A laboratory intelligent drying system and a drying method thereof

Abstract

The application provides a laboratory intelligent drying system and a drying method thereof, and relates to the technical field of drying technology, wherein the drying box comprises a laboratory management system, an intelligent control system and an intelligent drying box. Through real-time collection of sampling and sample preparation production progress information, the intelligent control system classifies and processes the materials, and combines the temperature rising rate, sampling period and sample preparation period of the intelligent drying box to intelligently start the temperature rising program, so that accurate matching of the drying process and the production rhythm is realized, the time of the materials waiting for drying is greatly shortened, and the material drying efficiency is significantly improved.

Description

Technical Field

[0001] This invention relates to the technical field of drying technology, and more particularly to a laboratory intelligent drying system and its drying method. Background Technology

[0002] Drying ovens are indispensable core equipment in daily laboratory operations and related production support experiments. They are widely used in various experimental scenarios such as chemistry, biology, and materials science, primarily for drying materials and samples. Their operating efficiency, energy consumption, and compatibility with production processes directly affect experimental progress, the timeliness and accuracy of experimental results, and also relate to the control of laboratory operating costs and the improvement of energy utilization efficiency. With the continuous improvement of laboratory automation and intelligence, and the popularization of green energy-saving concepts, traditional drying ovens are gradually failing to meet the needs of modern laboratories for efficient, energy-saving, and precise operation, and have many technical shortcomings that urgently need to be addressed.

[0003] Currently, drying ovens used in laboratories are generally manually controlled, relying entirely on manual operation. This includes manually turning the oven on and off and manually selecting the appropriate drying program. The entire operation lacks a linkage mechanism with the production process, making it impossible to achieve precise synchronization with production conditions. The problems caused by this manual control mode are becoming increasingly prominent, seriously affecting the operational efficiency and energy utilization efficiency of laboratories, specifically in the following aspects:

[0004] First, the drying oven is not well-matched with production processes, resulting in low utilization efficiency and severely impacting the experimental analysis cycle. In actual production and experimental procedures, the preparation progress of samples is often out of sync with the start-up status of the drying oven. Due to the lack of an automatic linkage control mechanism, situations frequently arise where samples are ready, but the drying oven has not been started in time, causing samples to fail to enter the drying stage in a timely manner. This delays subsequent experimental analysis, prolongs the overall experimental cycle, and fails to guarantee the timeliness of experimental results, making it difficult to meet the timeliness requirements of production and experiments. Especially in experiments that are extremely sensitive to temperature and time control, delays in the drying stage may also cause changes in sample properties, indirectly affecting the accuracy of experimental results, leading to distorted experimental data or even experimental failure.

[0005] Secondly, the serious energy waste is inconsistent with the development trend of green energy conservation. To avoid delays in experimental analysis due to untimely start-up of the drying oven, operators often turn it on prematurely, leaving it in standby or running mode for extended periods, even when no samples need drying, resulting in significant energy wastage. Furthermore, after the drying experiment, due to operator negligence or busy schedules, the drying oven is often not shut down promptly, causing it to run continuously without load, further exacerbating energy waste. This inefficient operating model not only increases laboratory operating costs but also contradicts the current advocacy of green, low-carbon, and energy-efficient development concepts. Existing drying ovens lack corresponding intelligent control mechanisms and cannot address these energy waste issues.

[0006] Furthermore, the existing manual control mode of drying ovens suffers from problems such as cumbersome operation and significant human error. When manually selecting drying programs, operators are prone to inexperience and errors, leading to the selection of inappropriate drying parameters. This can not only affect the drying effect of materials, resulting in insufficient or excessive drying, thus impacting the accuracy of experimental results, but also potentially increasing energy consumption. Simultaneously, the requirement for manual intervention in the entire process of starting and stopping the drying oven and controlling the program increases the workload of operators and hinders the improvement of laboratory automation levels.

[0007] In summary, the manual control mode currently used in traditional drying ovens in laboratories has many drawbacks, such as poor integration with the production process, low drying efficiency, low energy utilization, inability to guarantee the timeliness of experimental results, cumbersome operation, and susceptibility to errors. It can no longer meet the operational needs of modern laboratories for high efficiency, energy saving, precision, and intelligence.

[0008] Therefore, developing a laboratory intelligent drying oven and its drying method that can automatically link with production conditions, automatically start and stop, and precisely control the drying process, thereby improving material drying efficiency and energy utilization and ensuring the timeliness of experimental results, has become an urgent technical problem to be solved. Summary of the Invention

[0009] As mentioned in the background technology, the manual control mode currently used in traditional laboratory drying ovens has many technical problems, such as poor matching with the production process, low drying efficiency, low energy utilization, inability to guarantee the timeliness of experimental results, cumbersome operation, and easy to generate errors. Therefore, a laboratory intelligent drying system and its drying method are provided, including: a laboratory management system, an intelligent control system, and an intelligent drying oven, which can realize automatic start and stop according to the production situation, perfectly match the production, improve the material drying efficiency and energy utilization, and ensure the timeliness of experimental results.

[0010] The technical means employed in this invention are as follows: A laboratory intelligent drying system includes: a laboratory management system, an intelligent control system, and an intelligent drying oven; The laboratory management system is used to collect and send production status information; the production status information includes: material progress information, material name, material code, and analysis item information; the material progress information includes: time node information for material sampling and material sample preparation; The intelligent control system is communicatively connected to the laboratory management system and is used to receive the production status information and classify the material information. The classification process includes classifying materials with a drying temperature of a first preset temperature into first type materials and materials with a drying temperature of a second preset temperature into second type materials. The intelligent control system is also used to allocate drying tasks according to the current operating status and production status of the intelligent drying chamber. The intelligent drying chamber is communicatively connected to the intelligent control system and includes a first drying chamber and a second drying chamber. The intelligent drying chamber is used to automatically heat up according to the received material information and the assigned drying task, and automatically turn off the heating or switch to a low-power standby state after the drying experiment is completed.

[0011] Furthermore, the intelligent control system has preset sampling cycle parameters and sample preparation cycle parameters; the intelligent control system calculates the start time of the drying experiment based on the sampling cycle parameters, sample preparation cycle parameters and the material progress information, and controls the intelligent drying chamber to preheat so that the intelligent drying chamber reaches the preset drying temperature before the sample is manually weighed.

[0012] Furthermore, the intelligent drying oven includes: a temperature sensor, a timing module, and a communication module; the temperature sensor is used to monitor the temperature inside the oven in real time and feed it back to the intelligent control system; the timing module is used to record the drying time and the constant weight determination time; the communication module is used to perform bidirectional data interaction with the intelligent control system, receive control commands, and upload operating status data.

[0013] Furthermore, The intelligent control system includes: a PLC controller, a communication interface module, a parameter storage module, a timing module, and peripheral interaction hardware. The PLC controller is used to process material information classification, allocate drying tasks, calculate timing logic, and control equipment start-up and shutdown. The communication interface module includes communication hardware that interfaces with the laboratory management system and the intelligent drying chamber, enabling bidirectional data transmission and reception for system information exchange. The parameter storage module stores preset parameters: material name, material code, first / second preset temperature, sampling cycle parameters, and sample preparation cycle parameters, while also caching material progress, drying task allocation information, and equipment operating status data. The timing module receives sampling and sample preparation time node information and, combined with cycle parameters, calculates the drying experiment start time to control the drying chamber's heating sequence. The peripheral interaction hardware input / output control interface issues heating, shutdown, and low-power standby commands, while simultaneously collecting the actual operating status of the intelligent drying chamber. The intelligent control system software is used to receive production information from the laboratory management system, including material name, material code, analysis item information, and time node information for material sampling and sample preparation; the intelligent control system software is used to store material drying methods, including: the name, code, analysis item information, and drying temperature of each material; and to send drying task information to the intelligent drying oven, including material name, material code, and analysis item information.

[0014] Furthermore, the laboratory management system is also used to receive and store the experimental data uploaded by the intelligent drying oven; the experimental data includes: pre-drying mass, post-drying mass, constant weight determination result, drying time and energy consumption data, and automatically generates experimental reports.

[0015] This invention also includes a laboratory intelligent drying method, comprising the following steps: S1. Collect production status information through the laboratory management system and send the production status information to the intelligent control system; the production status information includes: material progress information, material name, material code and analysis item information; S2. The intelligent control system classifies the received material information, classifies materials with a drying temperature of a first preset temperature as first type of material, and classifies materials with a drying temperature of a second preset temperature as second type of material. S3. The intelligent control system intelligently allocates drying tasks to the corresponding intelligent drying boxes according to the current operating status and production rhythm of the intelligent drying boxes. S4. The intelligent drying chamber automatically starts the heating program based on the received material information and the assigned drying task. The start time of the heating program is determined according to the heating rate, sampling cycle and sample preparation cycle of the intelligent drying chamber. S5. After the temperature reaches the preset drying temperature, the manual operator weighs the sample according to the job operation standard requirements and puts it into the intelligent drying box to start the drying experiment. S6. After the constant weight condition is reached, the intelligent drying oven automatically ends the drying experiment, stops heating or enters a low-power state. S7: The drying experiment results are automatically transmitted to the laboratory management system to complete the collection and archiving of experimental data.

[0016] Furthermore, the material progress information in S1 includes: sampling time and sample preparation time; the intelligent control system predicts the sample preparation completion time based on the sample preparation time and sample preparation cycle, and calculates the optimal start time of the heating program accordingly.

[0017] Furthermore, the constant weight condition in S6 is: the mass change between two consecutive weighings does not exceed a preset threshold.

[0018] Furthermore, the intelligent allocation of drying tasks in S3 includes: when both the first drying chamber and the second drying chamber are busy, the intelligent control system prioritizes tasks and schedules drying chambers based on the urgency of the materials, the remaining time to reach the preset drying temperature, and the estimated time for the drying process.

[0019] Compared with the prior art, the present invention has the following advantages: This invention collects real-time production progress information such as material sampling and sample preparation, classifies and processes the materials through an intelligent control system, and intelligently pre-starts the heating program based on the heating rate, sampling cycle, and sample preparation cycle of the intelligent drying oven. This achieves precise matching between the drying process and the production cycle, significantly shortening the waiting time for materials to dry and greatly improving drying efficiency. Simultaneously, by automatically starting the heating program according to production tasks and automatically stopping the heating program or switching to low-power standby mode after the experiment, it avoids the energy waste caused by prolonged idle operation or ineffective insulation of traditional drying ovens, effectively improving energy utilization. Furthermore, because the drying experiment can be prepared in advance according to the sample preparation completion time and started immediately after sample preparation, it ensures that analysis and testing are synchronized with the production progress, obtaining drying experiment data in a timely manner, thus guaranteeing the timeliness of experimental results and providing rapid and reliable data support for production scheduling decisions. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the overall process of the present invention. Detailed Implementation

[0022] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] Example 1 This invention provides a laboratory intelligent drying system, comprising: a laboratory management system, an intelligent control system, and an intelligent drying chamber, which interact and transmit data through a wired or wireless network.

[0025] In a preferred embodiment, the laboratory management system in this application is deployed on a laboratory information management platform to collect and transmit production status information. This production status information includes: material progress information, material name, material code, and analysis item information (moisture content). Specifically, the material progress information includes the material sampling time and the time node information for material sample preparation. The laboratory management system also receives and stores experimental data uploaded by the intelligent drying oven, including pre-drying mass, post-drying mass, constant weight determination results, drying time, and energy consumption data, and automatically generates experimental reports.

[0026] In a preferred embodiment, the intelligent control system is communicatively connected to the laboratory management system, serving as a data transfer and processing hub. It receives production status information and classifies material information. The classification process includes categorizing materials dried at a first preset temperature (40°C) into a first type of material and materials dried at a second preset temperature (105°C) into a second type of material. The intelligent control system also intelligently allocates drying tasks based on the current operating status and production situation of the intelligent drying oven.

[0027] In this application, the intelligent drying oven is communicatively connected to the intelligent control system and includes a first drying oven and a second drying oven. The first drying oven is equipped with a 40°C drying program, mainly used for low-temperature drying of materials such as coal samples and some chemical raw materials; the second drying oven is equipped with a 105°C drying program, mainly used for high-temperature drying of materials such as iron concentrate and ore. The intelligent drying oven is used to automatically execute the heating program according to the received material information and the assigned drying task, and automatically shut down the heating program or switch to a low-power standby state after the drying experiment is completed.

[0028] In a preferred embodiment, the intelligent control system is pre-set with sampling cycle parameters and sample preparation cycle parameters. The sampling cycle parameters are set according to material characteristics and job operation standards, representing the average time required from material batching to completion of sampling; the sample preparation cycle parameters represent the average time required from completion of sampling to completion of sample preparation.

[0029] The intelligent control system calculates the start time of the drying experiment based on the sampling cycle parameters, sample preparation cycle parameters, and material progress information. Specifically, the calculation logic is as follows: based on the material batching time and sampling cycle, the sampling completion time is predicted; based on the sampling completion time and sample preparation cycle, the sample preparation completion time is predicted; based on the sample preparation completion time and the heating rate of the intelligent drying chamber, the optimal start time of the heating program is calculated in reverse, and a pre-heating command is sent to the intelligent drying chamber to ensure that the intelligent drying chamber reaches the preset drying temperature before the sample is manually weighed, achieving immediate drying and avoiding moisture absorption or process delays caused by sample waiting.

[0030] The intelligent control system includes a PLC controller, a communication interface module, a parameter storage module, a timing module, and peripheral interaction hardware. When multiple materials require drying simultaneously, the task scheduling module sorts the tasks and allocates drying chamber resources based on the priority of each material (determined by the urgency of production), the drying temperature type (40℃ or 105℃), and the current load status of the intelligent drying chamber (idle, heating up, constant temperature drying, or cooling down). For example, when both the first and second drying chambers are busy, the task scheduling module prioritizes tasks and schedules drying chambers based on the urgency of the materials, the remaining time to reach the preset drying temperature, and the estimated drying time, ensuring that urgent materials are processed first while balancing the load rate of the two drying chambers. Alternatively, a backup drying chamber can be activated.

[0031] Preferably, the intelligent drying oven includes a temperature sensor, a timing module, and a communication module.

[0032] The temperature sensor is a platinum resistance temperature sensor, arranged at the geometric center and four corners of the drying oven's working area. It monitors the oven temperature in real time and feeds it back to the intelligent control system, with a temperature control accuracy of ±1℃. Based on the temperature feedback data, the intelligent drying oven uses a PID algorithm to adjust the heating power, ensuring temperature uniformity and stability within the oven. The timing module has a built-in high-precision real-time clock for recording drying time and constant weight determination time. The constant weight determination time is the time interval between two consecutive weighings, with a default setting of 1 hour. The communication module supports RS-485, Ethernet, or Wi-Fi communication protocols for bidirectional data interaction with the intelligent control system, receiving control commands and uploading operating status data (including current temperature, set temperature, operating status, cumulative operating time, and fault codes).

[0033] Example 2 Taking the drying of iron concentrate as an example, the laboratory intelligent drying method of the present invention is described in detail: Step S1: The laboratory management system collects information on the production status of iron concentrate, including material name, material code (such as "TF-2026-001"), sampling time, sample preparation time, analysis items (moisture), etc., and sends the above information to the intelligent control system.

[0034] Step S2: The intelligent control system classifies the received material information. Iron concentrate belongs to the category of ore materials, and its standard drying temperature is 105℃, therefore it is classified as a second type of material.

[0035] Step S3: The intelligent control system queries the current operating status of the second drying chamber (105℃ drying chamber). If the second drying chamber is idle, a drying task is directly assigned; if the second drying chamber is performing other tasks, the task is queued or scheduled to the first drying chamber (if the first drying chamber is idle and can be temporarily compatible with the high-temperature program after evaluation) according to the algorithm of the task scheduling module, combined with the urgency of the iron concentrate material, the remaining time for the second drying chamber to complete the current task, and the estimated drying time of the iron concentrate (according to historical data, it takes about 2 hours to dry iron concentrate to constant weight).

[0036] Step S4: The intelligent control system calculates the optimal start time for the heating program as "2026-04-20 16:00" based on the sample preparation time and cycle (e.g., if the sample preparation cycle is 2 hours, the estimated completion time is "2026-04-20 16:00"), combined with the heating rate of the second drying oven (e.g., it takes 30 minutes to heat from room temperature 25℃ to 105℃). Upon reaching this time, the intelligent control system sends a start command to the second drying oven, and the second drying oven automatically starts the heating program.

[0037] Step S5: After the temperature reaches 105℃ and stabilizes, manually weigh 500 grams of iron concentrate sample according to the job operation standard requirements, spread it evenly in the drying tray, and put it into the second drying oven to start the drying experiment.

[0038] Step S6: During the drying process, the temperature sensor monitors the temperature inside the chamber in real time, and the timing module records the drying time. Every minute, the system automatically weighs the current weight. When the mass change between two consecutive weighings does not exceed 0.5g, the constant weight condition is determined to be met. At this time, the second drying chamber automatically ends the drying experiment, stops heating, or automatically adjusts to a low-power state according to subsequent production tasks. If the laboratory management system does not send a new drying task within a preset time window (e.g., 2 hours), the intelligent control system controls the second drying chamber to switch to a heat preservation mode, maintaining the temperature inside the chamber within the range of 40℃-50℃. This reduces the energy consumption of reheating and allows for rapid recovery to 105℃ when a new task is received.

[0039] Step S7: The drying experiment results (including the mass before drying 500.0g, the mass after drying 485.2g, the constant weight judgment result is qualified, the drying time is 2 hours, energy consumption data, etc.) are automatically transmitted to the laboratory management system. The laboratory management system automatically calculates the moisture content as 2.96%, generates an experimental report and archives it, thus completing the collection of experimental data.

[0040] Example 3 Taking coal sample drying as an example, the implementation of a 40℃ low-temperature drying procedure is explained: Step S1: The laboratory management system collects production information of coal samples, including material name, material code, sampling time, sample preparation time, analysis items (moisture), etc., and sends it to the intelligent control system.

[0041] Step S2: The intelligent control system classifies the coal sample into the first type of material (drying temperature 40℃).

[0042] Step S3: The intelligent control system assigns the drying task to the first drying chamber (40℃ drying chamber).

[0043] Step S4: Calculate and start the heating program based on the coal sample preparation completion time and the heating rate of the first drying oven, so that the first drying oven reaches 40°C before the sample preparation is completed.

[0044] Step S5: Manually weigh the coal sample (e.g., 500g, accurate to 0.1g) and place it in the first drying oven to begin the drying experiment.

[0045] Step S6: The coal sample is dried at 40℃ to constant weight (the mass change between two consecutive weighings does not exceed 0.1%). The first drying oven automatically ends the experiment and switches to low power mode.

[0046] Step S7: The experimental results are automatically transmitted to the laboratory management system to complete data collection and report generation.

[0047] Example 4 When the laboratory receives both iron concentrate and coal samples simultaneously, the task scheduling module of the intelligent control system executes the following logic: Receive information on iron concentrate (Type II, 105℃) and coal sample (Type I, 40℃); Check the operating status of the first and second drying chambers; If both the first and second drying chambers are idle, tasks are assigned to both drying chambers simultaneously, and the heating program is executed in parallel. If the second drying chamber is performing other iron concentrate drying tasks (estimated to have 2 hours remaining), and the new iron concentrate task has a high priority urgency, the task scheduling module will assess whether the first drying chamber can be temporarily switched to the 105℃ program (considering equipment compatibility and the risk of temperature cross-contamination) or the backup drying chamber can be activated.

[0048] If the first drying chamber is performing other coal sample tasks when the coal sample task arrives, a decision will be made on whether to queue up or start the backup drying chamber based on the coal sample preparation completion time and the estimated end time of the current drying task.

[0049] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. In the above embodiments of the present invention, the descriptions of each embodiment have their own emphasis; parts not described in detail in a certain embodiment can be referred to in the relevant descriptions of other embodiments. It should be understood that the disclosed technical content in the several embodiments provided in this application can be implemented in other ways.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A laboratory intelligent drying system, characterized in that, include: Laboratory management system, intelligent control system, and intelligent drying oven; The laboratory management system is used to collect and send production status information; The production status information includes: material progress information, material name, material code, and analysis item information; the material progress information includes: time node information for material sampling and material sample preparation; The intelligent control system is communicatively connected to the laboratory management system and is used to receive the production status information and classify the material information. The classification process includes classifying materials with a drying temperature of a first preset temperature into first type materials and materials with a drying temperature of a second preset temperature into second type materials. The intelligent control system is also used to allocate drying tasks according to the current operating status and production status of the intelligent drying chamber. The intelligent drying chamber is communicatively connected to the intelligent control system and includes a first drying chamber and a second drying chamber. The intelligent drying chamber is used to automatically heat up according to the received material information and the assigned drying task, and automatically turn off the heating or switch to a low-power standby state after the drying experiment is completed.

2. The intelligent laboratory drying system according to claim 1, characterized in that, The intelligent control system has preset sampling cycle parameters and sample preparation cycle parameters. Based on the sampling cycle parameters, sample preparation cycle parameters and material progress information, the intelligent control system calculates the start time of the drying experiment and controls the intelligent drying chamber to preheat so that the intelligent drying chamber reaches the preset drying temperature before the sample is manually weighed.

3. A laboratory intelligent drying system according to claim 1 or 2, characterized in that, The intelligent drying oven includes a temperature sensor, a timing module, and a communication module. The temperature sensor is used to monitor the temperature inside the oven in real time and feed it back to the intelligent control system. The timing module is used to record the drying time and the constant weight determination time. The communication module is used to perform bidirectional data interaction with the intelligent control system, receive control commands, and upload operating status data.

4. The intelligent laboratory drying system according to claim 1, characterized in that, The intelligent control system includes: a PLC controller, a communication interface module, a parameter storage module, a timing module, and peripheral interaction hardware. The PLC controller is used to process material information classification, allocate drying tasks, calculate timing logic, and control equipment start-up and shutdown. The communication interface module includes communication hardware that interfaces with the laboratory management system and the intelligent drying chamber, enabling bidirectional data transmission and reception for system information exchange. The parameter storage module stores preset parameters: material name, material code, first / second preset temperature, sampling cycle parameters, and sample preparation cycle parameters, while also caching material progress, drying task allocation information, and equipment operating status data. The timing module receives sampling and sample preparation time node information and, combined with cycle parameters, calculates the drying experiment start time to control the drying chamber's heating sequence. The peripheral interaction hardware input / output control interface issues heating, shutdown, and low-power standby commands, while simultaneously collecting the actual operating status of the intelligent drying chamber. The intelligent control system software is used to receive production information from the laboratory management system, including material name, material code, analysis item information, and time node information for material sampling and sample preparation; the intelligent control system software is used to store material drying methods, including: the name, code, analysis item information, and drying temperature of each material; and to send drying task information to the intelligent drying oven, including material name, material code, and analysis item information.

5. The intelligent laboratory drying system according to claim 1, characterized in that, The laboratory management system is also used to receive and store the experimental data uploaded by the intelligent drying oven; the experimental data includes: pre-drying mass, post-drying mass, constant weight determination result, drying time and energy consumption data, and automatically generates experimental reports.

6. A laboratory intelligent drying method, using the laboratory intelligent drying system according to any one of claims 1-5, characterized in that, Includes the following steps: S1. Collect production status information through the laboratory management system and send the production status information to the intelligent control system; the production status information includes: material progress information, material name, material code and analysis item information; S2. The intelligent control system classifies the received material information, classifies materials with a drying temperature of a first preset temperature as first type of material, and classifies materials with a drying temperature of a second preset temperature as second type of material. S3. The intelligent control system intelligently allocates drying tasks to the corresponding intelligent drying boxes according to the current operating status and production rhythm of the intelligent drying boxes. S4. The intelligent drying chamber automatically starts heating based on the received material information and the assigned drying task; the start time of heating is determined according to the heating rate, sampling cycle and sample preparation cycle of the intelligent drying chamber. S5. After the temperature reaches the preset drying temperature, the manual operator weighs the sample according to the job operation standard requirements and puts it into the intelligent drying box to start the drying experiment. S6. After the constant weight condition is reached, the intelligent drying oven automatically ends the drying experiment, stops heating or enters a low-power state. S7: The drying experiment results are automatically transmitted to the laboratory management system to complete the collection and archiving of experimental data.

7. The laboratory intelligent drying method according to claim 6, characterized in that, The material progress information in S1 includes: material sampling time and sample preparation time; the intelligent control system predicts the sample preparation completion time based on the sample preparation time and sample preparation cycle, and calculates the optimal start time of the heating program accordingly.

8. The laboratory intelligent drying method according to claim 6, characterized in that, The constant weight condition in S6 is: the mass change between two consecutive weighings does not exceed a preset threshold.

9. A laboratory intelligent drying method according to claim 6, characterized in that, The intelligent allocation of drying tasks in S3 includes: when both the first drying chamber and the second drying chamber are busy, the intelligent control system prioritizes tasks and schedules drying chambers based on the urgency of the materials, the remaining time to reach the preset drying temperature, and the estimated time for the drying process.

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