Teaching aid intelligent management method and system for automobile practical training

Abstract

The invention discloses a teaching aid intelligent management method and system for automobile practical training, and relates to the technical field of teaching aid intelligent management. Calculating an actual demand number of teaching aids, further calculating a teaching aid demand urgency index, and presetting a threshold value to judge a teaching aid demand urgency level; calculating a teaching aid temperature change rate TCR, further calculating a comprehensive abnormal index of each teaching aid, comparing with a preset threshold value, and judging whether the teaching aid state is normal or not; calculating a comprehensive loss index of each teaching aid, and further calculating a maintenance demand index of each teaching aid; comparing a preset threshold value and judging whether the teaching aid needs to be maintained; according to the method, intelligent management of the automobile practical training teaching aid is realized, real-time monitoring, accurate allocation, efficient maintenance and the like are covered, the management efficiency and the resource utilization rate are improved, and smooth development of practical training is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent management of teaching aids, and specifically to an intelligent management method and system for teaching aids used in automobile training. Background Art

[0002] In the school's automobile training teaching system, as a key teaching aid, the management of automobile engines faces many problems. On the one hand, for training courses from basic engine structure cognition to complex fault diagnosis and repair training, there are various requirements for the usage duration, usage frequency, and operation specifications of engine teaching aids. In addition, it is difficult to monitor the real-time status of engine teaching aids. For example, it is difficult to accurately grasp the power consumption, internal component wear, etc., making it impossible to detect and handle faults in time when teaching aids malfunction, thus affecting the normal development of training teaching.

[0003] Currently, for the management of automobile engine teaching aids, some basic management means are adopted. In terms of usage duration statistics, it mainly relies on manual recording of the lending and returning times of engine teaching aids to estimate the usage duration. For the control of usage frequency, simple statistics are carried out by manually registering the usage situation of each training. In terms of status monitoring, a simple power sensor is installed to monitor the power when the engine teaching aid is running, but it can only provide basic power data and lacks in-depth analysis of power change trends.

[0004] However, the existing engine teaching aid management technologies have many limitations. First of all, the method of manually recording usage duration and frequency is inefficient and error-prone, and it is difficult to meet the refined management requirements of teaching aid usage data in training teaching. Secondly, simple power monitoring means can only obtain static power data and cannot dynamically analyze power changes in combination with the actual usage scenarios and task requirements of engine teaching aids, resulting in the inability to detect potential faults caused by abnormal power in time. Summary of the Invention

[0005] (I) Technical Problems to be Solved

[0006] Aiming at the deficiencies of the prior art, the present invention provides an intelligent management method and system for teaching aids used in automobile training. By collecting multiple data of engine teaching aids; calculating the actual required quantity of teaching aids, and then calculating the urgency index of teaching aid requirements, and presetting thresholds to judge the urgency level of teaching aid requirements; calculating the teaching aid temperature change rate TCR of each teaching aid, further calculating the comprehensive anomaly index of each teaching aid, and presetting thresholds to compare and judge whether the state of the teaching aid is normal; calculating the comprehensive loss index of each teaching aid, and then calculating the maintenance requirement index of each teaching aid; presetting thresholds to compare and judge whether the teaching aid needs maintenance, which solves the problems of low efficiency and unreasonable maintenance in traditional teaching aid management.

[0007] (II) Technical Solutions

[0008] To achieve the above object, the present invention is realized by the following technical solutions: An intelligent management method for teaching aids in automobile training, including:

[0009] Collect the usage status data and performance parameter data of the engine teaching aids;

[0010] Calculate the actual demand quantity R of the teaching aids based on the usage status data; Calculate the urgency index P of the teaching aids according to the usage status data and the actual demand quantity R of the teaching aids; Preset the urgency index threshold of the teaching aids, compare the urgency index P of the teaching aids with the urgency index threshold of the teaching aids, and judge the urgency level of the teaching aids according to the comparison result; If the urgency of the teaching aids is high, send a teaching aid purchase reminder;

[0011] If the urgency of the teaching aids is low, calculate the teaching aid temperature change rate TCR of each teaching aid based on the usage status data; Calculate the comprehensive anomaly index EH of each teaching aid according to the teaching aid temperature change rate TCR, the usage status data and the performance parameter data; Preset the comprehensive anomaly index threshold, compare the comprehensive anomaly index EH with the comprehensive anomaly index threshold, and judge whether the status of each teaching aid is normal according to the comparison result; If the status of the teaching aid is abnormal, send an alarm reminder;

[0012] If the status of the teaching aid is normal, calculate the comprehensive loss index FT of each teaching aid according to the usage status data and the comprehensive anomaly index EH; Calculate the maintenance requirement index RKI of each teaching aid based on the comprehensive loss index FT; Preset the maintenance requirement index threshold, compare the maintenance requirement index RKI with the maintenance requirement index threshold, and judge whether each teaching aid needs maintenance according to the comparison result; If the teaching aid needs maintenance, take corresponding maintenance measures.

[0013] In the preferred scheme of the above intelligent management method for teaching aids in automobile training: The method for calculating the actual demand quantity R of the teaching aids is: The usage status data includes the total usage frequency F of the teaching aids within the usage cycle and the training time T; Calculate the actual demand quantity R of the teaching aids according to the total usage frequency F of the teaching aids and the training time T, and the formula is: ; where S is the number of students participating in the training; N is the number of teaching aids in the inventory; DP is the difficulty coefficient of the training project; CP is the complexity index of the training project; LS is the average skill level index of the students.

[0014] In the preferred scheme of the above intelligent management method for teaching aids in automobile training: The method for judging the urgency level of the teaching aids is: The usage status data also includes the historical failure rate U of the teaching aids within the usage cycle; Calculate the urgency index P of the teaching aids according to the total usage frequency F of the teaching aids, the actual demand quantity R of the teaching aids and the historical failure rate U of the teaching aids, and the formula is: where ω1 is The weight coefficient of ω1 ranges from 0.3 to 0.4; ω2 is The weight coefficient of ω2 ranges from 0.1 to 0.4; ω3 is the weight coefficient of the historical failure rate U of the teaching aids, and its value ranges from 0.2 to 0.5; and ω1 + ω2 + ω3 = 1; a preset urgency index threshold Pth of the teaching aid demand is set; when the urgency index P of the teaching aid demand is less than or equal to the urgency index threshold Pth of the teaching aid demand, it is determined that the urgency of the teaching aid demand is low, and the existing teaching aids are maintained for use; when the urgency index P of the teaching aid demand is greater than the urgency index threshold Pth of the teaching aid demand, it is determined that the urgency of the teaching aid demand is high, and a teaching aid purchase prompt is issued.

[0015] In a preferred embodiment of the above intelligent management method for teaching aids used in automobile training: The method for calculating the temperature change rate TCR of each teaching aid is as follows: The usage status data also includes the teaching aid temperature value TC of each teaching aid i ; Based on the teaching aid temperature value TC i , calculate the temperature change rate TCR of each teaching aid, and the calculation formula is: ; Wherein, TC i is the teaching aid temperature value measured at the i-th time point; i is the serial number of the time point, and its value ranges from [1, n - 1]; n is the total number of measured time points, and its value is a positive integer; is the teaching aid temperature value measured at the (i + 1)-th time point; is the i-th time point; is the (i + 1)-th time point; is the standard deviation of the temperature measurement value; is the weight of the teaching aid temperature value measured at the i-th time point.

[0016] In a preferred embodiment of the above intelligent management method for teaching aids used in automobile training: The method for calculating the comprehensive anomaly index EH of each teaching aid is as follows: The usage status data also includes the teaching aid vibration amplitude VA of each teaching aid; the performance parameter data also includes the total teaching aid usage duration TG and the actual power PR of each teaching aid; According to the teaching aid temperature change rate TCR, the teaching aid vibration amplitude VA, the total teaching aid usage duration TG and the actual power PR, calculate the comprehensive anomaly index EH of each teaching aid, and the formula is: ; Wherein, TS is the standard total usage duration of the teaching aid; PRS is the standard power when the teaching aid is operating normally; TCRmax is the maximum temperature change rate of the teaching aid; VAmax is the maximum vibration amplitude of the teaching aid; φ1 is The weight coefficient of, and its value ranges from 0.2 to 0.4; φ2 is The weight coefficient of, and its value ranges from 0.1 to 0.3; φ3 is The weight coefficient of, and its value ranges from 0.3 to 0.5; φ4 is The weight coefficient has a value ranging from 0.2 to 0.4; and φ1 + φ2 + φ3 + φ4 = 1.

[0017] In the preferred solution of the above intelligent management method for teaching aids in automobile training: The method for judging whether the teaching aid status of each teaching aid is normal is as follows:

[0018] Preset a comprehensive abnormal index threshold EHth;

[0019] When the comprehensive abnormal index EH ≤ the comprehensive abnormal index threshold EHth, it is judged that the teaching aid status of the corresponding teaching aid is normal;

[0020] When the comprehensive abnormal index EH > the comprehensive abnormal index threshold EHth, it is judged that the teaching aid status of the corresponding teaching aid is abnormal, and an alarm reminder is issued.

[0021] In the preferred solution of the above intelligent management method for teaching aids in automobile training: The method for calculating the comprehensive loss index FT of each teaching aid is as follows:

[0022] The usage status data also includes the average running speed Vavg, average power PGavg, maximum working temperature TE, and total vibration intensity SV of each teaching aid;

[0023] According to the total usage frequency F of the teaching aid, training time T, comprehensive abnormal index EH, average running speed Vavg, average power PGavg, maximum working temperature TE, and total vibration intensity SV, calculate the comprehensive loss index FT of each teaching aid. The calculation formula is: ; where TT is the total historical usage duration of each teaching aid; NR is the total historical maintenance times of each teaching aid.

[0024] In the preferred solution of the above intelligent management method for teaching aids in automobile training: The method for calculating the maintenance requirement index RKI of each teaching aid is as follows:

[0025] Based on the comprehensive loss index FT, calculate the maintenance requirement index RKI of each teaching aid. The formula used is: ; where HH is the average humidity in the training environment.

[0026] In the preferred solution of the above intelligent management method for teaching aids in automobile training: The method for judging whether each teaching aid needs maintenance is as follows:

[0027] The maintenance requirement index thresholds include a first maintenance requirement index threshold RKI1 and a second maintenance requirement index threshold RKI2, and RKI1 < RKI2;

[0028] When the maintenance requirement index RKI ≤ the first maintenance requirement index threshold RKI1, it is judged that the corresponding teaching aid does not need maintenance and continues to be used normally;

[0029] When the maintenance requirement index threshold one RKI1 < maintenance requirement index RKI ≤ maintenance requirement index threshold two RKI2, it is determined that the corresponding teaching aid is in a medium maintenance state, and maintenance measure one is taken;

[0030] When the maintenance requirement index RKI > maintenance requirement index threshold two RKI2, it is determined that the corresponding teaching aid is in a severe maintenance state, and maintenance measure two is taken.

[0031] The present invention also discloses an intelligent management system for teaching aids used in automobile training, which is used to implement the above-mentioned intelligent management method for teaching aids used in automobile training, including:

[0032] A data acquisition module, which is used to collect the usage status data and performance parameter data of the engine teaching aid;

[0033] An intelligent scheduling module, which is used to calculate the actual demand quantity R of the teaching aid based on the usage status data; calculate the urgency index P of the teaching aid demand according to the usage status data and the actual demand quantity R of the teaching aid; preset the urgency index threshold of the teaching aid demand, compare the urgency index P of the teaching aid demand with the urgency index threshold of the teaching aid demand, and judge the urgency level of the teaching aid demand according to the comparison result; if the urgency of the teaching aid demand is high, issue a teaching aid purchase reminder;

[0034] A reminder module, if the urgency of the teaching aid demand is low, calculate the teaching aid temperature change rate TCR of each teaching aid based on the usage status data; calculate the comprehensive anomaly index EH of each teaching aid according to the teaching aid temperature change rate TCR, usage status data and performance parameter data; preset the comprehensive anomaly index threshold, compare the comprehensive anomaly index EH with the comprehensive anomaly index threshold, and judge whether the teaching aid status of each teaching aid is normal according to the comparison result; if the teaching aid status is abnormal, issue an alarm reminder;

[0035] A maintenance module, if the teaching aid status is normal, calculate the comprehensive loss index FT of each teaching aid according to the usage status data and the comprehensive anomaly index EH; calculate the maintenance requirement index RKI of each teaching aid based on the comprehensive loss index FT; preset the maintenance requirement index threshold, compare the maintenance requirement index RKI with the maintenance requirement index threshold, and judge whether each teaching aid needs maintenance according to the comparison result; if the teaching aid needs maintenance, take the corresponding maintenance measure.

[0036] (III) Beneficial effects

[0037] The present invention provides an intelligent management method and system for teaching aids used in automobile training, which have the following beneficial effects:

[0038] (1) Collecting the usage status data and performance parameter data of the engine teaching aids can comprehensively and accurately grasp the actual situation of the teaching aids during the training process, providing a solid data foundation for a series of subsequent analyses and operations, and ensuring the scientificity and accuracy of management.

[0039] (2) Calculating the actual required quantity of the teaching aids can closely meet the actual needs of the training courses, avoiding the situation of excessive teaching aids causing resource idleness and waste, or insufficient quantity affecting the normal development of training teaching. Calculating the urgency index of teaching aid requirements and presetting a threshold for comparison can scientifically judge the requirement level. If the urgency of the requirement is high, a teaching aid purchase prompt will be issued, which can timely meet the teaching needs, avoid affecting the teaching quality due to insufficient teaching aids, and at the same time reasonably plan resources and improve the utilization efficiency of teaching resources.

[0040] (3) Calculating the temperature change rate of the teaching aids and further calculating the comprehensive anomaly index of each teaching aid can reflect the operating conditions of the teaching aids in all aspects. The preset threshold of the comprehensive anomaly index provides a clear standard for judging whether the state of the teaching aid is normal. When the comprehensive anomaly index exceeds the threshold, the system can quickly issue an alarm reminder to ensure the smooth progress of the training teaching.

[0041] (4) Calculating the comprehensive loss index of each teaching aid can comprehensively consider various loss factors during the use of the teaching aids, so as to accurately predict the loss degree of the teaching aids. Calculating the maintenance requirement index of each teaching aid further quantifies the maintenance requirements of the teaching aids. The preset threshold of the maintenance requirement index provides an objective basis for judging whether the teaching aid needs maintenance. According to the comparison results, a reasonable maintenance plan can be formulated in advance, and personalized and precise maintenance measures can be taken for each teaching aid with maintenance requirements. Description of the Drawings

[0042] Figure 1 It is a step schematic diagram of an intelligent management method for teaching aids used in automobile training according to the present invention. Detailed Embodiment

[0043] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0044] Please refer to Figure 1 , the present invention provides an intelligent management method for teaching aids used in automobile training, including:

[0045] Step 1: Collect the usage status data and performance parameter data of the engine teaching aids.

[0046] Comprehensive Step 1:

[0047] This method can comprehensively and accurately grasp the actual situation of the engine teaching aids during the training process, providing a solid data foundation for a series of subsequent analyses and management decisions, and ensuring the scientificity and accuracy of management.

[0048] Step 2: Calculate the actual required quantity R of the teaching aids based on the usage status data; calculate the urgency index P of the teaching aids according to the usage status data and the actual required quantity R of the teaching aids; preset the urgency index threshold of the teaching aids, compare the urgency index P of the teaching aids with the urgency index threshold of the teaching aids, and judge the urgency level of the teaching aids according to the comparison result; if the urgency of the teaching aids is high, send a teaching aid purchase reminder.

[0049] Step 201: Calculate the actual required quantity R of the teaching aids. The specific method is as follows:

[0050] The usage status data includes the total usage frequency F of the teaching aids within the usage period and the training time T.

[0051] It should be noted that a counter sensor is installed on the automotive engine teaching aids. When the engine teaching aids are used each time, the counter sensor will automatically record a usage action. By statistically analyzing the cumulative value of the counter within a certain period of time and then dividing it by the duration of this period, the usage frequency of the engine teaching aids can be obtained. By adding up the usage frequencies of all automotive engine teaching aids, the total usage frequency F of the teaching aids within the usage period is obtained.

[0052] Since the training course arrangement system will clearly set the start time and end time of each training course. By reading the time arrangement information of the corresponding courses in the system, the training time T can be accurately obtained.

[0053] Calculate the actual required quantity R of the teaching aids according to the total usage frequency F of the teaching aids and the training time T. The formula is as follows: ; where S is the number of students participating in the training; N is the number of teaching aids in stock; DP is the difficulty coefficient of the training project; CP is the complexity index of the training project; LS is the average skill level index of the students.

[0054] It should be noted that to obtain the number of students S participating in the training, by querying the student course selection information of the corresponding automotive training courses in the school's educational administration system, the number of students S participating in the training can be accurately obtained.

[0055] To obtain the number of teaching aids N in stock, by querying the inventory quantity field of the corresponding automotive training teaching aids in the school's inventory management system, the number of teaching aids N in stock can be obtained.

[0056] Obtain the difficulty coefficient DP of the practical training project by collecting the pass rate PI, average completion time TS and error rate RK of the students who completed the practical training project in the past; calculate the difficulty coefficient DP of the practical training project based on the pass rate PI, average completion time TS and error rate RK. The calculation formula is: ; TSD is the standard completion time set for the training project; a is The weight coefficient is 0.3~0.4; b is The weight coefficient of is 0.2~0.5; c is the weight coefficient of the error rate RK, which is 0.2~0.4; and a+b+c=1.

[0057] Obtain the complexity index CP of the training project. By obtaining the number of specific tasks NH, the number of dependencies between tasks DJ, and the number of different knowledge areas KJ involved in the training project, the complexity index CP of the training project is calculated. The calculation formula is: .

[0058] Obtain the average skill level index LS of students. Before the practical training begins, students are tested on theoretical knowledge and practical skills, and their skill levels are evaluated based on the test and assessment results. The scores of all students are summarized and statistically analyzed to calculate the average score, which is used as the average skill level index LS of students.

[0059] It should be noted that It represents the joint impact of the number of students and teaching aids in inventory on the actual demand quantity without considering other factors. Consider the difficulty and complexity of the training project. The greater the product of the difficulty coefficient DP and the complexity index CP of the training project, the more difficult and complex the project is, and the more teaching aids are required. It means that the longer the training time is and the higher the total frequency of using teaching aids is, the more teaching aids are needed. This means that the higher the students' skill level, the less dependent they are on teaching aids, and the number of teaching aids required will decrease accordingly.

[0060] Step 202: Determine the urgency level of the teaching aids demand. The specific method is:

[0061] The usage status data also includes the historical failure rate U of the teaching aids during the usage period.

[0062] It should be noted that the failure information of all automotive engine teaching aids within a certain period is obtained through the school's teaching aid failure record system, and the failure records of the teaching aids are summarized. Divide the number of failures of the engine teaching aid within this period by its actual usage times to obtain the failure rate within this period. For example, if the automotive engine training teaching aid has been used 200 times in the past year and has failed 10 times, then the failure rate of this teaching aid in this year is 10 / 200 = 0.05.

[0063] According to the total usage frequency F of the teaching aid, the actual required quantity R of the teaching aid, and the historical failure rate U of the teaching aid, calculate the urgency index P of the teaching aid demand. The formula is as follows: ;

[0064] where ω1 is the weight coefficient of, with a value range of 0.3 to 0.4; ω2 is the weight coefficient of, with a value range of 0.1 to 0.4; ω3 is the weight coefficient of the historical failure rate U of the teaching aid, with a value range of 0.2 to 0.5; and ω1 + ω2 + ω3 = 1.

[0065] It should be noted that represents the ratio of the actual required quantity of the teaching aid to the quantity of the teaching aid in the inventory. The larger this ratio is, the more difficult it is for the current inventory to meet the demand. This formula comprehensively considers the ratio of the actual required quantity of the teaching aid to the quantity of the teaching aid in the inventory 、 and the three important parts of the historical failure rate U of the teaching aid. Each part has a corresponding weight coefficient, indicating the degree of emphasis on different parameters when calculating the urgency index P of the teaching aid demand. By multiplying each part by its corresponding weight coefficient and then summing them up, the urgency index P of the teaching aid demand is obtained.

[0066] Preset the urgency index threshold Pth of the teaching aid demand; by collecting the total usage frequency F of the teaching aid, the actual required quantity R of the teaching aid, and the historical failure rate U of the teaching aid in different past periods, calculate the urgency index P of the teaching aid demand in each period; further calculate the average value Pavg of the urgency index of the teaching aid demand, and use the average value Pavg of the urgency index of the teaching aid demand as the urgency index threshold Pth of the teaching aid demand.

[0067] When the urgency index P of the teaching aid demand ≤ the urgency index threshold Pth of the teaching aid demand, it is judged that the urgency of the teaching aid demand is low, and the existing teaching aid usage is maintained;

[0068] When the urgency index P of the teaching aid demand > the urgency index threshold Pth of the teaching aid demand, it is judged that the urgency of the teaching aid demand is high, and a teaching aid purchase prompt is issued.

[0069] Integrate Step 201 to Step 202:

[0070] This method accurately quantifies the demand situation and urgency of teaching aids, enabling the management system to reasonably allocate teaching aid resources based on these quantified indicators, improve the utilization efficiency of resources, and avoid resource waste or insufficiency.

[0071] Step 3: If the urgency of teaching aid demand is low, calculate the teaching aid temperature change rate TCR for each teaching aid based on the usage status data; calculate the comprehensive anomaly index EH for each teaching aid according to the teaching aid temperature change rate TCR, usage status data, and performance parameter data; preset a comprehensive anomaly index threshold, compare the comprehensive anomaly index EH with the threshold, and determine whether the status of each teaching aid is normal based on the comparison result; if the status of the teaching aid is abnormal, issue an alarm reminder.

[0072] Step 301: Calculate the teaching aid temperature change rate TCR for each teaching aid. The specific method is as follows:

[0073] The usage status data also includes the teaching aid temperature value TC of each teaching aid i 。

[0074] It should be noted that by using a thermocouple temperature sensor installed at the cylinder part of each engine teaching aid, the teaching aid temperature value TC is measured and obtained i 。

[0075] Based on the teaching aid temperature value TC i , calculate the teaching aid temperature change rate TCR for each teaching aid. The calculation formula is: ; where TC i is the teaching aid temperature value measured at the i-th time point; i is the serial number of the time point, and the value range is [1, n - 1]; n is the total number of measured time points, and the value is a positive integer; is the teaching aid temperature value measured at the (i + 1)-th time point; is the i-th time point; is the (i + 1)-th time point; is the standard deviation of the temperature measurement value; is the weight of the teaching aid temperature value measured at the i-th time point.

[0076] It should be noted that to obtain the standard deviation of the temperature measurement value , through the teaching aid temperature value TC i , the average temperature can be obtained, and further calculate the standard deviation of the temperature measurement value . The calculation formula is: 。

[0077] It should be noted that This part first calculates the temperature change rate between adjacent time points and multiplies it by the corresponding weight , the contributions of different measurement points to the overall change rate are considered. This term is a correction to the temperature change rate. It represents the multiple of the temperature change amount between adjacent points relative to the standard deviation of the temperature data. When the temperature change amount between adjacent points is relatively large compared to the standard deviation, it indicates that this change is prominent in the overall temperature fluctuation. By multiplying by the influence of this change on the final temperature change rate can be enhanced; conversely, if the change amount is relatively small compared to the standard deviation, its influence on the final result is relatively small. is used for normalizing the numerator. The temperature change rate TCR of the teaching aid is calculated through this formula.

[0078] Step 302: Calculate the comprehensive anomaly index EH of each teaching aid. The specific method is as follows:

[0079] The usage status data also includes the vibration amplitude VA of each teaching aid.

[0080] It should be noted that by fixing the laser displacement sensor on a flat ground so that the emitted laser beam is vertically aligned with the surface of the engine teaching aid, the laser displacement sensor monitors and obtains the distance change data between the sensor and the teaching aid surface in real time. According to the obtained data, the difference between the maximum value and the minimum value of the distance change is calculated, and half of this difference is the vibration amplitude VA of the teaching aid.

[0081] The performance parameter data also includes the total usage duration TG and the actual power PR of each teaching aid.

[0082] It should be noted that when different engine teaching aids start to be used, the built-in timing module in the teaching aid automatically starts timing and stops when it is turned off. This module accumulates the usage duration each time, and finally obtains the total usage duration TG of each engine teaching aid. A power sensor is installed in the power supply circuit of each engine teaching aid to monitor the current I and voltage U flowing through the teaching aid in real time, then the actual power PR of each teaching aid = U×I.

[0083] According to the teaching aid temperature change rate TCR, the teaching aid vibration amplitude VA, the teaching aid total usage duration TG, and the actual power PR, calculate the comprehensive anomaly index EH of each teaching aid. The formula is as follows: ;

[0084] Among them, TS is the standard total usage duration of the teaching aid; PRS is the standard power when the teaching aid is operating normally; TCRmax is the maximum temperature change rate of the teaching aid; VAmax is the maximum vibration amplitude of the teaching aid; φ1 is the weight coefficient of, with a value range of 0.2 - 0.4; φ2 is the weight coefficient of, with a value range of 0.1 - 0.3; φ3 is The weight coefficient has a value range of 0.3 to 0.5; φ4 is The weight coefficient has a value range of 0.2 to 0.4; and φ1 + φ2 + φ3 + φ4 = 1.

[0085] It should be noted that by referring to the product manual of the automotive engine teaching aid, the total standard usage duration TS of the teaching aid and the standard power PRS during the normal operation of the teaching aid are obtained.

[0086] It should be noted that represents the deviation degree of the actual total usage duration of each teaching aid from the standard usage duration; represents that the rate of temperature change has been normalized so that EH can more comprehensively reflect the actual operating state of the teaching aid, in order to more accurately judge whether the teaching aid is abnormal; represents the deviation degree of the actual power of each teaching aid from the standard power; This item is considered and the vibration amplitude has been normalized; when VA is close to or exceeds VAmax, the value of will increase, thus reflecting the potential fault risk of the teaching aid due to abnormal vibration. Multiply these four parts by their respective corresponding weight coefficients and add them together to obtain the comprehensive anomaly index EH.

[0087] Step 303: Judge whether the state of each teaching aid is normal. The specific method is as follows:

[0088] Preset the comprehensive anomaly index threshold EHth; by collecting various parameters of multiple past automotive engine teaching aids of the same type under normal operation conditions, including the total usage duration TG of the teaching aid, the actual power PR, the teaching aid applicability score AH, and the total usage frequency F of the teaching aid, calculate the comprehensive anomaly index EH of each automotive engine teaching aid; further calculate the average value EHavg of the comprehensive anomaly index, and use the average value EHavg of the comprehensive anomaly index as the comprehensive anomaly index threshold EHth.

[0089] When the comprehensive anomaly index EH ≤ the comprehensive anomaly index threshold EHth, judge that the state of the corresponding teaching aid is normal;

[0090] When the comprehensive anomaly index EH > the comprehensive anomaly index threshold EHth, judge that the state of the corresponding teaching aid is abnormal and issue an alarm reminder.

[0091] Combining steps 301 to 303:

[0092] This method can timely and effectively detect abnormal situations that occur during the use of the teaching aid, make scientific judgments by setting thresholds, and give timely alarms in case of abnormalities, which is convenient for quickly taking measures to ensure the smooth progress of the training and reduce the adverse effects caused by teaching aid failures.

[0093] Step 4: If the teaching aid is in normal condition, calculate the comprehensive loss index FT of each teaching aid based on the usage status data and the comprehensive anomaly index EH; calculate the maintenance requirement index RKI of each teaching aid based on the comprehensive loss index FT; preset the threshold of the maintenance requirement index, compare the maintenance requirement index RKI with the threshold of the maintenance requirement index, and judge whether each teaching aid needs maintenance according to the comparison result; if the teaching aid needs maintenance, take corresponding maintenance measures.

[0094] Step 401: Calculate the comprehensive loss index FT of each teaching aid. The specific method is as follows:

[0095] The usage status data also includes the average running speed Vavg, average power PGavg, maximum working temperature TE, and total vibration intensity SV of each teaching aid.

[0096] It should be noted that by installing speed sensors on different automotive engine teaching aids, during the operation of the teaching aids, speed data is continuously collected. After the end of one operation cycle, all the collected speed values are added up and then divided by the number of collection times to obtain the average running speed Vavg of each engine teaching aid.

[0097] Connect a power meter to different automotive engine teaching aids, and continuously collect power data during the operation of the teaching aids. After the teaching aids stop running, all the collected power values are added up and then divided by the number of collection times to obtain the average power PGavg of each engine teaching aid.

[0098] Install a temperature sensor on the cylinder head of each automotive engine teaching aid, continuously record the temperature values during the operation of the teaching aid, and find the maximum value among these temperature values by comparison, which is the maximum working temperature TE of each engine teaching aid.

[0099] Install an accelerometer on each automotive engine teaching aid, measure the vibration acceleration in each direction during the operation of the teaching aid, and add up the root mean square values of the vibration accelerations in each direction to obtain the total vibration intensity SV of each engine teaching aid.

[0100] Calculate the comprehensive loss index FT of each teaching aid according to the total usage frequency F of the teaching aid, training time T, comprehensive anomaly index EH, average running speed Vavg, average power PGavg, maximum working temperature TE, and total vibration intensity SV. The calculation formula is: ; where TT is the total historical usage duration of each teaching aid; NR is the total historical repair times of each teaching aid.

[0101] It should be noted that the total historical usage duration TT of each teaching aid is obtained. According to the timing module built into each engine teaching aid, starting from the first activation of the teaching aid, this module automatically records the duration of each use and accumulatively calculates the total usage duration TT of each teaching aid.

[0102] The total historical maintenance times NR of each teaching aid can be obtained by querying the school's maintenance record system.

[0103] It should be noted that Taking into comprehensive consideration the usage duration and usage frequency of the teaching aid, the longer the usage duration and the higher the usage frequency, the greater the wear and tear on the teaching aid. It reflects the energy consumption situation of the teaching aid during operation. The larger the product of the average operating speed and the average power, the greater the load borne by the teaching aid during operation. Taking 25 degrees Celsius as the reference temperature, calculate the deviation degree between the highest working temperature of the teaching aid and the reference temperature. Excessive temperature will accelerate the aging of the teaching aid. Taking into comprehensive consideration the total historical usage duration TT, the total historical maintenance times NR of the teaching aid and the comprehensive anomaly index EH, and their combined influence on the comprehensive wear index FT. It shows that the longer the usage time, the greater the overall wear and tear of the teaching aid. The formula obtains the comprehensive wear index FT of each teaching aid by taking the square root and summarizing the calculation results of the above-mentioned various parts.

[0104] Step 402: Calculate the maintenance requirement index RKI of each teaching aid. The specific method is as follows: Based on the comprehensive wear index FT, calculate the maintenance requirement index RKI of each teaching aid. The formula is as follows: ; where HH is the average humidity in the training environment.

[0105] It should be noted that the average humidity HH in the training environment is obtained. Multiple humidity sensors are placed in the training venue to monitor the humidity of the surrounding environment in real time. By collecting humidity data at 5-minute intervals, after one day of collection, add up all the collected humidity values and divide by the number of collections to obtain the average humidity HH in the training environment during this period.

[0106] It should be noted that this formula calculates the urgency of the maintenance requirement of each teaching aid based on FT and factors such as historical usage duration, maintenance times, and environmental humidity. Considering again the relationship between the total historical usage duration and the maintenance times; It reflects the influence of environmental humidity on the maintenance requirement. As FT increases and with the combined influence of these factors, the denominator will approach 1. At this time, RKI approaches FT, indicating a higher urgency of the maintenance requirement; conversely, the urgency of the maintenance requirement is lower.

[0107] Step 403: Determine whether each teaching aid needs maintenance. The specific method is as follows: The maintenance requirement index thresholds include maintenance requirement index threshold one RKI1 and maintenance requirement index threshold two RKI2, and RKI1 < RKI2. By comprehensively collecting historical maintenance record data of multiple teaching aids of the same type of automotive engine under the same conditions, including the comprehensive loss index FT and the average humidity HH in the training environment, calculate the maintenance requirement index RKI for each teaching aid, and further calculate the average value RKIavg and the standard deviation σ of the maintenance requirement index. Take RKIavg - σ as the maintenance requirement index threshold one RKI1, and take RKIavg + σ as the maintenance requirement index threshold two RKI2.

[0108] When the maintenance requirement index RKI ≤ the maintenance requirement index threshold one RKI1, it is determined that the teaching aid does not need maintenance and continues to be used normally.

[0109] When the maintenance requirement index threshold one RKI1 < the maintenance requirement index RKI ≤ the maintenance requirement index threshold two RKI2, it is determined that the teaching aid is in a medium maintenance state, and maintenance measure one is taken; Maintenance measure one is to clean components such as the outer shell and radiator of the automotive engine, conduct a simple function test on the teaching aid, simulate the normal use scenario of the teaching aid, and check whether its various functions are operating normally.

[0110] When the maintenance requirement index RKI > the maintenance requirement index threshold two RKI2, it is determined that the teaching aid is in a heavy maintenance state, and maintenance measure two is taken; Maintenance measure two is to disassemble components such as the cylinder head and piston of the automotive engine, and check for wear and damage; For severely worn and damaged components found, replace them in a timely manner.

[0111] Integrate steps 401 to 403:

[0112] This method evaluates its potential loss situation. Through scientific calculation and threshold comparison, it accurately determines whether the automotive engine teaching aid needs maintenance, and takes appropriate maintenance measures for different situations, extends the service life of the teaching aid, reduces the maintenance cost, and ensures that the teaching aid is always in good working condition.

[0113] On the other hand, the present invention also discloses an intelligent management system for teaching aids for automotive training, which is used to implement the above-mentioned intelligent management method for teaching aids for automotive training, including:

[0114] A data acquisition module, which is used to collect the usage status data and performance parameter data of the engine teaching aid;

[0115] An intelligent scheduling module, which is used to calculate the actual demand quantity R of teaching aids based on usage status data; calculate the urgency index P of teaching aid demand according to the usage status data and the actual demand quantity R of teaching aids; preset the urgency index threshold of teaching aid demand, compare the urgency index P of teaching aid demand with the urgency index threshold of teaching aid demand, and judge the urgency level of teaching aid demand according to the comparison result; if the urgency of teaching aid demand is high, send a teaching aid purchase reminder.

[0116] A reminder module, if the urgency of teaching aid demand is low, calculates the teaching aid temperature change rate TCR of each teaching aid based on usage status data; calculates the comprehensive anomaly index EH of each teaching aid according to the teaching aid temperature change rate TCR, usage status data and performance parameter data; preset the comprehensive anomaly index threshold, compare the comprehensive anomaly index EH with the comprehensive anomaly index threshold, and judge whether the status of each teaching aid is normal according to the comparison result; if the status of the teaching aid is abnormal, send an alarm reminder.

[0117] A maintenance module, if the status of the teaching aid is normal, calculates the comprehensive loss index FT of each teaching aid according to the usage status data and the comprehensive anomaly index EH; calculates the maintenance requirement index RKI of each teaching aid based on the comprehensive loss index FT; preset the maintenance requirement index threshold, compare the maintenance requirement index RKI with the maintenance requirement index threshold, and judge whether each teaching aid needs maintenance according to the comparison result; if the teaching aid needs maintenance, take corresponding maintenance measures.

[0118] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution.

[0119] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0120] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application.

Claims

1. An intelligent management method for teaching aids for automobile training, characterized in that: include: Collect usage status data and performance parameter data of engine teaching aids; Calculate the actual required quantity R of teaching aids based on usage status data; According to the usage status data and the actual demand quantity R of teaching aids, the urgency index P of teaching aids demand is calculated; Preset a threshold value of the teaching aids demand urgency index, compare the teaching aids demand urgency index P with the teaching aids demand urgency index threshold value, and determine the teaching aids demand urgency level based on the comparison result; if the teaching aids demand urgency is high, issue a teaching aids purchase reminder; If the urgency of the teaching aid demand is low, the teaching aid temperature change rate TCR of each teaching aid is calculated based on the usage status data; the comprehensive abnormal index EH of each teaching aid is calculated according to the teaching aid temperature change rate TCR, the usage status data and the performance parameter data; a comprehensive abnormal index threshold is preset, the comprehensive abnormal index EH is compared with the comprehensive abnormal index threshold, and whether the teaching aid status of each teaching aid is normal is judged according to the comparison result; If the teaching aid is in an abnormal state, an alarm will be issued; If the teaching aid is in normal condition, calculate the comprehensive wear index FT of each teaching aid based on the usage status data and the comprehensive abnormality index EH; calculate the maintenance requirement index RKI of each teaching aid based on the comprehensive wear index FT; preset the maintenance requirement index threshold, compare the maintenance requirement index RKI with the maintenance requirement index threshold, and judge whether each teaching aid needs maintenance based on the comparison result; If the teaching aids require maintenance, take corresponding maintenance measures.

2. The intelligent management method of teaching aids for automobile training according to claim 1 is characterized in that: The method to calculate the actual required quantity R of teaching aids is: The usage status data includes the total frequency F of teaching aid use and the training time T during the usage cycle; According to the total frequency of use of teaching aids F and the training time T, the actual number of teaching aids required R is calculated based on the following formula: Among them, S is the number of students participating in the training; N is the number of teaching aids in stock; DP is the difficulty coefficient of the training project; CP is the complexity index of the training project; LS is the average skill level index of students.

3. The intelligent management method of teaching aids for automobile training according to claim 2 is characterized in that: The method to determine the urgency level of teaching aids needs is: The usage status data also includes the historical failure rate U of the teaching aids during the usage period; According to the total frequency of teaching aids use F, the actual number of teaching aids required R and the historical failure rate of teaching aids U, the teaching aids demand urgency index P is calculated based on the formula: Among them, ω1 is The weight coefficient is 0.3~0.4; ω2 is The weight coefficient is 0.1~0.4; ω3 is the weight coefficient of the historical failure rate U of the teaching aids, and its value is 0.2~0.5; and ω1+ω2+ω3=1; Preset the teaching aids demand urgency index threshold Pth; When the teaching aid demand urgency index P ≤ the teaching aid demand urgency index threshold Pth, the teaching aid demand urgency is judged to be low, and the existing teaching aids are maintained; When the teaching aid demand urgency index P>the teaching aid demand urgency index threshold Pth, it is judged that the teaching aid demand urgency is high, and a teaching aid purchase reminder is issued.

4. The intelligent management method of teaching aids for automobile training according to claim 3 is characterized in that: The method for calculating the teaching aid temperature change rate TCR of each teaching aid is: The usage status data also includes the temperature value TC of each teaching aid. i ; Based on the teaching aid temperature value TC i , calculate the temperature change rate TCR of each teaching aid, the calculation formula is: ； Among them, TC i is the temperature value of the teaching aid measured at the i-th time point; i is the sequence number of the time point, and its value is [1, n-1]; n is the total number of measured time points, and its value is a positive integer; is the temperature value of the teaching aid measured at the i+1th time point; is the i-th time point; is the i+1th time point; is the standard deviation of the temperature measurements; is the weight of the temperature value of the teaching aid measured at the i-th time point.

5. The intelligent management method of teaching aids for automobile training according to claim 4 is characterized in that: The method for calculating the comprehensive abnormal index EH of each teaching aid is: The usage status data also includes the vibration amplitude VA of each teaching aid; The performance parameter data also include the total teaching aid usage time TG and actual power PR of each teaching aid; According to the teaching aid temperature change rate TCR, teaching aid vibration amplitude VA, teaching aid total use time TG and actual power PR, the comprehensive abnormal index EH of each teaching aid is calculated based on the formula: Among them, TS is the total standard use time of the teaching aid; PRS is the standard power of the teaching aid during normal operation; TCRmax is the maximum temperature change rate of the teaching aid; VAmax is the maximum vibration amplitude of the teaching aid; φ1 is The weight coefficient is 0.2~0.4; φ2 is The weight coefficient is 0.1~0.3; φ3 is The weight coefficient is 0.3~0.5; φ4 is The weight coefficient is between 0.2 and 0.4; and φ1+φ2+φ3+φ4=1.

6. The intelligent management method of teaching aids for automobile training according to claim 5 is characterized in that: The method for judging whether the teaching aid status of each teaching aid is normal is: Preset comprehensive abnormal index threshold EHth; When the comprehensive abnormal index EH≤the comprehensive abnormal index threshold EHth, it is judged that the teaching aid state of the corresponding teaching aid is normal; When the comprehensive abnormal index EH>the comprehensive abnormal index threshold EHth, the teaching aid status of the corresponding teaching aid is judged to be abnormal, and an alarm is issued.

7. The intelligent management method of teaching aids for automobile training according to claim 6 is characterized in that: The method for calculating the comprehensive loss index FT of each teaching aid is: The usage status data also includes the average operating speed Vavg, average power PGavg, maximum operating temperature TE and total vibration intensity SV of each teaching aid; According to the total frequency of use of teaching aids F, training time T, comprehensive abnormal index EH, average operating speed Vavg, average power PGavg, maximum operating temperature TE and total vibration intensity SV, the comprehensive loss index FT of each teaching aid is calculated. The calculation formula is: ； Among them, TT is the total historical usage time of each teaching aid; NR is the total number of historical repairs of each teaching aid.

8. The intelligent management method of teaching aids for automobile training according to claim 7 is characterized in that: The method for calculating the maintenance requirement index RKI for each teaching aid is: Based on the comprehensive loss index FT, the maintenance requirement index RKI of each teaching aid is calculated according to the following formula: ; Where HH is the average humidity in the training environment.

9. The intelligent management method of teaching aids for automobile training according to claim 8 is characterized in that: The method to determine whether each teaching aid needs maintenance is: The maintenance demand indicator threshold includes the maintenance demand indicator threshold 1 RKI1 and the maintenance demand indicator threshold 2 RKI2, and RKI1 <RKI2; When the maintenance requirement index RKI≤the maintenance requirement index threshold value RKI1, it is judged that the corresponding teaching aid does not need maintenance and continues to be used normally; When the maintenance demand index threshold 1 RKI1 < maintenance demand index RKI ≤ maintenance demand index threshold 2 RKI2, it is judged that the corresponding teaching aid is in a medium maintenance state, and maintenance measure 1 is taken; When the maintenance demand indicator RKI> the maintenance demand indicator threshold value 2 RKI2, it is judged that the corresponding teaching aid is in a heavy maintenance state, and maintenance measure 2 is taken.

10. An intelligent management system for teaching aids used in automobile training, characterized in that: A data acquisition module, used to collect usage status data and performance parameter data of the engine teaching aid; An intelligent scheduling module is used to calculate the actual required number R of teaching aids based on the usage status data; and calculate the urgency index P of teaching aid demand based on the usage status data and the actual required number R of teaching aids; Preset a threshold value of the teaching aids demand urgency index, compare the teaching aids demand urgency index P with the teaching aids demand urgency index threshold value, and determine the teaching aids demand urgency level based on the comparison result; if the teaching aids demand urgency is high, issue a teaching aids purchase reminder; The reminder module, if the urgency of the teaching aid demand is low, calculates the teaching aid temperature change rate TCR of each teaching aid based on the usage status data; calculates the comprehensive abnormal index EH of each teaching aid based on the teaching aid temperature change rate TCR, the usage status data and the performance parameter data; presets the comprehensive abnormal index threshold, compares the comprehensive abnormal index EH with the comprehensive abnormal index threshold, and determines whether the teaching aid status of each teaching aid is normal based on the comparison result; If the teaching aid is in an abnormal state, an alarm will be issued; Maintenance module, if the teaching aid is in normal state, calculate the comprehensive loss index FT of each teaching aid according to the usage status data and the comprehensive abnormality index EH; calculate the maintenance requirement index RKI of each teaching aid based on the comprehensive loss index FT; preset the maintenance requirement index threshold, compare the maintenance requirement index RKI with the maintenance requirement index threshold, and judge whether each teaching aid needs maintenance according to the comparison result; If the teaching aids require maintenance, take corresponding maintenance measures.

Images