Coal quality test management system
By constructing a coal quality testing management system, automated and intelligent coal quality testing management has been achieved, solving the problems of low efficiency, poor accuracy, and management difficulties in traditional methods, and realizing efficient and accurate coal quality testing processes and equipment management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-03
- Publication Date
- 2026-03-31
AI Technical Summary
Traditional coal quality testing methods are inefficient, inaccurate, and difficult to manage, failing to meet the demands of rapid production and lacking unified standards and specifications.
A coal quality testing and management system is constructed, including a higher-level control platform, a task scheduling module, a code management module, a data acquisition and analysis module, an anomaly response module, and an environment and equipment monitoring module. This system enables automated and intelligent management through intelligent task scheduling, code tracking, automatic data analysis, and closed-loop anomaly response, combined with equipment monitoring and maintenance management.
It achieves full-process collaborative scheduling, solving the problems of process fragmentation, delayed response, and blind spots in operation and maintenance in traditional systems. It realizes closed-loop operation without human intervention, improves testing efficiency and accuracy, and ensures data reliability and equipment health status.
Smart Images
Figure CN121766908A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of coal quality testing technology, and more specifically to a coal quality testing management system. Background Technology
[0002] In the field of coal quality testing, traditional testing methods mainly rely on manual operation, while there are many shortcomings in the systematic management of coal quality testing.
[0003] 1. Inefficiency: Manual sampling, sample preparation, and testing require a significant amount of time and manpower, resulting in long testing cycles that cannot meet the demands of rapid production. For example, in the sampling stage, manual sampling makes it difficult to ensure the representativeness of the samples, requiring multiple samplings and screenings, which increases the workload; in the sample preparation stage, manual crushing and reduction operations are inefficient and prone to errors.
[0004] 2. Poor accuracy: Manual operation is easily affected by subjective factors, such as the operator's skill level, experience, and fatigue, which can affect the accuracy and reliability of test results. For example, in the weighing process, manual weighing may result in reading errors; in the experimental analysis process, manual operation may lead to inconsistent experimental conditions, affecting the accuracy of experimental results.
[0005] 3. Management difficulties: Traditional coal quality testing management methods lack unified standards and specifications. The recording, organization, and analysis of test data mainly rely on manual work, which easily leads to data loss and errors. At the same time, there is a lack of effective means to manage testing equipment, making it difficult to monitor the equipment's operating status and malfunctions in real time, thus affecting the normal operation and maintenance of the equipment.
[0006] Therefore, developing a coal quality testing system that can achieve automated and intelligent management is of great practical significance. Summary of the Invention
[0007] The technical problem to be solved by the present invention is to provide a coal quality testing and management system to overcome the shortcomings of the prior art.
[0008] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: a coal quality testing and management system, including a superior control platform, and a task scheduling module, a coding management module, a data acquisition and analysis module, an anomaly response module and an environment and equipment monitoring module connected to the superior control platform; The task scheduling module is used to generate testing tasks based on coal sample label information, and dynamically schedule the flow order of sample bottles among industrial analyzer, calorific value analyzer, sulfur analyzer and elemental analyzer based on preset process path and equipment load status. The coding management module is used to identify the incoming sample coding and generate a unique internal turnover code; The data acquisition and analysis module is used to connect to various testing equipment through a standard industrial communication interface, acquire equipment output data and operating parameters in real time, and perform automatic comparison and analysis based on standard range judgment rules. The anomaly response module is used to issue an alarm signal and upload it to the upper-level control platform when the test data exceeds the repeatability limit or range specification, and at the same time start the retest process or mark the abnormal sample to the manual sampling port. The environment and equipment monitoring module is used to display the laboratory temperature and humidity and the operating status of each piece of equipment in real time.
[0009] The beneficial effects of this invention are: This system, for the first time, deeply integrates five core functions: intelligent task scheduling, code tracking, automatic data analysis, anomaly closed-loop response, and environmental equipment monitoring, solving problems such as process fragmentation, delayed response, and blind spots in operation and maintenance in traditional systems. By constructing a full-process collaborative scheduling engine, it achieves closed-loop operation without human intervention.
[0010] Based on the above technical solution, the present invention can be further improved as follows.
[0011] Furthermore, the data acquisition and analysis module is specifically used for: Perform two initial measurements on the same coal sample; If the difference between two measurements does not exceed the repeatability limit T, the arithmetic mean is taken as the final result. If the value exceeds T, the third measurement will be automatically initiated. If the range of the three measurements is ≤1.2T, the average of the three measurements is taken; if the range is >1.2T, a fourth measurement is performed. If the four ranges are ≤1.3T, take the average of the four values; if the range of any three values is ≤1.2T, take the average of the three values. Otherwise, the coal sample is marked as an abnormal sample, and an alarm message is sent to the superior control platform.
[0012] Furthermore, it also includes a quality control module; the quality control module is used to automatically insert standard coal samples for synchronous testing in each batch of testing tasks; the user presets a standard coal verification plan, and the system automatically executes the standard sample verification experiment periodically according to the plan; when the standard sample test result deviates from the allowable error range, the system automatically alarms and suspends subsequent unknown sample testing until the equipment calibration is completed.
[0013] Furthermore, the environment and equipment monitoring module specifically monitors the following parameters: Industrial analyzer: Equipment operating status, target temperature, current temperature, heating rate; Calorific value meter: test time, outer tank water temperature, inner tank temperature, quantitative water tank temperature, constant temperature box temperature; Sulfur analyzer: Equipment operating status, target temperature, current temperature, heating rate; The environment and equipment monitoring module is also used to provide early warning of abnormal fluctuations by comparing historical trend charts with thresholds.
[0014] Furthermore, it also includes an equipment maintenance management module, which generates preventative maintenance plans based on the equipment's cumulative runtime, number of start-ups and shutdowns, and failure frequency, and updates the equipment health record after maintenance is completed.
[0015] Furthermore, it also includes a report management module; the report management module is used to provide historical test record query, operation log audit, electronic approval of the review process, and generate PDF / Excel formatted test reports according to preset templates.
[0016] Furthermore, it also includes a traceability management module; the traceability management module is used to associate and store the incoming sample information, coding information, weighing data, operator ID, operation timestamp, instrument number used, sample amount, complete test process log and fault events for each coal sample.
[0017] Furthermore, the task scheduling module is specifically used to optimize the sample bottle delivery path and waiting time by using a priority queue algorithm combined with an equipment availability prediction model, taking into account factors such as task urgency, sample type, and equipment idle window period, thereby reducing equipment idle rate. Attached Figure Description
[0018] Figure 1 This is a schematic diagram of the structure of the present invention. Detailed Implementation
[0019] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.
[0020] like Figure 1 As shown in Example 1, a coal quality testing and management system includes a higher-level control platform, and a task scheduling module, a coding management module, a data acquisition and analysis module, an anomaly response module, and an environment and equipment monitoring module connected to the higher-level control platform. The task scheduling module is used to generate testing tasks based on coal sample label information, and dynamically schedule the flow order of sample bottles among industrial analyzer, calorific value analyzer, sulfur analyzer and elemental analyzer based on preset process path and equipment load status. The coding management module is used to identify the incoming sample code and generate a unique internal turnover code, enabling full-process coding and tracking of samples. The data acquisition and analysis module is used to connect to various testing equipment through a standard industrial communication interface, acquire equipment output data and operating parameters in real time, and perform automatic comparison and analysis based on standard range judgment rules. The anomaly response module is used to issue an alarm signal and upload it to the upper-level control platform when the test data exceeds the repeatability limit or range specification, and at the same time start the retest process or mark the abnormal sample to the manual sampling port. The environment and equipment monitoring module is used to display the laboratory temperature and humidity and the operating status of each piece of equipment in real time in a graphical configuration manner.
[0021] This system is the first to deeply integrate five core functions: intelligent task scheduling, code tracking, automatic data analysis, closed-loop anomaly response, and environmental equipment monitoring. It solves problems such as fragmented processes, delayed responses, and blind spots in maintenance found in traditional systems. By building a full-process collaborative scheduling engine, it achieves closed-loop operation without human intervention.
[0022] Example 2 is a further improvement based on Example 1, and its details are as follows: The data acquisition and analysis module is also specifically used for: Perform two initial measurements on the same coal sample; If the difference between two measurements does not exceed the repeatability limit T, the arithmetic mean is taken as the final result. If the value exceeds T, the third measurement will be automatically initiated. If the range of the three measurements is ≤1.2T, the average of the three measurements is taken; if the range is >1.2T, a fourth measurement is performed. If the four ranges are ≤1.3T, take the average of the four values; if the range of any three values is ≤1.2T, take the average of the three values. Otherwise, the coal sample is marked as an abnormal sample, and an alarm message is sent to the superior control platform.
[0023] By introducing a multi-level range judgment logic based on the GB / T standard, the limitations of the traditional "only double testing + manual interpretation" are overcome, enabling the system to make autonomous decisions. Through progressively increasing tolerance boundaries and a flexible mean selection strategy, valid data is retained to the greatest extent possible while ensuring compliance, avoiding resource waste caused by frequent retesting. Simultaneously, an automatic anomaly sample marking mechanism ensures that unqualified results do not flow into downstream systems, guaranteeing the reliability of the data source.
[0024] Example 3 is a further improvement based on Example 1, and its details are as follows: It also includes a quality control module; the quality control module is used to automatically insert standard coal samples for synchronous testing in each batch of testing tasks; the user presets a standard coal verification plan, and the system automatically executes the standard sample verification experiment periodically according to the plan; when the standard sample test result deviates from the allowable error range, the system automatically alarms and suspends subsequent unknown sample testing until the equipment calibration is completed.
[0025] A proactive quality control system has been established, optimizing standard coal verification from "periodic sampling" to "embedded routine operations." The system can not only automatically run standard sample tests according to plan, but also proactively block unknown sample processes in case of loss of control, preventing the spread of contamination.
[0026] Example 4 is a further improvement based on Example 1, and its details are as follows: The environment and equipment monitoring module specifically monitors the following parameters: Industrial analyzer: Equipment operating status, target temperature, current temperature, heating rate; Calorific value meter: test time, outer tank water temperature, inner tank temperature, quantitative water tank temperature, constant temperature box temperature; Sulfur analyzer: Equipment operating status, target temperature, current temperature, heating rate; The environment and equipment monitoring module is also used to provide early warning of abnormal fluctuations by comparing historical trend charts with thresholds.
[0027] This system enables precise monitoring of key laboratory equipment parameters, covering basic operating conditions as well as implicit variables that directly affect measurement accuracy, such as temperature field distribution and water temperature uniformity. Combined with trend comparisons, it can issue early warnings in the initial stages of equipment performance degradation, rather than waiting until complete failure, significantly reducing false detection rates and maintenance costs.
[0028] Example 5 is a further improvement based on Example 1, and its details are as follows: The equipment maintenance management module generates preventative maintenance plans based on the equipment's cumulative runtime, number of start-ups and shutdowns, and failure frequency, and updates the equipment health record after maintenance is completed.
[0029] By performing equipment maintenance proactively, preventative measures can be effectively implemented. The system automatically records each maintenance action, creating a complete equipment lifecycle profile, which helps assess equipment utilization efficiency and optimize procurement strategies.
[0030] Example 6 is a further improvement based on Example 1, and its details are as follows: It also includes a report management module; this module provides access to historical test records, audits operation logs, and facilitates electronic approval processes, generating PDF / Excel formatted test reports according to preset templates. This achieves full lifecycle digital management of reports, overcoming the drawbacks of slow paper report circulation, easy loss, and difficulty in traceability.
[0031] Example 7 is a further improvement based on Example 1, and its details are as follows: It also includes a traceability management module; the traceability management module is used to associate and store the incoming sample information, coding information, weighing data, operator ID, operation timestamp, instrument number used, sample addition amount, complete laboratory process log, and fault events of each coal sample. A comprehensive data traceability mechanism is established, and once a dispute or over-standard event occurs, the problem link can be quickly located. In specific implementation, conditional combination retrieval and full-process backtracking can be performed.
[0032] Embodiment 8, this embodiment is a further improvement based on Embodiment 1, and is specifically as follows: The task scheduling module is specifically used to adopt a priority queue algorithm combined with an equipment availability prediction model, comprehensively consider factors including task urgency, sample type, and equipment idle window period, optimize the sample bottle conveying path and waiting time, and reduce the equipment empty load rate. Using an intelligent scheduling algorithm to optimize resource utilization, dynamically adjusting the task flow based on load prediction and priority sorting, can effectively alleviate the equipment congestion problem during peak hours and shorten the overall detection cycle.
[0033] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.
Claims
1. A coal quality assay management system, characterized by, The system comprises an upper control platform, a task scheduling module, an encoding management module, a data acquisition and analysis module, an abnormal response module and an environment and device monitoring module connected with the upper control platform; The task scheduling module is configured to generate an assay task according to coal sample label information, and dynamically schedule the flow sequence of sample bottles among an industrial analyzer, a calorimeter, a sulfur analyzer and an elemental analyzer based on a preset process path and a device load state. The encoding management module is configured to identify a sample code and generate a unique internal turnover code. The data acquisition and analysis module is configured to connect each assay device through a standard industrial communication interface, acquire device output data and operating parameters in real time, and perform automatic comparison and analysis according to a standard range determination rule. The abnormal response module is configured to send an alarm signal and upload it to the upper control platform when the assay data exceeds the repeatability limit or the range specification, and start a retest process or mark the abnormal sample to a manual sampling port. The environment and device monitoring module is configured to display the laboratory temperature and humidity and the operating state of each device in real time.
2. The coal quality test management system according to claim 1, characterized by The data acquisition and analysis module is further configured to: perform two initial determinations on the same coal sample; if the difference between the two determinations is not more than the repeatability limit T, take the arithmetic mean as the final result; if it exceeds T, automatically start a third determination; when the range of the three determinations is ≤1.2T, take the average of the three; if the range is >1.2T, perform a fourth determination; if the range of the four is ≤1.3T, take the average of the four; if the range of any three values is ≤1.2T, take the average of the three; otherwise, mark the coal sample as an abnormal sample and send an alarm information to the upper control platform.
3. The coal quality test management system according to claim 1, characterized by The system further comprises a quality control module configured to automatically insert a standard coal sample for synchronous testing in each batch of assay tasks; a user presets a standard coal verification scheme, and the system automatically performs the standard sample verification experiment periodically according to the scheme; when the standard sample test result deviates from the allowable error range, the system automatically alarms and suspends the subsequent unknown sample test until the device calibration is completed.
4. The coal quality test management system according to claim 1, characterized by The environment and device monitoring module specifically monitors the following parameters: industrial analyzer: device operating state, target temperature, current temperature, heating rate; calorimeter: test time, outer barrel water temperature, inner barrel temperature, quantitative water tank temperature, constant temperature box temperature; sulfur analyzer: device operating state, target temperature, current temperature, heating speed; The environment and device monitoring module is further configured to realize abnormal fluctuation early warning through comparison of historical trend chart and threshold value.
5. The coal quality management system according to claim 1, wherein The system further comprises a device maintenance management module configured to generate a preventive maintenance plan based on the cumulative operating time, start-stop times and fault frequency of the device, and update the device health record after maintenance is completed.
6. The coal quality management system according to claim 1, wherein The system further comprises a report management module configured to provide historical assay record query, operation log audit, electronic approval of audit process, and generate PDF / Excel formatted assay report according to a preset template.
7. The coal quality management system according to claim 1, wherein The system further comprises a traceability management module, which is configured to associate and store sample information, coding information, weighing data, operator ID, operation time stamp, instrument number, sample amount, complete assay process log and failure events of each coal sample.
8. The coal quality management system according to claim 1, wherein The task scheduling module is specifically configured to adopt a priority queue algorithm combined with a device availability prediction model, comprehensively consider factors including task urgency, sample type and device idle window period, optimize sample bottle conveying path and waiting time, and reduce device idle rate.