CN113702083A - Performance evaluation method and system of transmission loading platform - Google Patents

Performance evaluation method and system of transmission loading platform Download PDF

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CN113702083A
CN113702083A CN202111252842.2A CN202111252842A CN113702083A CN 113702083 A CN113702083 A CN 113702083A CN 202111252842 A CN202111252842 A CN 202111252842A CN 113702083 A CN113702083 A CN 113702083A
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CN113702083B (en
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奚乐
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Sixys (Nantong) Intelligent Equipment Manufacturing Co.,Ltd.
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Jiangsu Sikesi Machinery Manufacturing Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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    • G01M99/005—Testing of complete machines, e.g. washing-machines or mobile phones
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
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    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
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Abstract

The invention discloses a performance evaluation method and a system of a transmission carrying platform, which relate to the technical field of intelligent manufacturing, and are used for obtaining transmission parameter information according to carrying information; carrying out feature extraction on the chain wheel meshing information in the first image information to obtain predicted transmission influence information; inputting the predicted transmission influence information and the monitoring data set into an evaluation model, and obtaining an output result of the evaluation model, wherein the output result comprises a transmission evaluation result used for representing the transmission capacity of the transmission loading platform under the condition of predicting the transmission influence information and the monitoring data set; and judging whether the transmission evaluation result is matched with the transmission parameter information or not, and sending feedback information. The technical problems that in the prior art, performance evaluation and carrying parameter adjustment of a carrying platform depend on manual operation, influence of human factors exists, and accuracy is low are solved. The performance evaluation process is achieved without manual intervention, errors caused by human factors are avoided, and meanwhile, the technical effect of effectively improving the operation efficiency and accuracy by adding artificial intelligence is achieved.

Description

Performance evaluation method and system of transmission loading platform
Technical Field
The invention relates to the technical field of intelligent manufacturing, in particular to a performance evaluation method and system of a transmission loading platform.
Background
The sprocket is a wheel with cogged sprocket teeth for meshing with precisely pitched blocks on a chain link or cable. The chain wheel is widely applied to mechanical transmission and the like in the industries of chemical engineering, textile machinery, escalators, wood processing, three-dimensional parking garages, agricultural machinery, food processing, instruments, petroleum and the like. Cargo platform carries out the goods based on the drive power of sprocket, article transportation such as raw materials, the conveying, because the form of the article of delivery, the nature is different, the transportation requirement of operation difference, simultaneously should adopt rather than assorted cargo platform size to different sprockets, go on in order to ensure transfer process, how to select suitable transmission power and select the conveying platform of suitable size or distribute reasonable delivery weight to cargo platform, this process needs the manual work to select and adjust, operating personnel's work load and the work degree of difficulty have been aggravated, easily receive the influence of artificial experience simultaneously and cause the error.
Disclosure of Invention
The invention aims to solve the technical defects, and provides a performance evaluation method and a system of a transmission loading platform, which are used for solving the technical problem that the performance evaluation and loading parameter adjustment of the loading platform in the prior art depend on manual operation, and are influenced by human factors and have low accuracy.
To this end, a first objective of the present invention is to provide a method for evaluating performance of a transmission loading platform, the method being applied to a performance evaluation system, the system including a transmission force monitoring device, the transmission force monitoring device including an image capturing device and a pressure monitoring device, the method including: acquiring carrying information; acquiring transmission parameter information according to the carrying information; acquiring first image information through the image acquisition equipment, wherein the first image information comprises chain wheel meshing information of a transmission loading platform; carrying out feature extraction on the chain wheel meshing information in the first image information to obtain predicted transmission influence information; acquiring a monitoring data set through pressure monitoring equipment, wherein the monitoring data set comprises stress monitoring information of multiple nodes in the transmission process of a transmission loading platform; inputting the predicted transmission influence information and the monitoring data set into an evaluation model, wherein the evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the predicted transmission influence information, the monitoring data set and identification information for identifying a transmission evaluation result; obtaining an output of the evaluation model, the output comprising a transmission evaluation for indicating a transmission capability of the transmission stage with the predicted transmission impact information and the monitored data set; and judging whether the transmission evaluation result is matched with the transmission parameter information or not, and sending feedback information according to the judgment result.
Preferably, the obtaining of the transmission parameter information according to the carrying information includes: obtaining the property of the article according to the carrying information; acquiring a bearing requirement according to the article attribute; acquiring load weight information; obtaining a conveying influence coefficient according to the carrying weight information and the article attribute; and obtaining the transmission parameter information according to the transmission influence coefficient and the bearing requirement.
Preferably, the obtaining a conveying influence coefficient according to the carrying weight information and the article attribute includes: obtaining a stability coefficient according to the article attribute; obtaining predicted pressure information according to the stability coefficient and the load weight information; obtaining a size influence coefficient according to the carrying property and the carrying weight information; and obtaining the transmission influence coefficient according to the size influence coefficient and the predicted pressure information.
Preferably, the extracting the features of the sprocket meshing information in the first image information to obtain the predicted transmission influence information includes: acquiring an engagement element and an engagement relation according to the sprocket engagement information of the first image information; acquiring meshing depth information according to the meshing element and the meshing relation; obtaining a physical property of the element based on the engaging element; inputting the engagement relation and the engagement depth information into a pressure evaluation model, wherein the pressure evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the engagement relation, the engagement depth information and identification information for identifying the pressure evaluation information; obtaining an output result of the pressure evaluation model, wherein the output result comprises pressure evaluation information which is used for reflecting pressure information corresponding to the meshing relation and the meshing depth information; and obtaining the predicted transmission influence information according to the element physical characteristics and the pressure evaluation information.
Preferably, the obtaining of the meshing element and the meshing relationship based on the sprocket meshing information of the first image information includes: obtaining engaging element characteristic information; traversing and comparing the first image information according to the characteristic information of the meshing elements to obtain a first comparison result, wherein the first comparison result is all the meshing elements in the identified first image information, and marking the meshing elements; determining the position information of the engaging element according to the mark; and acquiring the engagement relation according to the position information of the engagement element and the engagement element.
Preferably, the method comprises: obtaining a matched carrying size according to the engaging element and the physical characteristics of the elements; acquiring a loading weight threshold according to the matched loading size and the loading information; and acquiring carrying scheme information according to the carrying information and the carrying weight threshold value.
Preferably, the transmission force monitoring device comprises a tightness monitoring device, the method comprising: acquiring tightness information of the chain wheel through the tightness monitoring equipment; inputting the engaging elements and the tightness information into a stress evaluation model, wherein the stress evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the engaging elements, the tightness information and identification information for identifying the stress evaluation information; obtaining an output result of the stress evaluation model, wherein the output result is a stress evaluation result which is used for reflecting stress requirements corresponding to the meshing element and the tightness information; judging whether the transmission evaluation result is matched with the stress evaluation result; and if the stress evaluation result is not satisfied, sending reminding information, and obtaining recommended adjustment information according to the stress evaluation result.
A second object of the present invention is to provide a system for evaluating performance of a transmission loading platform, the system comprising:
a first obtaining unit for obtaining the loading information;
the second obtaining unit is used for obtaining the transmission parameter information according to the carrying information;
the third obtaining unit is used for obtaining first image information through image acquisition equipment, wherein the first image information comprises chain wheel meshing information of a transmission loading platform;
a fourth obtaining unit, configured to perform feature extraction on sprocket meshing information in the first image information, and obtain predicted transmission influence information;
the fifth obtaining unit is used for obtaining a monitoring data set through pressure monitoring equipment, wherein the monitoring data set comprises stress monitoring information of multiple nodes in the transmission process of the transmission loading platform;
the first execution unit is used for inputting the predicted transmission influence information and the monitoring data set into an evaluation model, wherein the evaluation model is obtained by training and converging a plurality of groups of training data, and each group of training data comprises the predicted transmission influence information, the monitoring data set and identification information for identifying a transmission evaluation result;
a sixth obtaining unit, configured to obtain an output result of the evaluation model, where the output result includes a transmission evaluation result, and the transmission evaluation result is used to represent a transmission capability of the transmission loading platform under the condition of predicting the transmission influence information and the monitoring data set;
and the second execution unit is used for judging whether the transmission evaluation result is matched with the transmission parameter information or not and sending feedback information according to the judgment result.
A third object of the present invention is to provide a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above method when executing the computer program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
according to the performance evaluation method and system of the transmission loading platform, provided by the embodiment of the invention, loading information is obtained; acquiring transmission parameter information according to the carrying information; acquiring first image information through the image acquisition equipment, wherein the first image information comprises chain wheel meshing information of a transmission loading platform; carrying out feature extraction on the chain wheel meshing information in the first image information to obtain predicted transmission influence information; acquiring a monitoring data set through pressure monitoring equipment, wherein the monitoring data set comprises stress monitoring information of multiple nodes in the transmission process of a transmission loading platform; inputting the predicted transmission influence information and the monitoring data set into an evaluation model, wherein the evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the predicted transmission influence information, the monitoring data set and identification information for identifying a transmission evaluation result; obtaining an output of the evaluation model, the output comprising a transmission evaluation for indicating a transmission capability of the transmission stage with the predicted transmission impact information and the monitored data set; judging whether the transmission evaluation result, namely the transmission performance of the transmission loading platform meets the transmission parameter requirement of the object to be carried currently, if so, controlling the transmission loading platform according to the requirement corresponding to the transmission parameter information, if not, correspondingly reminding the current loading platform to ensure that the performance of the loading platform can not meet the current loading requirement, giving out corresponding unsatisfied projects or giving out corresponding adjustment schemes, giving out corresponding feedback information whether meeting or not, sending the feedback information to an evaluation system to be displayed for a user to refer, so as to carry out corresponding operation according to the bearing performance of the transmission loading platform, improve the working efficiency and avoid equipment loss, avoid errors caused by human factors without manual intervention in the whole performance evaluation process, and simultaneously add artificial intelligence to effectively improve the operational efficiency and accuracy, thereby solving the problem that the performance evaluation and the loading parameter adjustment of the loading platform in the prior art depend on manual operation, the method has the technical problem of low accuracy due to the influence of human factors.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
Fig. 1 is a schematic flow chart illustrating a performance evaluation method of a transmission loading platform according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart illustrating another method for evaluating the performance of a transmission stage according to an embodiment of the present disclosure;
FIG. 3 is a schematic flow chart illustrating another method for evaluating the performance of a transmission stage according to an embodiment of the present disclosure;
FIG. 4 is a schematic flow chart illustrating another method for evaluating the performance of a transmission stage according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a performance evaluation system for a transmission stage according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a fifth obtaining unit 15, a first executing unit 16, a sixth obtaining unit 17, a second executing unit 18, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 305.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention. On the contrary, the embodiments of the invention include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.
In the description of the present invention, it should be noted that any process or method descriptions in flowcharts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and that the scope of the preferred embodiments of the present invention includes additional implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present invention.
A method for evaluating the performance of a driven stage according to an embodiment of the present invention is described below with reference to the accompanying drawings.
The technical scheme of the application is as follows: acquiring carrying information; acquiring transmission parameter information according to the carrying information; acquiring first image information through the image acquisition equipment, wherein the first image information comprises chain wheel meshing information of a transmission loading platform; carrying out feature extraction on the chain wheel meshing information in the first image information to obtain predicted transmission influence information; acquiring a monitoring data set through pressure monitoring equipment, wherein the monitoring data set comprises stress monitoring information of multiple nodes in the transmission process of a transmission loading platform; inputting the predicted transmission influence information and the monitoring data set into an evaluation model, wherein the evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the predicted transmission influence information, the monitoring data set and identification information for identifying a transmission evaluation result; obtaining an output of the evaluation model, the output comprising a transmission evaluation for indicating a transmission capability of the transmission stage with the predicted transmission impact information and the monitored data set; and judging whether the transmission evaluation result is matched with the transmission parameter information or not, and sending feedback information according to the judgment result. The technical problems that in the prior art, performance evaluation and carrying parameter adjustment of a carrying platform depend on manual operation, influence of human factors exists, and accuracy is low are solved.
Example one
As shown in fig. 1, an embodiment of the present application provides a performance evaluation method for a transmission loading platform, where the method is applied to a performance evaluation system, where the system includes a transmission force monitoring device, the transmission force monitoring device includes an image acquisition device and a pressure monitoring device, and the method includes:
specifically, the embodiment of the application utilizes the communication connection of the transmission force monitoring equipment and the performance evaluation system to send the collected monitoring data of the carrying platform to the performance evaluation system, the monitoring data is carried out through the corresponding industrial monitoring equipment, the monitoring equipment of the embodiment of the application comprises image collecting equipment, pressure monitoring equipment and tightness monitoring equipment, but is not limited to the image collecting equipment, the meshing relation and the state of the chain wheels of the carrying platform are collected through the image collecting equipment, the pressure monitoring equipment is respectively arranged in a plurality of carrying processes of the carrying platform or on positions corresponding to the meshing of the chain wheels, so that the stress conditions of the transport nodes and the meshing relation in the whole process can be monitored, the tightness monitoring is mainly used for monitoring the meshing tightness condition in the chain wheels, and the tightness condition of the chain wheels has important influence on the transmission performance and the abrasion in the using process, through the real-time monitoring of the monitoring equipment, the monitored data are synchronized to the performance evaluation system, and accurate calculation and evaluation are carried out through a computer according to the data, so that the operation speed and accuracy are improved.
Step S100, acquiring carrying information;
step S200, acquiring transmission parameter information according to the carrying information;
further, referring to fig. 2, the step S200 of obtaining the transmission parameter information according to the loading information includes:
step S210, obtaining article attributes according to the carrying information;
step S220, acquiring a bearing requirement according to the article attribute;
step S230 obtaining load weight information;
step S240, obtaining a transmission influence coefficient according to the carrying weight information and the article attribute;
step S250 obtains the transmission parameter information according to the transmission impact coefficient and the bearer requirement.
Specifically, the carrying information is information of an article to be carried on the carrying platform, which includes a name, carrying time, carrying quantity, starting and stopping positions of the article, and different carrying articles differ in form and attribute, which may affect the placing mode, volume, and weight requirements of carrying, for example, speed and carrying requirements are different for liquid articles and solid articles during the carrying process, and for example, corresponding carrying conditions also exist for fragile articles, or a difference in relation between weight and volume ratio exists for articles with high density and low density, and sometimes corresponding transmission parameter information such as platform size requirement, carrying speed, stability and the like during the carrying process needs to be considered, the transmission parameter information corresponds to the carrying requirements according to the carrying information, and the corresponding carrying requirements are determined according to the article attribute of the carrying article, then, the weight information of the carried object is obtained from the object information, and comprehensive analysis is carried out according to the weight information of the carried object and the attribute of the object to determine a corresponding transmission influence coefficient, wherein the transmission influence coefficient refers to the influence degree of the object attribute and the carried object weight information in the transmission process, for example, for the objects with different attributes and different weights and the same weight, the maximum extrusion force and the transmission speed born in the transmission process can have difference, if the liquid is transmitted at high speed, the flowing of the liquid can not damage the characteristics of the liquid, the transmission influence coefficient is the influence size information calculated according to the object attribute and the weight, the larger the transmission influence coefficient is, the larger the influence is, the object characteristics of the liquid need to be considered, the carrying requirement is that the carrying object needs to be placed by a container, and the form exists in the transmission process, the size of the loading platform is also considered corresponding to the bearing requirement, the size of the loading platform is also related to the size of the chain wheel and the conveying speed, and finally, conveying parameter information is determined according to the conveying influence coefficient and the bearing requirement, namely, the specific requirements of the loading platform, the size of the chain wheel, the carrying speed, the carrying scheme and the like in the conveying process are required. In order to improve the efficiency and accuracy of calculation, an artificial intelligence technology can be added, a database is built through historical data, a model is built through database training, and correspondingly acquired data are calculated through the model, so that the calculation and output speed of the system is improved.
Step S300, acquiring first image information through the image acquisition equipment, wherein the first image information comprises chain wheel meshing information of a transmission loading platform;
particularly, first image information is the image information who carries out the collection to the sprocket structure of transmission year thing platform, sprocket connection relation in can reacting transmission year thing platform, connect like how many total thing platforms, through how many gears, the sprocket makes up and connects, set up respectively and connect through what mode again in which position, the direction of transfer of drive power etc. through the whole understanding to the sprocket meshing relation of transmission carrying platform, thereby the drive power of analysis sprocket and the platform atress condition that corresponds, so that carry out accurate grasp and aassessment to transmission thing platform's performance.
Step S400, extracting the characteristics of the chain wheel meshing information in the first image information to obtain predicted transmission influence information;
further, referring to fig. 3, the step S400 of performing feature extraction on the sprocket meshing information in the first image information to obtain predicted transmission influence information includes:
step S410, acquiring an engagement element and an engagement relation according to the chain wheel engagement information of the first image information;
step S420, acquiring meshing depth information according to the meshing element and the meshing relation;
step S430, acquiring element physical characteristics according to the meshing element;
step S440, inputting the engagement relation and the engagement depth information into a pressure evaluation model, wherein the pressure evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the engagement relation, the engagement depth information and identification information for identifying the pressure evaluation information;
step S450, obtaining an output result of the pressure evaluation model, wherein the output result comprises pressure evaluation information which is used for reflecting pressure information corresponding to the meshing relation and the meshing depth information;
step S460 obtains the predicted transmission influence information according to the element physical characteristics and the pressure evaluation information.
Further, the step S410 of obtaining the meshing element and the meshing relationship according to the sprocket meshing information of the first image information includes:
step S411 obtains the characteristic information of the meshing element;
step S412, traversing and comparing the first image information according to the engaging element feature information to obtain a first comparison result, wherein the first comparison result is all the engaging elements in the identified first image information, and marking the engaging elements;
step S413 determines the engaging element position information based on the mark;
step S414 obtains the engagement relationship based on the engagement element position information and the engagement element.
Specifically, image recognition is carried out on first image information, convolution kernel is used for carrying out traversal comparison on the first image information by utilizing the characteristic information of the meshing element, the partition size is determined firstly when the convolution kernel is used for carrying out the characteristic comparison, the first image information is partitioned according to the partition size, then the characteristic information of the meshing element is used for carrying out the characteristic traversal comparison in the partition, the first comparison result which meets the characteristic information of the meshing element is obtained and output as a first comparison result, the first comparison result is the recognized meshing element, the position of the meshing element is marked, and the position relation of the meshing element in the image is determined according to the marked position of the meshing element, so that the meshing relation of the fitting element is determined. Depth feature analysis and extraction are carried out on the image according to the mark positions and the meshing relationship of the meshing elements, so as to obtain the gear meshing depth between the meshing elements in the meshing relationship, namely the gear meshing depth is used for reflecting the meshing tightness of two gears, for example, the tooth grooves of the gears are deep and shallow, so that the meshing depth is large when the tooth grooves are deep when two gears or more than two gears are meshed, otherwise, the meshing depth is small, the meshing depth and the speed height in the transmission process correspond to different wear conditions, friction force and the like, the friction force is large when the meshing depth is too large, the risk of loosening and slipping exists when the meshing depth is too small, meanwhile, certain influence is also exerted on the transmission speed, so that the corresponding different meshing elements and the fitting relationship correspond to different transmission requirements in the transmission process, and the bearing degrees of the pressure, the speed and the friction force are different, if the chain wheels are arranged on the shaft and swing and skew exist, the end surfaces of the two chain wheels in the same transmission assembly are positioned in the same plane, and the deviation can be 1 mm when the center distance of the chain wheels is below 0.5 m; when the center distance of the chain wheel is more than 0.5 m, the deviation can be 2 mm. But there is no possibility of the phenomenon of rubbing the flanks of the sprocket, which risks being caused by the fact that the pressure to which the wheels are subjected during the transfer exceeds their bearing capacity, if the two wheels are displaced too much, and therefore the particular conditions and relationships of engagement of the sprockets are taken into account. Meanwhile, the material can be identified according to the image, such as plastic, rubber and metal, and different materials have different stress degrees and abrasion conditions in the transmission process, the physical characteristics of the elements are used for reflecting the physical characteristics of the meshing elements in the aspects of material, specification, size and the like, the stress requirement in transmission is determined by combining a specific meshing relation, the pressure evaluation information is used for reflecting the stress requirement corresponding to the meshing information of the chain wheel, in order to improve the accuracy of pressure evaluation information, a Neural network model is added, the pressure evaluation model is a Neural network model in machine learning, a Neural Network (NN) is a complex Neural network system formed by widely interconnecting a large number of simple processing units (called neurons), reflects many basic characteristics of human brain functions, and is a highly complex nonlinear dynamical learning system. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (ANN), is a description of the first-order properties of the human brain system. Briefly, it is a mathematical model. And through training of a large amount of training data, inputting the meshing relation and the meshing depth information into a neural network model, and outputting pressure evaluation information.
Furthermore, the training process is essentially a supervised learning process, each group of supervised data comprises an engagement relationship, engagement depth information and identification information for identifying pressure evaluation information, the engagement relationship and the engagement depth information are input into a neural network model, the neural network model is continuously self-corrected and adjusted according to the identification information for identifying the pressure evaluation information, and the group of supervised learning is ended and the next group of supervised learning is carried out until the obtained output result is consistent with the identification information; and when the output information of the neural network model reaches the preset accuracy rate/reaches the convergence state, finishing the supervised learning process. Through right the supervision study of neural network model, and then make neural network model handles input information is more accurate, and then makes the pressure assessment information of output more reasonable, accurate, and then reaches and promotes pressure assessment information accuracy, improves the operating efficiency, avoids artificial intervention's technological effect, tamps the basis for the follow-up accurate aassessment that carries out transmission objective platform performance.
Step S500, a monitoring data set is obtained through pressure monitoring equipment, and the monitoring data set comprises stress monitoring information of multiple nodes in the transmission process of a transmission loading platform;
step S600, inputting the predicted transmission influence information and the monitoring data set into an evaluation model, wherein the evaluation model is obtained by training and converging a plurality of groups of training data, and each group of training data comprises the predicted transmission influence information, the monitoring data set and identification information for identifying a transmission evaluation result;
step S700, obtaining output results of the evaluation model, wherein the output results comprise transmission evaluation results which are used for representing the transmission capacity of the transmission loading platform under the condition of predicting transmission influence information and monitoring data sets;
specifically, the monitoring data set is the sum of monitoring pressure data corresponding to each transportation stage and meshing element of the transmission loading platform, can reflect the stress condition of the current transmission loading platform, and is combined with the transmission element of the loading platform, namely sprocket meshing information, and correspondingly obtained predicted transmission influence information for judging how much pressure the current loading platform can bear and how much speed the current loading platform can receive, namely transmitting evaluation information, in order to improve the accuracy of transmitting the evaluation result, artificial intelligence is added in the application, the predicted transmission influence information and the monitoring data set are comprehensively analyzed through a neural network model, namely an evaluation model, and the evaluation model is obtained through training convergence through a large amount of data, so the artificial neural network has the characteristics of high operation efficiency and high accuracy of output values, and the artificial neural network is provided and developed on the basis of modern neuroscience, the neural network is an operation model formed by connecting a large number of nodes (or called neurons) with each other, each node represents a specific output function called an excitation function, the connection between every two nodes represents a weighted value for passing through a connection signal called a weight, the weighted value is equivalent to the memory of an artificial neural network, the output of the network is the expression of a logic strategy according to the connection mode of the network, and the consultation prediction model established based on the neural network model can output accurate consultation result prediction information, so that the model has strong analysis and calculation capacity and achieves the accurate and efficient technical effect. The estimation model obtained by training is used for estimating the predicted transmission influence information and the monitoring data set to obtain transmission estimation information matched with the estimation model, the transmission estimation information is used for reflecting how much pressure the transmission loading platform can bear and how much speed the transmission loading platform can accept, through the accuracy estimation of the performance of the transmission loading platform, the platform can be favorably controlled correspondingly according to the estimation performance, and the technical effects of ensuring the performance optimization of the loading platform and prolonging the service life by avoiding abrasion are achieved.
Step S800 determines whether the transmission evaluation result matches the transmission parameter information, and sends feedback information according to the determination result.
Specifically, whether the transmission performance of the transmission loading platform meets the transmission parameter requirement of the object to be carried currently or not is judged, if yes, the transmission loading platform is controlled according to the requirement corresponding to the transmission parameter information, if not, corresponding reminding is carried out, the performance of the current loading platform is reminded that the current loading platform cannot meet the current loading requirement, corresponding unsatisfied projects or corresponding adjustment schemes can be given, corresponding feedback information is given no matter whether the transmission performance meets the requirement or not and is sent to an evaluation system to be displayed for a user to refer, so that corresponding operation is carried out according to the bearing performance of the transmission loading platform, the working efficiency is improved, equipment loss is avoided, the whole performance evaluation process does not need manual intervention, errors caused by human factors are avoided, meanwhile, artificial intelligence is added, the operational efficiency and accuracy are effectively improved, and the problem that the performance evaluation and the loading parameter adjustment of the loading platform in the prior art depend on manual operation is solved, the method has the technical problem of low accuracy due to the influence of human factors.
Further, the obtaining a conveying influence coefficient according to the loading weight information and the article attribute, step S240 includes:
step S241, obtaining a stability coefficient according to the article attribute;
step S242, obtaining predicted pressure information according to the stability coefficient and the loading weight information;
step S243, obtaining a size influence coefficient according to the carrying object attribute and the carrying object weight information;
step S244 obtains the transmission influence coefficient based on the size influence coefficient and the predicted pressure information.
Specifically, the conveying influence coefficient of the object is determined according to the attributes of the object to be carried, and the difference of different density, specific gravity, fluidity, stability and the like of different object attributes is mainly considered, so that the conveying process is influenced by the characteristics of the object in the process of conveying the object with different attributes, for example, the shape of the object with poor stability is changed or damaged due to the movement of the object in the process of conveying, the stability of the object with large conveying platform area is required to be ensured in the process of conveying, certain requirements are required for the conveying speed or the size of the platform, the stability generated by the object with different speed and size is different under different conditions, for example, the stability of the object with large conveying platform area is higher than the stability with small platform area, the stability with high conveying speed and low conveying speed is poor, and naturally, in combination with the attributes of the product, some products may have high stability with high speed, therefore, when determining the conveying influence coefficient, the embodiment of the application determines the comprehensive conveying influence degree by considering the influence coefficients of the stability coefficient, the pressure information and the size of the conveyed article, and can select one main influence coefficient to determine the conveying influence coefficient or set different specific weights to perform comprehensive calculation when facing different product attributes, thereby more fitting the influence degrees of different articles in the conveying process, determining the final conveying parameter information according to the conveying influence coefficient, having the attribute characteristics of the fitted article, and ensuring the technical effects of stability and safety in the carrying process of the article.
Further, the method comprises:
step S910, obtaining the size of a matched carrying object according to the physical characteristics of the meshing element and the element;
step S920, acquiring a loading weight threshold value according to the matched loading size and the loading information;
and step S930, obtaining the loading scheme information according to the loading information and the loading weight threshold value.
Specifically, different sizes of the object carrying platforms need to be corresponded to different sizes of the chain wheels, manual adjustment and replacement are performed in the prior art, labor intensity is high, the matching object carrying size meeting the pressure threshold requirement is determined by analyzing the physical characteristics of the meshing element and the element, the carrying performance of the object carrying platform can be improved, the size range of the matched object carrying frequency platform is calculated according to the physical characteristics of the fitting element such as the size, specification, thickness and material of the chain wheel, the maximum value of the object carrying weight capable of bearing the object attribute in the platform corresponding to the chain wheel is determined by combining the characteristics of the object in the object carrying information, different bearing capacities are realized for different characteristics of the chain wheel, and the distribution of the carrying platforms is performed according to the object carrying weight threshold and the weight in the object carrying information in order to finish the conveying work of the object carrying information, can carry out a plurality of batches or a plurality of cargo platforms simultaneously transport according to carrying thing weight threshold value with the carrying article that require in the year thing information, formulate specific year thing scheme promptly, can carry out the scheme optimization and carry out to carrying the thing task under the condition of guaranteeing cargo platform performance and component characteristic, promoted the scientificity of carrying the thing scheme, intelligent degree is high, avoids artificial intervention.
Further, referring to fig. 4, the driving force monitoring device includes a tightness monitoring device, and the method includes:
step S1010, tightness information of the chain wheel is obtained through the tightness monitoring equipment;
step S1020, inputting the engaging elements and the tightness information into a stress evaluation model, wherein the stress evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the engaging elements, the tightness information and identification information for identifying the stress evaluation information;
step S1030, obtaining an output result of the stress evaluation model, wherein the output result is a stress evaluation result which is used for reflecting stress requirements corresponding to the meshing element and the tightness information;
step S1040 determines whether the transmission evaluation result matches the stress evaluation result;
and step S1050, when the condition is not met, sending reminding information, and obtaining recommended adjustment information according to the stress evaluation result.
Specifically, since the tightness of the sprocket affects the performance of the sprocket, if the working performance of the sprocket is to be improved, the proper tightness needs to be ensured, power consumption is increased if the working performance of the sprocket is too tight, and the bearing is easy to wear; too loose the sprocket tends to jump and derail. The tightness of a conventional sprocket is: the lifting or pressing from the middle part of the chain wheel is about 2-3% of the center distance between the two chain wheels. The embodiment of the application monitors the tightness of the chain wheel through the tightness monitoring equipment, and evaluates the stress requirement according to the characteristics and the relation of the monitored data set meshing elements, because the chain wheel with simple structure meshing relation can be controlled according to the conventional requirement, and under the condition that the meshing relation is complex and the number of the meshing elements is large, the mutual stress and transmission conditions can be influenced by each meshing relation, the meshing elements and the meshing relation should be comprehensively evaluated, the stress and transmission conditions in the chain wheel are analyzed through the meshing relation of the meshing elements, the stress requirement is evaluated, in order to improve the accuracy of the evaluation result, a neural network model is used, the stress evaluation model is a neural network model, the meshing elements and the tightness information are input into the stress evaluation model, and the stress evaluation result matched with the meshing elements and the tightness information is automatically output, the accuracy high efficiency of operation has been improved, judge whether conveying evaluation result and atress evaluation result match, if match then do not do the adjustment, if unsatisfied matching relation between, then send and remind, give the scheme and the requirement of adjusting the sprocket according to the atress evaluation result, ensure that cargo platform transports under the sprocket performance assorted condition, improve and transport efficiency, optimize cargo platform's performance, avoid causing wearing and tearing and cause the technological effect who transports the trouble to the sprocket.
Example two
Based on the same inventive concept as the performance evaluation method of the driving loading platform in the foregoing embodiment, the present invention further provides a performance evaluation system of the driving loading platform, as shown in fig. 5, the system includes:
a first obtaining unit 11 for obtaining the loading information;
a second obtaining unit 12, configured to obtain transmission parameter information according to the loading information;
a third obtaining unit 13, configured to obtain first image information through an image acquisition device, where the first image information includes sprocket meshing information of a transmission loading platform;
a fourth obtaining unit 14, configured to perform feature extraction on sprocket meshing information in the first image information, and obtain predicted transmission influence information;
a fifth obtaining unit 15, configured to obtain a monitoring data set through the pressure monitoring device, where the monitoring data set includes stress monitoring information of multiple nodes in a transmission process of the transmission loading platform;
the first execution unit 16 is configured to input the predicted transmission influence information and the monitoring data set into an evaluation model, where the evaluation model is obtained by performing training convergence on a plurality of sets of training data, and each set of training data includes the predicted transmission influence information, the monitoring data set, and identification information identifying a transmission evaluation result;
a sixth obtaining unit 17, configured to obtain an output result of the evaluation model, where the output result includes a transmission evaluation result, and the transmission evaluation result is used to represent a transmission capability of the transmission loading platform under the condition of predicting the transmission influence information and the monitoring data set;
and a second executing unit 18, configured to determine whether the transmission evaluation result matches the transmission parameter information, and send feedback information according to the determination result.
Further, the system further comprises:
a seventh obtaining unit, configured to obtain an attribute of the article according to the loading information;
an eighth obtaining unit, configured to obtain a carrying requirement according to the article attribute;
a ninth obtaining unit for obtaining the load weight information;
a tenth obtaining unit, configured to obtain a conveying influence coefficient according to the loading weight information and the article attribute;
an eleventh obtaining unit, configured to obtain the transmission parameter information according to the transmission impact coefficient and the bearer requirement.
Further, the system further comprises:
a twelfth obtaining unit, configured to obtain a stability coefficient according to the article attribute;
a thirteenth obtaining unit, configured to obtain predicted pressure information according to the stability coefficient and the loading weight information;
a fourteenth obtaining unit, configured to obtain a size influence coefficient according to the object attribute and the object weight information;
a fifteenth obtaining unit configured to obtain the transmission influence coefficient based on the size influence coefficient and the predicted pressure information.
Further, the system further comprises:
a sixteenth obtaining unit, configured to obtain an engagement element and an engagement relationship according to the sprocket engagement information of the first image information;
a seventeenth obtaining unit configured to obtain engagement depth information based on the engagement element and the engagement relationship;
an eighteenth obtaining unit that obtains an element physical characteristic from the engaging element;
a third execution unit, configured to input the engagement relationship and the engagement depth information into a pressure evaluation model, where the pressure evaluation model is obtained through training convergence of multiple sets of training data, and each set of training data includes the engagement relationship, the engagement depth information, and identification information that identifies the pressure evaluation information;
a nineteenth obtaining unit, configured to obtain an output result of the pressure evaluation model, where the output result includes pressure evaluation information, and the pressure evaluation information is used to reflect pressure information corresponding to the engagement relationship and the engagement depth information;
a twentieth obtaining unit configured to obtain the predicted transmission influence information based on the element physical property and the pressure evaluation information.
Further, the system further comprises:
a twenty-first obtaining unit configured to obtain characteristic information of the engaging element;
the first comparison unit is used for performing traversal comparison on the first image information according to the meshing element characteristic information to obtain a first comparison result, wherein the first comparison result is all the identified meshing elements in the first image information, and marking the meshing elements;
a first determination unit for determining the position information of the engagement element based on the mark;
a twenty-second obtaining unit configured to obtain the engagement relationship based on the engagement member position information and the engagement member.
Further, the system further comprises:
a twenty-third obtaining unit for obtaining a matching carrying size according to the engaging element and the physical characteristics of the elements;
a twenty-fourth obtaining unit, configured to obtain a loading weight threshold according to the matching loading size and the loading information;
and the twenty-fifth obtaining unit is used for obtaining the loading scheme information according to the loading information and the loading weight threshold value.
Further, the system further comprises:
a twenty-sixth obtaining unit configured to obtain tightness information of the sprocket through the tightness monitoring device;
the fourth execution unit is used for inputting the meshing element and the tightness information into a stress evaluation model, wherein the stress evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the meshing element, the tightness information and identification information for identifying the stress evaluation information;
a twenty-seventh obtaining unit, configured to obtain an output result of the stress evaluation model, where the output result is a stress evaluation result, and the stress evaluation result is used to reflect a stress requirement corresponding to the engagement element and the tightness information;
the first judgment unit is used for judging whether the transmission evaluation result is matched with the stress evaluation result or not;
and the twenty-eighth obtaining unit is used for sending reminding information when the condition is not met, and obtaining recommended adjustment information according to the stress evaluation result.
Various modifications and specific examples of the performance evaluation method for the driving object platform in the first embodiment of fig. 1 are also applicable to the performance evaluation system for the driving object platform in the present embodiment, and through the foregoing detailed description of the performance evaluation method for the driving object platform, those skilled in the art can clearly know the implementation method of the performance evaluation system for the driving object platform in the present embodiment, so for the brevity of the description, detailed description is omitted here.
The electronic apparatus of the embodiment of the present application is described below with reference to fig. 6.
Fig. 6 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the method for evaluating the performance of a powered object carrying platform as in the previous embodiment, the present invention further provides a computer device having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any one of the methods for evaluating the performance of a powered object carrying platform as described above.
Where in fig. 6 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other systems over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
according to the performance evaluation method and system of the transmission loading platform, provided by the embodiment of the invention, loading information is obtained; acquiring transmission parameter information according to the carrying information; acquiring first image information through the image acquisition equipment, wherein the first image information comprises chain wheel meshing information of a transmission loading platform; carrying out feature extraction on the chain wheel meshing information in the first image information to obtain predicted transmission influence information; acquiring a monitoring data set through pressure monitoring equipment, wherein the monitoring data set comprises stress monitoring information of multiple nodes in the transmission process of a transmission loading platform; inputting the predicted transmission influence information and the monitoring data set into an evaluation model, wherein the evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the predicted transmission influence information, the monitoring data set and identification information for identifying a transmission evaluation result; obtaining an output of the evaluation model, the output comprising a transmission evaluation for indicating a transmission capability of the transmission stage with the predicted transmission impact information and the monitored data set; judging whether the transmission evaluation result, namely the transmission performance of the transmission loading platform meets the transmission parameter requirement of the object to be carried currently, if so, controlling the transmission loading platform according to the requirement corresponding to the transmission parameter information, if not, correspondingly reminding the current loading platform to ensure that the performance of the loading platform can not meet the current loading requirement, giving out corresponding unsatisfied projects or giving out corresponding adjustment schemes, giving out corresponding feedback information whether meeting or not, sending the feedback information to an evaluation system to be displayed for a user to refer, so as to carry out corresponding operation according to the bearing performance of the transmission loading platform, improve the working efficiency and avoid equipment loss, avoid errors caused by human factors without manual intervention in the whole performance evaluation process, and simultaneously add artificial intelligence to effectively improve the operational efficiency and accuracy, thereby solving the problem that the performance evaluation and the loading parameter adjustment of the loading platform in the prior art depend on manual operation, the method has the technical problem of low accuracy due to the influence of human factors.
Those of ordinary skill in the art will understand that: the various numbers of the first, second, etc. mentioned in this application are only used for the convenience of description and are not used to limit the scope of the embodiments of this application, nor to indicate the order of precedence. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any," or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one (one ) of a, b, or c, may represent: a, b, c, a b, a c, b c, or a b c, wherein a, b, c may be single or plural.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer finger
The instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire or wirelessly. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium, an optical medium, a semiconductor medium, or the like.
The various illustrative logical units and circuits described in this application may be implemented or operated upon by design of a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in the embodiments herein may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software cells may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be disposed in a terminal. In the alternative, the processor and the storage medium may reside in different components within the terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present application has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the application.
Accordingly, the specification and figures are merely exemplary of the present application as defined in the appended claims and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations.

Claims (9)

1. A performance evaluation method of a transmission loading platform is applied to a performance evaluation system, the system comprises a transmission force monitoring device, the transmission force monitoring device comprises an image acquisition device and a pressure monitoring device, and the method comprises the following steps:
acquiring carrying information;
acquiring transmission parameter information according to the carrying information;
acquiring first image information through the image acquisition equipment, wherein the first image information comprises chain wheel meshing information of a transmission loading platform;
carrying out feature extraction on the chain wheel meshing information in the first image information to obtain predicted transmission influence information;
acquiring a monitoring data set through pressure monitoring equipment, wherein the monitoring data set comprises stress monitoring information of multiple nodes in the transmission process of a transmission loading platform;
inputting the predicted transmission influence information and the monitoring data set into an evaluation model, wherein the evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the predicted transmission influence information, the monitoring data set and identification information for identifying a transmission evaluation result;
obtaining an output of the evaluation model, the output comprising a transmission evaluation for indicating a transmission capability of the transmission stage with the predicted transmission impact information and the monitored data set;
and judging whether the transmission evaluation result is matched with the transmission parameter information or not, and sending feedback information according to the judgment result.
2. The method of claim 1, wherein said obtaining transfer parameter information from said carrier information comprises:
obtaining the property of the article according to the carrying information;
acquiring a bearing requirement according to the article attribute;
acquiring load weight information;
obtaining a conveying influence coefficient according to the carrying weight information and the article attribute;
and obtaining the transmission parameter information according to the transmission influence coefficient and the bearing requirement.
3. The method of claim 2, wherein said obtaining a conveying impact coefficient based on said payload weight information and said article property comprises:
obtaining a stability coefficient according to the article attribute;
obtaining predicted pressure information according to the stability coefficient and the load weight information;
obtaining a size influence coefficient according to the carrying property and the carrying weight information;
and obtaining the transmission influence coefficient according to the size influence coefficient and the predicted pressure information.
4. The method of claim 1, wherein said extracting features of sprocket engagement information in said first image information to obtain predicted drive effect information comprises:
acquiring an engagement element and an engagement relation according to the sprocket engagement information of the first image information;
acquiring meshing depth information according to the meshing element and the meshing relation;
obtaining a physical property of the element based on the engaging element;
inputting the engagement relation and the engagement depth information into a pressure evaluation model, wherein the pressure evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the engagement relation, the engagement depth information and identification information for identifying the pressure evaluation information;
obtaining an output result of the pressure evaluation model, wherein the output result comprises pressure evaluation information which is used for reflecting pressure information corresponding to the meshing relation and the meshing depth information;
and obtaining the predicted transmission influence information according to the element physical characteristics and the pressure evaluation information.
5. The method of claim 4, wherein obtaining engagement element, engagement relationship based on the sprocket engagement information of the first image information comprises:
obtaining engaging element characteristic information;
traversing and comparing the first image information according to the characteristic information of the meshing elements to obtain a first comparison result, wherein the first comparison result is all the meshing elements in the identified first image information, and marking the meshing elements;
determining the position information of the engaging element according to the mark;
and acquiring the engagement relation according to the position information of the engagement element and the engagement element.
6. The method of claim 4, wherein the method comprises:
obtaining a matched carrying size according to the engaging element and the physical characteristics of the elements;
acquiring a loading weight threshold according to the matched loading size and the loading information;
and acquiring carrying scheme information according to the carrying information and the carrying weight threshold value.
7. The method of claim 4, wherein the drive force monitoring device comprises a tightness monitoring device, the method comprising:
acquiring tightness information of the chain wheel through the tightness monitoring equipment;
inputting the engaging elements and the tightness information into a stress evaluation model, wherein the stress evaluation model is obtained by carrying out training convergence on a plurality of groups of training data, and each group of training data comprises the engaging elements, the tightness information and identification information for identifying the stress evaluation information;
obtaining an output result of the stress evaluation model, wherein the output result is a stress evaluation result which is used for reflecting stress requirements corresponding to the meshing element and the tightness information;
judging whether the transmission evaluation result is matched with the stress evaluation result;
and if the stress evaluation result is not satisfied, sending reminding information, and obtaining recommended adjustment information according to the stress evaluation result.
8. A performance evaluation system for a transmission loading platform, wherein the system is applied to the method of any one of claims 1 to 7, and the system comprises:
a first obtaining unit for obtaining the loading information;
the second obtaining unit is used for obtaining the transmission parameter information according to the carrying information;
the third obtaining unit is used for obtaining first image information through image acquisition equipment, wherein the first image information comprises chain wheel meshing information of a transmission loading platform;
a fourth obtaining unit, configured to perform feature extraction on sprocket meshing information in the first image information, and obtain predicted transmission influence information;
the fifth obtaining unit is used for obtaining a monitoring data set through pressure monitoring equipment, wherein the monitoring data set comprises stress monitoring information of multiple nodes in the transmission process of the transmission loading platform;
the first execution unit is used for inputting the predicted transmission influence information and the monitoring data set into an evaluation model, wherein the evaluation model is obtained by training and converging a plurality of groups of training data, and each group of training data comprises the predicted transmission influence information, the monitoring data set and identification information for identifying a transmission evaluation result;
a sixth obtaining unit, configured to obtain an output result of the evaluation model, where the output result includes a transmission evaluation result, and the transmission evaluation result is used to represent a transmission capability of the transmission loading platform under the condition of predicting the transmission influence information and the monitoring data set;
and the second execution unit is used for judging whether the transmission evaluation result is matched with the transmission parameter information or not and sending feedback information according to the judgment result.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of the preceding claims 1-7 when executing the computer program.
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Address before: 226000 Building 1, group 6 and 8, sunjiaqiao village, Xingren Town, Tongzhou District, Nantong City, Jiangsu Province

Patentee before: Jiangsu sikesi Machinery Manufacturing Co.,Ltd.