Information management method and device for higher vocational education and storage medium

Abstract

The invention relates to the technical field of information management, in particular to an information management method and device for higher vocational education and a storage medium, and the method comprises the steps: building a professional health degree based on the number of posts in a target region monitoring period, the number of posts in a historical monitoring period and an enterprise post recruitment text; determining the thermal stability state of the equipment based on the main shaft temperature rise gradient and the axial thermal deformation of the equipment collected in the monitoring period; evaluating the student operation specification degree based on the student cutter path deviation degree and the operation abnormity ratio collected in the monitoring period; generating a teaching resource scheduling strategy based on the equipment vacancy rate, the operation specification index, the equipment thermal stability index and the professional health degree in the monitoring period; and an adjustment factor is constructed based on the operation specification index of each student in the monitoring period, and a teaching resource scheduling strategy is updated in combination with the adjustment factor and the surface roughness of the processed workpiece. According to the invention, the information management efficiency and equipment utilization efficiency of higher vocational colleges are effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of information management, and in particular to an information management method, device and storage medium for higher vocational education. BACKGROUND

[0002] Under the new round of industrial reform, the intelligent upgrading of manufacturing industry accelerates the demand for compound technical and skilled talents, but there are still significant obstacles in the dynamic adaptation of higher vocational education system to industrial development. Traditional professional construction relies on lagging macro employment data, which is difficult to capture the technical iteration direction of regional industrial clusters in real time, resulting in the delay of curriculum system update in market changes, and the structural contradictions in the supply of talents in some fields are highlighted.

[0003] Precise numerical control training equipment generally lacks state intelligent monitoring means, and manual inspection mode is difficult to identify the hidden risks of mechanical thermal deformation and wear in time, and the non-planned shutdown of equipment threatens the continuity of practical teaching. The existing skill evaluation system focuses on a single dimension of product quality, and lacks dynamic tracking of process indicators such as processing track compliance and operation behavior standardization, which restricts the construction of personalized teaching feedback generation mechanism. Cross-professional training resource scheduling still uses static allocation strategy, and the real-time linkage model of equipment operation efficiency, student skill level and industrial demand intensity has not been established, and the problems of resource mismatch and vacancy coexist. The data island of production and education caused by technical barriers and the failure of multi-source information collaboration further weaken the agile response capability of vocational education serving industrial upgrading, and the construction of an intelligent management platform that connects all factors and links multiple scenes becomes a key breakthrough to solve the current difficulties. SUMMARY

[0004] The purpose of the present application is to provide an information management method, device and storage medium for higher vocational education to solve at least one of the problems in the prior art.

[0005] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0006] An information management method for higher vocational education, comprising:

[0007] constructing a professional health degree based on the number of posts in the target area monitoring period, the number of posts in the historical monitoring period and the enterprise post recruitment text;

[0008] constructing a device thermal stability index based on the device main shaft temperature rise gradient and axial thermal deformation amount collected in the monitoring period, and determining the device thermal stability state;

[0009] constructing an operation specification index based on the student tool path deviation and operation abnormality ratio collected in the monitoring period to evaluate the student operation specification degree;

[0010] Generate a teaching resource scheduling strategy based on the equipment idle rate, operation specification index, equipment thermal stability index and professional health degree in the monitoring period.

[0011] Optionally, the average of the number of posts in N historical monitoring periods is calculated, denoted as Mz, and the post fluctuation index is set as B, the enterprise demand keywords of the enterprise recruitment text are extracted, and the course keywords of the vocational college curriculum are extracted, the enterprise demand keywords are matched with the course keywords, the enterprise keywords that are successfully matched with the course keywords in the enterprise demand keywords are recorded as skill matching keywords, and the ratio of the number of skill keywords to the number of enterprise demand keywords is taken as the skill matching index.

[0012] Optionally, the post fluctuation index and the skill matching index are coupled and analyzed to determine the professional health degree, and the professional health degree is set as K. When the professional health degree is greater than the health degree threshold k0 for two consecutive monitoring periods, a course adjustment prompt is triggered.

[0013] Optionally, the i-th equipment spindle temperature rise gradient collected in the monitoring period is denoted as Ti, and the j-th equipment axial thermal deformation amount collected in the monitoring period is denoted as Lj.

[0014] The equipment thermal stability index is set as RRS, and the expression of RRS is:

[0015] In the formula, u1 is the temperature rise weight, u2 is the deformation weight, I is the number of equipment spindle temperature rise gradient data collected in the monitoring period, J is the number of equipment axial thermal deformation amount data collected in the monitoring period, β1 is the temperature rise abnormal factor, β2 is the deformation abnormal factor, Mt is the number of data greater than the second temperature rise threshold t0 in the equipment spindle temperature rise gradient collected in the monitoring period, ML is the number of data greater than the second deformation threshold L0 in the equipment axial thermal deformation amount collected in the monitoring period, Tmax is the first temperature rise threshold, and Lmax is the first deformation threshold.

[0016] The equipment thermal stability index RRS is compared with the thermal stability threshold rr. When RRS is greater than rr, it is determined that the equipment thermal stability state is abnormal, and a repair work order is pushed to the user, otherwise, it is determined that the equipment thermal stability state is normal, and no repair work order is pushed to the user.

[0017] Optionally, the tool path deviation degree of the n-th student in the monitoring period is denoted as Pn, the operation abnormality ratio of the n-th student is denoted as Yn, and the operation specification index of the n-th student is set as Gn, Gn = exp(3×Pn-3) + ln(5×Yn+1) / ln6.

[0018] The Gn is compared with the norm threshold g0, when the Gn is greater than g0, it is determined that the operation norm of the student is abnormal, and the standard operation demonstration is pushed to the student, otherwise, it is determined that the operation norm of the student is normal, and the standard operation demonstration is not pushed to the student.

[0019] Optionally, the average of the device stability index of each device in the monitoring period is calculated and recorded as TSD, and the average of the operation norm index of each student in the monitoring period is calculated and recorded as PD; the average of the idle rate of each device in the monitoring period is calculated and recorded as E;

[0020] The scheduling index C is determined according to the average PD of the operation norm index of each student and the professional health degree K, C=x1×PD+x2×K, wherein x1 is the operation norm weight, x2 is the professional health weight, and x1+x2=1;

[0021] When E is greater than the idle threshold E0, TSD is less than the thermal stability threshold rr, and the scheduling index C is greater than the scheduling threshold c0, cross-professional device sharing is initiated; otherwise, cross-professional device sharing is not initiated.

[0022] Optionally, an adjustment factor is constructed based on the operation norm index of each student in the monitoring period, and the teaching resource scheduling strategy is updated in combination with the adjustment factor and the surface roughness of the processed workpiece; the student skill dispersion is calculated based on the operation norm index of each student in the monitoring period, the student skill dispersion is set as S, and the student skill dispersion S is compared with the dispersion threshold s0 to determine the adjustment factor, when S is greater than s0, the adjustment factor is set as (1+η), otherwise, the adjustment factor is set as 1, and η is an adjustment coefficient.

[0023] Optionally, the average of the surface roughness of each processed workpiece in the monitoring period is calculated and recorded as Ra, and Ra is compared with the roughness threshold R0, when Ra is greater than R0, the scheduling threshold is updated as c1 to update the teaching resource scheduling strategy; otherwise, the teaching resource scheduling strategy is not updated.

[0024] According to another aspect of the present application, an information management device for higher vocational education is provided, comprising:

[0025] The health degree construction unit is used to construct the professional health degree based on the number of posts in the target area monitoring period, the number of posts in the historical monitoring period and the enterprise post recruitment text;

[0026] The state determination unit is used to construct the device thermal stability index based on the device spindle temperature rise gradient and the axial thermal deformation amount collected in the monitoring period, and determine the device thermal stability state;

[0027] The practical training analysis unit is used to construct an operation specification index based on the tool path deviation degree and operation abnormality ratio of the students collected in the monitoring period, so as to evaluate the operation specification degree of the students;

[0028] The strategy generation unit is used to generate a teaching resource scheduling strategy based on the equipment idle rate, operation specification index, equipment thermal stability index and professional health degree in the monitoring period;

[0029] The updating unit is used to construct an adjustment factor based on the operation specification index of each student in the monitoring period, and update the teaching resource scheduling strategy in combination with the adjustment factor and the surface roughness of the processed workpiece.

[0030] According to another aspect of the present application, a computer readable storage medium is provided, which stores a computer program, wherein the computer program is used to control an electronic device where the computer readable storage medium is located to execute an information management method for higher vocational education when running.

[0031] The beneficial effects of the present application are as follows: deeply integrating regional industry development dynamics and college major settings, using double-dimensional evaluation of post fluctuation index and skill matching degree, reflecting the adaptability of major settings and industry demand in real time, promoting the iterative upgrading of industry-education cooperation, innovating the construction of equipment full life cycle health monitoring system, effectively prolonging the service life of precision equipment through abnormal early warning models of thermodynamic parameters and mechanical properties, reducing the safety risk of practical training, at the same time, establishing a digital evaluation network of student operation behavior, converting the machining trajectory deviation degree and process abnormal behavior into quantifiable teaching feedback, accurately positioning the weak links of skills, accelerating the formation process of standardized skills; developing an intelligent scheduling system with multiple threshold linkage, integrating equipment utilization rate, teaching demand and resource state, realizing on-demand allocation of cross-major practical training resources, and significantly improving the use efficiency of equipment assets; through the closed-loop verification mechanism of roughness feedback and operation specification, dynamically correcting the teaching strategy, and building a three-dimensional quality assurance system of "demand-driven-process monitoring-quality verification", comprehensively enhancing the agile response capability and industry service value of vocational education, and providing a systematic solution for the cultivation of skilled personnel in the new era. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0033] Figure 1 The flowchart of the information management method for higher vocational education of the present embodiment.

[0034] Figure 2 The flow chart of the construction method of the professional health degree of the embodiment.

[0035] Figure 3 The flow chart of the teaching resource scheduling strategy updating method of the embodiment.

[0036] Figure 4 The structural schematic diagram of the information management device for higher vocational education of the embodiment.

[0037] Figure 5 The structural schematic diagram of the electronic device of the embodiment. DETAILED DESCRIPTION

[0038] In order to more clearly illustrate the present application, the present application will be further described below in conjunction with preferred embodiments and the accompanying drawings. Similar components are denoted by the same reference numerals in the drawings. It should be understood by those skilled in the art that the following specific description is illustrative rather than limiting, and should not limit the scope of protection of the present application.

[0039] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0040] Specifically, the embodiment is applicable to the digital teaching management scene of higher vocational colleges, and is particularly applicable to intelligent manufacturing, numerical control machining, industrial robots and other practical majors.

[0041] Please refer to Figure 1 The flow chart of the information management method for higher vocational education of the embodiment is shown, which comprises:

[0042] Step S101, based on the number of posts in the target area monitoring period, the number of posts in the historical monitoring period and the enterprise post recruitment text to construct the professional health degree, the target area is the city where the higher vocational college is located.

[0043] For example, the post described in the embodiment is a post related to the major, such as the post of numerical control machining major, which can be five-axis numerical control operator, CNC process engineer, intelligent production line commissioning personnel, etc.

[0044] Exemplarily, the monitoring period can be set to 7 days in the embodiment, and the setting of the monitoring period is not specifically limited in the embodiment, and a person skilled in the art can freely set according to the needs.

[0045] Exemplarily, the post quantity data and the enterprise post recruitment text can be captured by the crawler in the embodiment, and the data collection manner is not specifically limited in the embodiment, and a person skilled in the art can freely set according to the needs.

[0046] Please refer to Figure 2 As shown in the figure, the construction method of the professional health degree comprises:

[0047] In step S201, the post fluctuation index is calculated according to the post quantity in the target area monitoring period and the post quantity in the historical monitoring period.

[0048] Specifically, the average value of the post quantity in the N historical monitoring periods is calculated in step S201, and is recorded as Mz, and the post fluctuation index is set as B, and B=m / Mz is set, wherein m is the post quantity in the current monitoring period.

[0049] Specifically, the time series data is used to quantify the dynamic change characteristics of the regional post supply and demand, effectively reveals the short-term demand fluctuation law of the market, provides data visualization indexes for predicting the development trend of the industry, and assists colleges and universities to carry out professional early warning and resource allocation adjustment in advance.

[0050] Specifically, the N historical monitoring periods in the embodiment are N historical monitoring periods adjacent to the current monitoring period, and the setting of N is not specifically limited in the embodiment, and a person skilled in the art can freely set according to the needs, such as 5, 6, 10, etc.

[0051] Please continue to refer to Figure 2 As shown in the figure, the construction method of the professional health degree comprises:

[0052] In step S202, the skill matching index is constructed based on the enterprise recruitment text.

[0053] Specifically, the enterprise demand keywords of the enterprise recruitment text are extracted in step S202, and the course keywords of the vocational college curriculum outline are extracted, the enterprise demand keywords and the course keywords are matched, the enterprise demand keywords that are successfully matched with the course keywords are recorded as skill matching keywords, and the ratio of the number of skill keywords to the number of enterprise demand keywords is taken as the skill matching index.

[0054] Specifically, the semantic association model of production and teaching demand is established by natural language processing technology, and the matching blind area of the course content and the actual skill requirement of the enterprise is automatically identified, which provides accurate gap analysis basis for textbook development and practice teaching improvement.

[0055] Exemplarily, in the present embodiment, the job description text of the target post of the recruitment platform (such as Fangxingshuangyong and Liepin) can be grabbed, stored in the database after cleaning, the HTML tags, special symbols and non-Chinese characters are removed, the mixed word segmentation is performed by using the jieba word segmentation tool, only the nouns, verbs and self-defined technical terms (such as “CNC”) are retained, the irrelevant words such as pronouns and auxiliary words are filtered, the term frequency of the processed corpus is counted, the top 10% terms with the TF-IDF value are taken, the synonym mapping table (such as “CAD drawing = AutoCAD drawing”) is established to prevent repeated counting, the bottom operation terms (such as “G code writing”) are associated with the top skills (such as “numerical control programming”) to establish the association level, and finally the enterprise demand keyword library is output; the extraction process of the course keywords of the curriculum outline of the vocational school is the same as the extraction process of the enterprise demand keywords, and details are not described herein again; the matching success of the enterprise demand keywords and the course keywords in the present embodiment can be realized by Python, and the extraction process and the matching process of the keywords are not specifically limited herein, and a person skilled in the art can freely set them according to the requirements.

[0056] Please continue to refer to Figure 2 As shown, the method for constructing the professional health degree further comprises:

[0057] In step S203, the post fluctuation index and the skill matching index are coupled and analyzed to determine the professional health degree.

[0058] Specifically, the professional health degree is set as K, and the expression of K is K = a1 x 1 / (1+B) + a2 x lg(2-Np) / lg2, wherein a1 is the post fluctuation weight, a2 is the skill matching weight, a1 + a2 = 1, and Np is the skill matching index.

[0059] When the professional health degree is greater than the health degree threshold k0 for two consecutive monitoring periods, a course adjustment prompt is triggered.

[0060] Specifically, a multi-factor coupling evaluation mechanism is adopted to break through the limitation of a single index, a professional ecological health evaluation system that can be dynamically monitored is constructed, a threshold-driven intelligent early warning triggering mechanism is established, and the timeliness and scientificity of the teaching reform decision are ensured.

[0061] Exemplarily, in the present embodiment, the post fluctuation weight can be set as 0.4, the skill matching weight can be set as 0.6, and the health degree threshold can be set as 0.36, and the setting of the above data is not specifically limited herein, and a person skilled in the art can freely set them according to the requirements.

[0062] Please continue to refer to Figure 1 As shown, the information management method for higher vocational education further comprises:

[0063] In step S102, a thermal stability index of the equipment is constructed based on the collected spindle temperature rise gradient and the axial thermal deformation amount in the monitoring period, and a thermal stability state of the equipment is determined, the spindle temperature rise gradient is the temperature rise after the numerical control machine tool spindle works continuously for 30 minutes, and the axial thermal deformation amount is the radial offset amount of the spindle.

[0064] Specifically, a multi-sensor data fusion algorithm is introduced to construct an equipment state comprehensive evaluation model, early diagnosis and predictive maintenance of potential faults of the precision machining equipment are realized, the risk of unplanned downtime of the training equipment is reduced, and the whole life cycle management level of the high-value equipment is improved.

[0065] For example, in the present embodiment, the spindle surface temperature can be monitored by an infrared thermometer, and transmitted to the PLC through the Modbus protocol. The axial thermal deformation amount can be collected by a capacitive displacement sensor installed at the radial position of the spindle, and the data can be uploaded in real time through the EtherCAT bus. In the present embodiment, the data collection method is not specifically limited, and can be freely set by those skilled in the art according to the needs.

[0066] Specifically, the step S102 records the i-th equipment spindle temperature rise gradient collected in the monitoring period as Ti, and records the j-th equipment axial thermal deformation amount collected in the monitoring period as Lj.

[0067] The equipment thermal stability index is set as RRS, and the expression of RRS is:

[0068] In the formula, u1 is the temperature rise weight, u2 is the deformation weight, u1+u2=1, I is the number of equipment spindle temperature rise gradient data collected in the monitoring period, J is the number of equipment axial thermal deformation amount data collected in the monitoring period, β1 is the temperature rise abnormal factor, β2 is the deformation abnormal factor, Mt is the number of data greater than the second temperature rise threshold t0 in the equipment spindle temperature rise gradient collected in the monitoring period, ML is the number of data greater than the second deformation threshold L0 in the equipment axial thermal deformation amount collected in the monitoring period, Tmax is the first temperature rise threshold, and Lmax is the first deformation threshold.

[0069] The equipment thermal stability index RRS is compared with the thermal stability threshold rr, when RRS is greater than rr, it is determined that the thermal stability state of the equipment is abnormal, and a repair work order is pushed to the user, otherwise, it is determined that the thermal stability state of the equipment is normal, and no repair work order is pushed to the user.

[0070] Exemplarily, in the embodiment, the temperature rise weight can be set to 0.7, the deformation weight can be set to 0.3, the temperature rise abnormal factor can be set to 0.8, the deformation abnormal factor can be set to 0.7, the first temperature rise threshold can be set to 50℃, the second temperature rise threshold can be set to 30℃, the first deformation threshold can be set to 0.05mm, the second deformation threshold can be set to 0.015mm, and the thermal stability threshold can be set to 0.23.

[0071] Please continue to refer to Figure 1 As shown, the information management method for higher vocational education further comprises:

[0072] In step S103, an operation specification index is constructed based on the student tool path deviation and the operation abnormality ratio collected in the monitoring period to evaluate the student operation specification degree, the student tool path deviation is the deviation area proportion of the actual machining path of the student from the CAD model, and the operation abnormality ratio is the ratio of the number of emergency stop triggered by the tool changing action of the student to the number of tool changing actions.

[0073] Specifically, a student operation behavior quantitative index system is established based on motion trajectory anomaly detection, a closed-loop skill improvement intervention mechanism is formed, standardized operation awareness training is strengthened, and teaching quality is improved.

[0074] Exemplarily, in the embodiment, a numerical control machining program can be generated by CAM software, a coordinate sequence of a theoretical tool path is extracted, and motion instructions (such as G01 linear interpolation, G02 / G03 circular interpolation) in G code are analyzed to construct a theoretical trajectory point set. A high-precision encoder or a grating ruler built-in a numerical control machine tool is used to record X / Y / Z coordinates of a tool center point in real time, and a laser tracker is additionally installed to dynamically track a tool positioning ball position to obtain actual trajectory data. The theoretical path and the actual path are imported into MATLAB or Python algorithm, two sets of point clouds are aligned by ICP (iterative closest point) algorithm, and the deviation area proportion of the actual machining path of the student from the CAD model is calculated by using Delaunay triangulation method. Tool changing instructions and emergency stop signals can be synchronously collected through an EtherCAT bus. In the embodiment, the collection method of the above data is not specifically limited, and a person skilled in the art can freely set it according to the needs.

[0075] Specifically, in step S103, the tool path deviation of the nth student in the monitoring period is denoted as Pn, the operation abnormality ratio of the nth student is denoted as Yn, and the operation specification index of the nth student is denoted as Gn, Gn = exp(3×Pn-3) + ln(5×Yn+1) / ln6.

[0076] The Gn is compared with the norm threshold g0, when the Gn is greater than g0, it is determined that the operation norm of the student is abnormal, and the standard operation demonstration is pushed to the student, otherwise, it is determined that the operation norm of the student is normal, and the standard operation demonstration is not pushed to the student.

[0077] Exemplarily, the norm threshold can be set to 0.7 in the embodiment; the setting of the norm threshold is not specifically limited in the embodiment, and a person skilled in the art can freely set according to the needs.

[0078] Please continue to refer to Figure 1 As shown, the information management method for higher vocational education further comprises:

[0079] In step S104, a teaching resource scheduling strategy is generated based on the equipment idle rate, the operation norm index, the equipment thermal stability index and the professional health degree in the monitoring period.

[0080] Specifically, the equipment idle rate is the ratio of the idle time length of the equipment to the training time length in the student training time in the monitoring period, and can be obtained through interaction.

[0081] Specifically, the average of the equipment stability indexes of all the equipment in the monitoring period is calculated and denoted as TSD, the average of the operation norm indexes of all the students in the monitoring period is calculated and denoted as PD, and the average of the equipment idle rates of all the equipment in the monitoring period is calculated and denoted as E.

[0082] The scheduling index C is determined according to the average PD of the operation norm indexes of all the students and the professional health degree K, C=x1*PD+x2*K, wherein x1 is the operation norm weight, x2 is the professional health weight, and x1+x2=1.

[0083] When E is greater than the idle threshold E0, TSD is less than the thermal stability threshold rr, and the scheduling index C is greater than the scheduling threshold c0, cross-professional equipment sharing is initiated, otherwise, cross-professional equipment sharing is not initiated.

[0084] Specifically, the cross-professional equipment sharing in the embodiment is to allocate the idle period of the professional training equipment to other professionals in urgent need.

[0085] Specifically, the equipment running state, the teaching process quality and the regional industry demand data are integrated to construct a multi-objective optimization intelligent decision-making model, so as to realize dynamic allocation of cross-professional resource sharing and improve the comprehensive utilization rate and collaborative benefits of high-investment training equipment.

[0086] Exemplarily, the operation norm weight can be set to 0.65, the professional health weight can be set to 0.35, the idle threshold can be set to 0.4, and the scheduling threshold c0 can be set to 0.85 in the embodiment.

[0087] Please continue to refer to Figure 1 As shown in the information management method for higher vocational education further comprises:

[0088] Step S105, based on the monitoring period within each student's operation specification index adjustment factor is constructed, and combined with the adjustment factor and the surface roughness of the workpiece update teaching resource scheduling strategy.

[0089] Exemplary, in this embodiment can be measured by contact profilometer surface roughness of the workpiece; this embodiment does not make specific limitations on the data acquisition method, those skilled in the art can be freely set according to the needs.

[0090] Please refer to Figure 3 As shown in the teaching resource scheduling strategy update method comprises:

[0091] Step S301, based on the monitoring period within each student's operation specification index calculation of student skill dispersion, and according to the student skill dispersion to determine the adjustment factor.

[0092] Specifically, the step S301 will be the student skill dispersion S, S expression is:

[0093]

[0094] The student skill dispersion S and dispersion threshold s0 are compared to determine the adjustment factor, when S is greater than s0, the adjustment factor is set to (1+η), otherwise, the adjustment factor is set to 1, η is the adjustment coefficient.

[0095] Specifically, through the skill dispersion analysis to identify the group differentiation characteristics of skill training, to build a differentiated teaching intervention intensity parameters, to realize the quantitative formulation of classification guidance strategy, effective control of the homogeneity of the teaching process, promote collaborative talent training.

[0096] Exemplary, in this embodiment can be set to 0.15 dispersion threshold, can be set to 0.12 adjustment coefficient; this embodiment does not make specific limitations on the above data settings, those skilled in the art can be freely set according to the needs.

[0097] Please continue to refer to Figure 3 As shown in the teaching resource scheduling strategy update method comprises:

[0098] Step S302, combined with the adjustment factor and the surface roughness of the workpiece update teaching resource scheduling strategy.

[0099] Specifically, the average value of the surface roughness of each workpiece in the monitoring period is calculated, and is recorded as Ra, and Ra and the roughness threshold R0 are compared, when Ra is greater than R0, the scheduling threshold is updated to c1, c1=c0+0.1×c0×(e(Ra -R0) / (Ra+R0) +1) / (e+1); otherwise, the teaching resource scheduling strategy is not updated, and e is a natural logarithm.

[0100] Specifically, a surface processing quality reverse verification mechanism is introduced, a single evaluation dimension mainly based on traditional process specifications is broken through, a dynamic calibration system linking skill training effect and production quality standards is established, and output-oriented teaching quality guarantee capability is strengthened.

[0101] For example, in this embodiment, the roughness threshold can be set to 1.2 pm when processing TC4 titanium alloy; the setting of the roughness threshold is not specifically limited in this embodiment, and a person skilled in the art can freely set it according to the needs.

[0102] Referring to Figure 4 As shown in the figure, the information management device for higher vocational education comprises:

[0103] The health degree construction unit is configured to construct a professional health degree based on the number of posts in the target monitoring period, the number of posts in the historical monitoring period, and the enterprise post recruitment text;

[0104] The state determination unit is configured to construct a device thermal stability index based on the device main shaft temperature rise gradient and the axial thermal deformation amount collected in the monitoring period, and determine the device thermal stability state;

[0105] The training analysis unit is configured to construct an operation specification index based on the student tool path deviation degree and the operation abnormality ratio collected in the monitoring period, to evaluate the student operation specification degree;

[0106] The strategy generation unit is configured to generate a teaching resource scheduling strategy based on the device idle rate, the operation specification index, the device thermal stability index, and the professional health degree in the monitoring period;

[0107] The update unit is configured to construct an adjustment factor based on the operation specification index of each student in the monitoring period, and update the teaching resource scheduling strategy in combination with the adjustment factor and the surface roughness of the processed workpiece.

[0108] The information management device for higher vocational education provided in the embodiments of the present application can execute the information management method for higher vocational education provided in any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0109] The embodiments of the present application also provide an electronic device for executing the information management method for higher vocational education. As Figure 5As shown, the electronic device includes a processor 501, a memory 502, a communication interface 503 and a system bus 504. The processor includes at least one of a central processing unit (CPU), a graphics processing unit (GPU) or a field programmable gate array (FPGA), configured to call computer programs and data stored in the memory, and generate control instructions; the memory includes a random access memory (RAM) and / or a non-volatile memory (NVM), the NVM including a flash memory, a solid state disk (SSD) or a combination thereof, for storing computer programs, processing intermediate data and a set of historical data; the communication interface includes a wired communication module and a wireless communication module, the wired communication module supporting Ethernet or RS-485 protocol, for connecting a sensor network; the wireless communication module supports LoRa, 5G or satellite communication protocol, for transmitting processing results with a remote server; the system bus adopts a PCI Express or AXI bus architecture, realizing high-speed data interaction and clock synchronization between the processor, the memory and the communication interface.

[0110] The embodiment further provides a computer readable storage medium, which physically stores computer executable instructions, when the instructions are transmitted to a processing unit via an integrated circuit substrate, encapsulated and processed through a data channel of a bus system, and solidified to a non-volatile storage area of a storage module, the executable instructions are configured to realize the complete technical solution of the information management method for higher vocational education when executed by a processor.

[0111] Obviously, the above embodiments of the present application are only examples for clearly illustrating the present application, and are not intended to limit the embodiments of the present application. For those skilled in the art, on the basis of the above description, other different forms of changes or variations can also be made, and it is impossible to enumerate all the embodiments here. Any obvious changes or variations derived from the technical solutions of the present application are still within the protection scope of the present application.

Claims

1. An information management method for higher vocational education, characterized in that, include: Professional health is constructed based on the number of positions in the target area during the monitoring period, the number of positions in historical monitoring periods, and the job posting texts of enterprises. The thermal stability index of the equipment is constructed based on the temperature rise gradient of the equipment spindle and the axial thermal deformation collected during the monitoring period, and the thermal stability state of the equipment is determined. An operation standardization index is constructed based on the student tool path deviation and operation abnormality ratio collected during the monitoring period to evaluate the students' operation standardization. Teaching resource scheduling strategies are generated based on equipment idle rate, operation standard index, equipment thermal stability index, and professional health status within the monitoring period.

2. The information management method for higher vocational education according to claim 1, characterized in that, Calculate the average number of job postings over N historical monitoring periods, denoted as Mz, and set the job fluctuation index as B. Extract enterprise demand keywords from enterprise recruitment texts and course keywords from vocational school curriculum outlines. Match enterprise demand keywords with course keywords. Record the enterprise keywords that successfully match the course keywords as skill matching keywords, and use the ratio of the number of skill keywords to the number of enterprise demand keywords as the skill matching index.

3. The information management method for higher vocational education according to claim 2, characterized in that, The job fluctuation index and the skill matching index are coupled and analyzed to determine the professional health. The professional health is set as K. When the professional health exceeds the health threshold k0 for two consecutive monitoring periods, a course adjustment prompt is triggered.

4. The information management method for higher vocational education according to claim 3, characterized in that, The temperature rise gradient of the i-th equipment spindle collected during the monitoring period is denoted as Ti, and the axial thermal deformation of the j-th equipment collected during the monitoring period is denoted as Lj. Set the thermal stability index of the equipment to RRS. The expression for RRS is: In the formula, u1 is the temperature rise weight, u2 is the deformation weight, I is the number of equipment spindle temperature rise gradient data collected within the monitoring period, J is the number of equipment axial thermal deformation data collected within the monitoring period, β1 is the temperature rise anomaly factor, β2 is the deformation anomaly factor, Mt is the number of data in the equipment spindle temperature rise gradient collected within the monitoring period that are greater than the second temperature rise threshold t0, ML is the number of data in the equipment axial thermal deformation collected within the monitoring period that are greater than the second deformation threshold L0, Tmax is the first temperature rise threshold, and Lmax is the first deformation threshold. The thermal stability index RRS of the equipment is compared with the thermal stability threshold rr. If RRS is greater than rr, the thermal stability of the equipment is determined to be abnormal and a maintenance work order is pushed to the user. Otherwise, the thermal stability of the equipment is determined to be normal and no maintenance work order is pushed to the user.

5. The information management method for higher vocational education according to claim 4, characterized in that, The toolpath deviation of the nth student within the monitoring period is denoted as Pn, the operation abnormality rate of the nth student is denoted as Yn, and the operation standard index of the nth student is set as Gn, Gn=exp(3×Pn-3)+ln(5×Yn+1) / ln6; Gn is compared with the standardization threshold g0. If Gn is greater than g0, the student's operation standardization is determined to be abnormal, and a standard operation demonstration is pushed to the student. Otherwise, the student's operation standardization is determined to be normal, and a standard operation demonstration is not pushed to the student.

6. The information management method for higher vocational education according to claim 5, characterized in that, Calculate the average equipment stability index of each device during the monitoring period and record it as TSD. Calculate the average operation standardization index of each student during the monitoring period and record it as PD. Calculate the average equipment idle rate of each device during the monitoring period and record it as E. The scheduling index C is determined based on the average operational standardization index PD and professional health index K of each student. C = x1 × PD + x2 × K, where x1 is the operational standardization weight, x2 is the professional health weight, and x1 + x2 = 1. When E is greater than the idle threshold E0, TSD is less than the thermal stability threshold rr, and the scheduling index C is greater than the scheduling threshold c0, cross-professional equipment sharing is initiated; otherwise, cross-professional equipment sharing is not initiated.

7. The information management method for higher vocational education according to claim 6, characterized in that, An adjustment factor is constructed based on the operational standardization index of each student within the monitoring period, and the teaching resource scheduling strategy is updated in combination with the adjustment factor and the surface roughness of the processed workpiece. The student skill dispersion is calculated based on the operational standardization index of each student within the monitoring period. The student skill dispersion is set as S, and the student skill dispersion S is compared with the dispersion threshold s0 to determine the adjustment factor. When S is greater than s0, the adjustment factor is set to (1+η), otherwise the adjustment factor is set to 1, where η is the adjustment coefficient.

8. The information management method for higher vocational education according to claim 7, characterized in that, The average surface roughness of each processed workpiece during the monitoring period is statistically analyzed and denoted as Ra. Ra is compared with the roughness threshold RO. When Ra is greater than R0, the scheduling threshold is updated to c1 to update the teaching resource scheduling strategy; otherwise, the teaching resource scheduling strategy is not updated.

9. An information management device for higher vocational education, characterized in that, include: The health score building unit is used to construct professional health scores based on the number of positions in the target area during the monitoring period, the number of positions in the historical monitoring period, and the job posting texts of enterprises. The state determination unit is used to construct the equipment thermal stability index based on the equipment spindle temperature rise gradient and axial thermal deformation collected during the monitoring period, and to determine the equipment thermal stability state. The practical training analysis unit is used to construct an operation standardization index based on the student tool path deviation and operation abnormality ratio collected during the monitoring period, in order to evaluate the students' operation standardization. The strategy generation unit is used to generate teaching resource scheduling strategies based on equipment idle rate, operation standard index, equipment thermal stability index and professional health status within the monitoring period. The update unit is used to construct adjustment factors based on the operational standard index of each student within the monitoring period, and to update the teaching resource scheduling strategy by combining the adjustment factors with the surface roughness of the processed workpiece.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is used to control the electronic device on which the computer-readable storage medium is located to perform the information management method for higher vocational education as described in any one of claims 1-8 during runtime.

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