CN117707444B - Cloud printer abnormal state discernment maintenance management system - Google Patents
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Abstract
The embodiment of the invention provides a cloud printer abnormal state identification maintenance management system, and belongs to the technical field of printers. The system comprises a target printer, a first printing state and a second printing state, wherein the target printer receives printing content, and performs content analysis on the printing content to obtain the first printing state corresponding to the printing content; performing printing operation on the printing content to obtain a printing result corresponding to the printing content and a first printing time corresponding to the printing content; obtaining a printing image corresponding to the printing result; the cloud server predicts the time of the printing content, obtains a second printing time corresponding to the printing content, and determines a second printing state according to the first printing time and the second printing time; performing image analysis according to the print image to obtain a third print state corresponding to the target printer; determining a target printing state corresponding to the target printer according to the first printing state, the second printing state and the third printing state, and determining a processing strategy corresponding to the target printer according to the target printing state; and sending the processing strategy to the terminal equipment.
Description
Technical Field
The invention relates to the technical field of printers, in particular to a cloud printer abnormal state identification maintenance management system.
Background
With the rapid development of the internet, cloud printing becomes a convenient and efficient printing solution. The cloud printing technology is characterized in that cloud printing equipment is connected with a cloud server, a user sends a printing request to the cloud server through terminal equipment, and the cloud server re-sends the printing task to the corresponding cloud printing equipment to realize remote printing operation. However, as the number of cloud printing apparatuses increases and varies, when the cloud printing apparatuses are abnormal, a user cannot timely find the abnormality to perform maintenance, thereby affecting printing efficiency.
Disclosure of Invention
The embodiment of the invention mainly aims to provide a cloud printer abnormal state identification maintenance management system, which aims to solve the problems that in the related art, as the number of cloud printing equipment is increased and diversified, when the cloud printing equipment is abnormal, a user cannot timely find the abnormality to maintain, and the printing efficiency is affected.
In a first aspect, an embodiment of the present invention provides a system for identifying, maintaining and managing abnormal states of a cloud printer, where the system includes a cloud server, a printer communicatively connected to the cloud server, and a terminal device communicatively connected to the cloud server,
The terminal equipment sends an order request to the cloud server;
the cloud server receives the order request, analyzes the order request and obtains an order type corresponding to the order request and print content corresponding to the order request;
the cloud server determines a target printer corresponding to the order request from the printers according to the order type, and sends the printing content to the target printer;
The target printer receives the printing content, analyzes the printing content, and obtains a first printing state corresponding to the printing content; performing a printing operation on the printing content to obtain a printing result corresponding to the printing content and a first printing time corresponding to the printing content; obtaining a printing image corresponding to the printing result; transmitting the printed image, the first printing time and the first printing state to the cloud server;
the cloud server receives the print image, the first printing time and the first printing state, predicts the time of the print content, obtains second printing time corresponding to the print content, and determines the second printing state corresponding to the target printer according to the first printing time and the second printing time; performing image analysis according to the print image to obtain a third print state corresponding to the target printer; determining a target printing state corresponding to the target printer according to the first printing state, the second printing state and the third printing state, and determining a processing strategy corresponding to the target printer according to the target printing state; transmitting the processing strategy to the terminal equipment;
and the terminal equipment receives the processing strategy and maintains the target printer according to the processing strategy so as to enable the target printer to normally operate.
The embodiment of the invention provides a cloud printer abnormal state identification maintenance management system, which comprises a cloud server, a printer in communication connection with the cloud server and terminal equipment in communication connection with the cloud server, wherein in order to ensure the normal operation of the cloud printer, the system can timely discover the abnormal position in the cloud printer, generate a corresponding processing strategy to timely inform a user to maintain the printer with the abnormal problem, and solve the problem that the user cannot timely discover the abnormality to maintain when the printing equipment is abnormal along with the increase and diversification of the number of the cloud printing equipment, thereby influencing the printing efficiency.
The terminal equipment sends an order request to the cloud server; the cloud server receives the order request and analyzes the order request to obtain the order type corresponding to the order request and the printing content corresponding to the order request; the cloud server determines a target printer corresponding to the order request from printers according to the order type, and sends the printing content to the target printer; the target printer receives the printing content, analyzes the printing content, and obtains a first printing state corresponding to the printing content; performing printing operation on the printing content to obtain a printing result corresponding to the printing content and a first printing time corresponding to the printing content; obtaining a printing image corresponding to the printing result; transmitting the printed image, the first printing time and the first printing state to a cloud server; the cloud server receives the print image, the first printing time and the first printing state, predicts the time of the print content, obtains the second printing time corresponding to the print content, and determines the second printing state corresponding to the target printer according to the first printing time and the second printing time; performing image analysis according to the print image to obtain a third print state corresponding to the target printer; determining a target printing state corresponding to the target printer according to the first printing state, the second printing state and the third printing state, and determining a processing strategy corresponding to the target printer according to the target printing state; sending the processing strategy to the terminal equipment; and the terminal equipment receives the processing strategy and maintains the target printer according to the processing strategy so that the target printer operates normally.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic block diagram of a cloud printer abnormal state identification maintenance management system according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a cloud printer abnormal state identification maintenance management system according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The flow diagrams depicted in the figures are merely illustrative and not necessarily all of the elements and operations/steps are included or performed in the order described. For example, some operations/steps may be further divided, combined, or partially combined, so that the order of actual execution may be changed according to actual situations.
It is to be understood that 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. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The embodiment of the application provides a cloud printer abnormal state identification maintenance management system. The cloud printer abnormal state identification maintenance management system comprises a cloud server, a printer in communication connection with the cloud server and terminal equipment in communication connection with the cloud server. The cloud server can be a server or a server cluster, and the terminal equipment can be electronic equipment such as a tablet computer, a notebook computer, a desktop computer, a personal digital assistant, a wearable device and the like. The printer may be a thermal printer, ticket printer, bar code printer, or the like. The cloud printer abnormal state identification maintenance management system provided by the embodiment of the application can be applied to the fields of super business, catering (take-away), retail, logistics and the like.
Some embodiments of the invention are described in detail below with reference to the accompanying drawings. The following embodiments and features of the embodiments may be combined with each other without conflict.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a cloud printer abnormal state identification maintenance management system according to an embodiment of the present invention, including a cloud server, a printer communicatively connected to the cloud server, and a terminal device communicatively connected to the cloud server. The terminal equipment sends an order request to the cloud server, the cloud server further obtains corresponding printing content and order type according to the order request, and further selects a proper target printer according to the order type, and further sends the printing content to the target printer, so that the target printer prints the printing content, analysis is carried out on the printing content in the process of printing the printing content to obtain a first printing state, corresponding first printing time and printing images of the printing content are printed, the obtained content is fed back to the cloud server, the cloud server continuously analyzes the feedback content, so that a second printing state and a third printing state are obtained, the first printing state, the second printing state and the third printing state are integrated, the processing strategy of the target printer is determined according to the target printing state, and accordingly the target strategy is sent to the terminal equipment, so that a user maintains the target printer according to the processing strategy, normal operation of the target printer is guaranteed, and printing efficiency of the cloud printer is improved.
As shown in fig. 2, specific steps of interaction between each component in the cloud printer abnormal state identification maintenance management system include steps S101 to S106.
And step S101, the terminal equipment sends an order request to the cloud server.
The terminal device may be a terminal device for receiving a take-out order, a terminal device for receiving a logistics order, or the like, and if a user order is detected in the terminal device, the user order is packaged to obtain an order request, and the order request is sent to a cloud server in communication with the terminal device, so that printing of the user order is achieved.
Optionally, the communication connection between the terminal device and the cloud server may be wireless connection or wired connection, etc., which is not particularly limited in the present application, and the user may select according to the actual requirement.
Step S102, the cloud server receives the order request and analyzes the order request to obtain an order type corresponding to the order request and print content corresponding to the order request.
The cloud server receives an order request sent by the terminal device, and further analyzes the order request to obtain printing content corresponding to the order request.
The terminal device may directly encapsulate the order type corresponding to the user order into the order request when the user order is encapsulated to obtain the order request, and further, after receiving the order request, the cloud server may directly obtain the field content corresponding to the corresponding field in the analysis content after analyzing the order request, so as to determine the order type corresponding to the order request according to the field content.
For example, the order types include a restaurant order, a supermarket order, a logistics order and the like, when the terminal equipment receives the user order, the order type corresponding to the user order is determined according to the source of the received user order, and when the terminal equipment encapsulates the user order, the order type corresponding to the user order and the user order can be encapsulated together, for example { "dayin": "one meat bread," "style": "restaurant order" }, "dayin" field indicates the content of the user order, and "style" indicates the order type corresponding to the user order. Therefore, after receiving the order request, the cloud server can directly obtain the order type corresponding to the order request by analyzing the order request.
And step 103, the cloud server determines a target printer corresponding to the order request from the printers according to the order type, and sends the printing content to the target printer.
The cloud server is connected with a plurality of types of printers, and screens the printers according to the order type, so that a target printer corresponding to the order type can be obtained, and the cloud server sends the printing content to the target printer, so that the target printer can finish printing the printing content.
Step S104, the target printer receives the printing content, analyzes the printing content, and obtains a first printing state corresponding to the printing content; performing a printing operation on the printing content to obtain a printing result corresponding to the printing content and a first printing time corresponding to the printing content; obtaining a printing image corresponding to the printing result; and sending the printed image, the first printing time and the first printing state to the cloud server.
Illustratively, the cloud server transmits the print content to the target printer in the form of text, images, or PDF. After receiving the print content, the target printer uses a built-in or external device (e.g., a computer) to perform content analysis on the print content. To obtain the color or number of sheets required for the print content, and thus to obtain whether the target printer can print with the print content supported, such as whether the sheets of the target printer are normal, whether the consumables are sufficient, etc., during the content analysis. Thereby determining a first print status of the target printer.
For example, when the target printer receives the print content, the receiving time of the currently received print content may be recorded, and further, after the printing operation of completing the print content is performed, the printing completion time may also be recorded, and then the first printing time corresponding to the print content may be obtained according to the printing completion time and the receiving time. Further, since the target printer may be currently executing other print contents, in order to ensure the accuracy of the first print time, a difference between the time at which the print contents start printing and the print completion time may be obtained, thereby determining the difference as the first print time. That is, the first printing time is the time that the target printer consumes to perform the printing operation on the print content.
Illustratively, the target printer will obtain the print result after completing the printing operation. And shooting the printing result by using the camera, so as to obtain a printing image corresponding to the printing result. After the print image, the first printing time and the first printing state are obtained, the print image, the first printing time and the first printing state are sent to the cloud server, so that the cloud server analyzes the running state of the target printer according to the content, and the normal running of the target printer is ensured.
In some embodiments, the target printer performs content analysis on the print content, and obtains a first print status corresponding to the print content, including: the target printer performs word segmentation processing on the printing content to obtain initial keywords corresponding to the printing content; the target printer analyzes the importance degree of the initial keywords in the printing content to obtain first weight information corresponding to the initial keywords; the target printer screens the initial keywords according to the first weight information to obtain target keywords; and the target printer is matched with the printing keywords corresponding to the target printer according to the target keywords, and the first printing state corresponding to the printing content is obtained.
The print content received by the target printer is subjected to word segmentation processing by using a word segmentation algorithm based on statistics or a word segmentation algorithm based on character string matching, and the like, the print content is divided into a plurality of words, and then deactivated words in the divided words are removed by using a deactivated word list, so that initial keywords are obtained.
Illustratively, the importance of each initial keyword in the print content is determined by analyzing the importance of the initial keyword in the print content according to a TF-IDF (Term Frequency-Inverse Document Frequency) algorithm, and then the weight of each initial keyword is obtained.
Illustratively, the initial keywords are filtered according to the calculated weight information, and the most representative target keywords are selected. There are various screening methods available based on the weights of keywords, the frequencies of keywords, and other natural language processing algorithms.
The target keyword is illustratively matched with a preset printing keyword of the target printer, so as to obtain a matching result, when the matching result is greater than or equal to the preset result, the target printer is determined to be matched with the printing content, that is, the first printing state is print matching, and when the matching result is less than the preset result, the target printer is determined to be not matched with the printing content, that is, the first printing state is print non-matching.
The first print state is used for representing whether the print content is matched with the target printer or not, namely, whether the print content is properly printed by the target printer or not is represented, so that when the mismatch is detected, the terminal device can be timely informed, and damage can be timely prevented.
For example, when a student prints a graduation paper scene, the student performs misoperation, so that the graduation paper is printed into a label format, and because the general content of the graduation paper is more, more paper or time is wasted when the graduation paper is in misoperation, even if a proper target printer is selected by a terminal device according to the order type, whether the printing content is matched with the target printer or not is checked again before or during printing of the target printer, so that the loss is reduced, and the purpose of timely stopping the loss is achieved.
In some embodiments, the target printer analyzes the importance degree of the initial keyword in the print content, and obtains first weight information corresponding to the initial keyword, including: the target printer obtains a history text, and obtains frequency information corresponding to the history text and the text quantity corresponding to the history text of the initial keyword; the target printer determines first weight information corresponding to the initial keyword according to the frequency information and the text quantity; wherein the first weight information is determined according to the following formula:
；
representing the first weight information corresponding to the ith initial keyword in the jth historical text; /(I) Representing frequency information of the ith initial keyword in the jth historical text; ndoc represents the total number of texts corresponding to the history text; /(I)And representing the text quantity corresponding to the ith initial keyword.
Illustratively, if a plurality of history texts are stored in the target printer, the number of texts corresponding to the history texts is accumulated when the frequency information and the frequency information corresponding to the initial keywords in each history text are greater than 0.
Illustratively, the first weight information corresponding to the initial keyword is determined according to the frequency information corresponding to the initial keyword and the number of texts corresponding to the initial keyword according to the following formula. Wherein,Representing first weight information corresponding to the ith initial keyword in the jth historical text; /(I)Representing the frequency information of the ith initial keyword in the jth historical text; ndoc represents the total number of texts corresponding to the history text; /(I)And representing the number of texts corresponding to the ith initial keyword.
；
For example, if the initial keywords include keyword 1, keyword 2, and keyword 3, the history text includes history text 1, history text 2, history text 3, and history text 30, it is known that the total number of texts ndoc corresponding to the history text is 30. The frequency information of the keyword 1 in the history text 1 is queried, and the number of texts of the keyword 1 occurring in 30 history texts is obtained, for example, the number of texts is 15 if the keyword 1 occurs in 15 history texts. And further obtaining first weight information corresponding to the initial keywords in each historical text according to the formula.
For example, after the first weight information corresponding to the initial keyword in each history text is obtained, a sum of the first weight information corresponding to the initial keyword may be obtained, so that the initial keyword is filtered according to the size of the sum of the weight information, and thus the target keyword is obtained.
In some embodiments, the target printer matches the target keyword with a print keyword corresponding to the target printer, to obtain the first print state corresponding to the print content, including: the target printer obtains a standard text corresponding to the target printer, and obtains second weight information corresponding to the standard text of the target keyword and third weight information corresponding to the standard text of the printing keyword; the target printer determines distance information between the target keyword and the printing keyword according to the second weight information and the third weight information; the target printer compares the distance information with a preset distance to determine the association state between the target keyword and the printing keyword; and the target printer determines the first printing state corresponding to the printing content according to the association state.
The target printer is provided with a standard text corresponding to the text print type, and then second weight information corresponding to the target keyword in the standard text is calculated according to the following formula, and third weight information corresponding to the print keyword in the standard text is calculated according to the following formula.
；
Representing second weight information corresponding to the mth target keyword or the printing keyword in the t standard text; /(I)Representing the frequency information of the mth target keyword or the printing keyword in the t standard text; doc represents the total number of texts corresponding to the standard; /(I)And representing the number of texts corresponding to the mth target keyword or the printing keyword.
Illustratively, the target printer calculates distance information between the keywords based on the blur granularity after obtaining the second weight information corresponding to the target keyword and the third weight information corresponding to the print keyword. The distance information is calculated by the following formula:
；
wherein, Representing the a-th target keyword,/>Represents the b-th print keyword, k represents the k-th standard text, n represents the total number of standard texts,/>Second weight information indicating correspondence of the a-th target keyword in the kth standard text,Third weight information representing the correspondence of the b-th target keyword in the kth standard text,/>Distance information between the a-th target keyword and the b-th print keyword is represented.
The method includes the steps that after distance information between a target keyword and a printing keyword is obtained, the printing keyword corresponding to the minimum value of the distance information between the target keyword and the printing keyword is used as an associated word corresponding to the target keyword, the minimum value is used as a target distance corresponding to the target keyword, the target distance is compared with a preset distance, when the target distance is smaller than or equal to the preset distance, the associated state corresponding to the target keyword and the associated word is determined to be a similar word, and when the target distance is larger than the preset distance, the associated state corresponding to the target keyword and the associated word is determined to be a non-similar word, and then the associated state between each target keyword and the printing keyword is obtained.
Illustratively, after obtaining the association states between the respective target keywords and the print keywords, the target printer determines a first print state corresponding to the print content according to the number of the similar words corresponding in the association states. When the number of the corresponding similar words in the associated state is larger than the preset number, the first printing state corresponding to the printing content is the printing related state, namely, the printing content is the printing type of the target printer. When the number of the similar words in the associated state is smaller than or equal to the preset number, the first printing state corresponding to the printing content is in a printing irrelevant state, namely, the printing content is not the printing type of the target printer, and the printing content of the target printer is abnormal.
Step 105, the cloud server receives the print image, the first printing time and the first printing state, predicts the time of the print content, obtains a second printing time corresponding to the print content, and determines a second printing state corresponding to the target printer according to the first printing time and the second printing time; performing image analysis according to the print image to obtain a third print state corresponding to the target printer; determining a target printing state corresponding to the target printer according to the first printing state, the second printing state and the third printing state, and determining a processing strategy corresponding to the target printer according to the target printing state; and sending the processing strategy to the terminal equipment.
After receiving the print image, the first printing time and the first printing state sent by the target printer, the cloud server may directly determine that the target printing state is abnormal for selecting the printer according to the first printing state when the first printing state is in a printing irrelevant state, further determine whether the processing policy corresponding to the target printer reminds the user to reselect the printing type for reprinting, continue to execute printing, and so on according to the target printing state, and further send the processing policy to the terminal device.
After receiving the print image, the first print time and the first print state sent by the target printer, the cloud server performs time prediction on the print content when the first print state is a print-related state, and obtains a second print time corresponding to the print content.
For example, the print content is time-predicted using the time prediction model, thereby obtaining a second print time corresponding to the print content. The time prediction model is to establish a regression model according to the historical printing content and the historical printing time corresponding to the historical printing content, so that after the printing content is obtained, the printing content is input into the time prediction model, and the second printing time corresponding to the printing content is obtained.
Illustratively, after the second printing time is obtained, calculating a difference between the first printing time and the second printing time, and when the difference is smaller than or equal to a preset value, determining that the second printing state corresponding to the target printer is a printing time normal state; and when the difference value is larger than the preset value, determining that the second printing state corresponding to the target printer is the abnormal printing time state.
The cloud server receives the print image, performs quality analysis on the print image, and determines a third print state corresponding to the target printer according to a quality analysis result, and determines that the third print state corresponding to the target printer is a print quality normal state when the quality analysis result meets a preset quality; and when the quality analysis result does not meet the preset quality, determining that the third printing state corresponding to the target printer is the printing quality abnormal state.
In some embodiments, the cloud server performs time prediction on the print content to obtain a second print time corresponding to the print content, including: the cloud server constructs a stroke pattern, wherein the stroke pattern comprises characters, character strokes corresponding to the characters and corresponding relations between the characters and the character strokes; the cloud server inputs each print word in the print content to the stroke pattern to search information, and a target stroke corresponding to the print word and a target relation between the target strokes are obtained; the cloud server determines single word printing time corresponding to the printed text according to the target stroke and the target relation; and the cloud server determines the second printing time corresponding to the printing content according to the single-word printing time.
The existing character stroke data set is collected, or a stroke map is constructed on the cloud server by using a character body library, a character form description and the like, wherein the stroke map comprises characters, character strokes corresponding to the characters and corresponding relations between the characters and the character strokes.
Illustratively, each printed text in the print is entered into a stroke graph for information lookup. For example, the corresponding target stroke is found by matching the entered text with the text in the stroke pattern.
Illustratively, after the target strokes are found in the stroke atlas, target relationships between the target strokes may be further determined, the target relationships including, but not limited to, precedence relationships, inclusion relationships, surrounding relationships, semi-surrounding relationships, and the like.
Illustratively, the printing time corresponding to the correspondence between each of the strokes is predefined, and the single-word printing time corresponding to the printed text is determined according to the target stroke and the target relationship. The printing time may be adjusted and optimized in view of the speed of the printer and other relevant factors. And according to the single-word printing time, the second printing time of the whole printing content is calculated by combining the printing sequence of each word in the printing content.
In some embodiments, the cloud server determining the second printing time corresponding to the printing content according to the single-word printing time includes: the cloud server determines a third printing time corresponding to the printing content according to the single-word printing time; the cloud server obtains a history request and obtains corresponding history content according to the history request; the cloud server performs text clustering according to the historical content and the printing content to obtain a text clustering result; the cloud server obtains a text cluster corresponding to the printing content according to the text clustering result, and obtains an associated text corresponding to the printing content according to the text cluster; the cloud server obtains a third printing time corresponding to the associated text, and performs average value processing on the third printing time to obtain a fourth printing time corresponding to the printing content; and the cloud server determines the second printing time corresponding to the printing content according to the third printing time and the fourth printing time.
Illustratively, the cloud server obtains the history request corresponding to the history record and the history content corresponding to the history request through inquiring in the log record or the database. And further, using a clustering algorithm (such as K-means, hierarchical clustering and the like) to perform text clustering on the acquired historical content and the new printing content, and obtaining a text clustering result.
Illustratively, the text class cluster to which the print content belongs is determined according to the result of the text clustering. So that other text associated with the print content can be found. And obtaining the associated text corresponding to the printing content, and further obtaining a third printing time corresponding to the associated text after obtaining the associated text. This may be a third print time in the history that is related to the associated text. And performing average processing on the acquired third printing time to obtain a fourth printing time corresponding to the printing content.
Illustratively, a method such as weighted average or linear difference is performed on the third printing time and the fourth printing time, so as to determine the second printing time of the print content.
Specifically, by calculating the individual word printing time and determining the second printing time, the printing time can be calculated more accurately, thereby improving the printing efficiency. In addition, through text clustering and associated text query, other texts related to the printing content can be found, so that the printing time is adjusted, and the printing accuracy is improved. And then, by accurately calculating the printing time, good support is provided for the subsequent judgment of whether the printing time of the target printer is normal or not.
In some embodiments, the cloud server performs text clustering according to the historical content and the print content to obtain a text clustering result, including: the cloud server classifies the text types of the historical content to obtain first probability distribution corresponding to the historical content; the cloud server classifies the text types of the printing content to obtain a second probability distribution corresponding to the printing content; the cloud server calculates relative entropy according to the first probability distribution and the second probability distribution, and obtains entropy values between the first probability distribution and the second probability distribution; the cloud server obtains initial clustering number corresponding to the text clustering according to the first probability distribution, and obtains credibility corresponding to the initial clustering number according to the initial clustering number and the entropy value; when the reliability is detected to be smaller than or equal to a preset value by the cloud server, updating a first probability distribution corresponding to the historical content, a second probability distribution corresponding to the printing content and the initial clustering number corresponding to the first probability distribution, and recalculating the reliability corresponding to the updated initial clustering number according to the updated first probability distribution and the updated second probability distribution; when the cloud server detects that the credibility is larger than a preset value, obtaining the target clustering number corresponding to the text clustering according to the initial clustering number; and the cloud server performs text clustering on the historical content and the printing content according to the target clustering number, so that a text clustering result is obtained.
Illustratively, the historical content is subjected to text type classification by using a proper text classification algorithm (such as naive Bayes, support vector machines and the like), so as to obtain a first probability distribution corresponding to the historical content. And classifying the printing content by using the same method, and further obtaining a second probability distribution corresponding to the printing content. Based on the first probability distribution and the second probability distribution, a relative entropy between the two probability distributions is calculated. The relative entropy can be used to measure the difference between two probability distributions.
The first probability distribution is distributed correspondingly, the initial clustering number corresponding to the text clustering is determined, and the credibility of the initial clustering number is calculated according to the entropy value. The reliability corresponding to the initial cluster number can be calculated according to the following formula:
；
wherein k represents the initial cluster number, M (k) represents the credibility corresponding to the initial cluster number, Entropy value representing between probability of ith class in first probability distribution and probability of jth class in second probability distribution,/>And representing the entropy value between the probability of the ith category in the first probability distribution and the probability distribution mean value corresponding to the first probability distribution.
Illustratively, after the credibility corresponding to the initial clustering number is obtained, the credibility is compared with a preset value, and when the credibility is smaller than or equal to the preset value, the first probability distribution corresponding to the historical content, the second probability distribution corresponding to the printing content and the initial clustering number corresponding to the first probability distribution can be updated according to gradient descent, genetic algorithm and the like. And further, according to the updated first probability distribution and the updated second probability distribution, the reliability of the initial clustering number is recalculated. And when the reliability is larger than a preset value, determining the initial cluster number as the target cluster number corresponding to the text clusters. And further, after the target clustering number is obtained, text clustering is carried out on the historical content and the printing content by utilizing the target clustering number, and a corresponding text clustering result is obtained.
Specifically, the cloud server can dynamically update the probability distribution and the initial cluster number according to the comparison of the reliability and the preset value, and recalculate the reliability. This enables the system to optimize itself in real time, adapting to changing data and demand environments. When the reliability reaches a preset value, the target cluster number can be determined according to the initial cluster number. This facilitates more accurate text clustering, providing more rational and targeted results. This may provide more accurate, efficient and intelligent support for subsequent anomaly identification.
In some embodiments, the cloud server performs text clustering according to the historical content and the print content, and before obtaining a text clustering result, the method further includes: the cloud server calculates the similarity between the historical content and the printing content, and obtains a similarity value between the historical content and the printing content: and the cloud server screens the historical content according to the similarity value to obtain the screened historical content.
Illustratively, similarity between the history content and the print content is compared using a similarity calculation method (such as cosine similarity, edit distance, etc.), thereby obtaining a similarity value. Based on the similarity value, a threshold value, such as a similarity threshold value, may be set, and only the history content having a similarity with the print content higher than the threshold value is retained.
Illustratively, the historical content and the print content are converted into a digitized representation. Text may be converted to a vector representation using text embedding algorithms (e.g., word embedding, bert, etc.), or feature vectors may be extracted using conventional text feature extraction methods (e.g., word bag model, TF-IDF, etc.). According to the selected text representing method, a similarity value between the history content and the print content is calculated using a corresponding similarity calculating method. For example, for vector representation, cosine similarity may be used to calculate the similarity between two vectors. And setting a proper similarity threshold according to the requirements and the actual conditions. The threshold value should be adjusted according to the actual situation to ensure that the screened historical content meets the expected similarity requirement. And comparing the similarity between the historical content and the printing content according to the similarity threshold value, and only retaining the historical content with the similarity higher than the threshold value. An appropriate data structure (e.g., list, collection, etc.) may be selected to store and manage the filtered historical content.
In some embodiments, the cloud server performs image analysis according to the print image to obtain a third print state corresponding to the target printer, including: the cloud server performs chromaticity analysis on the printed image to obtain chromaticity distribution corresponding to the printed image; the cloud server determines a chromaticity state corresponding to the printed image according to the chromaticity distribution; the cloud server carries out text recognition on the printed image to obtain recognition probabilities corresponding to all characters in the printed image; the cloud server determines a display state corresponding to the print image according to the identification probability; and determining a third printing state corresponding to the target printer according to the chromaticity state and the display state.
Illustratively, the image processing technique is used to perform chromaticity analysis on the printed image, and chromaticity information is extracted therefrom to obtain chromaticity distribution corresponding to the printed image. The color space conversion may be used to extract the chrominance information or the analysis may be performed using image histogram or the like. From the resulting chromaticity distribution, the chromaticity state corresponding to the print image can be determined from the set threshold or the comparison distribution characteristics. For example, if the chromaticity distribution is concentrated within a certain specific range, the chromaticity state may be determined.
Illustratively, text recognition is performed on the printed image using OCR technology (Optical Character Recognition ) to convert text in the image into recognizable text. Text recognition may be performed using existing OCR libraries or services, such as TESSERACT, google Cloud Vision, etc. And obtaining the recognition probability corresponding to each text through the text recognition result. These probabilities represent the confidence of the recognition result and may reflect the confidence level of each word. Based on the recognition probability, a threshold value may be set, and characters having a probability higher than the threshold value may be judged as correctly recognized, and characters having a probability lower than the threshold value may be judged as incorrectly recognized. Based on the correct and incorrect ratios, the display state corresponding to the print image can be determined.
Illustratively, from the resulting chromaticity state and display state, a target print state corresponding to the print image may be determined. For example, if the chromaticity state is normal and the display state is correct, it can be determined that the target print state is normal.
In some embodiments, the cloud server determines, according to the identification probability, a display state corresponding to the print image, including: the cloud server determines a target probability and a target accumulated value, compares the target probability with the identification probability, and updates the target accumulated value when the target probability is smaller than or equal to the identification probability; and the cloud server determines the display state corresponding to the printed image according to the target accumulated value.
Illustratively, a target probability and an initial target cumulative value are set before processing of the print image is started. The target probability may be a fixed value or determined from previous analysis and testing. The initial target cumulative value may be zero or a suitable initial value. And comparing the target probability with the identification probability. If the target probability is smaller than or equal to the recognition probability, the current recognition probability reaches or exceeds the set target requirement. If the target probability is less than or equal to the recognition probability, the target accumulated value is updated. The target cumulative value may be set to the difference of the current target cumulative value plus the recognition probability. This difference may be the absolute difference between the two or a suitable value determined according to the actual requirements. According to the magnitude of the target accumulated value, the display state corresponding to the print image can be determined. The display state can be classified into normal and abnormal. If the target accumulated value is greater than or equal to a set threshold value, judging the abnormal display state, otherwise judging the normal display state.
Illustratively, the first print state is used to characterize whether the print content matches the target printer, the second print state is used to characterize whether the print time of the target printer is abnormal, and the third print state is used to characterize whether the print quality of the target printer is abnormal. Therefore, when any printing state is abnormal, a matched processing strategy is selected and sent to the terminal equipment, and the terminal equipment further maintains the target printer according to the processing strategy.
For example, different processing strategies may be set for different exception cases, and several common processing strategies are given below: when the print content does not match the target printer: whether to match the target printer can be determined by checking information such as the file type, format, etc. of the print content. If there is no match, the user may be prompted to reselect the printer or to convert the file format. In addition, the printing driver can perform self-adaptive printing adjustment, so that the printing content can be adapted to the characteristics and parameters of the target printer. When the printing time of the target printer is abnormal: an attempt may be made to restart the target printer or to check whether the printer connection is normal. If the problem can not be solved, the user can be prompted to replace the target printer and be reminded to contact related personnel for maintenance. When the print quality of the target printer is abnormal: print quality parameters, such as color, resolution, brightness, etc., may be adjusted by printer control commands to accommodate different print requirements. In addition, cleaning or replacement of the print head can be performed to improve print quality. If the problem cannot be solved, the user may be prompted to replace the target printer or adjust the print quality parameters.
It should be noted that the specific processing strategy should be selected according to the actual situation and requirement, and actual testing and evaluation should be performed to determine the effect and feasibility thereof. Meanwhile, when the processing strategy is realized, the factors such as safety, stability and usability are also required to be considered, so that various requirements and demands of users can be met.
And step S106, the terminal equipment receives the processing strategy and maintains the target printer according to the processing strategy so as to enable the target printer to normally operate.
Illustratively, the terminal device receives the processing policy so that the user can perform maintenance on the target printer according to the processing policy, thereby ensuring that the target printer operates normally. And then, the problem that in the related art, along with the increase and the diversification of the number of the cloud printing devices, when the cloud printing devices are abnormal, a user cannot timely find the abnormality to maintain, and then the printing efficiency is affected is solved.
The embodiment of the invention also provides a storage medium for computer readable storage, wherein the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors, so as to realize the steps of any cloud printer abnormal state identification maintenance management system provided by the embodiment specification of the invention.
The storage medium may be an internal storage unit of the terminal device or the cloud server or the printer according to the foregoing embodiment, for example, a hard disk or a memory of the terminal device or the cloud server or the printer. The storage medium may also be an external storage device of the terminal device or the cloud server or the printer, such as a plug-in hard disk provided on the terminal device or the cloud server or the printer, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD), or the like.
Those of ordinary skill in the art will appreciate that all or some of the steps, systems, functional modules/units in the apparatus, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware embodiment, the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed cooperatively by several physical components. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
It should be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments. While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (8)
1. A cloud printer abnormal state identification maintenance management system is characterized by comprising a cloud server, a printer in communication connection with the cloud server and terminal equipment in communication connection with the cloud server,
The terminal equipment sends an order request to the cloud server;
the cloud server receives the order request, analyzes the order request and obtains an order type corresponding to the order request and print content corresponding to the order request;
the cloud server determines a target printer corresponding to the order request from the printers according to the order type, and sends the printing content to the target printer;
The target printer receives the printing content, analyzes the printing content, and obtains a first printing state corresponding to the printing content; performing a printing operation on the printing content to obtain a printing result corresponding to the printing content and a first printing time corresponding to the printing content; obtaining a printing image corresponding to the printing result; transmitting the printed image, the first printing time and the first printing state to the cloud server;
the cloud server receives the print image, the first printing time and the first printing state, predicts the time of the print content, obtains second printing time corresponding to the print content, and determines the second printing state corresponding to the target printer according to the first printing time and the second printing time; performing image analysis according to the print image to obtain a third print state corresponding to the target printer; determining a target printing state corresponding to the target printer according to the first printing state, the second printing state and the third printing state, and determining a processing strategy corresponding to the target printer according to the target printing state; transmitting the processing strategy to the terminal equipment;
The terminal equipment receives the processing strategy and maintains the target printer according to the processing strategy so that the target printer normally operates;
the target printer performs content analysis on the print content and obtains a first print state corresponding to the print content, including:
the target printer performs word segmentation processing on the printing content to obtain initial keywords corresponding to the printing content;
The target printer analyzes the importance degree of the initial keywords in the printing content to obtain first weight information corresponding to the initial keywords;
The target printer screens the initial keywords according to the first weight information to obtain target keywords;
The target printer is matched with the printing keywords corresponding to the target printer according to the target keywords, and the first printing state corresponding to the printing content is obtained;
the target printer analyzes the importance degree of the initial keyword in the printing content to obtain first weight information corresponding to the initial keyword, and the first weight information comprises:
the target printer obtains a history text, and obtains frequency information corresponding to the history text and the text quantity corresponding to the history text of the initial keyword;
The target printer determines first weight information corresponding to the initial keyword according to the frequency information and the text quantity;
Wherein the first weight information is determined according to the following formula:
；
representing the first weight information corresponding to the ith initial keyword in the jth historical text; /(I) Representing frequency information of the ith initial keyword in the jth historical text; ndoc represents the total number of texts corresponding to the history text; /(I)And representing the text quantity corresponding to the ith initial keyword.
2. The system of claim 1, wherein the target printer obtains the first print status corresponding to the print content according to matching the target keyword with a print keyword corresponding to the target printer, comprising:
The target printer obtains a standard text corresponding to the target printer, and obtains second weight information corresponding to the standard text of the target keyword and third weight information corresponding to the standard text of the printing keyword;
the target printer determines distance information between the target keyword and the printing keyword according to the second weight information and the third weight information;
the target printer compares the distance information with a preset distance to determine the association state between the target keyword and the printing keyword;
and the target printer determines the first printing state corresponding to the printing content according to the association state.
3. The system of claim 1, wherein the cloud server performs a time prediction on the print content to obtain a second print time corresponding to the print content, comprising:
The cloud server constructs a stroke pattern, wherein the stroke pattern comprises characters, character strokes corresponding to the characters and corresponding relations between the characters and the character strokes;
the cloud server inputs each print word in the print content to the stroke pattern to search information, and a target stroke corresponding to the print word and a target relation between the target strokes are obtained;
the cloud server determines single word printing time corresponding to the printed text according to the target stroke and the target relation;
and the cloud server determines the second printing time corresponding to the printing content according to the single-word printing time.
4. The system of claim 3, wherein the cloud server determining the second printing time corresponding to the print content from the single word printing time comprises:
The cloud server determines a third printing time corresponding to the printing content according to the single-word printing time;
the cloud server obtains a history request and obtains corresponding history content according to the history request;
the cloud server performs text clustering according to the historical content and the printing content to obtain a text clustering result;
The cloud server obtains a text cluster corresponding to the printing content according to the text clustering result, and obtains an associated text corresponding to the printing content according to the text cluster;
The cloud server obtains a third printing time corresponding to the associated text, and performs average value processing on the third printing time to obtain a fourth printing time corresponding to the printing content;
And the cloud server determines the second printing time corresponding to the printing content according to the third printing time and the fourth printing time.
5. The system of claim 4, wherein the cloud server performs text clustering according to the history content and the print content to obtain a text clustering result, comprising:
The cloud server classifies the text types of the historical content to obtain first probability distribution corresponding to the historical content;
the cloud server classifies the text types of the printing content to obtain a second probability distribution corresponding to the printing content;
the cloud server calculates relative entropy according to the first probability distribution and the second probability distribution, and obtains entropy values between the first probability distribution and the second probability distribution;
The cloud server obtains initial clustering number corresponding to the text clustering according to the first probability distribution, and obtains credibility corresponding to the initial clustering number according to the initial clustering number and the entropy value;
When the reliability is detected to be smaller than or equal to a preset value by the cloud server, updating a first probability distribution corresponding to the historical content, a second probability distribution corresponding to the printing content and the initial clustering number corresponding to the first probability distribution, and recalculating the reliability corresponding to the updated initial clustering number according to the updated first probability distribution and the updated second probability distribution;
When the cloud server detects that the credibility is larger than a preset value, obtaining the target clustering number corresponding to the text clustering according to the initial clustering number;
and the cloud server performs text clustering on the historical content and the printing content according to the target clustering number, so that a text clustering result is obtained.
6. The system of claim 4, wherein the cloud server performs text clustering according to the history content and the print content, and further comprising, before obtaining a text clustering result:
the cloud server calculates the similarity between the historical content and the printing content, and obtains a similarity value between the historical content and the printing content:
and the cloud server screens the historical content according to the similarity value to obtain the screened historical content.
7. The system of claim 1, wherein the cloud server performing image analysis according to the print image to obtain a third print state corresponding to the target printer, comprises:
The cloud server performs chromaticity analysis on the printed image to obtain chromaticity distribution corresponding to the printed image;
The cloud server determines a chromaticity state corresponding to the printed image according to the chromaticity distribution;
The cloud server carries out text recognition on the printed image to obtain recognition probabilities corresponding to all characters in the printed image;
the cloud server determines a display state corresponding to the print image according to the identification probability;
And determining a third printing state corresponding to the target printer according to the chromaticity state and the display state.
8. The system of claim 7, wherein the cloud server determining a display state corresponding to the print image according to the recognition probability comprises:
the cloud server determines a target probability and a target accumulated value, compares the target probability with the identification probability, and updates the target accumulated value when the target probability is smaller than or equal to the identification probability;
And the cloud server determines the display state corresponding to the printed image according to the target accumulated value.
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| CN110147211A (en) * | 2019-05-23 | 2019-08-20 | 宜春宜联科技有限公司 | Print control program, terminal integrative machine and print system |
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