1, characterized in that: It also includes a pulverizing medium wear status diagnosis step, which includes: when the pulverizer is running at no load, by injecting a pulsed airflow and analyzing its acoustic echo signal, obtaining and storing a reference resonant frequency characterizing the pulverizing medium; during the operation of the pulverizer, performing spectral analysis on the collected acoustic echo signal at predetermined time intervals to obtain the current resonant frequency; when the deviation of the current resonant frequency relative to the reference resonant frequency exceeds the wear frequency threshold, outputting a pulverizing medium wear warning signal.

8. The method for dynamic stress control during the biofertilizer pulverization process according to claim 7, characterized in that: While outputting the pulverizing medium wear warning signal, the upper and lower limits of the dynamic control threshold range are also increased according to the size of the deviation.

9. The method for dynamic stress control during the biofertilizer pulverization process according to claim 1, characterized in that: The system also includes a state diagnosis step for a detection pulse airflow injection device, which includes: recording the initial sonic boom peak intensity of the acoustic echo signal collected each time the detection pulse airflow is injected; calculating the rate of change of the initial sonic boom peak intensity over multiple consecutive injection cycles; and outputting an injection device maintenance warning signal when the absolute value of the change rate exceeds a device state change rate threshold.

Images