Coal sample access management system based on intelligent identification and analysis

Abstract

The invention provides a coal sample access management system based on intelligent identification and analysis, and belongs to the technical field of coal sample access management, and the system comprises a configuration module which is used for configuring a unique RFID identifier for each coal sample, analyzing the type characteristics and appearance characteristics of each coal sample, and synchronously uploading the type characteristics, the appearance characteristics and the RFID identifiers to a database; the acquisition module is used for acquiring images for storing and taking coal samples in real time and determining coal sample inventory state information and single-time storage and taking quantity information according to the coal sample storage and taking images; the first generation module is used for generating a coal sample access report and an access coal sample analysis report based on the coal sample inventory state information and the single access quantity information, and uploading the report to the management server; and the early warning module is used for determining potential abnormal state parameters according to the coal sample analysis report and the coal sample access report in combination with the coal sample use condition and the access environment parameters and performing early warning. The problems that the information record of the coal sample is inaccurate, the stability and efficiency of the production process are influenced, and meanwhile, the sampling efficiency and accuracy are reduced are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of coal sample storage and access management, and in particular to a coal sample storage and access management system based on intelligent identification and analysis. Background Art

[0002] With the rapid development of my country's economy, the coal industry, as one of the pillar energy industries, plays a vital role in the development of the national economy.

[0003] In the traditional coal sample storage and retrieval management system, if the operator does not perform storage and retrieval operations according to the prescribed procedures, or is careless when recording information, it may lead to inaccurate information recording of coal samples, and thus fail to discover abnormal situations in time, affecting the stability and efficiency of the production process. At the same time, during the coal sample storage and retrieval process, the appearance characteristics of the coal samples cannot be automatically identified and sampled, which reduces the sampling efficiency and accuracy.

[0004] Therefore, the present invention provides a coal sample storage and access management system based on intelligent identification and analysis. Summary of the invention

[0005] The present invention provides a coal sample storage and retrieval management system based on intelligent identification and analysis, which is used to solve the problem that the information recording of coal samples in the prior art is inaccurate, and abnormal situations cannot be discovered in time, affecting the stability and efficiency of the production process. At the same time, during the coal sample storage and retrieval process, the appearance characteristics of the coal samples cannot be automatically identified and sampled, which reduces the sampling efficiency and accuracy.

[0006] On the one hand, the present invention provides a coal sample storage and access management system based on intelligent identification and analysis, comprising: Configuration module: configure a unique RFID tag for each coal sample, analyze the type and appearance characteristics of each coal sample through a machine learning algorithm, and upload the type and appearance characteristics and the RFID tag to the database synchronously; Collection module: collects images of workers accessing coal samples in real time to obtain coal sample access images, and determines coal sample inventory status information and single access quantity information based on the coal sample access images and the type characteristics and appearance characteristics of each coal sample; The first generation module generates a coal sample access report and an access coal sample analysis report based on the coal sample inventory status information and the single access quantity information, and uploads the coal sample access report and the access coal sample analysis report to the management server; Early warning module: Determine potential abnormal state parameters and issue early warning reports based on coal sample analysis reports and coal sample storage and access reports combined with coal sample usage and storage and access environmental parameters.

[0007] According to the coal sample storage and access management system based on intelligent identification and analysis provided by the present invention, the configuration module includes: The first acquisition unit: acquires the characteristics and access environment of the coal sample, and acquires the corresponding RFID tag type according to the characteristics and access environment; Setting unit: determining the corresponding RFID reader / writer according to the RFID tag type, and setting multiple parameters of the reader / writer according to the use environment; Configuration unit: configure a unique RFID identification for each coal sample according to the set reader / writer; The second acquisition unit: acquires the type and structure of each coal sample according to the RFID identification, and acquires the type characteristics and appearance characteristics of each coal sample based on the type and structure analysis of each coal sample according to the machine learning algorithm; Uploading unit: synchronously uploading the RFID identification, type characteristics and appearance characteristics to the database based on preset rules.

[0008] According to the coal sample storage and access management system based on intelligent identification and analysis provided by the present invention, the uploading unit further includes: Acquisition subunit: acquiring a data structure of an RFID identifier, a type feature, and an appearance feature, and acquiring a transmission protocol according to the data structure; A first determination subunit: obtaining the identity information of the operator according to the biometric recognition technology, and determining the identity level and authority level of the operator according to the identity information; A second determination subunit: determining the user's free operation authority and audit operation authority based on the authority management mechanism according to the identity level and authority level; Upload subunit: according to the transmission protocol, based on the free operation authority and the audit operation authority, the RFID identification, type characteristics and appearance characteristics are synchronously uploaded to the database, and log records are made, and important operations in the upload process are audited according to the log records.

[0009] The coal sample storage and access management system based on intelligent identification and analysis provided by the present invention also includes: The first determination module: determines the data storage method according to the amount of data stored and accessed coal samples, and determines the data arrangement method according to the data storage method; The second determination module determines the limiting factors of data storage according to the arrangement of data, and determines the queue mechanism when storing data according to the limiting factors; Selection module: selects the appropriate data query method according to the queue mechanism, and determines the data format for accessing coal sample data according to the data type; Positioning module: locate the target database according to the data format, and obtain the target data from the target database through data query.

[0010] According to the coal sample storage and access management system based on intelligent identification and analysis provided by the present invention, the collection module includes: Video recording unit: obtain a high-resolution camera and perform event detection based on the high-resolution camera, and record the staff entering a specific area and the operation of coal samples based on the event detection; Collection unit: collects images of the staff storing and accessing coal samples in real time according to the video results, obtains coal sample storage and access images, and determines the size and shape of the coal sample pile before and after the operation according to the coal sample storage and access images; The first determining unit determines the coal sample inventory status information and single access quantity information based on the size and shape of the coal sample pile and the type characteristics and appearance characteristics of each coal sample.

[0011] According to the coal sample storage and access management system based on intelligent identification and analysis provided by the present invention, the first generation module includes: A second determining unit: determining an inventory change and an inventory turnover rate according to the coal sample inventory status information; A third determining unit: determining the type and access quantity distribution of the accessed coal sample according to the single access quantity information; First evaluation unit: evaluate the frequency of coal sample access and the efficiency of access operations based on inventory changes, inventory turnover, types of coal samples accessed and accessed, and distribution of access quantities; Generating unit: Generates coal sample storage and access report and storage and access coal sample analysis report according to the evaluation results, and uploads the coal sample storage and access report and storage and access coal sample analysis report to the management server.

[0012] According to the coal sample storage and access management system based on intelligent identification and analysis provided by the present invention, the early warning module includes: The third acquisition unit: acquires the physical and chemical characteristic data of the coal sample according to the coal sample analysis report, and acquires the coal sample storage and access related parameters according to the coal sample storage and access report; The fourth determination unit: obtains the actual use of the coal sample and determines the storage and access environment parameters of the coal sample according to the actual use; The fifth determination unit: determines the quality of the coal sample based on the physicochemical characteristic data of the coal sample and the coal sample storage and access related parameters according to the storage and access environment parameters; The fourth acquisition unit: determines the potential risk point based on the preset threshold according to the coal sample quality, and acquires the potential abnormal state parameter according to the potential risk point; The second evaluation unit evaluates the abnormality level of the potential abnormal state parameter, determines the alarm level according to the abnormality level, and issues a warning report.

[0013] The coal sample storage and access management system based on intelligent identification and analysis provided by the present invention, after analyzing the type characteristics and appearance characteristics of each coal sample, further includes: Comparison module: extract weak texture features and strong texture features from the appearance features of each coal sample and compare them to obtain comparison results; The third determination module: determines the appearance fixed resolution feature and the appearance extended resolution feature of each coal sample according to the comparison results; Setting module: determining the color determination parameter and structure determination parameter of each coal sample based on the fixed appearance distinguishing feature, and setting the first classification feature of each coal sample according to the color determination parameter and structure determination parameter; The fourth determination module: determining the appearance difference attribute of each coal sample according to the appearance extension discrimination feature, and determining the sensory difference attribute of each coal sample according to the appearance difference attribute; The fifth determination module: determining the synchronization head width difference parameter and the synchronization head length difference parameter of each coal sample based on the sensory difference attribute; The sixth determination module: determining the visual matching analysis parameters of each coal sample according to the synchronization head width difference parameter and the synchronization head length difference parameter; The second generation module: sets the second classification feature of each coal sample according to the visual matching analysis parameters, and generates the classification rules of each coal sample according to the first classification feature and the second classification feature; Identification and evaluation module: Determine the classification vector of each coal sample based on the classification rules of the coal sample, and perform classification identification and inventory status and access classification evaluation on the subsequent access coal samples according to the classification vector.

[0014] Compared with the prior art, the present invention has the following beneficial effects: According to the coal sample access image, the coal sample inventory status information and single access quantity information are determined based on the type characteristics and appearance characteristics of each coal sample, and a coal sample access and analysis report is generated. In combination with the coal sample usage, potential abnormal situations are determined. No manual recording is required, which avoids inaccurate information recording of coal samples, can promptly discover abnormal situations, and improve the stability and efficiency of the production process. At the same time, during the coal sample access process, the appearance characteristics of the coal samples can be automatically identified and sampled, which improves the sampling efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a structural schematic diagram of a coal sample storage and access management system based on intelligent identification and analysis provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of the structure of the configuration module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Embodiment 1: The coal sample storage and access management system based on intelligent identification and analysis provided by the embodiment of the present invention is as follows: Figure 1 As shown, the system mainly includes the following modules: Configuration module: configure a unique RFID tag for each coal sample, analyze the type and appearance characteristics of each coal sample through a machine learning algorithm, and upload the type and appearance characteristics and the RFID tag to the database synchronously; Collection module: collects images of workers accessing coal samples in real time to obtain coal sample access images, and determines coal sample inventory status information and single access quantity information based on the coal sample access images and the type characteristics and appearance characteristics of each coal sample; The first generation module generates a coal sample access report and an access coal sample analysis report based on the coal sample inventory status information and the single access quantity information, and uploads the coal sample access report and the access coal sample analysis report to the management server; Early warning module: Determine potential abnormal state parameters and issue early warning reports based on coal sample analysis reports and coal sample storage and access reports combined with coal sample usage and storage and access environmental parameters.

[0019] In this embodiment, RFID is a wireless communication technology that realizes automatic identification of objects through radio waves. The unique RFID identifier is a code consisting of a group of numbers, letters or symbols, which is used to uniquely identify each object being tested and may include information such as a predetermined serial number, production batch number, and product type.

[0020] In this embodiment, machine learning is an artificial intelligence technology that allows computers to learn and improve autonomously by analyzing large amounts of data to complete designated tasks.

[0021] In this embodiment, the type characteristics of the coal sample refer to the different characteristics exhibited in chemistry, physics, quality analysis, etc., such as: Anthracite: Anthracite is a high calorific value, low ash, low sulfur coal with high combustion efficiency and cleanliness.

[0022] Bituminous coal: Bituminous coal is a type of coal that contains a certain amount of volatile matter and has a high ash content. Its main characteristics are high carbon content, but low calorific value, and it produces more smoke during combustion. Its particles are coarse, with a clear iron oxide layer on the surface, and are reddish brown.

[0023] In this embodiment, the appearance characteristics of the coal sample refer to that different types of coal have different appearance characteristics such as color, gloss, density, particle size, etc. For example, anthracite is usually black or gray with a smooth surface; bituminous coal is often black or brown with obvious pores and impurities on the surface.

[0024] In this embodiment, the coal sample inventory status information refers to information records about various states of the coal sample during storage, such as: coal sample number, coal sample name, and storage date.

[0025] In this embodiment, the coal sample storage and access report is a report that records the storage, allocation and use of coal samples during the coal mine production process.

[0026] In this embodiment, the access coal sample analysis report refers to a detailed report generated after analyzing the coal sample collected from the coal mine or other coal sources, including detailed analysis results of the chemical composition, physical properties and radioactivity of the coal sample.

[0027] In this embodiment, the actual usage conditions may be: combustion efficiency and emission composition.

[0028] In this embodiment, the storage and access environment parameters include: temperature and humidity in the warehouse, ventilation conditions, and whether there are moisture-proof measures.

[0029] In this embodiment, the potential abnormal state parameters may be: the access temperature is too high, the moisture content is too high, and the access environment humidity is too humid.

[0030] The beneficial effects of the above technical solution are: determining the coal sample inventory status information and single access quantity information based on the type characteristics and appearance characteristics of each coal sample according to the coal sample access image, generating a coal sample access and analysis report, and determining potential abnormal situations in combination with the coal sample usage. No manual recording is required, thus avoiding inaccurate information recording of coal samples, and abnormal situations can be discovered in time, thereby improving the stability and efficiency of the production process. At the same time, during the coal sample access process, the appearance characteristics of the coal samples can be automatically identified and sampled, thereby improving the sampling efficiency and accuracy.

[0031] Embodiment 2: Based on Example 1, the configuration module of the embodiment of the present invention is as follows: Figure 2 As shown, including: The first acquisition unit: acquires the characteristics and access environment of the coal sample, and acquires the corresponding RFID tag type according to the characteristics and access environment; Setting unit: determining the corresponding RFID reader / writer according to the RFID tag type, and setting multiple parameters of the reader / writer according to the use environment; Configuration unit: configure a unique RFID identification for each coal sample according to the set reader / writer; The second acquisition unit: acquires the type and structure of each coal sample according to the RFID identification, and acquires the type characteristics and appearance characteristics of each coal sample based on the type and structure analysis of each coal sample according to the machine learning algorithm; Uploading unit: synchronously uploading the RFID identification, type characteristics and appearance characteristics to the database based on preset rules.

[0032] In this embodiment, the characteristics of the coal sample include: type, size, shape, density, moisture content, and storage conditions of the coal sample.

[0033] In this embodiment, the access environment includes: temperature, humidity, light, and ventilation of the access environment.

[0034] In this embodiment, the corresponding RFID tag type may be: for bulk coal, a barcode or a QR code may be used for identification and tracking; and for granular coal, a near field communication chip tag with high resolution and fast reading and writing capabilities may be selected.

[0035] In this embodiment, the RFID reader is a device that can read and write RFID tag information.

[0036] In this embodiment, the multiple parameters of the reader / writer include: operating frequency, power, and reading / writing speed.

[0037] In this embodiment, the appearance characteristics of the coal sample refer to that different types of coal have different appearance characteristics such as color, gloss, density, particle size, etc. For example, anthracite is usually black or gray with a smooth surface; bituminous coal is often black or brown with obvious pores and impurities on the surface.

[0038] The beneficial effects of the above technical solution are: obtaining the corresponding RFID tag type according to the characteristics of the coal sample and the access environment, determining the corresponding RFID reader, and configuring a unique RFID identifier, which can ensure that the information of each coal sample is unique and cannot be tampered with, and can avoid inaccurate records or data loss due to human errors. Furthermore, the type characteristics and appearance characteristics of each coal sample are obtained and uploaded to the database simultaneously, which can ensure the accuracy of the data, reduce errors, and improve the efficiency of data upload.

[0039] Embodiment 3: Based on the second embodiment, the uploading unit in the embodiment of the present invention further includes: Acquisition subunit: acquiring a data structure of an RFID identifier, a type feature, and an appearance feature, and acquiring a transmission protocol according to the data structure; A first determination subunit: obtaining the identity information of the operator according to the biometric recognition technology, and determining the identity level and authority level of the operator according to the identity information; A second determination subunit: determining the user's free operation authority and audit operation authority based on the authority management mechanism according to the identity level and authority level; Upload subunit: according to the transmission protocol, based on the free operation authority and the audit operation authority, the RFID identification, type characteristics and appearance characteristics are synchronously uploaded to the database, and log records are made, and important operations in the upload process are audited according to the log records.

[0040] In this embodiment, the data structure refers to an organization method in a computer program for storing and managing data, such as an array, a linked list, or a stack.

[0041] In this embodiment, the transmission protocol refers to a set of rules and methods used to control data transmission in a computer network, such as TCP / IP protocol and FTP protocol.

[0042] In this embodiment, biometric technology refers to technology that uses human biological characteristics to verify identity, and identity can be confirmed by scanning or measuring specific biological characteristics, such as fingerprints, palm prints, facial images, voices, iris scans, etc.

[0043] In this embodiment, the identity level of the operators is usually determined according to their responsibilities and work content. During the production process, the operators may be divided into different levels, such as first-line operators, second-level operators, and third-level operators.

[0044] In this embodiment, the permission level of the operator refers to a division of the access rights and restrictions possessed by the operator in the computer operating system or other management system, such as: view, access, and modify.

[0045] In this embodiment, auditing refers to the process of systematically inspecting, investigating, and evaluating an object, event, activity, etc.

[0046] The beneficial effects of the above technical solution are: obtaining the transmission protocol according to the data structure of RFID identification, type characteristics and appearance characteristics, and at the same time, obtaining the identity information of the operator according to biometric technology, and determining the corresponding identity level and authority level, which can ensure the security and privacy of the data.

[0047] Embodiment 4: Based on Example 3, the embodiment of the present invention further includes: The first determination module: determines the data storage method according to the amount of data stored and accessed coal samples, and determines the data arrangement method according to the data storage method; The second determination module determines the limiting factors of data storage according to the arrangement of data, and determines the queue mechanism when storing data according to the limiting factors; Selection module: selects the appropriate data query method according to the queue mechanism, and determines the data format for accessing coal sample data according to the data type; Positioning module: locate the target database according to the data format, and obtain the target data from the target database through data query.

[0048] In this embodiment, the data volume of the stored and accessed coal samples refers to the size of the storage space required for storing and processing the coal samples.

[0049] In this embodiment, the data storage method can be: local storage, cloud storage, and distributed storage.

[0050] In this embodiment, the form of data organization refers to that in a database or other data processing system, data is arranged and organized according to certain rules, such as: sequential arrangement, random arrangement, and group arrangement.

[0051] In this embodiment, the limiting factors of data storage include: hardware limitation, software limitation, network limitation, and security limitation.

[0052] In this embodiment, the data queuing processing method is a commonly used data storage and management method, which puts data elements into a queue in sequence and processes them according to the first-in-first-out principle.

[0053] In this embodiment, data query refers to the process of obtaining information from a database or file system, including: SQL query, text search, and API call.

[0054] In this embodiment, the data type refers to a category representing different types of data, such as: string, integer, floating point number, Boolean value, array.

[0055] In this embodiment, the data format refers to the way in which data is organized and used in a computer program, such as text format, image format, and audio format.

[0056] The beneficial effects of the above technical solution are: determining the arrangement of data according to the coal sample data storage method, thereby determining the limiting factors of data storage, selecting an appropriate data query method, obtaining target data from the target database, and being able to quickly and accurately locate the target data, avoiding obtaining erroneous data, and improving the accuracy and speed of data acquisition.

[0057] Embodiment 5: Based on Example 4, the acquisition module of the embodiment of the present invention includes: Video recording unit: obtain a high-resolution camera and perform event detection based on the high-resolution camera, and record the staff entering a specific area and the operation of coal samples based on the event detection; Collection unit: collects images of the staff storing and accessing coal samples in real time according to the video results, obtains coal sample storage and access images, and determines the size and shape of the coal sample pile before and after the operation according to the coal sample storage and access images; The first determining unit determines the coal sample inventory status information and single access quantity information based on the size and shape of the coal sample pile and the type characteristics and appearance characteristics of each coal sample.

[0058] In this embodiment, the resolution of the high-resolution camera refers to the smallest detail that can be captured by the image sensor. The high-resolution camera has higher resolution and imaging quality and can present a clearer picture.

[0059] In this embodiment, event detection refers to the process of automatically identifying events or patterns of interest from a large amount of data and performing operations such as classification, filtering or labeling on them.

[0060] In this embodiment, the coal sample inventory status information refers to information records about various states of the coal sample during storage, such as: coal sample number, coal sample name, and storage date.

[0061] The beneficial effects of the above technical solution are: event detection is carried out based on high-definition cameras, images of workers storing and accessing coal samples are obtained in real time, and the size and shape of the coal sample pile before and after the operation are determined. This can realize self-realistic data collection and avoid errors and loopholes caused by human intervention. At the same time, through automated data collection, the manual workload can be greatly reduced and the accuracy and consistency of the data can be improved.

[0062] Embodiment 6: Based on Example 5, the first generation module of the embodiment of the present invention includes: A second determining unit: determining an inventory change and an inventory turnover rate according to the coal sample inventory status information; A third determining unit: determining the type and access quantity distribution of the accessed coal sample according to the single access quantity information; First evaluation unit: evaluate the frequency of coal sample access and the efficiency of access operations based on inventory changes, inventory turnover, types of coal samples accessed and accessed, and distribution of access quantities; Generating unit: Generates coal sample storage and access report and storage and access coal sample analysis report according to the evaluation results, and uploads the coal sample storage and access report and storage and access coal sample analysis report to the management server.

[0063] In this embodiment, the coal sample inventory status information refers to information records about various states of the coal sample during storage, such as: coal sample number, coal sample name, and storage date.

[0064] In this embodiment, the inventory change refers to the increase or decrease in the inventory of the coal sample within a certain period of time.

[0065] In this embodiment, the coal sample inventory turnover rate refers to the ratio of coal samples to complete sales or use within a certain period of time.

[0066] In this embodiment, the coal sample refers to unprocessed coal collected from a coal mine or other coal production site. The types of coal samples include: Classification by ash content: coal samples can be divided into anthracite, bituminous coal, lignite and low calorific value coal according to their ash content. Among them, anthracite has the lowest ash content and bituminous coal has the highest ash content; low calorific value coal has a lower calorific value.

[0067] Classification based on volatile matter: Coal samples can be divided into high volatile coal, medium volatile coal and low volatile coal according to their volatile matter.

[0068] In this embodiment, the access amount distribution includes: uniform distribution, uneven distribution, and enriched distribution.

[0069] In this embodiment, the coal sample storage and access report is a report that records the storage, allocation and use of coal samples during the coal mine production process.

[0070] The beneficial effects of the above technical solution are: the coal sample access frequency and the efficiency of the access operation are evaluated based on the coal sample inventory status information and the single access quantity information, and a corresponding report is generated, which can ensure the accuracy of the coal sample access report. At the same time, it can be quickly retrieved and referenced when needed, avoiding duplication of work and improving work efficiency.

[0071] Embodiment 7: Based on Example 6, the early warning module of this embodiment of the present invention includes: The third acquisition unit: acquires the physical and chemical characteristic data of the coal sample according to the coal sample analysis report, and acquires the coal sample storage and access related parameters according to the coal sample storage and access report; The fourth determination unit: obtains the actual use of the coal sample and determines the storage and access environment parameters of the coal sample according to the actual use; The fifth determination unit: determines the quality of the coal sample based on the physicochemical characteristic data of the coal sample and the coal sample storage and access related parameters according to the storage and access environment parameters; The fourth acquisition unit: determines the potential risk point based on the preset threshold according to the coal sample quality, and acquires the potential abnormal state parameter according to the potential risk point; The second evaluation unit evaluates the abnormality level of the potential abnormal state parameter, determines the alarm level according to the abnormality level, and issues a warning report.

[0072] In this embodiment, the physical and chemical property data include: ash content, volatile matter, fixed carbon, sulfur content, and calorific value of the coal sample.

[0073] In this embodiment, the coal sample storage and access related parameters include: coal sample collection time, location, batch number, and storage conditions.

[0074] In this embodiment, the actual usage conditions may be: combustion efficiency and emission composition.

[0075] In this embodiment, the storage and access environment parameters include: temperature and humidity in the warehouse, ventilation conditions, and whether there are moisture-proof measures.

[0076] In this embodiment, the coal sample quality refers to the basic indicators used to analyze and evaluate the physical, chemical and mineralogical properties of coal products.

[0077] In this embodiment, potential risk points include, for example, incomplete combustion.

[0078] In this embodiment, the potential abnormal state parameters refer to state parameters that may cause changes in the quality of the coal sample or create safety hazards under specific conditions, such as oxygen concentration, temperature, and water content.

[0079] The beneficial effects of the above technical scheme are: determining the quality of coal samples according to the access environment parameters based on the physical and chemical properties data of coal samples and coal sample access related parameters, determining potential risk points and corresponding abnormal state parameters, being able to quickly determine the factors affecting the quality of coal samples and ensure the quality of coal samples; at the same time, evaluating the abnormal state parameters, being able to determine targeted early warning reports, thereby making corresponding solution operations and improving the accuracy of coal sample access.

[0080] Embodiment 8: Based on Example 7, after analyzing the type characteristics and appearance characteristics of each coal sample, the embodiment of the present invention further includes: Comparison module: extract weak texture features and strong texture features from the appearance features of each coal sample and compare them to obtain comparison results; The third determination module: determines the appearance fixed resolution feature and the appearance extended resolution feature of each coal sample according to the comparison results; Setting module: determining the color determination parameter and structure determination parameter of each coal sample based on the fixed appearance distinguishing feature, and setting the first classification feature of each coal sample according to the color determination parameter and structure determination parameter; The fourth determination module: determining the appearance difference attribute of each coal sample according to the appearance extension discrimination feature, and determining the sensory difference attribute of each coal sample according to the appearance difference attribute; The fifth determination module: determining the synchronization head width difference parameter and the synchronization head length difference parameter of each coal sample based on the sensory difference attribute; The sixth determination module: determining the visual matching analysis parameters of each coal sample according to the synchronization head width difference parameter and the synchronization head length difference parameter; The second generation module: sets the second classification feature of each coal sample according to the visual matching analysis parameters, and generates the classification rules of each coal sample according to the first classification feature and the second classification feature; Identification and evaluation module: Determine the classification vector of each coal sample based on the classification rules of the coal sample, and perform classification identification and inventory status and access classification evaluation on the subsequent access coal samples according to the classification vector.

[0081] In this embodiment, the weak texture features in the appearance features of the coal sample refer to tiny lines on the surface or inside the coal sample. These lines are usually not obvious and can only be seen with a magnifying glass or a more advanced microscope.

[0082] In this embodiment, the strong texture features in the appearance features of the coal sample refer to obvious textures on the surface or inside of the coal sample. These textures are usually clear and can be seen with the naked eye.

[0083] In this embodiment, the fixed distinguishing features of the appearance of the coal sample may be: color, size, hardness and toughness.

[0084] In this embodiment, the extended distinguishing features of the appearance of the coal sample may be: fracture structure, pore structure, bonding material, and solid residue.

[0085] In this embodiment, the color parameters refer to parameters used to describe the appearance properties of coal, such as color, glossiness, transparency, and ash content.

[0086] In this embodiment, the structural parameters are parameters used to describe the physical properties of the coal sample, such as: density, hardness, melting point, boiling point, specific heat capacity, electrical conductivity, and thermal conductivity of the coal sample.

[0087] In this embodiment, the appearance difference attribute of the coal samples refers to the appearance difference that can be identified by visual means when observing and comparing different coal samples, such as: color, glossiness, cracks and porosity, and powdery state.

[0088] In this embodiment, the sensory difference attributes of the coal samples refer to the differences that can be perceived through smell, taste, touch, etc. when observing and comparing different coal samples, such as: smell, taste, humidity.

[0089] In this embodiment, the synchronization head width difference parameter is used to describe the degree of difference between the particle size distributions of different particle sizes generated when coal samples of different particle sizes are classified by the same device (such as a vibrating screen) during the coal sample sorting process.

[0090] In this embodiment, the synchronization head length difference parameter is used to measure the degree of difference in synchronization head lengths of coals of different particle sizes during movement.

[0091] In this embodiment, the visual matching analysis parameters are used to describe and evaluate the performance of the image recognition system when processing actual objects, such as: false detection rate, missed detection rate, and repetition rate.

[0092] In this embodiment, with respect to the classification of coal samples, corresponding classification rules are usually formulated based on the appearance characteristics, physical properties, chemical composition and other attributes of the coal samples.

[0093] In this embodiment, the classification vectors of the coal sample may be: density, hardness, and volatility.

[0094] The beneficial effects of the above technical solution are: by establishing classification rules for each coal sample and determining the corresponding classification vector, different types of coal can be accurately classified, thereby better managing inventory and ensuring the accuracy of coal mining. At the same time, by classifying and identifying different coal samples and evaluating inventory status, abnormal situations and potential problems can be discovered in time, and corresponding measures can be taken to deal with them, avoiding coal quality problems and safety hazards, which helps to improve the efficiency and safety of coal mine production.

[0095] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable access medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A coal sample storage and access management system based on intelligent identification and analysis, characterized in that: include: Configuration module: configure a unique RFID tag for each coal sample, analyze the type and appearance characteristics of each coal sample through a machine learning algorithm, and upload the type and appearance characteristics and the RFID tag to the database synchronously; Collection module: collects images of workers accessing coal samples in real time to obtain coal sample access images, and determines coal sample inventory status information and single access quantity information based on the coal sample access images and the type characteristics and appearance characteristics of each coal sample; The first generation module generates a coal sample access report and an access coal sample analysis report based on the coal sample inventory status information and the single access quantity information, and uploads the coal sample access report and the access coal sample analysis report to the management server; Early warning module: Determine potential abnormal state parameters and make early warning reports based on coal sample analysis reports and coal sample storage and access reports combined with coal sample usage and storage and access environment parameters.

2. The coal sample storage and access management system based on intelligent identification and analysis according to claim 1 is characterized in that: Configuration modules, including: The first acquisition unit: acquires the characteristics and access environment of the coal sample, and acquires the corresponding RFID tag type according to the characteristics and access environment; Setting unit: determining the corresponding RFID reader / writer according to the RFID tag type, and setting multiple parameters of the reader / writer according to the use environment; Configuration unit: configure a unique RFID identification for each coal sample according to the set reader / writer; The second acquisition unit: acquires the type and structure of each coal sample according to the RFID identification, and acquires the type characteristics and appearance characteristics of each coal sample based on the type and structure analysis of each coal sample according to the machine learning algorithm; Uploading unit: synchronously uploading the RFID identification, type characteristics and appearance characteristics to the database based on preset rules.

3. The coal sample storage and access management system based on intelligent identification and analysis according to claim 2 is characterized in that: The upload unit also includes: Acquisition subunit: acquiring a data structure of an RFID identifier, a type feature, and an appearance feature, and acquiring a transmission protocol according to the data structure; A first determination subunit: obtaining the identity information of the operator according to the biometric recognition technology, and determining the identity level and authority level of the operator according to the identity information; A second determination subunit: determining the user's free operation authority and audit operation authority based on the authority management mechanism according to the identity level and authority level; Upload subunit: according to the transmission protocol, based on the free operation authority and the audit operation authority, the RFID identification, type characteristics and appearance characteristics are synchronously uploaded to the database, and log records are made, and important operations in the upload process are audited according to the log records.

4. The coal sample storage and access management system based on intelligent identification and analysis according to claim 1 is characterized in that: Also includes: The first determination module: determines the data storage method according to the amount of data stored and accessed coal samples, and determines the data arrangement method according to the data storage method; The second determination module determines the limiting factors of data storage according to the arrangement of data, and determines the queue mechanism when storing data according to the limiting factors; Selection module: selects the appropriate data query method according to the queue mechanism, and determines the data format for accessing coal sample data according to the data type; Positioning module: locate the target database according to the data format, and obtain the target data from the target database through data query.

5. The coal sample storage and access management system based on intelligent identification and analysis according to claim 1 is characterized in that: Acquisition module, including: Video recording unit: obtain a high-resolution camera and perform event detection based on the high-resolution camera, and record the staff entering a specific area and the operation of coal samples based on the event detection; Collection unit: collects images of the staff storing and accessing coal samples in real time according to the video results, obtains coal sample storage and access images, and determines the size and shape of the coal sample pile before and after the operation according to the coal sample storage and access images; The first determining unit determines the coal sample inventory status information and single access quantity information based on the size and shape of the coal sample pile and the type characteristics and appearance characteristics of each coal sample.

6. The coal sample storage and access management system based on intelligent identification and analysis according to claim 1 is characterized in that: The first generation module includes: A second determining unit: determining an inventory change and an inventory turnover rate according to the coal sample inventory status information; A third determining unit: determining the type and access quantity distribution of the accessed coal sample according to the single access quantity information; First evaluation unit: evaluate the frequency of coal sample access and the efficiency of access operations based on inventory changes, inventory turnover, types of coal samples accessed and accessed, and distribution of access quantities; Generating unit: Generates coal sample storage and access report and storage and access coal sample analysis report according to the evaluation results, and uploads the coal sample storage and access report and storage and access coal sample analysis report to the management server.

7. The coal sample storage and access management system based on intelligent identification and analysis according to claim 1 is characterized in that: Early warning module, including: The third acquisition unit: acquires the physical and chemical characteristic data of the coal sample according to the coal sample analysis report, and acquires the coal sample storage and access related parameters according to the coal sample storage and access report; The fourth determination unit: obtains the actual use of the coal sample and determines the storage and access environment parameters of the coal sample according to the actual use; The fifth determination unit: determines the quality of the coal sample based on the physicochemical characteristic data of the coal sample and the coal sample storage and access related parameters according to the storage and access environment parameters; The fourth acquisition unit: determines the potential risk point based on the preset threshold according to the coal sample quality, and acquires the potential abnormal state parameter according to the potential risk point; The second evaluation unit evaluates the abnormality level of the potential abnormal state parameter, determines the alarm level according to the abnormality level, and issues a warning report.

8. The coal sample storage and access management system based on intelligent identification and analysis according to claim 1 is characterized in that: After analyzing the type and appearance characteristics of each coal sample, it also includes: Comparison module: extract weak texture features and strong texture features from the appearance features of each coal sample and compare them to obtain comparison results; The third determination module: determines the appearance fixed resolution feature and the appearance extended resolution feature of each coal sample according to the comparison results; Setting module: determining the color determination parameter and structure determination parameter of each coal sample based on the fixed appearance distinguishing feature, and setting the first classification feature of each coal sample according to the color determination parameter and structure determination parameter; The fourth determination module: determining the appearance difference attribute of each coal sample according to the appearance extension discrimination feature, and determining the sensory difference attribute of each coal sample according to the appearance difference attribute; The fifth determination module: determining the synchronization head width difference parameter and the synchronization head length difference parameter of each coal sample based on the sensory difference attribute; The sixth determination module: determining the visual matching analysis parameters of each coal sample according to the synchronization head width difference parameter and the synchronization head length difference parameter; The second generation module: sets the second classification feature of each coal sample according to the visual matching analysis parameters, and generates the classification rules of each coal sample according to the first classification feature and the second classification feature; Identification and evaluation module: Determine the classification vector of each coal sample based on the classification rules of the coal sample, and perform classification identification and inventory status and access classification evaluation on the subsequent access coal samples according to the classification vector.

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