CN117319355A - Method and system for detecting CANopen (code addressable by digital weighing instrument) - Google Patents
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G23/00—Auxiliary devices for weighing apparatus
- G01G23/01—Testing or calibrating of weighing apparatus
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/28—Determining representative reference patterns, e.g. by averaging or distorting; Generating dictionaries
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/40—Bus networks
- H04L12/40006—Architecture of a communication node
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L61/00—Network arrangements, protocols or services for addressing or naming
- H04L61/50—Address allocation
- H04L61/5038—Address allocation for local use, e.g. in LAN or USB networks, or in a controller area network [CAN]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/40—Bus networks
- H04L2012/40208—Bus networks characterized by the use of a particular bus standard
- H04L2012/40215—Controller Area Network CAN
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention relates to the technical field of communication detection, in particular to a method and a system for detecting CANopen coding and addressing of a digital weighing instrument, wherein the method comprises the following steps: intermittently sending weighing signals, receiving corresponding weighing information, integrating the weighing information obtained each time into a counterweight information set, and acquiring the weighing signals by a weighing sensor; acquiring a child node allocation rule of digital weighing according to a CANopen protocol; traversing the state word object, and obtaining equipment state information through the state word object; acquiring object dictionary information, and performing error checking judgment on child node allocation rules and equipment state information through the object dictionary information; if the information is consistent, address signals of weighing information in the counterweight information set are read, an addressing signal result is obtained, the counterweight information set and the addressing signal result are input into a self-addressing detection model, and a coded addressing detection result is obtained. The invention effectively solves the problems of deviation or disorder of material counterweight information possibly occurring in the programming and addressing of the digital weighing instrument.
Description
Technical Field
The invention relates to the technical field of communication detection, in particular to a method and a system for detecting CANopen coding and addressing of a digital weighing instrument.
Background
The material metering is an important link in industrial production and trade circulation, and the weighing device or instrument is an indispensable metering tool, so that the weighing device or instrument is not only a monomer instrument for providing weight data, but also plays roles in shortening the operation time, improving the operation condition, reducing the consumption of energy and materials, improving the product quality, strengthening the enterprise management and the like in the modernization process of industrial production management. Along with the development of industrial and agricultural production and the expansion of commodity circulation, intelligent weighing meters with the advantages of rapidness, accuracy, convenient operation, personal error elimination and function diversity have been increasingly demanded.
The CANOpen is an open standard communication protocol for communication and equipment management in a control system, a digital weighing instrument can be easily integrated into the existing CANOpen network and work together with other equipment to realize more complex automation and control tasks, and as node addresses are distributed by LSS, if address errors occur, material balance weight information deviation is even disordered, and serious loss is brought to commodity quality.
The information disclosed in this background section is only for enhancement of understanding of the general background of the disclosure and is not to be taken as an admission or any form of suggestion that this information forms the prior art that is well known to a person skilled in the art.
Disclosure of Invention
The invention provides a method and a system for detecting CANopen coding and addressing of a digital weighing instrument, which can effectively solve the problems in the background technology.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
a method of detecting a digital weighing instrument CANopen coded addressing, the method comprising:
intermittently sending weighing signals, receiving corresponding weighing information, and integrating the weighing information obtained each time into a counterweight information set, wherein the weighing signals are obtained by a weighing sensor;
acquiring a child node allocation rule of digital weighing according to a CANopen protocol;
traversing a state word object, and obtaining equipment state information through the state word object;
acquiring object dictionary information, performing error checking judgment on the child node allocation rule and the equipment state information through the object dictionary information, and if the information is inconsistent, entering a first checking process;
if the information is consistent, reading address signals of weighing information in the counterweight information set to obtain an address signal result;
establishing a self-addressing detection model, and inputting the counterweight information set and an addressing signal result into the self-addressing detection model to obtain an addressing detection result;
and adjusting node address allocation according to the coding and addressing detection result.
Further, the first checking process includes:
recording a specific object dictionary identifier which causes information inconsistency and comprises an index, a sub-index and a time stamp, and obtaining node allocation error information;
verifying whether configuration parameters of the equipment are correct or not, wherein the configuration parameters comprise parameters related to node allocation rules and state information;
and adjusting the child node allocation rules and the equipment state information, and carrying out error checking judgment on the child node allocation rules and the equipment state information through the object dictionary information.
Further, traversing the state word object, obtaining device state information through the state word object, including:
determining an index of the state word object;
reading the value of the status word object according to the index of the status word object;
and acquiring a status bit definition, and acquiring the equipment status information through the status bit definition and the value of the status word object.
Further, establishing a self-addressing detection model includes:
collecting historical detection information data and acquiring the distribution condition of the historical detection information data;
carrying out missing value and abnormal value processing on the history detection information data according to the distribution condition;
extracting historical self-addressing related characteristic data from the processed historical detection information data;
selecting a proper learning model to perform deep learning on the historical self-addressing related characteristic data;
and constructing a training set and a verification set to train and evaluate the self-addressing detection model.
Further, the addressing fault data is imported to the self-addressing detection model, and sensitive setting is carried out on the addressing fault data, wherein the sensitive setting comprises the following steps:
acquiring a material weight result of the addressing fault data, and clustering the addressing fault data according to the material weight result to acquire a clustering result;
and setting a sensitive threshold according to the clustering result, and setting sensitive response to the self-addressing detection model.
Further, constructing a training set and a verification set to train and evaluate the self-addressing detection model includes:
selecting the historical detection information data to construct a data set;
dividing the data set into k subsets, and orderly arranging the k subsets;
taking the first subset as the verification set, and taking the remaining k-1 subsets as the training set;
training the self-addressing detection model using the training set, evaluating performance of the self-addressing detection model using the verification set, and recording performance metrics on a current subset;
repeating the above steps until each of the subsets acts as a verification set;
and calculating the average value of the performance indexes of the self-addressing detection model in each subset serving as the verification set to obtain comprehensive performance evaluation.
Further, inputting the counterweight information set and the addressing signal result into the self-addressing detection model to obtain an encoded addressing detection result, including:
setting a double-channel detection path for the self-addressing detection model, wherein a first channel detection path is used for detecting the counterweight information set, and a second channel detection path is used for detecting the addressing signal result;
acquiring a material information weight standard, inputting the material information weight standard into the first detection path, and setting a weight standard threshold for the material information weight standard;
and obtaining a first detection result through the first detection path, obtaining a second detection result through the second detection path, and obtaining a coded address detection result through the first detection result and the second detection result.
Further, adjusting node address allocation according to the encoded address detection result includes:
analyzing the coding fault reason according to the coding detection result;
according to the addressing fault reasons, corresponding adjustment is made to an address allocation algorithm, equipment configuration and network topology;
and formulating a backup and rollback strategy in the adjustment process, and logging the adjustment process.
A system for detecting a digital weighing cell CANopen addressing, said system comprising:
the weighing information acquisition module is used for intermittently transmitting weighing signals and receiving corresponding weighing information, and integrating the weighing information obtained each time into a weighing information set, wherein the weighing signals are acquired by a weighing sensor;
the distribution rule acquisition module acquires a child node distribution rule of digital weighing according to a CANopen protocol;
the equipment state information module traverses the state word object and obtains equipment state information through the state word object;
the information error checking judging module is used for acquiring object dictionary information, carrying out error checking judgment on the child node allocation rule and the equipment state information through the object dictionary information, and entering a first checking process if the information is inconsistent;
the addressing signal processing module is used for reading address signals of weighing information in the counterweight information set if the information is consistent, and obtaining an addressing signal result;
the coding and addressing detection module establishes a self-addressing detection model, and inputs the counterweight information set and the addressing signal result into the self-addressing detection model to obtain a coding and addressing detection result;
and the node address adjustment module adjusts node address allocation according to the coding and addressing detection result.
Further, the information error checking and judging module includes:
the child node allocation detection unit records specific object dictionary identifiers which cause information inconsistency, wherein the specific object dictionary identifiers comprise indexes, child indexes and time stamps, and node allocation error information is obtained;
a device parameter verification unit for verifying whether the configuration parameters of the device are correct, including parameters related to node allocation rules and status information;
and the parameter adjustment rechecking unit adjusts the child node allocation rule and the equipment state information and re-performs error checking judgment on the child node allocation rule and the equipment state information through the object dictionary information.
By the technical scheme of the invention, the following technical effects can be realized:
the problem that deviation or disorder of material counterweight information possibly occurs in the digital weighing instrument programming based on the CANopen protocol is effectively solved, the quality of material commodities is guaranteed, the loss of products due to weight fluctuation is avoided, and compared with the traditional manual detection, the labor cost is greatly reduced in the whole detection process.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to the drawings without inventive effort to those skilled in the art.
FIG. 1 is a flow chart of a method for detecting CANopen addressing of a digital weighing instrument;
FIG. 2 is a flow chart of a first screening process;
FIG. 3 is a schematic flow chart of a self-addressing detection model;
FIG. 4 is a schematic flow chart of training and evaluating a self-addressing detection model;
FIG. 5 is a flow chart of obtaining the result of the address detection;
fig. 6 is a schematic diagram of the system for detecting the addressing of the digital weighing instrument CANopen.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
Example 1
As shown in fig. 1, the present application provides a method for detecting a digital weighing cell CANopen, which includes:
s100: intermittently sending weighing signals, receiving corresponding weighing information, integrating the weighing information obtained each time into a counterweight information set, and acquiring the weighing signals by a weighing sensor; in the step, the time interval can be freely set, the time interval can also be divided according to the total time length of weighing, the weighing signals are obtained by the weighing sensor, the weighing signals on each path received at the same time each time are integrated into a counterweight information set, the error of the weighing information can be reduced by intermittently sending, and the real-time property of the counterweight of the material is ensured.
S200: acquiring a child node allocation rule of digital weighing according to a CANopen protocol; in the step, a CANopen protocol is used for communication with the digital weighing equipment, rules related to sub-node allocation in the object dictionary are read through the CANopen protocol, sub-node allocation rules are obtained, the configuration relation between the digital weighing equipment and the CANopen network is known, and necessary information is provided for subsequent automatic addressing and equipment state monitoring.
S300: traversing the state word object, and obtaining equipment state information through the state word object;
s400: acquiring object dictionary information, performing error checking judgment on child node allocation rules and equipment state information through the object dictionary information, and if the information is inconsistent, entering a first checking process;
in the above steps, the CANopen protocol is used to read the value of the object of the status word, and the various bits of the status word are defined and analyzed according to the status bit, so as to obtain the information such as the running status of the equipment. And reading information related to child node allocation and equipment state in the object dictionary by using a CANopen protocol, comparing the read information with actual conditions, judging whether the information is consistent, recording a specific object dictionary identifier which is inconsistent and comprises an index, a sub-index and a time stamp if the information is inconsistent, entering first checking processing, wherein the first checking processing is in an intermediate link of the whole addressing detection and is the front detection of the addressing detection, ensuring that the node allocation and the equipment state are not abnormal before the addressing detection is entered, stopping subsequent detection if the node allocation and the equipment state are abnormal in the link, immediately checking a problem item, and otherwise, leading the subsequent detection item to lose meaning.
S500: if the information is consistent, reading address signals of weighing information in the counterweight information set to obtain an address signal result;
s600: establishing a self-addressing detection model, and inputting a counterweight information set and an addressing signal result into the self-addressing detection model to obtain an encoding and addressing detection result;
s700: and adjusting node address allocation according to the coded address detection result.
In the above steps, the address signal result is used as the important input data of the model, the address signals of each weighing information in the counterweight information set are read, firstly, the data structure of the weighing information and the interface specification of the sensor are required to be known, the output of the sensor is converted into the signal readable by the system by using the corresponding hardware interface such as analog output, digital output or serial communication, the address signals contained in each weighing information are extracted by using the analog-to-digital converter, the digital interface or the corresponding communication protocol, the validity verification is required in the reading process, the accuracy and the rationality of the address signals are ensured, then, the self-addressing detection model is established by using machine learning or other modeling methods, the model outputs the coded address detection result, whether the node address allocation error exists is judged, and the corresponding node address allocation condition is adjusted according to the result of the self-addressing detection model.
By the technical scheme, the problem of deviation or disorder of material balance weight information possibly occurring in the programming and addressing of the digital weighing instrument based on the CANopen protocol is effectively solved, the quality of material commodity is ensured, the loss of products due to weight fluctuation is avoided, and the labor cost is greatly reduced in the whole detection process compared with the traditional manual detection.
Further, as shown in fig. 2, the first checking process includes:
s410: recording a specific object dictionary identifier which causes information inconsistency and comprises an index, a sub-index and a time stamp, and obtaining node allocation error information;
s420: verifying whether configuration parameters of the equipment are correct or not, wherein the configuration parameters comprise parameters related to node allocation rules and state information;
s430: and adjusting the child node allocation rules and the equipment state information, and carrying out error checking judgment on the child node allocation rules and the equipment state information through the object dictionary information.
As a preference of the above embodiment, when detecting that the information is inconsistent, recording the related object dictionary identifier may be implemented by a CANopen debugging tool or a custom monitoring program, recording the identifier is helpful to accurately locate the occurrence time and position of the problem, providing a basis for subsequent investigation, ensuring that the acquisition of the node allocation error information generally involves configuration of the device node address, referring to the CANopen object dictionary document according to the recorded object dictionary identifier, acquiring the error information related to the node allocation, including an error code or an error description, acquiring the cause that the node allocation error information is helpful to understand the information inconsistency, providing a guide for subsequent adjustment and repair, verifying whether the configuration parameter of the device meets the expectation, verifying that the correctness of the device configuration parameter is helpful to eliminate the possibility that the configuration error leads to the information inconsistency, ensuring that the basic configuration of the device is correct, adjusting the sub-node allocation rule and the device state information according to the obtained error information and the verified device configuration parameter, possibly including reconfiguring the node, updating the state information, judging that the error information is beneficial to the error information is judged by the method of the node allocation error information, and the error information is judged by the error condition verification, and the error information is judged to be valid after the error condition is judged, and the error condition is judged.
Further, traversing the state word object, obtaining device state information through the state word object, including:
determining an index of the status word object;
reading the value of the status word object according to the index of the status word object;
and acquiring a status bit definition, and acquiring the device status information through the status bit definition and the value of the status word object.
As a preference of the above embodiment, it may be selected to consult a CANopen object dictionary document or a related manual of the device, confirm an index of a state word object, and determine that communication in a CANopen network is normal, and use a read instruction of a CANopen communication protocol, read a value of the state word object from the device through a CANopen driver or tool, a state bit definition is a detailed description provided by a device manufacturer for the value of the state word object, including a meaning of each bit and a corresponding state, and in combination with traversing the CANopen object dictionary document of the device, find a state bit definition associated with the state word object, ensure that the state bit definition is consistent with actual state information of the device, so as to correctly interpret the value of the state word object, use the value of the state word object and the state bit definition to perform bit operation or analysis, thereby obtain specific state information of the device, for example, and perform and operation with a specific bit mask to extract specific state bits, and by reading the value of the state word object, the running state of the device can be monitored in real time, an abnormal or alarm condition can be found, after the state information is obtained, the running state information of the device can be located quickly, and the fault condition can be better understood, and the system can be better diagnosed, and the system can be better visually and the system can be better diagnosed.
Further, as shown in fig. 3, the self-addressing detection model is built, including:
s610: collecting historical detection information data and acquiring the distribution condition of the historical detection information data;
s620: carrying out missing value and abnormal value processing on the historical detection information data according to the distribution condition;
s630: extracting historical self-addressing related characteristic data from the processed historical detection information data;
s640: selecting a proper learning model to perform deep learning on the historical self-addressing related characteristic data;
s650: the training set and the verification set are constructed to train and evaluate the self-addressing detection model.
As a preference of the above embodiment, when collecting the historical detection information data, the diversity of the data is to be focused on, and ensure that the training data set contains samples from different working conditions, environmental changes and equipment states, so as to avoid the influence of other factors on the correlation of the data result, which can be achieved by collecting the data at different times, places and operation situations, secondly, the relative balance of the number of data samples in each category needs to be ensured, so as to avoid the situation that the model is too biased for a large number of categories, after collecting the data, the historical data information may have the condition that the data value is missing or abnormal, the missing value is supplemented, and the abnormal value is removed, the historical data information is preprocessed, so as to ensure the validity of the deep learning data, and the abnormal value is detected and processed by adopting, for example, deleting the samples containing the missing value, using the average value or median filling the missing value, and the abnormal value can be detected and processed by using a statistical method or a model-based method, so as to ensure that the abnormal value does not negatively affect the model; suitable learning models may include support vector machines, random forests, and the like.
Further, the addressing fault data is imported to the self-addressing detection model, and the addressing fault data is subjected to sensitive setting, wherein the sensitive setting comprises:
acquiring a material weight result of addressing fault data, and clustering the addressing fault data according to the material weight result to acquire a clustering result;
and setting a sensitivity threshold according to the clustering result, and setting a sensitivity response to the self-addressing detection model.
On the basis of the embodiment, the relevant data of addressing faults in the digital weighing instrument are collected, the relevant data comprise node address errors and weight information deviations, the weight results of the materials are respectively obtained for the data of normal addressing and addressing faults, the actual results of weighing the materials by the weighing instrument can be obtained, clustering algorithms such as K-means clustering can be used for clustering the weight results of the materials, the data are divided into different clusters, the data are helpful for finding possible modes or anomalies under the addressing faults, the characteristics of each cluster are analyzed according to the clustering results, the clusters of the addressing faults are particularly focused, a sensitivity threshold is determined based on the clustering results, the threshold can be used for identifying the weight results of the materials which are possibly addressing faults, the threshold can be determined by considering the self-addressing detection model, the previously determined sensitivity threshold can be applied to the output of the model to identify the parts of the model output which are possibly sensitive to the addressing faults, and when the model output exceeds the sensitivity threshold, a sensitivity response mechanism can be set for alarming, logging or triggering further inspection and maintenance.
Further, as shown in fig. 4, constructing the training set and the verification set to train and evaluate the self-addressing detection model includes:
s651: selecting historical detection information data to construct a data set;
s652: dividing the data set into k subsets, and orderly arranging the k subsets;
s653: taking the first subset as a verification set, and taking the remaining k-1 subsets as training sets;
s654: training the self-addressing detection model using a training set, evaluating performance of the self-addressing detection model using a verification set, and recording performance metrics on the current subset;
s655: repeating the steps until each subset acts as a verification set;
s656: and calculating the average value of the performance indexes of the self-addressing detection model in each subset serving as a verification set to obtain comprehensive performance evaluation.
In this embodiment, representative features are selected from the history detection information, and appropriate output is marked, so that various possible situations are ensured to be contained in the data set, and in this process, it is noted that the model is more comprehensively evaluated, and in this process, history data information inconsistent with deep learning is selected, so that the model can be more objectively and accurately verified and evaluated through a data set outside the deep learning; partitioning the data set ensures that each subset has enough samples, and allows for the use of hierarchical sampling to maintain consistency of the class distribution,
the training set is used for training the self-addressing detection model, then performance evaluation is carried out on the verification set, wherein recorded performance indexes can comprise accuracy, precision, recall rate and the like, model training and verification steps are circularly carried out until each subset is used as the verification set, the average value of the performance indexes of the model on each subset is calculated to obtain final comprehensive performance evaluation, the performance of the self-addressing detection model can be evaluated more comprehensively by using different verification sets, accidental differences caused by specific data division are reduced, the performance of the model on different data sets is verified for multiple times, the generalization capability of the model, namely the performance of the model on unseen data can be better evaluated, repeated training and verification are also facilitated, the overfitting of the model on the specific data set is reduced, and the robustness of the model is improved.
Further, as shown in fig. 5, inputting the counterweight information set and the addressing signal result into the self-addressing detection model to obtain the coded addressing detection result, including:
s601: setting a double-channel detection path for the self-addressing detection model, wherein the first channel detection path is a detection counterweight information set, and the second channel detection path is a detection addressing signal result;
s602: acquiring a material information weight standard, inputting the material information weight standard into a first detection path, and setting a weight standard threshold value for the material information weight standard;
s603: the first detection result is obtained through the first detection path, the second detection result is obtained through the second detection path, and the coded address detection result is obtained through the first detection result and the second detection result.
In this embodiment, a parallel detection path is set for a self-addressing detection model, wherein a material information weight standard is input into a first detection path in advance according to actual production and proportion requirement, a weight standard threshold is set according to actual standard floating requirement, the weight standard threshold reflects weight accuracy requirement on different batches of products, a first detection result of a data sample in the weight standard threshold is qualified, the material weight information accuracy error is indicated to be in the weight standard threshold, if the detection results of a double detection path are all qualified, the weight addressing condition is indicated to meet the production requirement, and the aim of increasing the detection item is to avoid that some data may have addressing qualification, but the proportion information has error condition, and further the accuracy of the bidirectional feedback strengthening detection on the addressing condition and the material information weight is achieved.
Further, adjusting the node address allocation according to the encoded address detection result includes:
analyzing the reason of the coding and addressing fault according to the coding and addressing detection result;
according to the addressing failure cause, corresponding adjustment is made to an address allocation algorithm, equipment configuration and network topology;
and making a backup and rollback strategy in the adjustment process, and logging the adjustment process.
On the basis of the embodiment, the method analyzes the addressing detection results to determine specific reasons for the problem of node address allocation, possible problems include address conflict, wrong address allocation algorithm and network topology problem, if the problem is caused by the address allocation algorithm, the algorithm is considered to be modified to better adapt to the requirement of the system, the algorithm is ensured to avoid address conflict and can correctly process when the node joins or exits, in some cases, the node address can be required to be manually adjusted, the configuration tool or the device can be directly adjusted, new problems can not be introduced when the manual adjustment is ensured, if the system supports automatic addressing, the automatic addressing process can be considered to be triggered again, the system can be used for allocating the address to the node again, the allocated address is ensured to be unique, the analysis result node allocation problem is related to the network topology, the optimization of the network topology is considered, the position of the device can be required to be rearranged or the network structure is required to be adjusted, the address allocation problem is solved, the monitoring function and log record of the system can be enabled in the process of the node address adjustment, the potential problem can be tracked and found in time, the potential problem can be found, and the prior to the node address adjustment is suggested, the rolling back to be rapidly carried out, and the fault-tolerant state can be quickly when the problem is improved.
Embodiment two:
based on the same inventive concept as the method for detecting the CANopen addressing of the digital weighing instrument in the foregoing embodiment, as shown in fig. 6, the present invention further provides a system for detecting the CANopen addressing of the digital weighing instrument, where the system includes:
the weighing information acquisition module is used for intermittently transmitting weighing signals and receiving corresponding weighing information, integrating the weighing information obtained each time into a weighing information set, and acquiring the weighing signals by the weighing sensor;
the distribution rule acquisition module acquires a child node distribution rule of digital weighing according to a CANopen protocol;
the equipment state information module traverses the state word object and obtains equipment state information through the state word object;
the information error checking judging module is used for acquiring object dictionary information, carrying out error checking judgment on the child node allocation rule and the equipment state information through the object dictionary information, and entering first checking processing if the information is inconsistent;
the addressing signal processing module is used for reading address signals of weighing information in the counterweight information set if the information is consistent, and obtaining an addressing signal result;
the coding and addressing detection module establishes a self-addressing detection model, and inputs the counterweight information set and the addressing signal result into the self-addressing detection model to obtain a coding and addressing detection result;
and the node address adjustment module is used for adjusting node address allocation according to the coding and addressing detection result.
The adjusting system can effectively realize the method for detecting the CANopen programming addressing of the digital weighing instrument, and has the technical effects as described in the embodiment, and the description is omitted here.
Further, the information error checking and judging module includes:
the child node allocation detection unit records specific object dictionary identifiers which cause information inconsistency, wherein the specific object dictionary identifiers comprise indexes, child indexes and time stamps, and node allocation error information is obtained;
a device parameter verification unit for verifying whether the configuration parameters of the device are correct, including parameters related to node allocation rules and status information;
and the parameter rechecking unit is used for adjusting the child node allocation rule and the equipment state information and carrying out error checking judgment on the child node allocation rule and the equipment state information through the object dictionary information.
Similarly, the above-mentioned optimization schemes of the system may also respectively correspond to the optimization effects corresponding to the methods in the first embodiment, which are not described herein again.
Although the present application has been described in connection with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary illustrations of the application as defined in the appended claims and are to be construed as covering any and all modifications, variations, combinations, or equivalents that are within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can 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 present application and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (10)
1. A method of detecting a digital weighing cell CANopen coded addressing, the method comprising:
intermittently sending weighing signals, receiving corresponding weighing information, and integrating the weighing information obtained each time into a counterweight information set, wherein the weighing signals are obtained by a weighing sensor;
acquiring a child node allocation rule of digital weighing according to a CANopen protocol;
traversing a state word object, and obtaining equipment state information through the state word object;
acquiring object dictionary information, performing error checking judgment on the child node allocation rule and the equipment state information through the object dictionary information, and if the information is inconsistent, entering a first checking process;
if the information is consistent, reading address signals of weighing information in the counterweight information set to obtain an address signal result;
establishing a self-addressing detection model, and inputting the counterweight information set and an addressing signal result into the self-addressing detection model to obtain an addressing detection result;
and adjusting node address allocation according to the coding and addressing detection result.
2. The method of detecting a digital weighing cell CANopen addressing according to claim 1, characterized in that said first checking process comprises:
recording a specific object dictionary identifier which causes information inconsistency and comprises an index, a sub-index and a time stamp, and obtaining node allocation error information;
verifying whether configuration parameters of the equipment are correct or not, wherein the configuration parameters comprise parameters related to node allocation rules and state information;
and adjusting the child node allocation rules and the equipment state information, and carrying out error checking judgment on the child node allocation rules and the equipment state information through the object dictionary information.
3. The method of detecting a digital weighing cell CANopen addressing according to claim 1, characterized by traversing a status word object from which device status information is obtained, comprising:
determining an index of the state word object;
reading the value of the status word object according to the index of the status word object;
and acquiring a status bit definition, and acquiring the equipment status information through the status bit definition and the value of the status word object.
4. The method for detecting the CANopen addressing of a digital weighing instrument according to claim 1, wherein the establishing of the self-addressing detection model comprises:
collecting historical detection information data and acquiring the distribution condition of the historical detection information data;
carrying out missing value and abnormal value processing on the history detection information data according to the distribution condition;
extracting historical self-addressing related characteristic data from the processed historical detection information data;
selecting a proper learning model to perform deep learning on the historical self-addressing related characteristic data;
and constructing a training set and a verification set to train and evaluate the self-addressing detection model.
5. The method for detecting the CANopen addressing of a digital weighing instrument according to claim 4, wherein addressing fault data is imported to said self-addressing detection model and sensitive settings are made to said addressing fault data, said sensitive settings comprising:
acquiring a material weight result of the addressing fault data, and clustering the addressing fault data according to the material weight result to acquire a clustering result;
and setting a sensitive threshold according to the clustering result, and setting sensitive response to the self-addressing detection model.
6. The method of detecting a digital weighing cell CANopen-coded addressing according to claim 4 or 5, characterized in that constructing training and validation sets for training and evaluating the self-addressing detection model comprises:
selecting the historical detection information data to construct a data set;
dividing the data set into k subsets, and orderly arranging the k subsets;
taking the first subset as the verification set, and taking the remaining k-1 subsets as the training set;
training the self-addressing detection model using the training set, evaluating performance of the self-addressing detection model using the verification set, and recording performance metrics on a current subset;
repeating the above steps until each of the subsets acts as a verification set;
and calculating the average value of the performance indexes of the self-addressing detection model in each subset serving as the verification set to obtain comprehensive performance evaluation.
7. The method for detecting the coded addressing of the digital weighing instrument CANopen according to claim 1, wherein the step of inputting the counterweight information set and the addressing signal result into the self-addressing detection model to obtain the coded addressing detection result comprises the following steps:
setting a double-channel detection path for the self-addressing detection model, wherein a first channel detection path is used for detecting the counterweight information set, and a second channel detection path is used for detecting the addressing signal result;
acquiring a material information weight standard, inputting the material information weight standard into the first detection path, and setting a weight standard threshold for the material information weight standard;
and obtaining a first detection result through the first detection path, obtaining a second detection result through the second detection path, and obtaining a coded address detection result through the first detection result and the second detection result.
8. The method for detecting the CANopen addressing of the digital weighing instrument according to claim 1, wherein the adjusting the node address allocation according to the addressing detection result comprises:
analyzing the coding fault reason according to the coding detection result;
according to the addressing fault reasons, corresponding adjustment is made to an address allocation algorithm, equipment configuration and network topology;
and formulating a backup and rollback strategy in the adjustment process, and logging the adjustment process.
9. A system for detecting the addressing of a digital weighing cell CANopen, said system comprising:
the weighing information acquisition module is used for intermittently transmitting weighing signals and receiving corresponding weighing information, and integrating the weighing information obtained each time into a weighing information set, wherein the weighing signals are acquired by a weighing sensor;
the distribution rule acquisition module acquires a child node distribution rule of digital weighing according to a CANopen protocol;
the equipment state information module traverses the state word object and obtains equipment state information through the state word object;
the information error checking judging module is used for acquiring object dictionary information, carrying out error checking judgment on the child node allocation rule and the equipment state information through the object dictionary information, and entering a first checking process if the information is inconsistent;
the addressing signal processing module is used for reading address signals of weighing information in the counterweight information set if the information is consistent, and obtaining an addressing signal result;
the coding and addressing detection module establishes a self-addressing detection model, and inputs the counterweight information set and the addressing signal result into the self-addressing detection model to obtain a coding and addressing detection result;
and the node address adjustment module adjusts node address allocation according to the coding and addressing detection result.
10. The system for detecting a digital weighing cell CANopen addressing according to claim 9, wherein said information error checking and judging module comprises:
the child node allocation detection unit records specific object dictionary identifiers which cause information inconsistency, wherein the specific object dictionary identifiers comprise indexes, child indexes and time stamps, and node allocation error information is obtained;
a device parameter verification unit for verifying whether the configuration parameters of the device are correct, including parameters related to node allocation rules and status information;
and the parameter adjustment rechecking unit adjusts the child node allocation rule and the equipment state information and re-performs error checking judgment on the child node allocation rule and the equipment state information through the object dictionary information.
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