Drying process management control system based on recycling of lithium iron phosphate battery

Abstract

The invention relates to a drying process management control system based on lithium iron phosphate battery recycling. The drying process management control system comprises a recycled material conveying monitoring module, a recycled material conveying evaluation module, a workshop monitoring analysis module, a workshop drying evaluation module and a drying workshop supervision terminal. The material paving performance in the conveying process is accurately fed back in real time through the recycled material conveying monitoring module, and the recycled material conveying evaluation module comprehensively analyzes the conveying performance of recycled materials so as to guarantee the conveying effect of the recycled materials. The workshop monitoring analysis module analyzes the drying environment in the drying workshop to achieve timely regulation and control of the drying environment, and the workshop drying evaluation module evaluates the drying control performance of the drying workshop to timely enhance workshop environment monitoring and take reasonable improvement measures. And the drying effect and the drying efficiency of the lithium iron phosphate recycled material are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of battery recycling management and control, and in particular to a drying process management and control system based on the recycling of lithium iron phosphate batteries. Background Art

[0002] With the vigorous development of the new energy industry, lithium iron phosphate batteries, as a new energy product with high energy density, high customizability, low cost, many charge and discharge times, and high safety performance, are widely used in electric vehicles, public transportation, energy storage, ships, remote control toys, and smart phones. However, the recycling of waste lithium iron phosphate batteries faces many challenges, especially the control and management of drying workshops, which directly affects the recycling efficiency and product quality.

[0003] At present, in the management of the drying process of lithium iron phosphate battery recycling, the temperature in the workshop is mainly monitored and controlled. It is impossible to effectively monitor the transportation status of lithium iron phosphate recycled materials in the drying workshop and reasonably evaluate the transportation performance. It is also difficult to identify abnormalities in the workshop drying environment and accurately evaluate the environmental control performance, which is not conducive to ensuring the drying effect and drying efficiency of lithium iron phosphate recycled materials.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a drying process management and control system based on the recycling of lithium iron phosphate batteries to solve the technical defects proposed by the background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a drying process management and control system based on the recycling of lithium iron phosphate batteries, including a recycling material transportation monitoring module, a recycling material transportation evaluation module, a workshop monitoring and analysis module, a workshop drying evaluation module and a drying workshop supervision terminal;

[0007] When the recycled materials of lithium iron phosphate batteries are dried, the conveyor belt of the conveying equipment conveys the recycled materials, and the recycled material conveying monitoring module monitors the recycled materials spread on the conveyor belt and analyzes their paving performance, thereby determining whether to assign the paving symbol ZP-1, and when the paving symbol ZP-1 is assigned, it is sent to the recycled material conveying evaluation module;

[0008] The recycling material transportation assessment module will conduct a comprehensive analysis on the transportation performance of recycled materials, generate a transportation assessment qualified signal or a transportation assessment early warning signal through analysis, and send the transportation assessment qualified signal or the transportation assessment early warning signal to the supervision end of the drying workshop;

[0009] The workshop monitoring and analysis module analyzes the drying environment in the drying workshop, and determines whether the drying workshop is in an abnormal drying state through analysis. When it is determined that the drying workshop is in an abnormal drying state, the corresponding judgment information is sent to the workshop drying evaluation module and the drying workshop supervision end, and when it is determined that the drying workshop is in an abnormal drying state, the drying environment of the drying workshop is adaptively regulated;

[0010] The workshop drying assessment module will evaluate the drying control performance of the drying workshop, generate a drying assessment qualified signal or a drying assessment early warning signal through analysis, and send the drying assessment qualified signal or the drying assessment early warning signal to the drying workshop supervision end; the drying workshop supervision end will issue a corresponding early warning when it receives the transmission assessment early warning signal or the drying assessment early warning signal.

[0011] Furthermore, the specific analysis process of the recycling material transportation monitoring module is as follows:

[0012] The paving thickness of the recycled materials at several positions on the conveyor belt is collected, and the variance of the paving thickness at all positions is calculated to obtain the paving non-uniformity value, and the paving thickness at the corresponding position is numerically compared with the preset paving thickness range. If the paving thickness is not within the preset paving thickness range, the corresponding position is marked as a thick outlier point, and the number ratio of the thick outliers is obtained and marked as a poor paving thickness value;

[0013] The paving unevenness value and the paving thickness inferiority value are numerically compared with the preset paving unevenness threshold and the preset paving thickness inferiority threshold respectively. If the paving unevenness value or the paving thickness inferiority value exceeds the corresponding preset threshold, the paving symbol ZP-1 is assigned.

[0014] Furthermore, if the paving non-uniformity value and the paving thickness poor value do not exceed the corresponding preset threshold value, the paving thickness at all positions is averaged to obtain the paving thickness value, and the difference between the paving thickness value and the median of the preset paving thickness range is calculated and the absolute value is taken to obtain the paving thickness inspection value;

[0015] The transport paving coefficient is obtained by numerically calculating the paving unevenness value, the paving thickness defect value and the paving thickness inspection value. The transport paving coefficient is numerically compared with the preset transport paving coefficient threshold. If the transport paving coefficient exceeds the preset transport paving coefficient threshold, the paving symbol ZP-1 is assigned.

[0016] Furthermore, the specific analysis process of the recycling material transportation evaluation module includes:

[0017] The number of times the paving symbol ZP-1 is generated per unit time is obtained and marked as the paving abnormality detection value, and the paving abnormality detection value is numerically compared with the preset paving abnormality detection threshold. If the paving abnormality detection value exceeds the preset paving abnormality detection threshold, a transportation assessment warning signal is generated;

[0018] If the paving abnormality detection value does not exceed the preset paving abnormality detection threshold, the variance value of the conveying speed of the recycled materials per unit time is used to obtain the conveying fluctuation value, and the conveying time per unit time during which the conveying speed is not within the preset standard conveying speed range is marked as the conveying speed abnormality value;

[0019] The vibration amplitude of the conveyor belt during the conveying process is collected, and the average of all vibration amplitudes per unit time is calculated to obtain the conveying vibration condition value, and the conveying time length during which the vibration amplitude per unit time exceeds the preset vibration amplitude threshold is marked as the conveying vibration abnormality value;

[0020] The recycled material output evaluation value is obtained by numerically calculating the paving abnormality value, conveying fluctuation value, conveying speed abnormality value, conveying vibration condition value and conveying vibration abnormality value, and the recycled material output evaluation value is numerically compared with the preset recycled material output evaluation threshold value. If the recycled material output evaluation value exceeds the preset recycled material output evaluation threshold value, a conveying evaluation warning signal is generated; if the recycled material output evaluation value does not exceed the preset recycled material output evaluation threshold value, a conveying evaluation qualified signal is generated.

[0021] Furthermore, the specific analysis process of the drying workshop monitoring and analysis module includes:

[0022] A number of monitoring points are set in the drying workshop, and the poor drying points in the drying workshop are determined through analysis; the number of poor drying points in the drying workshop is obtained and the ratio is calculated with the total number of monitoring points to obtain the poor condition value of the drying workshop, and the average of the dry point abnormal control table values ​​of all monitoring points is calculated to obtain the dry point condition value, and the dry point abnormal control table value with the largest value is marked as the dry shop table amplitude;

[0023] The drying workshop monitoring value is obtained by numerically calculating the drying workshop poor condition value, the drying workshop surface condition value and the drying workshop surface amplitude value. The drying workshop monitoring value is numerically compared with the preset drying workshop monitoring threshold value. If the drying workshop monitoring value exceeds the preset drying workshop monitoring threshold value, it is judged that the drying workshop is in an abnormal drying state.

[0024] Furthermore, the specific analysis process to determine the drying inferior surface points in the drying workshop is as follows:

[0025] The ambient temperature and ambient humidity of the corresponding monitoring point are collected, and the deviation value of the ambient temperature compared with the set standard drying temperature is marked as the drying temperature control abnormality coefficient, and the ratio of the ambient humidity to the set standard drying humidity threshold is marked as the drying humidity control abnormality coefficient, and the air flow velocity of the corresponding monitoring point is collected and the deviation value of the air flow velocity compared with the set standard air flow velocity is marked as the drying airflow abnormality coefficient;

[0026] The drying point control abnormality table value is obtained by numerically calculating the drying temperature control abnormality coefficient, the drying humidity control abnormality coefficient and the drying airflow abnormality coefficient. The drying point control abnormality table value is numerically compared with the preset drying point control abnormality table threshold. If the drying point control abnormality table value exceeds the preset drying point control abnormality table threshold, the corresponding monitoring point will be marked as a poor drying table point.

[0027] Furthermore, the specific analysis process of the workshop drying evaluation module is as follows:

[0028] When it is determined that the drying workshop is in an abnormal drying state, the timing starts and ends until the abnormal drying state in the drying workshop ends, thereby obtaining the abnormal drying time;

[0029] All drying abnormality durations within a unit time are obtained and summed up to obtain a total drying abnormality duration value, and the drying abnormality duration is numerically compared with a preset drying abnormality duration threshold. If the drying abnormality duration exceeds the preset drying abnormality duration threshold, the corresponding drying abnormality duration is marked as a drying warning duration; the number of drying warning durations within a unit time is obtained and marked as a drying warning detection value;

[0030] And the mean of all drying workshop monitoring values ​​within unit time is calculated to obtain the drying workshop control value, the workshop drying control evaluation value is obtained by numerically calculating the total drying abnormality time value, the drying early warning inspection value and the drying workshop control value, and the workshop drying control evaluation value is numerically compared with the preset workshop drying control evaluation threshold. If the workshop drying control evaluation value exceeds the preset workshop drying control evaluation threshold, a drying evaluation early warning signal is generated; if the workshop drying control evaluation value does not exceed the preset workshop drying control evaluation threshold, a drying evaluation qualified signal is generated.

[0031] Furthermore, the drying workshop supervision end is communicated with the drying control decision output module. The drying control decision output module is used to set the detection period, and conduct a control planning decision analysis on the drying workshop for recycling lithium iron phosphate batteries. The analysis is used to determine whether to generate a control enhancement signal, and the control enhancement signal is sent to the drying workshop supervision end. When the drying workshop supervision end receives the control enhancement signal, it issues a corresponding warning.

[0032] Furthermore, the specific analysis process of the control planning decision analysis is as follows:

[0033] The total time that the drying workshop is in working state during the detection period is obtained and marked as the workshop operation time value, and the number of times the drying workshop generates a transportation evaluation warning signal and the number of times the drying workshop generates a drying evaluation warning signal during the detection period are obtained and marked as the transportation evaluation abnormality value and the drying evaluation abnormality value respectively;

[0034] The number of times the single working time of the drying workshop exceeds the preset single working time threshold value during the detection period is collected and marked as the operation time control abnormal value, and the number of times the drying workshop is suspended due to a fault during the detection period is collected and marked as the drying fault value;

[0035] The drying workshop planning coefficient is obtained by numerically calculating the workshop operation time value, conveying evaluation value, drying evaluation value, operation time control abnormal value and drying fault value. The drying workshop planning coefficient is numerically compared with the preset drying workshop planning coefficient threshold. If the drying workshop planning coefficient exceeds the preset drying workshop planning coefficient threshold, a management and control enhancement signal is generated.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] 1. In the present invention, the material spreading performance of the conveying process is accurately fed back in real time through the recycled material conveying monitoring module, the recycled material conveying evaluation module will conduct a comprehensive analysis on the conveying performance of the recycled material to ensure the conveying effect of the recycled material, the workshop monitoring and analysis module will analyze the drying environment in the drying workshop to achieve timely regulation of the drying environment, and the workshop drying evaluation module will accurately evaluate the drying control performance of the drying workshop and give a timely warning, which is conducive to ensuring the drying effect and drying efficiency of the lithium iron phosphate recycled material;

[0038] 2. In the present invention, the drying control decision output module is used to conduct control planning decision analysis on the drying workshop for lithium iron phosphate battery recycling to determine whether to generate a control enhancement signal. It can reasonably analyze and accurately determine the control status of the drying workshop during the detection period, and timely strengthen the subsequent control of the drying workshop, further ensuring the subsequent drying stability and drying effect of the lithium iron phosphate recycled materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0040] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0041] Figure 2 This is a system block diagram of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] Embodiment 1: Figure 1 As shown, the drying process management and control system based on the recycling of lithium iron phosphate batteries proposed in the present invention includes a recycling material transportation monitoring module, a recycling material transportation evaluation module, a workshop monitoring and analysis module, a workshop drying evaluation module and a drying workshop supervision terminal;

[0044] When the recycled materials of lithium iron phosphate batteries are dried, the conveyor belt of the conveying equipment in the drying workshop transports the recycled materials. The recycled material transportation monitoring module monitors the recycled materials spread on the conveyor belt and analyzes their paving performance, and determines whether to assign the paving symbol ZP-1 based on this;

[0045] When the paving symbol ZP-1 is assigned, it is sent to the recycled material transportation evaluation module, which can not only accurately feedback the material paving performance of the transportation process in real time, but also provide data support for the analysis process of the recycled material transportation evaluation module to ensure the accuracy of its analysis results; the specific analysis process of the recycled material transportation monitoring module is as follows:

[0046] The paving thickness of the recycled materials at several positions on the conveyor belt is collected, and the variance of the paving thickness at all positions is calculated to obtain the paving non-uniformity value. The larger the value of the paving non-mean value is, the more uneven the thickness of the recycled materials distributed on the conveyor belt is.

[0047] The paving thickness at the corresponding position is numerically compared with the preset paving thickness range. If the paving thickness is not within the preset paving thickness range, indicating that the material paving thickness at the corresponding position does not meet the requirements, the corresponding position is marked as a thick outlier point, and the number ratio of the thick outliers is obtained and marked as a poor paving thickness value.

[0048] The paving unevenness value and the paving thickness poorness value are numerically compared with the preset paving unevenness threshold value and the preset paving thickness poorness threshold value respectively. If the paving unevenness value or the paving thickness poorness value exceeds the corresponding preset threshold value, indicating that the material paving performance on the conveyor belt at the corresponding moment is poor, the paving symbol ZP-1 is assigned.

[0049] If the paving unevenness value and the paving thickness poor value do not exceed the corresponding preset threshold value, the paving thickness of all positions is averaged to obtain the paving thickness value, and the difference between the paving thickness value and the median of the preset paving thickness range is calculated and the absolute value is taken to obtain the paving thickness inspection value;

[0050] The conveying paving coefficient LX is obtained by numerically calculating the paving non-uniformity value LF, the paving thickness defect value LP and the paving thickness inspection value LP through the formula LX=ur1*LF+ur2*LP+ur3*LP / (ur1+ur2); wherein ur1, ur2 and ur3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the conveying paving coefficient LX, the worse the material paving condition on the conveyor belt is overall;

[0051] The transport paving coefficient LX is numerically compared with the preset transport paving coefficient threshold. If the transport paving coefficient LX exceeds the preset transport paving coefficient threshold, it indicates that the material paving condition on the conveyor belt is generally poor, which is not conducive to ensuring the drying effect and drying efficiency of the recycled materials, and the paving symbol ZP-1 is assigned.

[0052] The recycling material transportation assessment module will conduct a comprehensive analysis on the transportation performance of recycled materials, generate a transportation assessment qualified signal or a transportation assessment early warning signal through analysis, and send the transportation assessment qualified signal or the transportation assessment early warning signal to the supervision end of the drying workshop;

[0053] When the dry workshop supervisor receives the transportation assessment warning signal, it will issue a corresponding warning. It can conduct a comprehensive analysis of the transportation performance of lithium iron phosphate recycling materials and issue a timely warning to remind supervisors to conduct traceability investigations and make reasonable regulatory measures, thereby ensuring the transportation effect of recycled materials and reducing the difficulty of supervision for supervisors. The specific analysis process of the recycling material transportation assessment module is as follows:

[0054] The number of times the paving symbol ZP-1 is generated per unit time is obtained and marked as the paving abnormality detection value, and the paving abnormality detection value is numerically compared with the preset paving abnormality detection threshold. If the paving abnormality detection value exceeds the preset paving abnormality detection threshold, it indicates that the paving execution during the transportation process is relatively abnormal, and a transportation assessment warning signal is generated;

[0055] If the paving abnormal detection value does not exceed the preset paving abnormal detection threshold, the variance value of the conveying speed of the recycled material in unit time is used to obtain the conveying fluctuation value, wherein the larger the value of the conveying fluctuation value is, the more unstable the conveying process is in unit time;

[0056] The conveying speed is compared with the preset conveying speed threshold in real time, and the conveying time length during which the conveying speed is not within the preset standard conveying speed range per unit time is marked as a conveying speed anomaly value; the vibration amplitude of the conveyor belt during the conveying process is collected, and the average of all vibration amplitudes per unit time is calculated to obtain a conveying vibration condition value, and the vibration amplitude is compared with the preset vibration amplitude threshold in real time, and the conveying time length during which the vibration amplitude per unit time exceeds the preset vibration amplitude threshold is marked as a conveying vibration anomaly value;

[0057] The recycled material transport evaluation value WL is obtained by numerically calculating the paving abnormality inspection value WS, the transport fluctuation value WY, the transport speed abnormality value WN, the transport vibration condition value WR and the transport vibration abnormality value WP through the formula WL=rq1*WS+rq2*WY+rq3*WN+rq4*WR+rq5*WP; wherein rq1, rq2, rq3, rq4 and rq5 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the recycled material transport evaluation value WL, the worse the overall transport performance of the recycled material per unit time is.

[0058] The recycled material input evaluation value WL is numerically compared with the preset recycled material input evaluation threshold. If the recycled material input evaluation value WL exceeds the preset recycled material input evaluation threshold, indicating that the transportation performance of the recycled material per unit time is generally poor, then a transportation evaluation warning signal is generated; if the recycled material input evaluation value WL does not exceed the preset recycled material input evaluation threshold, indicating that the transportation performance of the recycled material per unit time is generally good, then a transportation evaluation qualified signal is generated.

[0059] The workshop monitoring and analysis module analyzes the drying environment in the drying workshop, and determines whether the drying workshop is in an abnormal drying state through analysis. When it is determined to be in an abnormal drying state, the corresponding judgment information is sent to the workshop drying evaluation module and the drying workshop supervision end, and when it is determined to be in an abnormal drying state, the drying environment of the drying workshop is adaptively regulated to ensure the drying effect and drying efficiency for lithium iron phosphate recovery materials; the specific analysis process of the drying workshop monitoring and analysis module is as follows:

[0060] Several monitoring points are set in the drying workshop, and the ambient temperature and ambient humidity of the corresponding monitoring points are collected. The deviation value of the ambient temperature compared with the set standard drying temperature is marked as the drying temperature control abnormality coefficient, and the ratio of the ambient humidity to the set standard drying humidity threshold is marked as the drying humidity control abnormality coefficient. The air flow velocity at the corresponding monitoring point is collected and the deviation value from the set standard air flow velocity is marked as the drying airflow abnormality coefficient;

[0061] The drying point control abnormality table value XM is obtained by numerically calculating the drying temperature control abnormality coefficient XF, the drying humidity control abnormality coefficient XS and the drying airflow abnormality coefficient XP through the formula XM=up1*XF+up2*XS+up3*XP; wherein up1, up2 and up3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the drying point control abnormality table value XM is, the worse the real-time environmental condition of the corresponding monitoring point in the drying workshop is;

[0062] The drying point control abnormality meter value XM is numerically compared with the preset drying point control abnormality meter threshold value. If the drying point control abnormality meter value XM exceeds the preset drying point control abnormality meter threshold value, it indicates that the real-time environmental condition of the corresponding monitoring point in the drying workshop is poor, and the corresponding monitoring point is marked as a poor drying meter point;

[0063] The number of poor drying points in the drying workshop is obtained and the ratio is calculated with the total number of monitoring points to obtain the poor condition value of the drying workshop, and the average of the abnormal drying point values ​​of all monitoring points is calculated to obtain the condition value of the drying workshop, and the abnormal drying point value with the largest value is marked as the amplitude of the drying workshop;

[0064] The drying workshop monitoring value NY is obtained by numerically calculating the drying workshop poor condition value NL, the drying workshop surface condition value NG and the drying workshop surface amplitude value NW through the formula NY=ru1*NL+(ru2*NG+ru3*NW) / 2; wherein ru1, ru2 and ru3 are preset proportional coefficients, ru1>ru2>ru3>0; and the larger the value of the drying workshop monitoring value NY is, the worse the current environmental condition of the drying workshop is in general;

[0065] The drying workshop monitoring value NY is numerically compared with the preset drying workshop monitoring threshold. If the drying workshop monitoring value NY exceeds the preset drying workshop monitoring threshold, it indicates that the current environmental conditions of the drying workshop are generally poor, and the drying workshop is judged to be in an abnormal drying state.

[0066] The workshop drying assessment module will evaluate the drying control performance of the drying workshop, generate a drying assessment qualified signal or a drying assessment early warning signal through analysis, and send the drying assessment qualified signal or the drying assessment early warning signal to the drying workshop supervision end. When the drying workshop supervision end receives the drying assessment early warning signal, it will issue a corresponding early warning, which can accurately evaluate the environmental control status in the drying workshop and issue a timely early warning to remind the supervisors to strengthen the workshop environment monitoring and make reasonable improvement measures, so as to further ensure the drying effect and drying efficiency of lithium iron phosphate recovery materials; the specific analysis process of the workshop drying assessment module is as follows:

[0067] When it is determined that the drying workshop is in an abnormal drying state, the timing starts and the abnormal drying state ends in the drying workshop, and the abnormal drying time is obtained accordingly; wherein, the larger the value of the abnormal drying time is, the worse the control condition for the corresponding abnormal drying state is;

[0068] All drying abnormality durations within a unit time are obtained and summed up to obtain a total drying abnormality duration value, and the drying abnormality duration is numerically compared with a preset drying abnormality duration threshold. If the drying abnormality duration exceeds the preset drying abnormality duration threshold, the corresponding drying abnormality duration is marked as a drying warning duration; the number of drying warning durations within a unit time is obtained and marked as a drying warning detection value;

[0069] And all the drying workshop monitoring values ​​within a unit time are averaged to obtain the drying workshop control value, and the drying abnormal total time value QS, the drying early warning inspection value QN and the drying workshop control value QF are numerically calculated by the formula QP=hy2*QN+hy1*QS+hy3*QF to obtain the workshop drying control evaluation value QP; wherein hy1, hy2, hy3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the workshop drying control evaluation value QP is, the worse the environmental control performance of the drying workshop is in general within a unit time;

[0070] The workshop drying control evaluation value QP is numerically compared with the preset workshop drying control evaluation threshold. If the workshop drying control evaluation value QP exceeds the preset workshop drying control evaluation threshold, it indicates that the environmental control performance of the drying workshop per unit time is generally poor, and a drying evaluation early warning signal is generated; if the workshop drying control evaluation value QP does not exceed the preset workshop drying control evaluation threshold, it indicates that the environmental control performance of the drying workshop per unit time is generally good, and a drying evaluation qualified signal is generated.

[0071] Embodiment 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the drying workshop supervision end is connected to the drying control decision output module by communication, and the drying control decision output module is used to set the detection period, preferably, the detection period is seven days; the control planning decision analysis is performed on the drying workshop for lithium iron phosphate battery recycling, and the analysis is used to determine whether to generate a control enhancement signal;

[0072] The control enhancement signal is sent to the supervision end of the drying workshop. When the supervision end of the drying workshop receives the control enhancement signal, it issues a corresponding warning, which can reasonably analyze and accurately judge the control status of the drying workshop during the detection period, and strengthen the subsequent control of the drying workshop when the control enhancement signal is generated, so as to ensure the subsequent drying stability and drying effect of the lithium iron phosphate recycled materials; the specific analysis process of the control planning decision analysis is as follows:

[0073] The total time that the drying workshop is in working state during the detection period is obtained and marked as the workshop operation time value, and the number of times the drying workshop generates a transportation evaluation warning signal and the number of times the drying workshop generates a drying evaluation warning signal during the detection period are obtained and marked as the transportation evaluation abnormality value and the drying evaluation abnormality value respectively;

[0074] The number of times the single working time of the drying workshop exceeds the preset single working time threshold value during the detection period is collected and marked as the operation time control abnormal value, and the number of times the drying workshop is suspended due to a fault during the detection period is collected and marked as the drying fault value;

[0075] The drying workshop planning coefficient MY is obtained by numerically calculating the workshop operation time value MS, the transportation evaluation value MT, the drying evaluation value ML, the operation time control value MP and the drying fault value MF through the formula MY=(b2*MT+b3*ML+b4*MP+b5*MF) / (b1*MS+1.625); wherein b1, b2, b3, b4 and b5 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the drying workshop planning coefficient MY is, the worse the control condition of the drying workshop during the detection period is, and the more it is necessary to strengthen the subsequent control of the drying workshop;

[0076] The drying workshop planning coefficient MY is numerically compared with the preset drying workshop planning coefficient threshold. If the drying workshop planning coefficient MY exceeds the preset drying workshop planning coefficient threshold, it indicates that the control status of the drying workshop during the detection period is poor, and the subsequent control of the drying workshop needs to be strengthened, then a control enhancement signal is generated.

[0077] The working principle of the present invention is as follows: when in use, the recycled material conveying monitoring module is used to monitor and analyze the recycled material spread on the conveyor belt to provide real-time and accurate feedback on the material spreading performance of the conveying process; the recycled material conveying evaluation module will conduct a comprehensive analysis on the conveying performance of the recycled material, and when a conveying evaluation warning signal is generated, the supervisor will be reminded to conduct a traceback investigation and make reasonable control measures to ensure the conveying effect of the recycled material; and the workshop monitoring and analysis module will analyze the drying environment in the drying workshop to determine whether the drying workshop is in an abnormal drying state; when it is determined to be in an abnormal drying state, the drying environment of the drying workshop is adaptively controlled; and the workshop drying evaluation module will evaluate the drying control performance of the drying workshop, and when a drying evaluation warning signal is generated, the supervisor will be reminded to strengthen workshop environment monitoring and make reasonable improvement measures, which is beneficial to ensuring the drying effect and drying efficiency of ferric phosphate recycled materials, significantly reducing the supervision difficulty of supervisors, and having a high degree of intelligence.

[0078] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. Drying process management and control system based on lithium iron phosphate battery recycling, characterized in that: It includes recycling material transportation monitoring module, recycling material transportation evaluation module, workshop monitoring and analysis module, workshop drying evaluation module and drying workshop supervision terminal; The recycled material conveying monitoring module monitors the recycled materials spread on the conveyor belt and analyzes their spreading performance, and determines whether to assign the spreading symbol ZP-1, and sends it to the recycled material conveying evaluation module when the spreading symbol ZP-1 is assigned; the recycled material conveying evaluation module conducts a comprehensive analysis on the conveying performance of the recycled materials, generates a conveying evaluation qualified signal or a conveying evaluation early warning signal through the analysis, and sends the conveying evaluation qualified signal or the conveying evaluation early warning signal to the drying workshop supervision end; The workshop monitoring and analysis module analyzes the drying environment in the drying workshop, and determines whether the drying workshop is in an abnormal drying state through analysis. When it is determined to be in an abnormal drying state, the drying environment of the drying workshop is adaptively adjusted; the workshop drying evaluation module evaluates the drying control performance of the drying workshop, and generates a drying evaluation qualified signal or a drying evaluation early warning signal through analysis, and sends the drying evaluation qualified signal or the drying evaluation early warning signal to the drying workshop supervision end.

2. The drying process management and control system based on lithium iron phosphate battery recycling according to claim 1 is characterized in that: The specific analysis process of the recycling material transportation monitoring module is as follows: The paving thickness of the recycled materials at several positions on the conveyor belt is collected, and the variance of the paving thickness at all positions is calculated to obtain the paving non-uniformity value. The number percentage of thick points is obtained and marked as the paving thickness poor value; if the paving non-uniformity value or the paving thickness poor value exceeds the corresponding preset threshold, the paving symbol ZP-1 is assigned.

3. The drying process management and control system based on lithium iron phosphate battery recycling according to claim 2 is characterized in that: If the paving unevenness value and the paving thickness inferior value do not exceed the corresponding preset threshold values, the paving unevenness value, the paving thickness inferior value and the paving thickness inspection value will be numerically calculated to obtain the transport paving coefficient. If the transport paving coefficient exceeds the preset transport paving coefficient threshold value, the paving symbol ZP-1 will be assigned.

4. The drying process management and control system based on lithium iron phosphate battery recycling according to claim 1 is characterized in that: The specific analysis process of the recycling material conveying assessment module includes: The number of times the paving symbol ZP-1 is generated per unit time is obtained and marked as the paving abnormality detection value. If the paving abnormality detection value exceeds the preset paving abnormality detection threshold, a transportation assessment warning signal is generated; If the paving abnormality inspection value does not exceed the preset paving abnormality inspection threshold, the recycled material output evaluation value is obtained by numerically calculating the paving abnormality inspection value, conveying fluctuation value, conveying speed abnormality value, conveying vibration condition value and conveying vibration abnormality value. If the recycled material output evaluation value exceeds the preset recycled material output evaluation threshold, a conveying evaluation warning signal is generated; if the recycled material output evaluation value does not exceed the preset recycled material output evaluation threshold, a conveying evaluation qualified signal is generated.

5. The drying process management and control system based on lithium iron phosphate battery recycling according to claim 1 is characterized in that: The specific analysis process of the drying workshop monitoring and analysis module includes: The analysis is performed to determine the poor drying point in the drying workshop; the poor condition value of the drying workshop, the surface condition value of the drying workshop and the surface amplitude of the drying workshop are numerically calculated to obtain the monitoring value of the drying workshop. If the monitoring value of the drying workshop exceeds the preset monitoring threshold of the drying workshop, it is judged that the drying workshop is in an abnormal drying state.

6. The drying process management and control system based on lithium iron phosphate battery recycling according to claim 5 is characterized in that: The specific analysis and determination process of the drying inferior surface point is as follows: The drying point control abnormality table value is obtained by numerically calculating the drying temperature control abnormality coefficient, the drying humidity control abnormality coefficient and the drying airflow abnormality coefficient. If the drying point control abnormality table value exceeds the preset drying point control abnormality table threshold, the corresponding monitoring point will be marked as a poor drying table point.

7. The drying process management and control system based on lithium iron phosphate battery recycling according to claim 1 is characterized in that: The specific analysis process of the workshop drying assessment module is as follows: The workshop drying control evaluation value is obtained by numerically calculating the total drying abnormality time value, the drying warning inspection value and the drying workshop control meter value. If the workshop drying control evaluation value exceeds the preset workshop drying control evaluation threshold, a drying evaluation warning signal is generated; if the workshop drying control evaluation value does not exceed the preset workshop drying control evaluation threshold, a drying evaluation qualified signal is generated.

8. The drying process management and control system based on lithium iron phosphate battery recycling according to claim 1 is characterized in that: The dry workshop supervision end is communicated with the dry control decision output module. The dry control decision output module is used to set the detection period and conduct a control planning decision analysis on the dry workshop for lithium iron phosphate battery recycling. If the dry workshop planning coefficient exceeds the preset dry workshop planning coefficient threshold, a control enhancement signal is generated.

Images