Laboratory specimen operation process flow monitoring system

Abstract

The invention relates to the technical field of information, and discloses a laboratory specimen operation technological process monitoring system. Comprising a specimen knowledge base construction module, a specimen receiving and checking module, a process flow data acquisition module, a machine fault detection module, a machine fault early warning module, a specimen quality monitoring module, a specimen quality early warning module and an early warning result output module. A sensor is used for monitoring machine operation data and specimen quality parameter data in the specimen processing process in real time, a machine operation power coefficient is calculated through an operation monitoring mathematical model, whether machine operation is normal or not is judged, abnormal results are displayed in an early warning mode, and an electrolysis activity coefficient of a specimen is calculated through a specimen quality monitoring model. Whether the specimen quality is normal or not is judged, an abnormal result is pre-warned and displayed, all links of the specimen operation technological process are monitored in real time, and the safety of the specimen is ensured.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and more specifically to a laboratory specimen operation process monitoring system and method. Background Art

[0002] The rapid development of information technology, especially breakthroughs in computer network technology, database technology, software development technology, etc., has provided strong technical support for the development of process flow monitoring systems. These technologies enable the system to collect, process, store and transmit large amounts of data in real time, providing strong support for monitoring and decision-making. The information management system can provide strong support for the construction of high-quality and high-standard sample libraries. The development of automation and intelligent control technology has enabled each link in the process to achieve automated operation and intelligent control. Each link in the specimen collection, transportation, preservation, and testing requires extremely high accuracy. Errors in any link will affect the accuracy of the test results, and thus affect clinical diagnosis and treatment.

[0003] The current sample libraries in my country have a low level of informatization. Information and data are collected using paper records and then manually entered into computers by sample library staff. This model is not only time-consuming and labor-intensive, but also prone to errors. The early biological sample libraries only have simple storage functions, and the research on samples is not in-depth, making it difficult to make due contributions to translational medicine, which is mainly reflected in the following aspects: Data lag: Traditional process flow monitoring systems need to collect data, analyze data, and then generate reports, which takes a certain amount of time, resulting in data lag and inability to reflect real-time situations in a timely manner; Data analysis difficulties: Lack of intelligent analysis functions, data cannot be effectively classified, stored, and quickly retrieved, making it time-consuming and labor-intensive for staff to find specific information, and it is difficult to quickly obtain the required data, affecting work efficiency and decision-making speed; Passive monitoring: Traditional process flow monitoring systems can only play a recording role and lack active early warning and intervention capabilities. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a laboratory specimen operation process monitoring system and method to solve the problems existing in the above-mentioned background technology.

[0005] The present invention provides the following technical solution: a laboratory specimen operation process monitoring system, comprising: a specimen knowledge base construction module, a specimen receiving and checking module, a process data acquisition module, a machine fault detection module, a machine fault early warning module, a specimen quality monitoring module, a specimen quality early warning module and an early warning result output module; The specimen knowledge base construction module stores different specimen data into the specimen knowledge base according to the specimen type, and formulates a unique identification code for each specimen; The specimen receiving and checking module comprises a specimen receiving unit and a specimen checking unit. After receiving the specimen, the specimen receiving unit uses a barcode scanner to scan the unique identification code on the specimen and enters the identification information into the system. The specimen checking unit checks the specimen information and confirms receipt of the specimen after checking that it is correct. The process data acquisition module includes a machine data acquisition unit and a specimen parameter acquisition unit. The machine data acquisition unit uses sensors to monitor the operation data of the machine in the specimen processing process in real time. The specimen parameter acquisition unit uses sensors to acquire specimen quality parameter data and transmits the specimen quality parameter data to the machine fault detection module and the specimen quality monitoring module respectively. The machine fault detection module calculates the machine operation power coefficient through the operation monitoring mathematical model based on the operation data transmitted by the process flow data acquisition module, and transmits the calculated machine operation power coefficient to the machine fault warning module; The machine fault warning module receives the machine operation power coefficient transmitted by the machine fault detection module, determines whether the machine operation is normal, and displays an early warning of abnormal results; The sample quality monitoring module calculates the electrolysis activity coefficient of the sample through the sample quality monitoring model based on the sample quality parameters transmitted by the process data acquisition module, and transmits the calculated electrolysis activity coefficient to the sample quality early warning module; The sample quality early warning module receives the electrolysis activity coefficient transmitted by the sample quality monitoring module, determines whether the sample quality is normal, and displays an early warning for abnormal results; The warning result output module receives the abnormal result and transmits the result to the user terminal.

[0006] Preferably, in the specimen knowledge base construction module, different specimen data are stored in the specimen knowledge base according to the specimen type, and the specimen data includes a temperature control range and specimen storage conditions.

[0007] Preferably, in the specimen receiving and checking module, the specimen receiving unit uses a barcode scanner to scan the unique identification code on the specimen, enters the identification information into the system, the system receives and calibrates the specimen, and outputs the corresponding specimen data in the specimen knowledge base, and the specimen checking unit checks whether the specimen is complete and whether necrosis occurs, and confirms receipt of the specimen after verification.

[0008] Preferably, in the process flow data acquisition module, the machine data acquisition unit uses sensors to monitor in real time the operation data of the machine during the specimen processing process, including the pressure value in the atmospheric state, the pressure loss value before the stage during the operation of the machine, the pressure value in the exhaust state, the pressure loss value after the stage during the operation of the machine, and the air volume flow before the stage during the operation of the machine; the specimen parameter acquisition unit uses sensors to acquire specimen quality parameter data, including the charge of positive ions during the electrolysis process, the charge of negative ions during the electrolysis process, the current density during the electrolysis process, the viscosity of the specimen electrolysis solvent, and the molar conductivity before dilution.

[0009] Preferably, in the machine fault detection module, based on the operation data transmitted by the process flow data acquisition module, the specific content of the machine operation power coefficient calculated by the operation monitoring mathematical model is as follows: Step S01: using an automated specimen processing machine to process the received specimen; Step S02: Calculate the pre-stage pressure during the operation of the machine, and the calculation formula is: in Indicates the pre-stage pressure during the operation of the machine. Indicates the pressure value under atmospheric conditions. Indicates the pre-stage pressure loss value during the operation of the machine; Step S03: Calculate the post-stage pressure during the operation of the machine, and the calculation formula is: in Indicates the post-stage pressure during the operation of the machine. Indicates the pressure value under exhaust state. Indicates the post-stage pressure loss value during the operation of the machine; Step S04: Calculate the machine operation compression power according to step S02 and step S03, and the calculation formula is: Where Wp represents the machine operation compression power, Indicates the volume flow of air before the stage during the operation of the machine. represents the adiabatic index; Step S05: Calculate the machine operation power coefficient, the calculation formula is: in Indicates the machine operating power coefficient, Indicates the adiabatic efficiency of the machine operation.

[0010] Preferably, the machine fault warning module receives the machine operation power coefficient transmitted by the machine fault detection module , and the machine operating power coefficient With the preset machine operating power threshold Compare and judge whether the machine is running normally. If the machine power coefficient is Greater than the preset machine operating power threshold , the machine is judged to be operating abnormally, an abnormal result warning is displayed, and the warning information of the abnormal result is transmitted to the warning result output module. If the machine operating power coefficient Less than or equal to the preset machine operating power threshold , it is judged that the machine is operating normally.

[0011] Preferably, in the sample quality monitoring module, based on the sample quality parameters transmitted by the process data acquisition module, the specific content of the electrolytic activity coefficient of the sample is calculated by the sample quality monitoring model as follows: Step S01: Calculate the dielectric constant of the specimen using the following formula: in represents the dielectric constant of the specimen, It represents the charge of positive ions during electrolysis. Indicates the charge of negative ions during electrolysis. is the current density during electrolysis, represents the dielectric constant of the specimen, T represents the thermodynamic temperature; Step S02: Calculate the viscosity coefficient of the specimen, the calculation formula is: in represents the viscosity coefficient of the specimen, Indicates the viscosity of the specimen electrolysis solvent; Step S03: Calculate the electrolytic dilution molar conductivity according to step S01 and step S02, and the calculation formula is: in represents the electrolytic dilution molar conductivity, represents the molar conductivity before dilution, Indicates the current value during the electrolysis process; Step S04: Calculate the electrolytic activity coefficient of the sample, the calculation formula is: in Represents the electrolytic activity coefficient of the specimen.

[0012] Preferably, the sample quality warning module receives the electrolysis activity coefficient transmitted by the sample quality monitoring module. , and the electrolytic activity coefficient With the preset electrolytic activity threshold Compare and judge whether the sample quality is normal. If the electrolysis activity coefficient Less than the preset electrolytic activity threshold , the sample quality is judged to be abnormal, an abnormal result warning is displayed, and the warning information of the abnormal result is transmitted to the warning result output module. If the electrolysis activity coefficient Greater than or equal to the preset electrolytic activity threshold , it is judged that the machine is operating normally.

[0013] Preferably, the warning result output module receives the warning information transmitted by the machine failure warning module and the specimen quality warning module, and transmits the warning result to the user terminal via information reminder.

[0014] A laboratory specimen operation process monitoring method comprises the following steps: Step S1: storing different specimen data into a specimen knowledge base according to the specimen type, and generating a unique identification code for each specimen; Step S2: Use a barcode scanner to scan the unique identification code on the specimen, verify the specimen information, and confirm receipt of the specimen after verification; Step S3: using sensors to monitor the machine operation data and sample quality parameter data in real time during the sample processing process; Step S4: Based on the operation data transmitted by the process data acquisition module, the machine operation power coefficient is calculated through the operation monitoring mathematical model; Step S5: judging whether the machine is operating normally according to the machine operating power coefficient, and displaying an early warning of abnormal results; Step S6: Based on the sample quality parameters transmitted by the process data acquisition module, the electrolysis activity coefficient of the sample is calculated by the sample quality monitoring model; Step S7: judging whether the sample quality is normal based on the electrolytic activity coefficient, and displaying an early warning for abnormal results; Step S8: Receive abnormal results and transmit the results to the user terminal.

[0015] Technical effects and advantages of the present invention: The present invention is provided with a specimen knowledge base construction module, a specimen receiving and checking module, a process flow data acquisition module, a machine fault detection module, a machine fault warning module, a specimen quality monitoring module, a specimen quality warning module and a warning result output module. By using a barcode scanner to scan a unique identification code on the specimen, the specimen information is checked, and the operation data and specimen quality parameter data of the machine during the specimen processing are monitored in real time by a sensor. The machine operation power coefficient is calculated by an operation monitoring mathematical model to determine whether the machine operation is normal, and an abnormal result warning is displayed. The electrolytic activity coefficient of the specimen is calculated by a specimen quality monitoring model to determine whether the specimen quality is normal, and an abnormal result warning is displayed. In short, a laboratory specimen operation process flow monitoring system and method monitors each link of the specimen operation process flow in real time to ensure the safety of the specimen. When potential risks or problems are found, the system automatically issues a warning to remind relevant personnel to deal with them in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flow chart of a monitoring module of a laboratory specimen operation process monitoring system.

[0017] Figure 2 The present invention is a schematic diagram of the method steps of a laboratory specimen operation process monitoring method. DETAILED DESCRIPTION

[0018] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures recorded in the following embodiments are merely illustrative. The laboratory specimen operation process monitoring system and method involved in the present invention are not limited to the various structures recorded in the following embodiments. All other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0019] like Figure 1 As shown, the present invention provides a laboratory specimen operation process monitoring system, including: a specimen knowledge base construction module, a specimen receiving and checking module, a process data acquisition module, a machine fault detection module, a machine fault warning module, a specimen quality monitoring module, a specimen quality warning module and a warning result output module; The specimen knowledge base construction module stores different specimen data into the specimen knowledge base according to the specimen type, and formulates a unique identification code for each specimen; The specimen receiving and checking module comprises a specimen receiving unit and a specimen checking unit. After receiving the specimen, the specimen receiving unit uses a barcode scanner to scan the unique identification code on the specimen and enters the identification information into the system. The specimen checking unit checks the specimen information and confirms receipt of the specimen after checking that it is correct. The process data acquisition module includes a machine data acquisition unit and a specimen parameter acquisition unit. The machine data acquisition unit uses sensors to monitor the operation data of the machine in the specimen processing process in real time. The specimen parameter acquisition unit uses sensors to acquire specimen quality parameter data and transmits the specimen quality parameter data to the machine fault detection module and the specimen quality monitoring module respectively. The machine fault detection module calculates the machine operation power coefficient through the operation monitoring mathematical model based on the operation data transmitted by the process flow data acquisition module, and transmits the calculated machine operation power coefficient to the machine fault warning module; The machine fault warning module receives the machine operation power coefficient transmitted by the machine fault detection module, determines whether the machine operation is normal, and displays an early warning of abnormal results; The sample quality monitoring module calculates the electrolysis activity coefficient of the sample through the sample quality monitoring model based on the sample quality parameters transmitted by the process data acquisition module, and transmits the calculated electrolysis activity coefficient to the sample quality early warning module; The sample quality early warning module receives the electrolysis activity coefficient transmitted by the sample quality monitoring module, determines whether the sample quality is normal, and displays an early warning for abnormal results; The warning result output module receives the abnormal result and transmits the result to the user terminal.

[0020] In this embodiment, it should be specifically explained that in the specimen knowledge base construction module, different specimen data are stored in the specimen knowledge base according to the specimen type, and the specimen data includes the temperature control range and the specimen storage conditions.

[0021] In this embodiment, it should be specifically explained that in the specimen receiving and checking module, the specimen receiving unit uses a barcode scanner to scan the unique identification code on the specimen, enters the identification information into the system, and the system receives and calibrates the specimen and outputs the corresponding specimen data in the specimen knowledge base. The specimen checking unit checks whether the specimen is complete and whether necrosis occurs, and confirms the receipt of the specimen after the verification is correct; Commonly used barcode scanners include one-dimensional barcode scanners and two-dimensional barcode scanners. It is very important to choose the right scanner according to the type of barcode on the specimen. Performance requirements: The scanner needs to have high reading speed, high reliability and the ability to read over a long distance and a large range to meet the scanning needs in different environments. Speciality: Considering the particularity of the medical industry, choosing a scanner with a medical industry-specific optimized decoding algorithm can improve recognition accuracy and reduce the occurrence of errors and missing codes. The scanner will automatically read the information in the barcode and convert it into digital signals for processing. After the scanning is completed, the scanner displays the read information and transmits the information to the computer database connected to it for storage.

[0022] In the present embodiment, it should be specifically explained that in the process data acquisition module, the machine data acquisition unit uses sensors to monitor the operation data of the machine in the sample processing process in real time, including the pressure value in the atmospheric state, the pressure loss value before the stage during the operation of the machine, the pressure value in the exhaust state, the pressure loss value after the stage during the operation of the machine, and the air volume flow before the stage during the operation of the machine; the sample parameter acquisition unit uses sensors to obtain sample quality parameter data, including the charge of positive ions in the electrolysis process, the charge of negative ions in the electrolysis process, the current density in the electrolysis process, the viscosity of the sample electrolysis solvent, and the molar conductivity before dilution.

[0023] In this embodiment, it should be specifically explained that, in the machine fault detection module, based on the operation data transmitted by the process flow data acquisition module, the specific content of the machine operation power coefficient calculated by the operation monitoring mathematical model is as follows: Step S01: using an automated specimen processing machine to process the received specimen; Step S02: Calculate the pre-stage pressure during the operation of the machine, and the calculation formula is: in Indicates the pre-stage pressure during the operation of the machine. Indicates the pressure value under atmospheric conditions. Indicates the pre-stage pressure loss value during the operation of the machine; Step S03: Calculate the post-stage pressure during the operation of the machine, and the calculation formula is: in Indicates the post-stage pressure during the operation of the machine. Indicates the pressure value under exhaust state. Indicates the post-stage pressure loss value during the operation of the machine; Step S04: Calculate the machine operation compression power according to step S02 and step S03, and the calculation formula is: Where Wp represents the machine operation compression power, Indicates the volume flow of air before the stage during the operation of the machine. represents the adiabatic index; Step S05: Calculate the machine operation power coefficient, the calculation formula is: in Indicates the machine operating power coefficient, Indicates the adiabatic efficiency of the machine operation.

[0024] In this embodiment, it should be specifically explained that the machine fault warning module receives the machine operation power coefficient transmitted by the machine fault detection module. , and the machine operating power coefficient With the preset machine operating power threshold Compare and judge whether the machine is running normally. If the machine power coefficient is Greater than the preset machine operating power threshold , the machine is judged to be operating abnormally, an abnormal result warning is displayed, and the warning information of the abnormal result is transmitted to the warning result output module. If the machine operating power coefficient Less than or equal to the preset machine operating power threshold , it is judged that the machine is operating normally.

[0025] In this embodiment, it should be specifically explained that in the sample quality monitoring module, based on the sample quality parameters transmitted by the process data acquisition module, the specific content of the electrolytic activity coefficient of the sample calculated by the sample quality monitoring model is as follows: Step S01: Calculate the dielectric constant of the specimen using the following formula: in represents the dielectric constant of the specimen, It represents the charge of positive ions during electrolysis. Indicates the charge of negative ions during electrolysis. is the current density during electrolysis, represents the dielectric constant of the specimen, T represents the thermodynamic temperature; Step S02: Calculate the viscosity coefficient of the specimen, the calculation formula is: in represents the viscosity coefficient of the specimen, Indicates the viscosity of the specimen electrolysis solvent; Step S03: Calculate the electrolytic dilution molar conductivity according to step S01 and step S02, and the calculation formula is: in represents the electrolytic dilution molar conductivity, represents the molar conductivity before dilution, Indicates the current value during the electrolysis process; Step S04: Calculate the electrolytic activity coefficient of the sample, the calculation formula is: in Represents the electrolytic activity coefficient of the specimen.

[0026] In this embodiment, it should be specifically explained that the sample quality warning module receives the electrolysis activity coefficient transmitted by the sample quality monitoring module. , and the electrolytic activity coefficient With the preset electrolytic activity threshold Compare and judge whether the sample quality is normal. If the electrolysis activity coefficient Less than the preset electrolytic activity threshold , the sample quality is judged to be abnormal, an abnormal result warning is displayed, and the warning information of the abnormal result is transmitted to the warning result output module. If the electrolysis activity coefficient Greater than or equal to the preset electrolytic activity threshold , it is judged that the machine is operating normally.

[0027] In this embodiment, it should be specifically explained that the warning result output module receives the warning information transmitted by the machine failure warning module and the specimen quality warning module, and transmits the warning result to the user terminal through information reminder.

[0028] like Figure 2 As shown, in this embodiment, it should be specifically explained that the method for using a laboratory specimen operation process monitoring system and method includes the following steps: Step S1: storing different specimen data into a specimen knowledge base according to the specimen type, and generating a unique identification code for each specimen; Step S2: Use a barcode scanner to scan the unique identification code on the specimen, verify the specimen information, and confirm receipt of the specimen after verification; Step S3: using sensors to monitor the machine operation data and sample quality parameter data in real time during the sample processing process; Step S4: Based on the operation data transmitted by the process data acquisition module, the machine operation power coefficient is calculated through the operation monitoring mathematical model; Step S5: judging whether the machine is operating normally according to the machine operating power coefficient, and displaying an early warning of abnormal results; Step S6: Based on the sample quality parameters transmitted by the process data acquisition module, the electrolysis activity coefficient of the sample is calculated by the sample quality monitoring model; Step S7: judging whether the sample quality is normal based on the electrolytic activity coefficient, and displaying an early warning for abnormal results; Step S8: Receive abnormal results and transmit the results to the user terminal.

[0029] In this embodiment, it should be specifically explained that the difference between this embodiment and the prior art lies mainly in that this embodiment is provided with a specimen knowledge base construction module, a specimen receiving and checking module, a process flow data acquisition module, a machine fault detection module, a machine fault warning module, a specimen quality monitoring module, a specimen quality warning module and a warning result output module. By using a barcode scanner to scan the unique identification code on the specimen, the specimen information is checked, and the sensor is used to monitor the operation data and specimen quality parameter data of the machine in real time during the specimen processing process. The machine operation power coefficient is calculated by the operation monitoring mathematical model to determine whether the machine operation is normal, and an abnormal result warning is displayed. The electrolytic activity coefficient of the specimen is calculated by the specimen quality monitoring model to determine whether the specimen quality is normal, and an abnormal result warning is displayed. In short, a laboratory specimen operation process flow monitoring system and method monitors each link of the specimen operation process flow in real time to ensure the safety of the specimen. When potential risks or problems are found, the system automatically issues a warning to remind relevant personnel to deal with them in time.

[0030] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0031] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A laboratory specimen operation process monitoring system, characterized in that: include: Specimen knowledge base construction module, specimen receiving and checking module, process data acquisition module, machine fault detection module, machine fault early warning module, specimen quality monitoring module, specimen quality early warning module and early warning result output module; The specimen knowledge base construction module stores different specimen data into the specimen knowledge base according to the specimen type, and formulates a unique identification code for each specimen; The specimen receiving and checking module comprises a specimen receiving unit and a specimen checking unit. After receiving the specimen, the specimen receiving unit uses a barcode scanner to scan the unique identification code on the specimen and enters the identification information into the system. The specimen checking unit checks the specimen information and confirms receipt of the specimen after checking that it is correct. The process data acquisition module includes a machine data acquisition unit and a specimen parameter acquisition unit. The machine data acquisition unit uses sensors to monitor the operation data of the machine in the specimen processing process in real time. The specimen parameter acquisition unit uses sensors to acquire specimen quality parameter data and transmits the specimen quality parameter data to the machine fault detection module and the specimen quality monitoring module respectively. The machine fault detection module calculates the machine operation power coefficient through the operation monitoring mathematical model based on the operation data transmitted by the process flow data acquisition module, and transmits the calculated machine operation power coefficient to the machine fault warning module; The machine fault warning module receives the machine operation power coefficient transmitted by the machine fault detection module, determines whether the machine operation is normal, and displays an early warning of abnormal results; The sample quality monitoring module calculates the electrolysis activity coefficient of the sample through the sample quality monitoring model based on the sample quality parameters transmitted by the process data acquisition module, and transmits the calculated electrolysis activity coefficient to the sample quality early warning module; The sample quality early warning module receives the electrolysis activity coefficient transmitted by the sample quality monitoring module, determines whether the sample quality is normal, and displays an early warning for abnormal results; The warning result output module receives the abnormal result and transmits the result to the user terminal.

2. A laboratory specimen operation process monitoring system according to claim 1, characterized in that: In the specimen knowledge base construction module, different specimen data are stored in the specimen knowledge base according to the specimen type, and the specimen data includes the temperature control range and the specimen storage conditions.

3. A laboratory specimen operation process monitoring system according to claim 1, characterized in that: In the specimen receiving and checking module, the specimen receiving unit uses a barcode scanner to scan the unique identification code on the specimen, enters the identification information into the system, the system receives and calibrates the specimen, and outputs the corresponding specimen data in the specimen knowledge base. The specimen checking unit checks whether the specimen is complete and whether necrosis occurs, and confirms receipt of the specimen after verification.

4. A laboratory specimen operation process monitoring system according to claim 1, characterized in that: In the process data acquisition module, the machine data acquisition unit uses sensors to monitor the operation data of the machine in the sample processing process in real time, including the pressure value in the atmospheric state, the pressure loss value before the stage during the operation of the machine, the pressure value in the exhaust state, the pressure loss value after the stage during the operation of the machine, and the air volume flow before the stage during the operation of the machine. The sample parameter acquisition unit uses sensors to obtain sample quality parameter data, including the charge of positive ions in the electrolysis process, the charge of negative ions in the electrolysis process, the current density in the electrolysis process, the viscosity of the sample electrolysis solvent, and the molar conductivity before dilution.

5. A laboratory specimen operation process monitoring system according to claim 1, characterized in that: In the machine fault detection module, based on the operation data transmitted by the process data acquisition module, the specific content of the machine operation power coefficient is calculated by the operation monitoring mathematical model as follows: Step S01: using an automated specimen processing machine to process the received specimen; Step S02: Calculate the pre-stage pressure during the operation of the machine, and the calculation formula is: in Indicates the pressure before the stage during the operation of the machine. Indicates the pressure value under atmospheric conditions. Indicates the pre-stage pressure loss value during the operation of the machine; Step S03: Calculate the post-stage pressure during the operation of the machine, and the calculation formula is: in Indicates the post-stage pressure during the operation of the machine. Indicates the pressure value under exhaust state. Indicates the post-stage pressure loss value during the operation of the machine; Step S04: Calculate the machine operation compression power according to step S02 and step S03, and the calculation formula is: Where Wp represents the machine operation compression power, Indicates the volume flow of air before the stage during the operation of the machine. represents the adiabatic index; Step S05: Calculate the machine operation power coefficient, the calculation formula is: in Indicates the machine operating power coefficient, Indicates the adiabatic efficiency of the machine operation.

6. A laboratory specimen operation process monitoring system according to claim 1, characterized in that: The machine fault warning module receives the machine operation power coefficient transmitted by the machine fault detection module , and the machine operating power coefficient With the preset machine operating power threshold Compare and judge whether the machine is running normally. If the machine power coefficient is Greater than the preset machine operating power threshold , the machine is judged to be operating abnormally, an abnormal result warning is displayed, and the warning information of the abnormal result is transmitted to the warning result output module. If the machine operating power coefficient Less than or equal to the preset machine operating power threshold , it is judged that the machine is operating normally.

7. A laboratory specimen operation process monitoring system according to claim 1, characterized in that: In the sample quality monitoring module, based on the sample quality parameters transmitted by the process data acquisition module, the specific content of the electrolytic activity coefficient of the sample is calculated by the sample quality monitoring model as follows: Step S01: Calculate the dielectric constant of the specimen using the following formula: in represents the dielectric constant of the specimen, It represents the charge of positive ions during electrolysis. Indicates the charge of negative ions during electrolysis. is the current density during electrolysis, represents the dielectric constant of the specimen, T represents the thermodynamic temperature; Step S02: Calculate the viscosity coefficient of the specimen, the calculation formula is: in represents the viscosity coefficient of the specimen, Indicates the viscosity of the specimen electrolysis solvent; Step S03: Calculate the electrolytic dilution molar conductivity according to step S01 and step S02, and the calculation formula is: in represents the electrolytic dilution molar conductivity, represents the molar conductivity before dilution, Indicates the current value during the electrolysis process; Step S04: Calculate the electrolytic activity coefficient of the sample, the calculation formula is: in Represents the electrolytic activity coefficient of the specimen.

8. A laboratory specimen operation process monitoring system according to claim 1, characterized in that: The sample quality warning module receives the electrolysis activity coefficient transmitted by the sample quality monitoring module. , and the electrolytic activity coefficient With the preset electrolytic activity threshold Compare and judge whether the sample quality is normal. If the electrolysis activity coefficient Less than the preset electrolytic activity threshold , the sample quality is judged to be abnormal, an abnormal result warning is displayed, and the warning information of the abnormal result is transmitted to the warning result output module. If the electrolysis activity coefficient Greater than or equal to the preset electrolytic activity threshold , it is judged that the machine is operating normally.

9. A laboratory specimen operation process monitoring system according to claim 1, characterized in that: The warning result output module receives the warning information transmitted by the machine failure warning module and the specimen quality warning module, and transmits the warning result to the user terminal through information reminder.

10. A laboratory specimen operation process monitoring method, used for using a laboratory specimen operation process monitoring system according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step S1: storing different specimen data into a specimen knowledge base according to the specimen type, and generating a unique identification code for each specimen; Step S2: Use a barcode scanner to scan the unique identification code on the specimen, verify the specimen information, and confirm receipt of the specimen after verification; Step S3: using sensors to monitor the machine operation data and sample quality parameter data in real time during the sample processing process; Step S4: Based on the operation data transmitted by the process data acquisition module, the machine operation power coefficient is calculated through the operation monitoring mathematical model; Step S5: judging whether the machine is operating normally according to the machine operating power coefficient, and displaying an early warning of abnormal results; Step S6: Based on the sample quality parameters transmitted by the process data acquisition module, the electrolysis activity coefficient of the sample is calculated by the sample quality monitoring model; Step S7: judging whether the sample quality is normal based on the electrolytic activity coefficient, and displaying an early warning for abnormal results; Step S8: Receive abnormal results and transmit the results to the user terminal.

Images