CN117527859B - Equipment monitoring method and system based on industrial Internet - Google Patents
Equipment monitoring method and system based on industrial Internet Download PDFInfo
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Abstract
The invention relates to the technical field of data processing, and discloses an equipment monitoring method and system based on an industrial Internet. The equipment monitoring method based on the industrial Internet comprises the following steps: performing configuration analysis on equipment through a preset industrial Internet platform, generating a corresponding equipment configuration file, performing parameter configuration on the equipment according to the equipment configuration file, and generating an equipment parameter configuration result; the method comprises the steps of collecting feedback data of equipment through an industrial Internet platform, and generating equipment running state data; the invention can convert the equipment state information into the coding format which is convenient for transmission and storage through standardized conversion patterns and coding rules, thereby being beneficial to realizing the efficient management of a large number of equipment.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an equipment monitoring method and system based on an industrial Internet.
Background
In modern industrial production, monitoring and maintenance of equipment are key factors for ensuring production continuity and efficiency. Along with the development of industrial Internet technology, the real-time monitoring and analysis of the equipment state are possible, and the intelligent level of equipment management is greatly improved. The device data is collected and processed by using the industrial Internet platform, the device performance can be evaluated, potential abnormal behaviors can be found in time, and faults are avoided.
The operating state of the device is currently monitored generally by a basic sensor network and a data acquisition system. These systems are capable of recording the operating parameters of the device and performing simple data processing, such as recording temperature, vibration, energy consumption, etc. However, these schemes often have problems of insufficient data processing capability, inability to effectively fuse multi-source data, lack of predictive anomaly detection, and the like, so that quick and accurate judgment of an equipment anomaly state cannot be made. This results in low monitoring accuracy, slow response speed, and insufficient recognition of complex abnormal behavior. These problems not only affect the efficient operation of the equipment, but may also lead to production stalls and increased maintenance costs.
Accordingly, there is a need for a method that enables more efficient deep analysis and processing of device state data to achieve more accurate device monitoring.
Disclosure of Invention
The invention provides an equipment monitoring method and system based on an industrial Internet, which are used for quickly and accurately judging the abnormal state of equipment and realizing more accurate equipment monitoring.
The first aspect of the invention provides an industrial internet-based equipment monitoring method, which comprises the following steps:
Performing configuration analysis on equipment through a preset industrial Internet platform, generating a corresponding equipment configuration file, performing parameter configuration on the equipment according to the equipment configuration file, and generating an equipment parameter configuration result;
the method comprises the steps of collecting feedback data of equipment through an industrial Internet platform, and generating equipment running state data;
performing coding fusion processing on the acquired equipment running state data and the equipment parameter configuration result to generate equipment coding state data, and performing feature analysis on the equipment coding state data to generate equipment state feature information; the database stores coding rules for converting the collected equipment running state data and the equipment parameter configuration result in advance;
decomposing the equipment state characteristic information to generate a plurality of pieces of equipment state characteristic sub-information, performing matrix conversion processing on each piece of equipment state characteristic sub-information to generate each mapping word vector of each piece of equipment state characteristic sub-information, and performing splicing processing on each mapping word vector to obtain a target state characteristic vector;
inputting the target state feature vector into a trained abnormal state recognition model, analyzing the abnormal behavior of the equipment to obtain an equipment abnormal behavior analysis result, and analyzing the monitoring strategy of the equipment based on the equipment abnormal behavior analysis result to obtain a target monitoring strategy of the equipment; the abnormal state identification model is obtained through training in advance.
Optionally, in a first implementation manner of the first aspect of the present invention, the device parameter configuration result includes at least a function parameter configuration result and a performance parameter configuration result.
Optionally, in a second implementation manner of the first aspect of the present invention, the converting the collected device operation state data and the device parameter configuration result to generate device coding state data includes:
respectively converting the acquired equipment running state data and the equipment parameter configuration result to obtain a corresponding first character combination and a corresponding second character combination;
acquiring a preset standard conversion map; wherein the standard conversion map at least comprises a conversion number and a conversion text character mapping rule; the conversion characters take Chinese characters as conversion carriers;
converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to the equipment operation state data; the first target conversion map is obtained by transforming a preset first design rule based on the preset standard conversion map;
converting the second character combination based on a second target conversion map to obtain second conversion data corresponding to the equipment parameter configuration result; the second target conversion map is obtained by transforming the second target conversion map through a second preset design rule based on the preset standard conversion map;
Based on a preset coding rule, respectively coding the first conversion data and the second conversion data to obtain a corresponding first coding character combination and a corresponding second coding character combination;
and based on a preset character combination rule, respectively selecting a plurality of characters from the first coding character combination and the second coding character combination to combine, and obtaining a target character combination as final equipment coding state data.
Optionally, in a third implementation manner of the first aspect of the present invention, the converting, based on the first target conversion map, the first character combination to obtain first conversion data corresponding to the equipment operation state data includes:
comparing the target character combination with converted character in the preset standard conversion map by referring to a character set, and marking Chinese characters corresponding to the target character combination as invalid character for successfully compared character; frequency spectrum analysis is carried out on unlabeled effective literal characters, and a priority sequence is established for the effective literal characters according to the sequence from high frequency to low frequency, so as to obtain a dynamic priority sequence;
in a preset standard conversion map, reassigning a conversion number to each effective text character according to the dynamic priority sequence; the database stores allocation rules for reallocating conversion numbers for each effective text character based on the dynamic priority sequence in advance;
Generating a series of random sequences, and optimally sequencing the series of random sequences to obtain a first random number set and a second random number set after sequencing; wherein, the optimized sorting means that each random number in the random number set is classified according to the number parity of the random sequence, and each classified random number is sorted in a descending order; the first random number set is an odd-numbered descending random number set, and the second random number set is an even-numbered descending random number set;
after the allocation of new conversion serial numbers of the effective coding characters is completed, sequentially matching the conversion serial numbers which are the same as the random numbers based on the random numbers in the ordered first random number set, and sequentially adding invalid character characters corresponding to the matched conversion serial numbers into the preset standard conversion map and being positioned in front of the effective character characters;
integrating all characters and the new conversion serial numbers obtained by distribution in a preset standard conversion map, and regenerating an optimized standard conversion map to obtain a first target conversion map; and converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to the equipment operation state data.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the random numbers in the sorted first random number set at least include conversion serial numbers of invalid text characters, and a mapping relationship exists between the conversion serial numbers of the first random number set and the invalid text characters.
The second aspect of the present invention provides an industrial internet-based device monitoring system, comprising:
the analysis module is used for carrying out configuration analysis on equipment through a preset industrial Internet platform, generating a corresponding equipment configuration file, carrying out parameter configuration on the equipment according to the equipment configuration file, and generating an equipment parameter configuration result;
the generation module is used for collecting feedback data of the equipment through the industrial Internet platform and generating equipment running state data;
the coding module is used for carrying out coding fusion processing on the acquired equipment running state data and the equipment parameter configuration result to generate equipment coding state data, carrying out characteristic analysis on the equipment coding state data and generating equipment state characteristic information; the database stores coding rules for converting the collected equipment running state data and the equipment parameter configuration result in advance;
The splicing module is used for carrying out decomposition processing on the equipment state characteristic information to generate a plurality of pieces of equipment state characteristic sub-information, carrying out matrix conversion processing on each piece of equipment state characteristic sub-information to generate each mapping word vector of each piece of equipment state characteristic sub-information, and carrying out splicing processing on each mapping word vector to obtain a target state characteristic vector;
the prediction module is used for inputting the target state feature vector into the trained abnormal state recognition model, analyzing the abnormal behavior of the equipment to obtain an equipment abnormal behavior analysis result, and analyzing the monitoring strategy of the equipment based on the equipment abnormal behavior analysis result to obtain a target monitoring strategy of the equipment; the abnormal state identification model is obtained through training in advance.
A third aspect of the present invention provides an industrial internet-based device monitoring apparatus, comprising: a memory and at least one processor, the memory having instructions stored therein; the at least one processor invokes the instructions in the memory to cause the industrial internet-based device monitoring apparatus to perform the industrial internet-based device monitoring method described above.
A fourth aspect of the present invention provides a computer readable storage medium having instructions stored therein which, when run on a computer, cause the computer to perform the above-described industrial internet-based device monitoring method.
In the technical scheme provided by the invention, the beneficial effects are as follows: the invention provides a device monitoring method and a device monitoring system based on an industrial Internet, which are characterized in that a preset industrial Internet platform is used for carrying out configuration analysis on a device to generate a corresponding device configuration file, and the device is subjected to parameter configuration according to the device configuration file to generate a device parameter configuration result; the method comprises the steps of collecting feedback data of equipment through an industrial Internet platform, and generating equipment running state data; performing coding fusion processing on the acquired equipment running state data and the equipment parameter configuration result to generate equipment coding state data, and performing feature analysis on the equipment coding state data to generate equipment state feature information; decomposing the equipment state characteristic information to generate a plurality of pieces of equipment state characteristic sub-information, performing matrix conversion processing on each piece of equipment state characteristic sub-information to generate each mapping word vector of each piece of equipment state characteristic sub-information, and performing splicing processing on each mapping word vector to obtain a target state characteristic vector; and inputting the target state feature vector into a trained abnormal state recognition model, analyzing the abnormal behavior of the equipment to obtain an equipment abnormal behavior analysis result, and analyzing the monitoring strategy of the equipment based on the equipment abnormal behavior analysis result to obtain a target monitoring strategy of the equipment. According to the invention, the device parameter configuration and the real-time data acquisition are carried out through the industrial Internet platform, so that the high-precision monitoring of the device state can be realized, the tiny change of the device can be found in time, and the monitoring intellectualization level is improved compared with the prior art. The method can effectively integrate multi-source data, improve data processing capacity and provide a richer and more accurate information basis for anomaly analysis. The method improves the recognition accuracy and response speed of complex abnormal behaviors by decomposing the equipment state characteristic information and performing matrix conversion processing on the equipment state characteristic information, splicing various mapping word vectors to obtain target state characteristic vectors, and inputting the target state characteristic vectors into a trained abnormal state recognition model. The monitoring strategy analysis is carried out based on the equipment abnormal behavior analysis result, and the target monitoring strategy can be formulated more pertinently, so that early warning and fault prevention are realized, the risk of production interruption is reduced, and the maintenance cost is reduced. The invention can automatically monitor the operation state of industrial equipment, realize the timely diagnosis of abnormal state, reduce the requirement of manual intervention and improve the overall equipment management efficiency.
Drawings
FIG. 1 is a schematic diagram of an embodiment of an apparatus monitoring method based on the industrial Internet according to the embodiment of the invention;
FIG. 2 is a schematic diagram of an embodiment of an industrial Internet-based device monitoring system according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a device monitoring method and a device monitoring system based on an industrial Internet. The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
For ease of understanding, a specific flow of an embodiment of the present invention is described below with reference to fig. 1, where an embodiment of an apparatus monitoring method based on the industrial internet in the embodiment of the present invention includes:
step 101, carrying out configuration analysis on equipment through a preset industrial internet platform to generate a corresponding equipment configuration file, carrying out parameter configuration on the equipment according to the equipment configuration file, and generating an equipment parameter configuration result;
it will be appreciated that the implementation subject of the present invention may be an industrial internet-based device monitoring system, or may be a terminal or a server, which is not limited herein. The embodiment of the invention is described by taking a server as an execution main body as an example.
Specifically, the implementation of step 101 is as follows:
and carrying out configuration analysis on the equipment through a preset industrial Internet platform:
based on the industrial internet technology, the data acquisition and analysis are carried out on the equipment by utilizing an automatic configuration tool. And the device interface is connected with the industrial Internet platform, and information such as device operation data, performance parameters and communication interfaces is collected to perform device configuration analysis.
Generating a corresponding device configuration file:
and the industrial Internet platform generates a corresponding equipment configuration file by combining the equipment model, the communication protocol and the actual operation parameters, wherein the corresponding equipment configuration file comprises information such as equipment parameters, communication protocol configuration, alarm threshold values and the like and is used for carrying out parameter configuration on equipment by the system.
Parameter configuration is carried out on the equipment according to the equipment configuration file:
and using an automatic configuration tool to apply the generated equipment configuration file to equipment, and automatically configuring various parameters including communication protocol setting, data acquisition frequency, alarm parameters and the like. The system is remotely communicated and configured with the equipment through an industrial internet platform.
Generating a device parameter configuration result:
and monitoring and recording the process of equipment parameter configuration, and ensuring that the equipment configuration is carried out according to expectations. The actual parameter data after the equipment is configured is collected through an industrial Internet platform, and an equipment parameter configuration result report is generated, wherein the report comprises the information of the success rate of equipment configuration, the time cost, the actual performance parameters of the equipment after configuration and the like.
Step 102, collecting feedback data of equipment through an industrial Internet platform to generate equipment running state data;
specifically, the implementation of step 102 is as follows:
feedback data acquisition is carried out on equipment in an industrial Internet platform:
on an industrial Internet platform, a data acquisition node is arranged to be connected with equipment so as to realize real-time acquisition of equipment running state data. By communicating with the device interface, various operating parameters of the device, such as temperature, pressure, current, voltage, etc., are obtained.
Generating device operating state data:
the collected equipment operation state data is processed and analyzed through the industrial Internet platform, and the steps of data cleaning, anomaly detection, data conversion and the like are included to generate equipment operation state data for analysis and application. Such data includes device runtime, load status, fault information, etc.
Step 103, performing coding fusion processing on the acquired equipment running state data and the equipment parameter configuration result to generate equipment coding state data, and performing feature analysis on the equipment coding state data to generate equipment state feature information; the database stores coding rules for converting the collected equipment running state data and the equipment parameter configuration result in advance;
specifically, the implementation of step 103 is as follows:
and carrying out coding fusion processing on the collected equipment running state data and the equipment parameter configuration result:
and based on a predefined coding rule, uniformly coding the acquired equipment running state data and the equipment parameter configuration result, and converting different types of data into a uniform coding state data format. For example, the device running state data such as temperature and pressure, the communication protocol configuration, the alarm threshold value and the device parameter configuration result are converted into a unified coding format.
Generating device encoded state data:
and integrating the data after the coding fusion processing to generate coding state data containing the running state and configuration result of the equipment. These data are in a consistent format in the encoded state to facilitate subsequent feature analysis and processing.
Performing feature analysis on the device coding state data:
and performing feature extraction and analysis on the equipment coding state data by using methods such as data mining, statistical analysis and the like, and identifying key features of the data. For example, machine learning algorithms are used to identify and pattern identify features in the device encoded state data to reveal potential laws and abnormal features of the device state.
Generating device state characteristic information:
based on the results of the feature analysis, device state feature information is generated. The information can comprise key characteristics of the running state of the equipment, abnormal detection results, state trends and the like, and provides important basis for subsequent equipment state monitoring, prediction and decision.
104, decomposing the equipment state characteristic information to generate a plurality of pieces of equipment state characteristic sub-information, performing matrix conversion processing on each piece of equipment state characteristic sub-information to generate each mapping word vector of each piece of equipment state characteristic sub-information, and performing splicing processing on each mapping word vector to obtain a target state characteristic vector;
Specifically, the implementation of step 104 is as follows:
decomposing the equipment state characteristic information to generate a plurality of pieces of equipment state characteristic sub-information:
and decomposing the extracted equipment state characteristic information into a plurality of sub-characteristic information, such as the sub-characteristic information of each aspect of equipment operation stability, power consumption characteristics, temperature characteristics, vibration characteristics and the like.
Performing matrix conversion processing on the state characteristic sub-information of each device to generate each mapping word vector of the state characteristic sub-information of each device:
each device state feature sub-information is matrix converted into a corresponding mapped word vector, for example, the device state feature sub-information is converted into a mapped word vector in a high-dimensional vector space using a Principal Component Analysis (PCA) method or the like.
Each mapping word vector is spliced to obtain a target state feature vector:
and splicing the mapping word vectors of the state characteristic sub-information of each device to form a complete target state characteristic vector. The target state feature vector contains multiple aspects of the device operating state information and is a high-dimensional abstract representation of the device state feature information.
Step 105, inputting the target state feature vector into a trained abnormal state recognition model, analyzing the abnormal behavior of the equipment to obtain an equipment abnormal behavior analysis result, and analyzing the monitoring strategy of the equipment based on the equipment abnormal behavior analysis result to obtain a target monitoring strategy of the equipment; the abnormal state identification model is obtained through training in advance.
Specifically, the implementation of step 105 is as follows:
inputting the target state feature vector into a trained abnormal state recognition model, and analyzing abnormal behaviors of equipment:
the state of the equipment is analyzed and processed by utilizing a machine learning algorithm or a deep learning algorithm by inputting the target state feature vector into a pre-trained abnormal state recognition model so as to judge whether the equipment has abnormal behaviors currently. For example, abnormal state recognition is performed by using a Support Vector Machine (SVM), a neural network and other models, and the state of the equipment is automatically monitored and evaluated.
Obtaining an equipment abnormal behavior analysis result:
based on the output of the abnormal state identification model, the abnormal behavior analysis result of the equipment is obtained, namely, whether the current state of the equipment is normal or not and the type and degree of the abnormal behavior are judged. These results can help engineers or operators identify equipment anomalies in time and quickly address problems.
Based on the analysis result of the abnormal behavior of the equipment, carrying out monitoring policy analysis on the equipment to obtain a target monitoring policy of the equipment:
and evaluating and adjusting the equipment monitoring strategy according to the equipment abnormal behavior analysis result. According to the specific condition of equipment abnormality, a targeted monitoring strategy is formulated to ensure the safe operation of the equipment and prevent the occurrence of potential faults. For example, for a particular type of abnormal behavior, measures such as adjusting the monitoring parameters, increasing the monitoring frequency, etc. may be taken.
Another embodiment of the device monitoring method based on the industrial internet in the embodiment of the invention comprises the following steps: the device parameter configuration result at least comprises a function parameter configuration result and a performance parameter configuration result.
Another embodiment of the device monitoring system based on the industrial internet in the embodiment of the invention comprises:
the converting process is performed on the collected equipment running state data and the equipment parameter configuration result to generate equipment coding state data, which comprises the following steps:
respectively converting the acquired equipment running state data and the equipment parameter configuration result to obtain a corresponding first character combination and a corresponding second character combination;
acquiring a preset standard conversion map; wherein the standard conversion map at least comprises a conversion number and a conversion text character mapping rule; the conversion characters take Chinese characters as conversion carriers;
Converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to the equipment operation state data; the first target conversion map is obtained by transforming a preset first design rule based on the preset standard conversion map;
converting the second character combination based on a second target conversion map to obtain second conversion data corresponding to the equipment parameter configuration result; the second target conversion map is obtained by transforming the second target conversion map through a second preset design rule based on the preset standard conversion map;
based on a preset coding rule, respectively coding the first conversion data and the second conversion data to obtain a corresponding first coding character combination and a corresponding second coding character combination;
and based on a preset character combination rule, respectively selecting a plurality of characters from the first coding character combination and the second coding character combination to combine, and obtaining a target character combination as final equipment coding state data.
In particular, term interpretation
Device operational status data: refers to data collected from the device sensors and control system that reflect the real-time operating conditions of the device, such as the values of variables such as temperature, pressure, speed, etc.
Device parameter configuration results: refers to the setup and configuration information of the device, which may include parameters of the model, specification, function options, etc. of the device.
Conversion treatment: and converting the collected data into another format or structure through a certain algorithm or rule.
The device encodes status data: the coded data which is generated after conversion processing and is convenient to store and transmit is used for representing the running state and parameter configuration of the equipment.
Character combination: refers to concatenating individual characters or codes into a string to form an ordered sequence of characters representing information.
Conversion map: the preset reference template comprises a series of numbers and corresponding conversion rules or characters and is used for converting the original data into the coded data in a specific format.
Coding rules: a predefined set of rules for further converting the converted data into a standardized coded form.
Character combination rules: for deciding how to select a particular character from the encoded character combinations to be concatenated into the final device encoding state data.
Application scenario
The technical scheme is applied to the equipment monitoring system in the industrial Internet environment. In the industrial production process, the operation state and configuration parameters of the monitoring equipment are critical to ensuring production safety and improving efficiency. By collecting the running state data and parameter configuration information of the equipment in real time and converting the information into the coding state data of the equipment, the remote monitoring and intelligent analysis of the equipment state can be realized, so that adjustment and maintenance decisions can be made in time.
Example 1
The equipment monitoring system of the industrial Internet firstly acquires equipment running state data and equipment parameter configuration results from monitored equipment. The data is converted into a first character combination and a second character combination by a corresponding algorithm. And then, the system respectively converts the two groups of character combinations by utilizing the first target conversion spectrum and the second target conversion spectrum according to a preset standard conversion spectrum to obtain first conversion data and second conversion data. The standard conversion map contains a series of conversion numbers and mapping rules of literal characters, facilitating the conversion of operational data and parameter configurations into standardized kanji character carriers.
And then, carrying out coding processing on the first conversion data and the second conversion data according to the set coding rule to generate corresponding first coding character and second coding character combinations. And finally, selecting a plurality of characters from the two groups of coding characters according to the character combination rule to combine to form final equipment coding state data.
Example 1 (refinement)
In a specific embodiment of the technical scheme, the equipment monitoring system of the industrial internet monitors and analyzes the equipment state by adopting the following steps:
Data acquisition and primary conversion: the monitoring system collects running state data (such as temperature, pressure, running speed and the like) from each device in real time, and parameter configuration results (such as model, specification and the like) of the device. These data are converted into a first character combination (representing the operational state data) and a second character combination (representing the parameter configuration result) through preliminary processing.
Conversion map application: the system uses two different sets of target conversion maps (a first target conversion map and a second target conversion map) according to the set standard conversion map. The patterns convert the character combinations into a more standardized kanji character format according to preset rules. For example, specific operating state data is converted into a specific set of kanji characters by a first target conversion pattern, and parameter configuration results are converted into another set of kanji characters by a second target conversion pattern.
Encoding: the converted data is further processed according to the coding rules to form two groups of coding characters (a first coding character combination and a second coding character combination). This process involves further encoding of the kanji character to facilitate the transmission and storage of data.
Character combination generation: the final step is to select a number of characters from the first and second encoded character combinations according to a character combination rule, and combine them into final device encoded state data in a specific order. The combination process considers the integrity and the readability of the data, ensures that the generated equipment coding state data not only can comprehensively reflect the running state and the configuration parameters of the equipment, but also is convenient for monitoring personnel to understand and use
In the embodiment of the invention, the beneficial effects are as follows: the technical scheme provides an efficient data processing and encoding method, and can realize accurate monitoring and analysis of equipment operation states and parameter configuration. The device state information can be converted into a coding format which is convenient for transmission and storage through standardized conversion patterns and coding rules, thereby facilitating the efficient management of a large number of devices. In addition, the adoption of Chinese characters as a conversion carrier enhances the readability and easy understanding of information, is beneficial to an operator to quickly grasp the state of equipment, and provides powerful support for equipment maintenance and fault elimination.
Another embodiment of the device monitoring system based on the industrial internet in the embodiment of the invention comprises:
Converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to equipment operation state data, wherein the first conversion data comprises:
comparing the target character combination with converted character in the preset standard conversion map by referring to a character set, and marking Chinese characters corresponding to the target character combination as invalid character for successfully compared character; frequency spectrum analysis is carried out on unlabeled effective literal characters, and a priority sequence is established for the effective literal characters according to the sequence from high frequency to low frequency, so as to obtain a dynamic priority sequence;
in a preset standard conversion map, reassigning a conversion number to each effective text character according to the dynamic priority sequence; the database stores allocation rules for reallocating conversion numbers for each effective text character based on the dynamic priority sequence in advance;
generating a series of random sequences, and optimally sequencing the series of random sequences to obtain a first random number set and a second random number set after sequencing; wherein, the optimized sorting means that each random number in the random number set is classified according to the number parity of the random sequence, and each classified random number is sorted in a descending order; the first random number set is an odd-numbered descending random number set, and the second random number set is an even-numbered descending random number set;
After the allocation of new conversion serial numbers of the effective coding characters is completed, sequentially matching the conversion serial numbers which are the same as the random numbers based on the random numbers in the ordered first random number set, and sequentially adding invalid character characters corresponding to the matched conversion serial numbers into the preset standard conversion map and being positioned in front of the effective character characters;
integrating all characters and the new conversion serial numbers obtained by distribution in a preset standard conversion map, and regenerating an optimized standard conversion map to obtain a first target conversion map; and converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to the equipment operation state data.
In particular, term interpretation
Reference text set control: the method is to compare the target character combination with the literal characters in the preset standard conversion map so as to identify and classify the effective and ineffective literal characters.
Invalid literal characters: literal characters marked as not participating in subsequent processing during the conversion process.
Frequency spectrum analysis: the frequency of occurrence of characters in a data set is analyzed to determine the importance or priority of the characters.
Dynamic priority sequence: and arranging the formed priority sequences from high to low according to the occurrence frequency of the effective literal characters.
And (5) reassigning conversion numbers: and reassigning the conversion number to the valid text character based on the dynamic priority sequence.
Random sequence optimization ordering: a process of classifying and ordering the generated random sequences by a specific rule (e.g., parity).
A first random number set, a second random number set: respectively, refers to a set of random numbers arranged in descending order based on parity classification.
Application scenario
The technical scheme is suitable for equipment monitoring systems in industrial Internet environments, and particularly under the condition that a large amount of equipment data is required to be processed and converted efficiently. The technology can improve the accuracy and efficiency of data processing, further support real-time monitoring and data analysis of the running state of equipment, and has important significance for improving the running efficiency and reliability of an industrial system.
Embodiment 2 (refinement) in a further embodiment of the present technical solution, the device monitoring system performs data processing by:
control and frequency analysis: the system first compares the target character combination with the character in the standard conversion map to mark invalid character. Frequency spectrum analysis is then performed on the unlabeled valid literal characters to create a dynamic priority sequence.
And (5) reassigning conversion numbers: the system reassigns the conversion number to the valid literal character according to the dynamic priority sequence, which is based on the assignment rules stored in the database.
Generating and optimizing a random sequence: the system generates a series of random sequences and obtains first and second random number sets respectively by optimizing the ordering process.
Reintegration of standard conversion patterns: and the system performs new sequencing on the invalid text characters according to the first random number set, adds the invalid text characters into the standard conversion map, and finally generates an optimized first target conversion map.
Data conversion: and converting the first character combination based on the optimized first target conversion map to generate first conversion data corresponding to the final equipment operation state data.
In the embodiment of the invention, the beneficial effects are as follows: according to the technical scheme, the flexibility and the accuracy of data processing are improved by dynamically adjusting the conversion rule and the coding process. The efficiency and the reliability of data conversion can be effectively improved by utilizing frequency spectrum analysis and random sequence optimization sequencing. In addition, through optimizing the conversion map, the readability and the understandability of the data are enhanced, and the rapid response to the state change of the equipment is facilitated, so that more accurate and efficient support is provided for the real-time monitoring and maintenance of the equipment.
Another embodiment of the device monitoring system based on the industrial internet in the embodiment of the invention comprises:
the random numbers in the ordered first random number set at least comprise conversion sequence number numbers of invalid characters, and a mapping relation exists between the conversion sequence number numbers of the ordered first random number set and the conversion sequence number numbers of the invalid characters.
The method for monitoring the device based on the industrial internet in the embodiment of the present invention is described above, and the system for monitoring the device based on the industrial internet in the embodiment of the present invention is described below, referring to fig. 2, where an embodiment of the system for monitoring the device based on the industrial internet in the embodiment of the present invention includes:
the equipment monitoring system based on the industrial Internet comprises:
the analysis module is used for carrying out configuration analysis on equipment through a preset industrial Internet platform, generating a corresponding equipment configuration file, carrying out parameter configuration on the equipment according to the equipment configuration file, and generating an equipment parameter configuration result;
the generation module is used for collecting feedback data of the equipment through the industrial Internet platform and generating equipment running state data;
the coding module is used for carrying out coding fusion processing on the acquired equipment running state data and the equipment parameter configuration result to generate equipment coding state data, carrying out characteristic analysis on the equipment coding state data and generating equipment state characteristic information; the database stores coding rules for converting the collected equipment running state data and the equipment parameter configuration result in advance;
The splicing module is used for carrying out decomposition processing on the equipment state characteristic information to generate a plurality of pieces of equipment state characteristic sub-information, carrying out matrix conversion processing on each piece of equipment state characteristic sub-information to generate each mapping word vector of each piece of equipment state characteristic sub-information, and carrying out splicing processing on each mapping word vector to obtain a target state characteristic vector;
the prediction module is used for inputting the target state feature vector into the trained abnormal state recognition model, analyzing the abnormal behavior of the equipment to obtain an equipment abnormal behavior analysis result, and analyzing the monitoring strategy of the equipment based on the equipment abnormal behavior analysis result to obtain a target monitoring strategy of the equipment; the abnormal state identification model is obtained through training in advance.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, and may also be a volatile computer readable storage medium, where instructions are stored in the computer readable storage medium, when the instructions are executed on a computer, cause the computer to perform the steps of the industrial internet-based device monitoring method.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (6)
1. An equipment monitoring method based on the industrial Internet is characterized by comprising the following steps:
performing configuration analysis on equipment through a preset industrial Internet platform, generating a corresponding equipment configuration file, performing parameter configuration on the equipment according to the equipment configuration file, and generating an equipment parameter configuration result;
the method comprises the steps of collecting feedback data of equipment through an industrial Internet platform, and generating equipment running state data;
performing coding fusion processing on the acquired equipment running state data and the equipment parameter configuration result to generate equipment coding state data, and performing feature analysis on the equipment coding state data to generate equipment state feature information; the database stores coding rules for converting the collected equipment running state data and the equipment parameter configuration result in advance;
Decomposing the equipment state characteristic information to generate a plurality of pieces of equipment state characteristic sub-information, performing matrix conversion processing on each piece of equipment state characteristic sub-information to generate each mapping word vector of each piece of equipment state characteristic sub-information, and performing splicing processing on each mapping word vector to obtain a target state characteristic vector;
inputting the target state feature vector into a trained abnormal state recognition model, analyzing the abnormal behavior of the equipment to obtain an equipment abnormal behavior analysis result, and analyzing the monitoring strategy of the equipment based on the equipment abnormal behavior analysis result to obtain a target monitoring strategy of the equipment; the abnormal state identification model is obtained through training in advance;
the converting process is performed on the collected equipment running state data and the equipment parameter configuration result to generate equipment coding state data, which comprises the following steps:
respectively converting the acquired equipment running state data and the equipment parameter configuration result to obtain a corresponding first character combination and a corresponding second character combination;
acquiring a preset standard conversion map; wherein the standard conversion map at least comprises a conversion number and a conversion text character mapping rule; the conversion characters take Chinese characters as conversion carriers;
Converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to the equipment operation state data; the first target conversion map is obtained by transforming a preset first design rule based on the preset standard conversion map;
converting the second character combination based on a second target conversion map to obtain second conversion data corresponding to the equipment parameter configuration result; the second target conversion map is obtained by transforming the second target conversion map through a second preset design rule based on the preset standard conversion map;
based on a preset coding rule, respectively coding the first conversion data and the second conversion data to obtain a corresponding first coding character combination and a corresponding second coding character combination;
based on a preset character combination rule, respectively selecting a plurality of characters from the first coding character combination and the second coding character combination to be combined to obtain a target character combination as final equipment coding state data;
converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to equipment operation state data, wherein the first conversion data comprises:
Comparing the target character combination with converted character in the preset standard conversion map by referring to a character set, and marking Chinese characters corresponding to the target character combination as invalid character for successfully compared character; frequency spectrum analysis is carried out on unlabeled effective literal characters, and a priority sequence is established for the effective literal characters according to the sequence from high frequency to low frequency, so as to obtain a dynamic priority sequence;
in a preset standard conversion map, reassigning a conversion number to each effective text character according to the dynamic priority sequence; the database stores allocation rules for reallocating conversion numbers for each effective text character based on the dynamic priority sequence in advance;
generating a series of random sequences, and optimally sequencing the series of random sequences to obtain a first random number set and a second random number set after sequencing; wherein, the optimized sorting means that each random number in the random number set is classified according to the number parity of the random sequence, and each classified random number is sorted in a descending order; the first random number set is an odd-numbered descending random number set, and the second random number set is an even-numbered descending random number set;
After the allocation of new conversion serial numbers of the effective coding characters is completed, sequentially matching the conversion serial numbers which are the same as the random numbers based on the random numbers in the ordered first random number set, and sequentially adding invalid character characters corresponding to the matched conversion serial numbers into the preset standard conversion map and being positioned in front of the effective character characters;
integrating all characters and the new conversion serial numbers obtained by distribution in a preset standard conversion map, and regenerating an optimized standard conversion map to obtain a first target conversion map; and converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to the equipment operation state data.
2. The industrial internet-based device monitoring method of claim 1, wherein the device parameter configuration results include at least a function parameter configuration result and a performance parameter configuration result.
3. The industrial internet-based device monitoring method of claim 1, wherein the random numbers in the ordered first set of random numbers at least include conversion sequence numbers of invalid text characters, and a mapping relationship exists between the conversion sequence numbers of the ordered first set of random numbers and the conversion sequence numbers of the invalid text characters.
4. An industrial internet-based device monitoring system, comprising:
the analysis module is used for carrying out configuration analysis on equipment through a preset industrial Internet platform, generating a corresponding equipment configuration file, carrying out parameter configuration on the equipment according to the equipment configuration file, and generating an equipment parameter configuration result;
the generation module is used for collecting feedback data of the equipment through the industrial Internet platform and generating equipment running state data;
the coding module is used for carrying out coding fusion processing on the acquired equipment running state data and the equipment parameter configuration result to generate equipment coding state data, carrying out characteristic analysis on the equipment coding state data and generating equipment state characteristic information; the database stores coding rules for converting the collected equipment running state data and the equipment parameter configuration result in advance;
the splicing module is used for carrying out decomposition processing on the equipment state characteristic information to generate a plurality of pieces of equipment state characteristic sub-information, carrying out matrix conversion processing on each piece of equipment state characteristic sub-information to generate each mapping word vector of each piece of equipment state characteristic sub-information, and carrying out splicing processing on each mapping word vector to obtain a target state characteristic vector;
The prediction module is used for inputting the target state feature vector into the trained abnormal state recognition model, analyzing the abnormal behavior of the equipment to obtain an equipment abnormal behavior analysis result, and analyzing the monitoring strategy of the equipment based on the equipment abnormal behavior analysis result to obtain a target monitoring strategy of the equipment; the abnormal state identification model is obtained through training in advance;
the coding module is specifically configured to:
respectively converting the acquired equipment running state data and the equipment parameter configuration result to obtain a corresponding first character combination and a corresponding second character combination;
acquiring a preset standard conversion map; wherein the standard conversion map at least comprises a conversion number and a conversion text character mapping rule; the conversion characters take Chinese characters as conversion carriers;
converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to the equipment operation state data; the first target conversion map is obtained by transforming a preset first design rule based on the preset standard conversion map;
converting the second character combination based on a second target conversion map to obtain second conversion data corresponding to the equipment parameter configuration result; the second target conversion map is obtained by transforming the second target conversion map through a second preset design rule based on the preset standard conversion map;
Based on a preset coding rule, respectively coding the first conversion data and the second conversion data to obtain a corresponding first coding character combination and a corresponding second coding character combination;
based on a preset character combination rule, respectively selecting a plurality of characters from the first coding character combination and the second coding character combination to be combined to obtain a target character combination as final equipment coding state data;
converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to equipment operation state data, wherein the first conversion data comprises:
comparing the target character combination with converted character in the preset standard conversion map by referring to a character set, and marking Chinese characters corresponding to the target character combination as invalid character for successfully compared character; frequency spectrum analysis is carried out on unlabeled effective literal characters, and a priority sequence is established for the effective literal characters according to the sequence from high frequency to low frequency, so as to obtain a dynamic priority sequence;
in a preset standard conversion map, reassigning a conversion number to each effective text character according to the dynamic priority sequence; the database stores allocation rules for reallocating conversion numbers for each effective text character based on the dynamic priority sequence in advance;
Generating a series of random sequences, and optimally sequencing the series of random sequences to obtain a first random number set and a second random number set after sequencing; wherein, the optimized sorting means that each random number in the random number set is classified according to the number parity of the random sequence, and each classified random number is sorted in a descending order; the first random number set is an odd-numbered descending random number set, and the second random number set is an even-numbered descending random number set;
after the allocation of new conversion serial numbers of the effective coding characters is completed, sequentially matching the conversion serial numbers which are the same as the random numbers based on the random numbers in the ordered first random number set, and sequentially adding invalid character characters corresponding to the matched conversion serial numbers into the preset standard conversion map and being positioned in front of the effective character characters;
integrating all characters and the new conversion serial numbers obtained by distribution in a preset standard conversion map, and regenerating an optimized standard conversion map to obtain a first target conversion map; and converting the first character combination based on a first target conversion map to obtain first conversion data corresponding to the equipment operation state data.
5. An industrial internet-based device monitoring apparatus, comprising: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invoking the instructions in the memory to cause the industrial internet-based device monitoring apparatus to perform the industrial internet-based device monitoring method of any of claims 1-3.
6. A computer readable storage medium having instructions stored thereon, which when executed by a processor, implement the industrial internet-based device monitoring method of any of claims 1-3.
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