CN118071334A

CN118071334A - Licorice tablet preparation equipment operation and maintenance method and system based on Internet of things

Info

Publication number: CN118071334A
Application number: CN202410481144.7A
Authority: CN
Inventors: 思希军
Original assignee: Jingbian Tianrun Agricultural Technology Co ltd
Current assignee: Jingbian Tianrun Agricultural Technology Co ltd
Priority date: 2024-04-22
Filing date: 2024-04-22
Publication date: 2024-05-24
Anticipated expiration: 2044-04-22

Abstract

The invention relates to the technical field of operation and maintenance of traditional Chinese medicine preparation equipment, in particular to an operation and maintenance method and system of liquorice tablet preparation equipment based on the Internet of things. Performing preliminary judgment and analysis on each key monitoring component according to the standard abrasion state three-dimensional model diagram and the actual abrasion state three-dimensional model diagram; if a certain key monitoring part is a normal part in a wearing state, marking the key monitoring part as a part capable of continuing to be in service; if a certain key monitoring part is an abnormal part in the abrasion state, further analyzing the key monitoring part; if a certain key monitoring part is a part which can continue to be in service, continuously monitoring the key monitoring part; if a certain key monitoring part is a part which can not be continuously serviced, a recommended operation and maintenance scheme of the key monitoring part is generated.

Description

Licorice tablet preparation equipment operation and maintenance method and system based on Internet of things

Technical Field

The invention relates to the technical field of operation and maintenance of traditional Chinese medicine preparation equipment, in particular to an operation and maintenance method and system of liquorice tablet preparation equipment based on the Internet of things.

Background

Licorice is a common Chinese herbal medicine and has various medicinal values, such as anti-inflammatory, antiviral, antiallergic and the like. The licorice tablet is a tablet product prepared from the roots or stems of licorice through processing, and is convenient to store and use. The licorice root or stem can be processed into the licorice root tablet by the licorice tablet preparation equipment, and in the actual working process of the licorice tablet preparation equipment, the problems of abrasion, aging and the like of part of components possibly occur along with the increase of the service time of the equipment, so that the operation efficiency is reduced and the maintenance cost is increased, and in order to keep the efficient operation of the equipment, the equipment needs to be checked and maintained regularly. At present, equipment is maintained and checked manually, however, the operation and maintenance of the liquorice piece preparation equipment need a certain skill and experience, and operators need professional training to be able to master the using method and maintenance skill of the equipment; and with the introduction of new technology and the updating of equipment, operators need to constantly learn to adapt to new equipment and technology, so that the operation and maintenance cost of the equipment is greatly increased, the operation and maintenance effect is influenced by personal factors, and great subjectivity is generated, so that the operation and maintenance of the liquorice piece preparation equipment through manual experience has certain limitations and defects. In order to improve the operation and maintenance effect and the production efficiency, an operation and maintenance method adopting automation, intellectualization and standardization needs to be developed, and professional knowledge and technical support are combined to ensure the stable operation of equipment and the quality of products.

Disclosure of Invention

The invention overcomes the defects of the prior art and provides an operation and maintenance method and system for liquorice tablet preparation equipment based on the Internet of things.

The technical scheme adopted by the invention for achieving the purpose is as follows:

The invention discloses an operation and maintenance method of licorice tablet preparation equipment based on the Internet of things, which comprises the following steps:

acquiring total labor time information of the licorice tablet preparation equipment, and determining key monitoring components in the licorice tablet preparation equipment according to the total labor time information;

Acquiring a standard wear state three-dimensional model diagram and an actual wear state three-dimensional model diagram of each key monitoring part, performing preliminary judgment and analysis on each key monitoring part according to the standard wear state three-dimensional model diagram and the actual wear state three-dimensional model diagram, and analyzing whether the key monitoring part is a normal wear state part or an abnormal wear state part;

If a certain key monitoring part is a normal part in a wearing state, marking the key monitoring part as a part capable of continuing to be in service; if a certain key monitoring part is an abnormal part in the abrasion state, further analyzing the key monitoring part to analyze whether the key monitoring part is a part which can be continuously serviced or a part which cannot be continuously serviced;

If a certain key monitoring part is a part which can continue to be in service, continuously monitoring the key monitoring part; if a certain key monitoring component is a component which can not be continuously serviced, generating a recommended operation and maintenance scheme of the key monitoring component, and pushing the recommended operation and maintenance scheme to a preset platform through the Internet of things.

Further, in a preferred embodiment of the present invention, total time of labor information of the licorice tablet preparation device is obtained, and key monitoring components in the licorice tablet preparation device are determined according to the total time of labor information, specifically:

Acquiring functional characteristic information of each part in the licorice tablet preparation equipment, and determining the parts easy to wear in the licorice tablet preparation equipment according to the functional characteristic information;

Acquiring operation log information of the licorice tablet preparation equipment, and acquiring total labor time information of the licorice tablet preparation equipment according to the operation log information;

the predicted abrasion loss of the easily-abraded part in the liquorice piece preparation equipment is obtained according to the total labor time information in an estimated mode; presetting a wear threshold of each easily-worn part;

comparing the predicted wear amount of each of the easily worn components to a corresponding wear amount threshold; if the predicted wear amount of one of the easily worn components is greater than the corresponding wear amount threshold, the easily worn component is marked as an important monitoring component.

Further, in a preferred embodiment of the present invention, a standard wear state three-dimensional model diagram and an actual wear state three-dimensional model diagram of each key monitoring component are obtained, and preliminary judgment analysis is performed on each key monitoring component according to the standard wear state three-dimensional model diagram and the actual wear state three-dimensional model diagram, so as to analyze whether the key monitoring component is a normal wear state component or an abnormal wear state component, specifically:

Prefabricating a standard abrasion state three-dimensional model diagram corresponding to each abrasion-prone part in the liquorice piece preparation equipment in advance in different working time stages; constructing a knowledge graph, and importing a standard abrasion state three-dimensional model graph corresponding to each abrasion part in different working time stages into the knowledge graph;

Acquiring each key monitoring component in the liquorice piece preparation equipment and acquiring the total labor time information of each key monitoring component; pairing the information of the total labor time of each key monitoring part in the knowledge graph to obtain a standard abrasion state three-dimensional model diagram of each key monitoring part;

scanning each key monitoring part through an industrial CT scanner, collecting scanning data, and constructing an actual abrasion state three-dimensional model diagram of each key monitoring part according to the scanning data and combining industrial three-dimensional software;

calculating the similarity between the actual abrasion state three-dimensional model diagram of each key monitoring part and the corresponding standard abrasion state three-dimensional model diagram through a cosine similarity algorithm;

If the similarity between the actual abrasion state three-dimensional model diagram of a certain key monitoring part and the corresponding standard abrasion state three-dimensional model diagram is larger than the preset similarity, marking the key monitoring part as an abrasion state normal part;

And if the similarity between the actual wear state three-dimensional model diagram of a certain key monitoring part and the corresponding standard wear state three-dimensional model diagram is not greater than the preset similarity, marking the key monitoring part as an abnormal wear state part.

Further, in a preferred embodiment of the present invention, if a certain key monitoring component is an abnormal component in a wear state, the key monitoring component is further analyzed to determine whether the key monitoring component is a component that can be continuously serviced or a component that cannot be continuously serviced, specifically:

if a certain key monitoring part is an abnormal part in the abrasion state, acquiring a standard abrasion state three-dimensional model diagram and an actual abrasion state three-dimensional model diagram of the key monitoring part;

Constructing a three-dimensional coordinate system, and importing a standard abrasion state three-dimensional model diagram and an actual abrasion state three-dimensional model diagram of the key monitoring component into the three-dimensional coordinate system;

Retrieving the assembly reference surfaces of the standard wear state three-dimensional model diagram and the actual wear state three-dimensional model diagram in the three-dimensional coordinate system, and enabling the assembly reference surfaces of the two three-dimensional model diagrams to coincide with each other so as to align the standard wear state three-dimensional model diagram and the actual wear state three-dimensional model diagram;

removing model parts, which are overlapped with the standard abrasion state three-dimensional model diagram and the actual abrasion state three-dimensional model diagram, from the three-dimensional coordinate system, and storing model parts which are not overlapped with each other to obtain an abrasion state deviation model diagram;

Calculating the volume value of the abrasion state deviation model diagram based on a gridding method in the three-dimensional coordinate system to obtain the actual abrasion loss of the key monitoring part; presetting a second abrasion loss threshold value of the key monitoring part; comparing the actual wear of the key monitoring component with a second wear threshold;

And if the actual abrasion loss of the key monitoring part is larger than the second abrasion loss threshold value, marking the key monitoring part as a part which can not be continuously serviced.

Further, in a preferred embodiment of the present invention, the method further comprises the steps of:

If the actual abrasion loss of the key monitoring part is not greater than the second abrasion loss threshold value, acquiring crack characteristic data of the key monitoring part according to the three-dimensional model diagram of the actual abrasion loss of the key monitoring part; wherein the crack characteristic data comprises a crack position, a crack length, a crack width and a crack depth;

calculating to obtain a total crack volume value of the key monitoring part according to the crack characteristic data, and calculating to obtain a total volume value of the key monitoring part according to the actual abrasion state three-dimensional model diagram; performing ratio processing on the total crack volume value and the total volume value to obtain the crack concentration of the key monitoring part;

Judging whether the crack concentration is larger than a preset concentration or not; if the service life of the key monitoring part is larger than the service life of the key monitoring part, marking the key monitoring part as a part which can not continue to be serviced;

If the actual abrasion state three-dimensional model diagram of the key monitoring component is not larger than the actual abrasion state three-dimensional model diagram, finite element analysis is carried out on the actual abrasion state three-dimensional model diagram of the key monitoring component, and a simulated internal stress value of the key monitoring component is obtained; obtaining the limit internal stress value which can be born by the key monitoring component according to the material performance and the design standard of the key monitoring component;

comparing the simulated internal stress value of the key monitoring part with the limit internal stress value which can be born; if the simulated internal stress value of the key monitoring part is larger than the bearable limit internal stress value, marking the key monitoring part as a part which can not be continuously serviced;

and if the simulated internal stress value of the key monitoring part is not greater than the bearable limit internal stress value, marking the key monitoring part as a part which can be continuously serviced.

Further, in a preferred embodiment of the present invention, if a certain key monitoring component is a component that cannot be continuously serviced, a recommended operation and maintenance scheme of the key monitoring component is generated, and the recommended operation and maintenance scheme is pushed to a preset platform through the internet of things, specifically:

acquiring operation and maintenance log information of the same type of licorice tablet preparation equipment in a production workshop based on an Internet of things mode, and acquiring a plurality of historical operation and maintenance schemes according to the operation and maintenance log information;

The method comprises the steps of obtaining model information of parts maintained by each historical operation and maintenance scheme, judging whether the model information of the parts maintained by each historical operation and maintenance scheme is the same as the model information of the parts which cannot be continuously serviced one by one, and if the model information of the parts are different from the model information of the parts which cannot be continuously serviced one by one, removing the corresponding historical operation and maintenance scheme to obtain the residual historical operation and maintenance scheme;

Acquiring maintenance time required by maintaining the licorice tablet preparation equipment through each remaining historical operation and maintenance scheme according to the operation and maintenance log information;

Constructing a size sorting table, inputting maintenance time required by maintaining the liquorice piece preparation equipment through each remaining historical operation and maintenance scheme into the size sorting table for size sorting, obtaining a sorting result, and extracting the shortest maintenance time from the sorting result;

and marking the residual historical operation and maintenance scheme corresponding to the shortest maintenance time as a recommended operation and maintenance scheme, and pushing the recommended operation and maintenance scheme to a preset platform through the Internet of things.

The invention discloses a licorice tablet preparation equipment operation and maintenance system based on the Internet of things, which comprises a memory and a processor, wherein a licorice tablet preparation equipment operation and maintenance method program is stored in the memory, and when the licorice tablet preparation equipment operation and maintenance method program is executed by the processor, the following steps are realized:

The invention solves the technical defects existing in the background technology, and has the following beneficial effects: the method can evaluate the abrasion state of the easily-abraded part more accurately by detecting and analyzing the easily-abraded part in the liquorice piece preparation equipment, thereby providing basis for equipment maintenance and replacement; and the potential problems of the parts can be found in time, the parts easy to wear can be replaced or repaired in advance, equipment faults and production interruption caused by serious wear are avoided, production accidents caused by the damage of the parts can be prevented, and the operation safety of the equipment is improved.

Drawings

In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other embodiments of the drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of the overall method of operation and maintenance of a licorice tablet manufacturing device based on the Internet of things;

FIG. 2 is a partial flow chart of an operation and maintenance method of a licorice tablet preparation device based on the Internet of things;

fig. 3 is a system block diagram of an operation and maintenance system of a licorice tablet preparation device based on the internet of things.

Detailed Description

In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present application and features in the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.

As shown in fig. 1, the first aspect of the present invention discloses an operation and maintenance method for a licorice tablet preparation device based on the internet of things, comprising the following steps:

s102: acquiring total labor time information of the licorice tablet preparation equipment, and determining key monitoring components in the licorice tablet preparation equipment according to the total labor time information;

S104: acquiring a standard wear state three-dimensional model diagram and an actual wear state three-dimensional model diagram of each key monitoring part, performing preliminary judgment and analysis on each key monitoring part according to the standard wear state three-dimensional model diagram and the actual wear state three-dimensional model diagram, and analyzing whether the key monitoring part is a normal wear state part or an abnormal wear state part;

S106: if a certain key monitoring part is a normal part in a wearing state, marking the key monitoring part as a part capable of continuing to be in service; if a certain key monitoring part is an abnormal part in the abrasion state, further analyzing the key monitoring part to analyze whether the key monitoring part is a part which can be continuously serviced or a part which cannot be continuously serviced;

S108: if a certain key monitoring part is a part which can continue to be in service, continuously monitoring the key monitoring part; if a certain key monitoring component is a component which can not be continuously serviced, generating a recommended operation and maintenance scheme of the key monitoring component, and pushing the recommended operation and maintenance scheme to a preset platform through the Internet of things.

As shown in fig. 2, in a further preferred embodiment of the present invention, total working time information of the licorice tablet preparation device is obtained, and an important monitoring component in the licorice tablet preparation device is determined according to the total working time information, specifically:

s202: acquiring functional characteristic information of each part in the licorice tablet preparation equipment, and determining the parts easy to wear in the licorice tablet preparation equipment according to the functional characteristic information;

wherein, the functional function of the part represented by the functional characteristic information, such as slicing knife, is used for slicing the liquorice into slices; the bearing is used for supporting the rotary motion of the mechanical shaft, reducing friction and friction coefficient, thereby reducing energy loss and improving mechanical efficiency;

s204: acquiring operation log information of the licorice tablet preparation equipment, and acquiring total labor time information of the licorice tablet preparation equipment according to the operation log information;

The running log information of the licorice tablet preparation equipment refers to recording detailed reports of various operations, states and abnormal conditions in the production process of the licorice tablet;

s206: the predicted abrasion loss of the easily-abraded part in the liquorice piece preparation equipment is obtained according to the total labor time information in an estimated mode; presetting a wear threshold of each easily-worn part;

For example, a deep learning method may be used to predict the predicted wear of an easily worn component, where first operational data of the equipment needs to be collected, including total time of service, component materials, operating conditions, and maintenance records. The historical wear data is then analyzed to learn the wear rules of the component, and a wear model, such as a linear regression or exponential model, is built and trained. Then, inputting the total working time and other related parameters into a trained abrasion model for prediction, so as to calculate a predicted abrasion loss;

Wherein the wear threshold of each of the wear-prone components is set to 90% of the wear-prone components in an unworn state; if the inner diameter of the bearing is 40mm, the abrasion loss threshold value of the bearing is set to be 44mm;

S208: comparing the predicted wear amount of each of the easily worn components to a corresponding wear amount threshold; if the predicted wear amount of one of the easily worn components is greater than the corresponding wear amount threshold, the easily worn component is marked as an important monitoring component.

It is to be noted that, through this step, can preliminary analysis out the wearing and tearing state of wearing and tearing part in the licorice piece preparation equipment to judge whether corresponding wearing and tearing part need carry out important monitoring part, can effectively improve equipment operation and maintenance efficiency, can prevent latent trouble and equipment damage, reduce the equipment fault rate.

The Knowledge Graph (knowledgegraph) is a structured Knowledge base, which represents entities and interrelationships in the real world through entities (entities) and relations (Relation). The knowledge graph can help the machine to better understand and process natural language, and improve the performance of fields such as search engines, recommendation systems, semantic analysis and the like. In the invention, constructing a knowledge graph and importing a standard wear state three-dimensional model graph of an easy-to-wear part refers to creating a structured database, wherein the database comprises entity information of the easy-to-wear part, total labor time range information corresponding to various labor time phases, wear states corresponding to the parts in different labor time phases and standard wear state three-dimensional model graphs thereof, and corresponding relations between the different total labor time information and the standard wear state three-dimensional model graphs. In the process, firstly, the entity of the parts easy to wear is identified from various data sources, then the relation of the wear states of the parts in different time phases is extracted and expressed, then a three-dimensional model diagram is created for each wear state, and the model diagrams are associated with the entity and the relation to form a complete and visual knowledge graph so as to be convenient for analyzing, predicting and maintaining the wear condition of the parts;

It should be noted that, a three-dimensional model diagram of a standard abrasion state corresponding to each abrasion-prone part in different working time stages in advance prefabrication of licorice tablet preparation equipment in SolidWorks by a relevant technician; and (3) a three-dimensional model diagram of the standard abrasion state corresponding to the total working time of the slicing knife under the condition of 4000 min. The standard wear state three-dimensional model diagram is the three-dimensional model diagram in the normal wear state.

The cosine similarity algorithm is used for measuring the similarity of two models in the direction by vectorizing the characteristics of the three-dimensional models and calculating the cosine value of an included angle between the characteristics. The value of the similarity ranges from-1 to 1, the closer the value is to 1, the more similar the directions of the two vectors are; the closer the value is to-1, the more opposite the direction of the two vectors; a value close to 0 indicates that the two vectors are orthogonal in space, i.e. there is no similarity between them.

The preset similarity setting range is 0.8 to 1, and the higher the set value is, the higher the operation precision requirement of the equipment is, and the scheme is set to be 0.8;

It should be noted that, if the similarity between the actual wear state three-dimensional model diagram of a certain key monitoring component and the corresponding standard wear state three-dimensional model diagram is greater than the preset similarity, the actual wear state of the key monitoring component under the current working time condition is highly similar to the normal wear state, and at this time, the key monitoring component is marked as the normal wear state component; if the similarity between the actual abrasion state three-dimensional model diagram of a certain key monitoring component and the corresponding standard abrasion state three-dimensional model diagram is not greater than the preset similarity, and the fact that the actual abrasion state of the key monitoring component under the current working time condition is lower in similarity with the normal abrasion state is indicated, the key monitoring component is marked as an abnormal abrasion state component. The method can automatically analyze whether the abrasion state of each key monitoring part in the liquorice piece preparation equipment is normal or not.

Calculating the volume value of the abrasion state deviation model diagram based on a gridding method in the three-dimensional coordinate system to obtain the actual abrasion loss of the key monitoring part; presetting a second abrasion loss threshold value of the key monitoring part; comparing the actual wear of the key monitoring component with a second wear threshold:

The algorithm principle of the gridding method is that a model is divided into a plurality of regular small cube grids (or called voxels), and then the total volume value of the whole model is obtained through calculating the number and the volume of cubes occupied by the model in the grids;

Wherein the second wear threshold is set to 85% of the wear-prone component in the unworn state;

If the actual abrasion loss of the key monitoring component is larger than the second abrasion loss threshold value, the key monitoring component is marked as a component which can not be continuously serviced, and the component is required to be replaced immediately at the moment, so that production accidents caused by the deterioration and collapse of the component in the working process of subsequent equipment are avoided, and the safety of staff and the equipment is ensured.

The method comprises the steps of respectively calculating the volume value of each crack according to the crack characteristic data such as the crack length, the crack width, the crack depth and the like of each crack, and then summing the volume values of each crack to obtain the total crack volume value of the key monitoring component;

Judging whether the crack concentration is larger than a preset concentration or not; if the service life of the key monitoring part is larger than the service life of the key monitoring part, marking the key monitoring part as a part which can not continue to be serviced; wherein the preset concentration is set to 5%;

Wherein, the material performance refers to the mechanical performance, thermal performance, electrical performance, magnetic performance, corrosion resistance and the like of the material under different environments and working conditions; design criteria refers to a series of technical specifications, requirements and guidelines to be followed when designing a component, which typically include specifications in terms of size, shape, tolerances, surface treatments, manner of connection, etc., which help ensure the quality and performance of the component while meeting the regulatory requirements of a particular industry; obtaining a limit internal stress value which can be born by the key monitoring part according to the material performance and the design standard of the key monitoring part and by combining experience and knowledge of a material engineer and a structural engineer;

If the actual wear amount of a certain key monitoring component is not greater than the second wear amount threshold, the actual wear amount of the key monitoring component is still within the allowable range, and the crack concentration of the key monitoring component is further calculated at this time; if the crack concentration of the key monitoring component is greater than the preset concentration, the fact that the actual abrasion loss of the key monitoring component is within the allowable range is indicated, but the crack concentration of the key monitoring component is too large, the key monitoring component belongs to an unstable component, the key monitoring component is extremely easy to deteriorate and collapse, the key monitoring component is marked as a component which can not be continuously used, and the component needs to be replaced immediately.

If the crack concentration of the key monitoring part is not more than the preset concentration, the actual abrasion loss and the crack concentration of the key monitoring part are both in the allowable range, and at the moment, finite element analysis is carried out on the three-dimensional model diagram of the actual abrasion state of the key monitoring part, so that the simulated internal stress value of the key monitoring part is obtained through simulated analysis; if the simulated internal stress value of the key monitoring component is larger than the tolerable limit internal stress value, the key monitoring component is an unstable component, and is extremely easy to deteriorate and collapse, and the key monitoring component is marked as a component which can not be continuously serviced, and the component needs to be replaced immediately. If the simulated internal stress value of the key monitoring part is not greater than the bearable limit internal stress value, the key monitoring part is slightly oversized except for the abrasion loss (but the abrasion loss is still in the allowable range), and other indexes are normal, and the key monitoring part is marked as a part which can continue to be in service.

In summary, the method can more accurately evaluate the abrasion state of the easily worn parts by carrying out systematic detection and analysis on the easily worn parts in the liquorice piece preparation equipment, thereby providing basis for equipment maintenance and replacement; and the potential problems of the parts can be found in time, the parts easy to wear can be replaced or repaired in advance, equipment faults and production interruption caused by serious wear are avoided, production accidents caused by the damage of the parts can be prevented, and the operation safety of the equipment is improved.

The operation and maintenance log information of the licorice tablet preparation equipment refers to records and data generated in the equipment maintenance process. Such information typically includes information about the operating state of the equipment, operational records, maintenance measures, fault diagnosis, replacement of components, and the like. The operation and maintenance log has important significance in ensuring the normal operation of equipment, analyzing fault reasons, improving production efficiency, optimizing maintenance plans and the like. Through analysis of the operation and maintenance log, the service condition of the equipment can be better known, and basis is provided for continuous improvement and optimization of the equipment;

It should be noted that, through this step, the recommended operation and maintenance scheme when maintaining the unable continuous service part of current licorice piece preparation equipment can be automatically matched according to the operation and maintenance log information of all licorice piece preparation equipment in the production shop, and the recommended operation and maintenance scheme is pushed to the preset platform through the internet of things, so that relevant personnel can quickly obtain fault information and solution, thereby improving the response speed to equipment faults, being beneficial to shortening equipment maintenance time, reducing production dead time caused by faults, and improving production efficiency.

Furthermore, the method comprises the following steps:

Obtaining a fault time period corresponding to various faults of the licorice preparation equipment in a historical working process through running log information of the licorice preparation equipment, and obtaining a licorice image produced by the licorice preparation equipment in the fault time period;

performing feature recognition on the licorice tablet images produced by the licorice tablet preparation equipment in the fault time period to obtain abnormal licorice tablet images; performing image conversion treatment on the abnormal licorice slices to obtain gray level co-occurrence matrixes corresponding to the images of the abnormal licorice slices;

Constructing a database, and importing gray level co-occurrence matrixes corresponding to the images of the different liquorice pieces into the database to obtain a characteristic database;

In the actual working process of the licorice preparation equipment, obtaining an actual licorice image produced by the licorice preparation equipment, and performing image conversion processing on the actual licorice image to obtain a gray level co-occurrence matrix corresponding to the actual licorice image;

Importing the gray level co-occurrence matrix corresponding to the actual licorice root slice image into the characteristic database, and calculating the pearson correlation coefficient between the gray level co-occurrence matrix corresponding to the actual licorice root slice image and the gray level co-occurrence matrix corresponding to each abnormal licorice root slice image;

comparing the pearson correlation coefficient between the gray level co-occurrence matrix corresponding to the actual licorice root slice image and the gray level co-occurrence matrix corresponding to each abnormal licorice root slice image with a preset threshold one by one;

if at least one pearson correlation coefficient is larger than a preset threshold value, generating fault early warning information, and displaying the fault early warning information on a preset platform.

It should be noted that the pearson correlation coefficient is used to measure the linear relationship between two variables. For two gray co-occurrence matrix matrices, their pearson correlation coefficients can be calculated to evaluate the linear relationship between them, from which the similarity of the two is determined. The range of values of the correlation coefficient is [ -1, 1], the closer the value is to 1, the more similar the two gray level co-occurrence matrices are represented. Wherein the preset threshold is set to 0.9.

The abnormal licorice root tablet image includes images of surface defects, abnormal colors, irregular shapes, abnormal textures, and the like. If at least one pearson correlation coefficient is larger than a preset threshold value, the fact that in the actual working process of the licorice piece preparation equipment, the licorice piece produced by the licorice piece preparation equipment is abnormal is indicated, fault early warning information is generated at the moment, workers can be reminded of further detecting the equipment, the situation that the equipment prepares large quantities of abnormal licorice pieces is avoided, and the production yield is improved.

Furthermore, the method comprises the following steps:

Determining possible states of the licorice tablet preparation equipment, including normal operation, performance degradation and faults; acquiring historical data of the licorice tablet preparation equipment in various states according to the operation log information, wherein the historical data comprises equipment states, operation time and operation parameters;

Constructing a transition frequency table, wherein the rows of the table represent the current state and the columns represent the target state; traversing the historical data, counting the times of each state transferring to another state, and filling the counted times of each state transferring to another state into the transferring frequency table;

Summing elements of rows in the transition frequency table to obtain the total number of times each state is moved to any other state, and calculating the transition probability between the states according to the total number of times each state is moved to any other state; constructing a state transition probability matrix by using the calculated transition probability, wherein the rows of the state transition probability matrix represent the current state, the columns represent the target state, and the elements in the matrix represent the transition probabilities among the states;

constructing a hidden Markov model, and training the hidden Markov model according to the state transition probability matrix to obtain a trained hidden Markov model;

In the actual working process of the licorice tablet preparation equipment, acquiring actual working parameters of the licorice tablet preparation equipment in a preset time period, and importing the actual working parameters into the trained hidden Markov model for prediction to obtain the state transition probability of the licorice tablet preparation equipment in a future time period;

If the state transition probability is larger than the preset probability, the state transition type of the licorice preparation equipment is obtained, if the state transition type of the licorice preparation equipment is a fault, fault early warning information is generated, and the fault early warning information is displayed on a preset platform. Wherein the preset probability is set to 95%.

It should be noted that, first, a state in which the device may be is determined. For the licorice tablet preparation equipment, the states may be "normal operation", "performance decline", and "failure", etc. Historical data for device operation is collected, including device status, runtime, fault records, etc., which will be used to train the Markov model. Based on the collected data, transition probabilities between states are calculated. For example, a probability of transitioning from a "normal operation" state to a "performance degradation" state is calculated. These probabilities are organized into a state transition matrix. Using the collected data and state transition matrices, a Ma Yin Markov model is trained, which may be accomplished through statistical analysis, machine learning libraries (e.g., the scikit-learn library of Python), or other related tools. The future state of the equipment is predicted through the hidden Markov model, so that potential fault risks are found in advance, timely preventive measures are facilitated, faults are avoided, and the accuracy and reliability of equipment management are improved.

As shown in fig. 3, the second aspect of the present invention discloses a system for operating and maintaining a licorice root tablet preparation device based on the internet of things, the system for operating and maintaining a licorice root tablet preparation device includes a memory 60 and a processor 100, the memory 60 stores a licorice root tablet preparation device operation and maintenance method program, when the licorice root tablet preparation device operation and maintenance method program is executed by the processor 100, the following steps are implemented:

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.

The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.

Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or optical disk, or the like, which can store program codes.

Or the above-described integrated units of the invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.

The foregoing is merely illustrative embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think about variations or substitutions within the technical scope of the present invention, and the invention should be covered. Therefore, the protection scope of the invention is subject to the protection scope of the claims.

Claims

1. The operation and maintenance method of the liquorice tablet preparation equipment based on the Internet of things is characterized by comprising the following steps of:

2. The operation and maintenance method of a licorice tablet preparation device based on the internet of things according to claim 1, wherein the method is characterized in that total labor time information of the licorice tablet preparation device is obtained, and key monitoring components in the licorice tablet preparation device are determined according to the total labor time information, and specifically:

3. The operation and maintenance method of a licorice root tablet preparation device based on the internet of things according to claim 1, wherein a standard wear state three-dimensional model diagram and an actual wear state three-dimensional model diagram of each key monitoring component are obtained, preliminary judgment analysis is performed on each key monitoring component according to the standard wear state three-dimensional model diagram and the actual wear state three-dimensional model diagram, and whether the key monitoring component is a normal wear state component or an abnormal wear state component is analyzed specifically:

4. The operation and maintenance method of a licorice tablet preparation device based on the internet of things according to claim 1, wherein if a certain key monitoring component is an abnormal component in a wear state, further analyzing the key monitoring component to analyze whether the key monitoring component is a continuously-serviceable component or a non-continuously-serviceable component, specifically:

5. The operation and maintenance method for the preparation equipment of the liquorice tablets based on the internet of things according to claim 4, further comprising the following steps:

6. The operation and maintenance method of a licorice tablet preparation device based on the internet of things according to claim 1, wherein if a certain key monitoring component is a component which can not be continuously serviced, a recommended operation and maintenance scheme of the key monitoring component is generated, and the recommended operation and maintenance scheme is pushed to a preset platform through the internet of things, specifically:

7. The operation and maintenance system of the licorice tablet preparation equipment based on the Internet of things is characterized by comprising a memory and a processor, wherein the memory stores a licorice tablet preparation equipment operation and maintenance method program, and when the licorice tablet preparation equipment operation and maintenance method program is executed by the processor, the following steps are realized: