Calorimeter software auxiliary nested control module and calorimeter

Abstract

The invention relates to the technical field of coal quality detection, in particular to a calorimeter software-assisted nested control module and a calorimeter, and the module comprises an identification unit which is used for identifying current time data of a system, time data set according to user demands, and working state data of the calorimeter; the analysis unit is used for determining the influence level of the maintenance operation on the heat capacity of the calorimeter according to the maintenance operation data and the working state data of the calorimeter, and generating a corresponding countdown reminding instruction according to the user configuration requirement and issuing the countdown reminding instruction to the management unit when the influence level is greater than or equal to a target level; and the management unit responds to the countdown reminding instruction, starts countdown from the target countdown moment set according to the user demand and recorded by the identification unit, and reminds the user to execute the corresponding target operation when the countdown is finished. Therefore, the problems that calibration period management depends on manual work and the misjudgment rate is high in the prior art are solved; and the quality control means are fragmented, and the tracing efficiency is low.

Description

Technical Field

[0001] This application relates to the field of coal quality testing technology, and in particular to a calorimeter software-assisted nested control module and a calorimeter. Background Technology

[0002] In the fields of coal, petroleum, and chemical engineering, calorimeters are key equipment for determining the calorific value of energy, and the accuracy and reliability of their measurement results directly affect quality control and energy settlement.

[0003] In related technologies, traditional calorimeters have the following technical defects during use: First, the heat capacity calibration process lacks intelligent management, requiring users to manually record calibration time, which can easily lead to missed periodic calibration cycles and measurement bias; second, the assessment of the impact of equipment maintenance on heat capacity relies entirely on the operator's experience, lacking a systematic basis for judgment; third, the quality control of standard substance measurement data still relies on manual recording or nesting with other systems, which is inefficient and prone to errors; in addition, the process of confirming the heat capacity operating range after the commissioning of new equipment or the replacement of key components is cumbersome and lacks standardized guidance procedures. Summary of the Invention

[0004] This application provides a software-assisted nested control module for a calorimeter and a calorimeter to solve problems in related technologies, such as the reliance on manual calibration cycle management, high risk of measurement bias, lack of quantitative basis for post-maintenance impact assessment, high rate of human error, fragmented quality control methods, and low traceability efficiency.

[0005] The first aspect of this application provides a software-assisted nested control module for a calorimeter, comprising: an identification unit for identifying the current time data of the system and time data set according to user requirements, as well as the working status data of the calorimeter; an analysis unit for determining the impact level of maintenance operations on the heat capacity of the calorimeter based on maintenance operation data and the working status data of the calorimeter, and generating a corresponding countdown reminder instruction according to user configuration requirements and sending it to a management unit when the impact level is greater than or equal to a target level; and a management unit for responding to the countdown reminder instruction by starting a countdown from the target countdown time set according to user requirements recorded by the identification unit, and reminding the user to perform the corresponding target operation when the countdown ends.

[0006] Optionally, it also includes: a first data processing unit, used to generate corresponding calibration results based on the calibration parameters of each calibration test after each calibration test is completed.

[0007] Optionally, generating corresponding calibration results based on calibration parameters from the calibration test includes: extracting heat capacity values ​​that meet the target requirements from the calibration parameters; calculating the average value and standard deviation of the heat capacity values; calculating the relative standard deviation based on the average value and standard deviation; and if the relative standard deviation meets the target effective adjustment, then the calibration result is valid.

[0008] Optionally, the identification unit is further configured to: record the timestamp of the maintenance operation, and dynamically adjust the calibration strategy according to the working status data of the calorimeter, wherein the working status data of the calorimeter includes the heat capacity calibration working mode, the calorific value measurement working mode, and the measurement data corresponding to different modes.

[0009] Optionally, the step of dynamically adjusting the calibration strategy based on the calorimeter's operating status data includes: if the maintenance operation occurs in the heat capacity calibration mode, a calibration reminder for a first target duration is triggered; if the maintenance operation occurs in the calorific value measurement mode, a calibration reminder for a second target duration is triggered.

[0010] Optionally, it further includes: a second data processing unit, used to generate a corresponding first quality control chart based on the difference between the measured values ​​of all standard substances and the standard values ​​in the historical calibration data, and to generate a corresponding second quality control chart for the measured data of each standard substance.

[0011] Optionally, the second data processing unit is further configured to: receive and store standard substance parameters, and establish a standard substance database based on the standard substance parameters, wherein the standard substance parameters include the standard substance name, standard calorific value, user reference uncertainty, and validity period of the set value.

[0012] Optionally, it also includes a data export and report generation module, which is used to export calibration records, maintenance operation data, quality control charts and equipment stability assessment reports to a target format through a target interface that matches the calorimeter, and upload them to the target equipment.

[0013] A second aspect of this application provides a calorimeter, including a software-assisted nested control module as described in the above embodiments.

[0014] Therefore, this application has at least the following beneficial effects: In this embodiment, the identification unit automatically identifies the current time data of the system and monitors and acquires the historical operating status data of the calorimeter in real time, ensuring that the system can operate based on accurate time information and provide more accurate subsequent operation suggestions or reminders based on historical data. The analysis unit automatically analyzes the potential impact of maintenance records on the heat capacity of the equipment through a built-in algorithm, and triggers the corresponding countdown reminder function when it determines that the maintenance operation affects the heat capacity, effectively avoiding measurement errors caused by neglecting recalibration and improving the reliability and accuracy of the measurement results. The management unit responds to the countdown reminder command received from the analysis unit, starts the countdown according to the target countdown time set by the user, and reminds the user to perform the corresponding operation when the countdown ends. By timely reminding the user to perform necessary operations, it ensures that the calorimeter is always in the best working state, thereby improving the quality control level of the entire measurement process.

[0015] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0016] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a block diagram of a software-assisted nested control module for a calorimeter according to an embodiment of this application; Figure 2 This is a schematic diagram of a heat capacity expiration reminder provided according to an embodiment of this application; Figure 3 This is a schematic diagram of the original records for heat capacity calibration and verification provided according to the embodiments of this application; Figure 4 This is a difference quality control chart provided according to an embodiment of this application. Detailed Implementation

[0017] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0018] Most calorimeter software currently on the market only has basic data acquisition and processing functions, and cannot achieve: 1) correlation analysis between maintenance records and changes in heat capacity; 2) automatic determination of calibration validity; 3) trend analysis of historical data and equipment status assessment; 4) full-process quality control of standard substance determination. The lack of these functions leads to problems such as significant human interference, weak quality control, and difficulties in data traceability during instrument use. Although some high-end equipment is equipped with data recording functions, manual intervention is still required for analysis, which cannot meet the needs of intelligent laboratory management.

[0019] Existing calorimeter software systems often suffer from incomplete functionality, and improper operation by personnel can lead to problems such as inconsistent calibration management, lack of maintenance impact assessment, and limited quality control methods. This application addresses these issues by implementing an intelligent, nested control module that enables full-cycle management of heat capacity calibration. This includes functions such as automatic countdown reminders, intelligent analysis of maintenance impact, and automatic determination of calibration validity, resolving the problems of omissions in manual management and inaccurate post-maintenance assessments. The innovative use of standard substance management and quality control chart generation functions establishes a complete quality monitoring system, overcoming the shortcomings of traditional manual recording and analysis, which is characterized by low efficiency and large errors. A specially designed temperature rise-heat capacity relationship model and new equipment guidance function significantly improve the standardization and efficiency of instrument debugging. These technological innovations collectively constitute a complete intelligent calorimeter management solution, improving the accuracy of measurement results by over 30% and operational efficiency by 50%, providing reliable technical support for testing work in the energy, chemical, and other fields.

[0020] The following description, with reference to the accompanying drawings, describes a calorimeter software-assisted nested control module and a calorimeter according to embodiments of this application.

[0021] Specifically, Figure 1 This is a block diagram illustrating a software-assisted nested control module for a calorimeter, as provided in an embodiment of this application.

[0022] like Figure 1 As shown, the calorimeter software-assisted nested control module 10 includes: an identification unit 100, an analysis unit 200, and a management unit 300.

[0023] The identification unit 100 is used to identify the current time data of the system and the time data set according to user needs, as well as the working status data of the calorimeter; the analysis unit 200 is used to determine the impact level of the maintenance operation on the heat capacity of the calorimeter based on the maintenance operation data and the working status data of the calorimeter. When the impact level is greater than or equal to the target level, the analysis unit generates a corresponding countdown reminder instruction according to the user configuration requirements and sends it to the management unit; the management unit 300 responds to the countdown reminder instruction by starting the countdown from the target countdown time set according to user needs recorded by the identification unit, and reminds the user to perform the corresponding target operation when the countdown ends.

[0024] It is understood that in this embodiment, the identification unit automatically identifies the current time data of the system and monitors and acquires the historical working status data of the calorimeter in real time, ensuring that the system can operate based on accurate time information and provide more accurate subsequent operation suggestions or reminders based on historical data; the analysis unit automatically analyzes the potential impact of maintenance records on the heat capacity of the equipment through built-in algorithms, and triggers the corresponding countdown reminder function when it is determined that the maintenance operation affects the heat capacity, effectively avoiding measurement errors caused by neglecting recalibration and improving the reliability and accuracy of measurement results; the management unit responds to the countdown reminder command received from the analysis unit, starts the countdown according to the target countdown time set by the user, and reminds the user to perform the corresponding operation when the countdown ends. By timely reminding the user to perform necessary operations, it ensures that the calorimeter is always in the best working state, thereby improving the quality control level of the entire measurement process.

[0025] Specifically, the auxiliary nested control module automatically identifies the current date and time data of the system, and monitors and acquires historical calorimeter software operating status data in real time, including but not limited to the "heat capacity calibration" working mode, the "calorific value measurement" working mode, and related measurement data; the auxiliary nested control module integrates a calorific value equipment maintenance record function module, which provides a maintenance date input interface and a maintenance location selection interface, where maintenance options include at least preset options such as "replace calorimeter thermometer", "replace oxygen bomb head", and "equipment relocation"; the auxiliary nested control module automatically analyzes and identifies the potential impact of maintenance operations on the equipment's heat capacity through built-in algorithms, and when it is determined that the maintenance operation affects the heat capacity, it automatically triggers the calibration countdown reminder function to prompt the user to perform heat capacity recalibration.

[0026] The auxiliary nested control module is equipped with a heat capacity calibration countdown function module. This function module provides multiple preset countdown duration options for users to select and configure through the calorimeter software setting interface. The preset countdown duration options include at least four standard duration settings: 3 days, 7 days, 15 days, and 30 days. Users can select the corresponding countdown duration parameter through the setting interface according to their actual needs.

[0027] In this embodiment of the application, it further includes: a first data processing unit, used to generate corresponding calibration results based on the calibration parameters of the calibration test after each calibration test is completed.

[0028] It is understood that, in the embodiments of this application, after each calibration test is completed, this unit is responsible for generating the corresponding calibration results based on the parameters of the calibration test, which improves the automation of the calibration process, reduces the influence of human factors on the measurement results, ensures the accuracy and reliability of the calibration results, improves work efficiency, and at the same time ensures the consistency and validity of the data.

[0029] Specifically, the auxiliary nested control module automatically generates a complete calibration record file containing calibration validity verification records and calibration conclusions, and automatically determines the qualification and validity status of the calibration results through a built-in algorithm; at the same time, it combines the maintenance content data recorded in the maintenance record of the calorific equipment to intelligently analyze the potential impact of maintenance operations on the instrument's heat capacity, and then comprehensively judges the validity status of the current calibration results and generates corresponding validity judgment conclusions.

[0030] In this embodiment of the application, generating corresponding calibration results based on calibration parameters of the calibration test includes: extracting heat capacity values ​​that meet the target requirements from the calibration parameters; calculating the average value and standard deviation of the heat capacity values; calculating the relative standard deviation based on the average value and standard deviation; and if the relative standard deviation meets the target effective adjustment, the calibration result is valid.

[0031] It is understood that the embodiments of this application can extract heat capacity data that meets preset standards from calibration tests, avoid manual intervention, reduce human error, ensure the accuracy and consistency of data collection, calculate the average value and standard deviation of heat capacity values, improve data processing efficiency, and calculate the relative standard deviation based on the average value and standard deviation; if the relative standard deviation meets the target effective adjustment, the calibration result is valid, improve the intelligence level of equipment operation, reduce the subjectivity of manual judgment, improve the overall measurement accuracy, and facilitate traceability, archiving and subsequent quality analysis.

[0032] In this embodiment, the identification unit is further used to: record the timestamp of the maintenance operation, and dynamically adjust the calibration strategy according to the working status data of the calorimeter, wherein the working status data of the calorimeter includes the heat capacity calibration working mode, the calorific value measurement working mode, and the measurement data corresponding to different modes.

[0033] It is understood that, in this embodiment of the application, the system can automatically record a timestamp after each maintenance operation, including the specific date and time, as well as relevant maintenance details. By accurately recording the maintenance time and content, and dynamically adjusting the calibration strategy based on this, measurement errors caused by neglecting necessary calibration after maintenance can be effectively avoided, thereby ensuring the accuracy and reliability of measurement results. The system's built-in algorithm automatically analyzes the potential impact of maintenance operations on the equipment's heat capacity. Based on maintenance records and current calorimeter operating status data, the system can intelligently adjust the calibration strategy. Combining historical maintenance records and operating status data, the system can more comprehensively assess the stability of equipment operation, provide early warnings of potential problems, and help maintenance personnel take timely measures. The calibration frequency and depth can be flexibly adjusted according to actual needs, ensuring measurement quality while avoiding unnecessary repetitive work and improving laboratory work efficiency.

[0034] In this embodiment of the application, the calibration strategy is dynamically adjusted based on the working status data of the calorimeter, including: if the maintenance operation occurs in the heat capacity calibration working mode, a calibration reminder for a first target duration is triggered; if the maintenance operation occurs in the calorific value measurement working mode, a calibration reminder for a second target duration is triggered.

[0035] The duration of the first and second objectives can be set according to actual needs, without specific limitations.

[0036] It is understood that by distinguishing maintenance conditions under different working modes, this application embodiment sets different calibration reminder durations, which can more accurately respond to potential heat capacity change risks and avoid the overly conservative approach of using a uniform standard in all cases. This ensures necessary precision maintenance while reducing unnecessary frequent calibration processes and improving overall work efficiency.

[0037] In this embodiment of the application, it further includes: a second data processing unit, configured to generate a corresponding first quality control chart based on the difference between the measured values ​​of all standard substances and the standard values ​​in the historical calibration data, and to generate a corresponding second quality control chart for the measured data of each standard substance.

[0038] It is understood that, in this embodiment of the application, the second data processing unit generates two types of quality control charts by analyzing historical calibration data: a first quality control chart and a second quality control chart. This not only improves the transparency and controllability of the measurement process, but also improves the reliability and consistency of the overall measurement results and enhances data analysis capabilities. Specifically, the auxiliary nested control module is equipped with a standard substance input function module. This module receives and stores the standard substance parameter data input by the user, including key information such as the standard substance name, standard calorific value, user reference uncertainty, and validity period of the set value. By automatically collecting the measurement data of all standard substances in the calorific value determination working mode, the system establishes a standard substance database. Based on this database, two types of quality control charts are automatically generated: a historical quality control chart / table for a single standard substance, and a difference quality control chart / table reflecting the deviation of all standard substance measurement values ​​from the standard values, thereby realizing the quality monitoring and analysis function of the measurement process.

[0039] In this embodiment of the application, the second data processing unit is further configured to: receive and store standard substance parameters, and establish a standard substance database based on the standard substance parameters, wherein the standard substance parameters include the standard substance name, standard calorific value, user reference uncertainty, and validity period of the set value.

[0040] It is understood that the embodiments of this application can simplify the data management and retrieval process by centrally managing the information and measurement data of standard substances, which greatly improves work efficiency. The existence of the standard substance database enables each measurement to be quickly compared with historical data and standard values, and abnormalities can be detected in a timely manner, thereby strengthening the quality control level of the calorimeter and improving the scientificity, accuracy and efficiency of the entire experimental process.

[0041] Specifically, the auxiliary nested control module performs intelligent comprehensive analysis and processing on all stored historical calibration data, conducts multi-dimensional evaluation of the equipment's operational stability and reliability through a preset algorithm model, and provides users with conclusive information including equipment stability level determination and reliability recommendations.

[0042] In this embodiment of the application, it also includes: a data export and report generation module, which is used to export calibration records, maintenance operation data, quality control charts and equipment stability assessment reports into a target format through a target interface that matches the calorimeter, and upload them to the target device.

[0043] It is understood that the embodiments of this application can record and accurately export information for each calibration and maintenance operation in detail, making the entire measurement process more transparent, greatly improving data traceability, and reducing the time required for manual data recording and processing through automated processes, thereby improving work efficiency and enhancing the accuracy and usability of the data.

[0044] In this embodiment of the application, it further includes: a working range guidance unit, used to perform a valid working range confirmation of heat capacity when the calorimeter device is enabled.

[0045] It is understood that the embodiments of this application can realize the real-time assessment of the device status and usage guidance by automatically performing the confirmation of the effective working range of thermal capacity when the device is enabled, which significantly improves the measurement accuracy, operational safety and management efficiency.

[0046] Specifically, the auxiliary nested control module is equipped with a heat capacity effective working range confirmation and guidance function module. This module is automatically activated when a new device is started or when user needs trigger it, and provides complete workflow support including operation process guidance for confirming the heat capacity effective working range, automatic calculation of the weighing mass of benzoic acid standard material, confirmation conclusion, and generation of temperature rise-heat capacity value relationship curve and corresponding mathematical relationship derivation.

[0047] According to the calorimeter software-assisted nested control module proposed in this application embodiment, the identification unit automatically identifies the current time data of the system and monitors and acquires the historical working status data of the calorimeter in real time, ensuring that the system can operate based on accurate time information and provide more accurate subsequent operation suggestions or reminders based on historical data; the analysis unit automatically analyzes the potential impact of maintenance records on the heat capacity of the equipment through a built-in algorithm, and triggers the corresponding countdown reminder function when it is determined that the maintenance operation affects the heat capacity, effectively avoiding measurement errors caused by neglecting recalibration and improving the reliability and accuracy of measurement results; the management unit responds to the countdown reminder command received from the analysis unit, starts the countdown according to the target countdown time set by the user, and reminds the user to perform the corresponding operation when the countdown ends. By timely reminding the user to perform necessary operations, it ensures that the calorimeter is always in the best working state, thereby improving the quality control level of the entire measurement process.

[0048] The following will combine Figures 2-4 The specific embodiments of the calorimeter software-assisted nested control module of this application are described below: The auxiliary nested control module features automatic identification, enabling it to acquire real-time system time and calorific value measurement software status data, including key parameters such as heat capacity calibration mode and calorific value measurement mode. It innovatively incorporates a heat capacity calibration countdown function, allowing users to select from multiple preset periods such as 3 days, 7 days, 15 days, and 30 days to ensure standardized periodic calibration. For equipment maintenance management, the module provides comprehensive maintenance record functionality, detailing maintenance dates, repair locations, and other information. Through intelligent algorithms, it analyzes the potential impact of maintenance operations on heat capacity and automatically triggers necessary calibration reminders.

[0049] In terms of data management, the module automatically generates calibration records and determines calibration validity. Through comprehensive analysis of historical calibration data, it comprehensively assesses the operational stability of the equipment and provides reliability recommendations to users. The module also features a standard substance management function, allowing users to input parameters such as standard substance name, standard value, user reference uncertainty, and validity period. The module automatically collects relevant measurement data and generates quality control charts / tables, including historical quality control charts / tables for individual standard substances and difference quality control charts / tables for all standard substances, providing a visual monitoring method for measurement quality.

[0050] For new equipment commissioning or specific user needs, the module provides a guided function to confirm the effective operating range of heat capacity. This function ensures the standardization of key steps such as benzoic acid weighing through standardized operating procedures, and automatically generates a curve and mathematical formula relating temperature rise to heat capacity. Specific implementation examples: The auxiliary nested control module communicates with different brands of calorific value measurement software via a customized interface. Upon startup, the module automatically initializes, first synchronizing the clock, then scanning the connected measurement software to identify the current operating mode. When the "calorific value calibration" mode is detected, the calibration management function is automatically activated, including modules for recording calibration parameters and evaluating calibration quality.

[0052] The process for implementing the heat capacity expiration reminder function is as follows: After the user selects a 7-day countdown period in the original settings interface, the system automatically records the last calibration time and starts the countdown. For example... Figure 2 The diagram shown illustrates the heat capacity expiration reminder. The top of the interface displays a countdown message: "5 days and 12 hours until the next calibration!" The middle section uses a progress bar to visually display the remaining time percentage, and the bottom features two operation buttons: "Calibrate Now" and "Postponement Reminder." When the countdown reaches zero, the system automatically pops up a reminder window and repeats the reminder every 2 hours until the user completes the calibration process.

[0053] The specific operation of the maintenance record management function is as follows: After replacing the oxygen bomb head, the user selects the "Replace Oxygen Bomb Head" option on the maintenance record interface, fills in the maintenance date as 2023-05-10, and notes that an oxygen bomb head of model XY-203 was replaced. The module automatically analyzes the impact of this maintenance operation and determines it as "moderate impact" according to preset rules, triggering a reminder that recalibration must be performed within 3 days. At the same time, a maintenance record number WX20230510003 is generated, which is automatically associated with subsequent calibration records.

[0054] The automatic calibration record generation function works as follows: After completing the calibration experiment, the system automatically extracts the repeated calibration heat capacity values ​​that meet the standard requirements (e.g., 10453 J / K, 10461 J / K, 10458 J / K, 10455 J / K, 10459 J / K), and calculates the average (10457 J / K) and standard deviation (3.2 J / K). When the standard deviation of 5 measurements exceeds 0.20%, the system automatically prompts for a 6th calibration; if the standard deviation of any 5 of the 6 measurements still exceeds 0.20%, the user is reminded to check the cause and recalibrate. Figure 3 The calibration record template shown includes basic information such as calibration date, operator, and instrument number, as well as a table of key parameters and a conclusion section. The module automatically determines the calibration conclusion, including that the relative standard deviation of this calibration is no greater than 0.20%, the difference from the previous heat capacity value is no greater than 0.25% (except after maintenance), and the standard material verification result is within the user reference uncertainty range. When all three conditions are met, the module determines it as "qualified" and generates a complete calibration record. Special note: When there is a maintenance record that affects heat capacity, the condition "difference from the previous heat capacity value ≤ 0.25%" is not used as a judgment criterion.

[0055] The historical data analysis function is implemented as follows: the module automatically statistically analyzes the changing trends of quality control on a calorimeter-by-meter basis. It subtracts the median value from the measured value of the standard substance (converted to a national standard repeatability comparison benchmark), divides the difference by the user's reference uncertainty multiplied by 100%, and uses this difference as the quality control data. The module has the function of displaying historical quality control charts / tables for a single standard substance and difference quality control charts / tables for all standard substances, and makes judgments based on the quality control procedures of the target rules.

[0056] Taking benzoic acid as a specific example: The user first enters the benzoic acid standard substance information in the "Standard Substance Entry" interface, including the standard value of 26480 J / g, uncertainty of 30 J / g, and expiration date of 2024-06-30. The module then automatically collects 10 measurement results of the standard substance (such as 26475 J / g, 26482 J / g, etc.) and generates a result as shown below. Figure 4 The difference quality control chart shown is plotted with the measurement date on the horizontal axis and the difference between the measured value and the standard value on the vertical axis, displaying upper and lower control lines (±2σ) and upper and lower warning lines (±3σ). When a measured value exceeds the warning line, the module automatically marks the anomaly and indicates the possible cause.

[0057] Example of operation for the heat capacity operating range confirmation function: When using a newly installed calorimeter for the first time, the module guides the user through a confirmation experiment. Benzoic acid has a calorific value of 26460 J / g, and laboratory tests show its calorific value ranges from 19000 J / g to 34000 J / g. Therefore, at least 8 calibration experiments (two repetitions at each endpoint) should be performed using 0.7-1.3 g of benzoic acid. The system automatically records the temperature rise ΔT (e.g., 1.85 K, 2.93 K, etc.) and the corresponding heat capacity E value (e.g., 10450-10470 J / K). By plotting a ΔT-E scatter plot, the system determines the trend of heat capacity change with temperature rise: if it shows a random distribution, it is considered a constant; if a correlation exists, it automatically fits a linear equation E=α+bΔT (e.g., E=10455+5.2ΔT) and calculates the relative standard deviation (≤0.20%). Finally, a validation report is generated that includes the effective operating range (e.g., ΔT = 1.5-3.5K) and applicability conclusions, ensuring that the instrument meets the measurement requirements within the temperature rise range specified in the standard.

[0058] The module also includes data export and report customization functions. Users can choose to export calibration records as PDF or Excel format, and report templates can include custom content such as company logo and contact information. The data interface supports LIMS system integration, enabling automatic uploading of test data.

[0059] Therefore, this application establishes a correlation analysis mechanism between maintenance records and changes in heat capacity, realizing intelligent assessment of maintenance impact; develops an automatic algorithm for determining calibration validity, improving quality control; and constructs a complete data traceability and quality monitoring system, including functional modules such as historical data analysis, standard material management, and work scope confirmation. These technological innovations together constitute a complete intelligent management system for calorimeters. Standardized management significantly improves the accuracy of measurement results, bringing significant economic benefits, especially in energy sectors such as coal and oil; secondly, automation reduces the workload of operators and lowers the risk of human error; finally, comprehensive data recording and analysis functions provide a reliable basis for laboratory quality management. The module is suitable for the intelligent upgrading and transformation of various calorimeter equipment and has broad market application prospects.

[0060] In summary, this application includes functional modules such as automatic identification of system time and measurement mode, countdown reminder for heat capacity calibration, equipment maintenance records and impact analysis, automatic generation and validity determination of calibration records. Among them, the auxiliary nested control module automatically collects calorimeter data and standard material parameters, establishes quality control charts and temperature rise-heat capacity relationship models, and realizes full-process monitoring of the measurement process. The auxiliary nested control module can intelligently analyze the impact of maintenance records on heat capacity, automatically determine the validity of calibration, and conduct stability assessment of historical calibration data. It realizes standardized management of calorimeter use, improves the reliability and accuracy of measurement results, and is suitable for intelligent upgrading and transformation of various calorimeter equipment.

[0061] This application also provides a calorimeter, such as the calorimeter software-assisted nested control module described in the above embodiments.

[0062] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0063] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0064] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0065] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0066] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

Claims

1. A calorimeter software assisted nesting control module, characterized by, Comprising: An identification unit for identifying current time data of the system and time data set according to user demand, and working state data of the calorimeter; An analysis unit for determining an influence level of the maintenance operation on the heat capacity of the calorimeter according to the maintenance operation data and the working state data of the calorimeter, and generating a corresponding countdown reminder instruction according to the user configuration demand and issuing it to the management unit when the influence level is greater than or equal to a target level; A management unit for starting countdown from a target countdown time set according to user demand recorded by the identification unit in response to the countdown reminder instruction, and reminding the user to perform the corresponding target operation when the countdown ends.

2. The calorimeter software assisted nesting control module of claim 1, wherein, Further comprising: A first data processing unit for generating a corresponding calibration result according to calibration parameters of each calibration test after the calibration test is completed.

3. The calorimeter software assisted nesting control module of claim 2, wherein, The generation of the corresponding calibration result according to the calibration parameters of the calibration test comprises: Extracting heat capacity values that meet target requirements in the calibration parameters; Calculating the average value and the standard deviation of the heat capacity values; Calculating the relative standard deviation according to the average value and the standard deviation; If the relative standard deviation meets the target effective adjustment, the calibration result is valid.

4. The calorimeter software assisted nesting control module of claim 1, wherein, The identification unit is further used for: Recording the timestamp of the maintenance operation and dynamically adjusting the calibration strategy according to the working state data of the calorimeter, wherein the working state data of the calorimeter includes heat capacity calibration working mode, heat generation measurement working mode, and measurement data corresponding to different modes.

5. The calorimeter software assisted nesting control module of claim 4, wherein, The dynamic adjustment of the calibration strategy according to the working state data of the calorimeter comprises: If the maintenance operation occurs in the heat capacity calibration working mode, a calibration reminder of a first target duration is triggered; If the maintenance operation occurs in the heat generation measurement working mode, a calibration reminder of a second target duration is triggered.

6. The calorimeter software assisted nesting control module of claim 1, wherein, Further comprising: A second data processing unit for generating a corresponding first quality control chart according to the difference between all standard substance measurement values and standard values in historical calibration data, and generating a corresponding second quality control chart for the measurement data of each standard substance.

7. The calorimeter software assisted nesting control module of claim 6, wherein, The second data processing unit is further used for: receiving and storing standard substance parameters, and establishing a standard substance database according to the standard substance parameters, wherein the standard substance parameters include standard substance name, standard heat value, user reference uncertainty, and value effective period.

8. The calorimeter software assisted nesting control module of claim 1, wherein, Further comprising: A data export and report generation module for exporting calibration records, maintenance operation data, quality control charts, and equipment stability evaluation reports into a target format through a target interface matched with the calorimeter, and uploading them to a target device.

9. The calorimeter software assisted nesting control module of claim 1, wherein, Further comprising: A working range guiding unit for performing heat capacity effective working range confirmation when the calorimeter device is enabled.

10. A calorimeter characterized in that, Comprising: The calorimeter software assisted nested control module according to any one of claims 1-9.

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