Component abnormality detection system, automatic analyzer, and component abnormality detection method

Abstract

Provided is a component abnormality detecting system for detecting an abnormality of a component of a liquid transport system that sucks in and discharges a liquid to and from a sample inspection sensor of an automated analyzing device, the component abnormality detecting system comprising a storage device for storing data of an electrical signal output by the sensor, and a processing device for processing the data recorded in the storage device, wherein the processing device detects an abnormality of a component of the liquid transport system on the basis of the electrical signal.

Description

[Technical Field]

[0001] The present invention relates to a component abnormality detection system, an automatic analyzer, and a component abnormality detection method. [Background technology]

[0002] An automated analyzer generally consists of more than 1,000 different parts. If a part fails, it must be repaired or replaced immediately to minimize downtime.

[0003] Patent Document 1 discloses a technology that generates a failure prediction algorithm from data related to the occurrence of failures in an automatic analyzer, and uses this algorithm to predict failures such as damage to parts based on at least one of the calibration and quality control data of the automatic analyzer. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2019-536049 Summary of the Invention [Problem to be solved by the invention]

[0005] Some automated analyzers are equipped with a liquid transport system that supplies and discharges liquids such as samples, reagents, and cleaning solutions to sensors (such as flow cells) that measure samples. The liquid transport system is composed of components such as a flow path through which the liquid flows, multiple valves that open and close the flow path, and syringes that draw in and discharge the liquid. These liquid transport system components are usually replaced periodically, and automated analyzers generally do not have a mechanism for actively detecting failures in the liquid transport system components.

[0006] An object of the present invention is to provide a component abnormality detection system capable of detecting abnormalities in components of a liquid transport system, an automatic analyzer equipped with this component abnormality detection system, and a component abnormality detection method. [Means for solving the problem]

[0007] In order to achieve the above object, the present invention provides a component abnormality detection system that detects abnormalities in components of a liquid transport system that draws in and discharges liquid to a sensor for sample testing in an automatic analyzer, the component abnormality detection system comprising a memory device that stores data on the electrical signal output by the sensor, and a processing device that processes the data recorded in the memory device, and the processing device detects abnormalities in components of the liquid transport system based on the electrical signal. [Effects of the Invention]

[0008] According to the present invention, abnormalities in components of the liquid transport system of an automatic analyzer can be detected. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a plan view schematically illustrating an example of the configuration of an automatic analyzer to which the component abnormality detection system according to the first embodiment is applied; [Figure 2] Schematic diagram of the liquid transport system installed in the automatic analyzer shown in Figure 1 [Figure 3] Schematic diagram of the sensor used to measure samples in the automated analyzer shown in Figure 1 [Figure 4] Timing chart showing the measurement cycle in the automatic analyzer shown in FIG. 1 [Figure 5] Block diagram showing the data processing flow in the automatic analyzer shown in Figure 1. [Figure 6] FIG. 1 is a diagram showing an example of time-series data of luminescence intensity measured during sample measurement. [Figure 7] FIG. 10 is a diagram showing an example of time-series data of voltage values ​​measured during sample measurement. [Figure 8] FIG. 1 is a diagram showing an example of time-series data of current values ​​measured during sample measurement. [Figure 9] FIG. 10 is a diagram showing an example of time-series data of resistance values ​​measured during sample measurement. [Figure 10]Block diagram showing the process flow for detecting component abnormalities in a server [Figure 11] Flowchart showing the detailed steps of the flow in Figure 10 [Figure 12] A diagram showing an example of a screen for setting anomaly detection conditions. [Figure 13] FIG. 10 is a block diagram showing a data processing flow in a component abnormality detection system according to a second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] (overview) The component abnormality detection system according to this embodiment is a system that detects abnormalities in components of a liquid transport system that draws in and discharges liquid to a sensor for liquid sample testing in an automatic analyzer.

[0011] A liquid sample testing sensor provided in an automated analyzer is a sensor used to measure analytical parameters of biological samples in, for example, a biochemical analyzer, an immunoanalyzer, a blood coagulation time analyzer, or an ISE analyzer. One example of such a sensor is a flow cell-type sensor for electrochemiluminescence measurement. This flow cell-type sensor includes, for example, a flow cell, electrodes (a reference electrode, a counter electrode, and a working electrode) provided in the flow cell, and a photoelectric conversion sensor (e.g., a photomultiplier tube) positioned on the opposite side of the flow cell from the reference electrode. This type of sensor outputs, as a response value, not only the measured value of the analytical parameter of the sample (the concentration of the analyte component) but also analog electrical signals (current, voltage, and resistance) generated between the counter electrode and the working electrode when a voltage is applied between the reference electrode and the working electrode. In an automated analyzer, sensor outputs (analog electrical signals output from the sensor) at multiple times during the measurement cycle of the same sample, for example, during sample measurement, sensor cleaning, and electrode conditioning.

[0012] The components of the liquid transport system that draw in and discharge liquid from the sensor are the targets of diagnosis by the component abnormality detection system. The liquid transport system includes, for example, a flow path through which the liquid flows, multiple valves that open and close the flow path, and a syringe that generates a pressure difference in the flow path to draw in and discharge the liquid. The liquid transported by the liquid transport system includes samples, reagents, and cleaning solutions. Samples include at least one type (one or more types) of patient specimens (blood, urine, etc.), calibration samples (standard samples), QC (quality control) samples, and dummy samples. Calibration samples are prepared samples that are measured to create a calibration curve when calibrating an automatic analyzer. QC samples are prepared samples that are measured during QC of an automatic analyzer. Dummy samples are predetermined samples that are measured as a preparatory operation before measuring patient samples.

[0013] The component abnormality detection system can be configured, for example, by a computer provided in the automatic analyzer. Alternatively, the component abnormality detection system can be configured by a single or multiple computers (e.g., servers) connected to the computer provided in the automatic analyzer via a network (e.g., local area network, global network). The component abnormality detection system can also be configured by a computer provided in the automatic analyzer and at least one computer connected to it.

[0014] The component abnormality detection system includes a storage device (storage medium such as RAM, ROM, HHD, SSD, etc.) that stores the sensor output data, and a processing device (CPU, etc.) that processes the data recorded in the storage device. The processing device detects abnormalities in components of the liquid transport system, such as valves, based on the output of sensors used in liquid sample testing in the automatic analyzer. The storage device stores the sensor output data as well as a component abnormality detection program and various data used in the program's algorithm.

[0015] To detect component abnormalities, a preset value (threshold value) can be set based on the relationship between sensor output and component abnormalities, and an algorithm can be applied that simply compares the sensor output with the preset value to determine whether or not a component abnormality exists.

[0016] Another preferred example is an algorithm that calculates a statistical value of sensor output data as an index and detects an abnormality in a component of the liquid transport system, such as a valve, based on this statistical value. One example is an algorithm that reads sensor output data extracted from a set period from a storage device, calculates the data variance for the set period as the statistical value, and determines that an abnormality exists in a component of the liquid transport system if the statistical value is equal to or greater than a set value. The set period is a period that is preset and stored in a storage device, such as a period ending at the present time (e.g., the last 24 hours). The sensor output on which the statistical value is based can be at least one of the sensor outputs acquired during measurement, cleaning, and conditioning. If an abnormality in a component is detected by comparing the sensor output with a set value, the timing of the sensor output can be used to identify the abnormal component of the liquid transport system or the type of abnormality (abnormal mode). In this case, the abnormal component or abnormal mode of the liquid transport system can be estimated based on a single sensor output, or multiple sensor outputs output from sensors at multiple times during the measurement cycle of the same sample.

[0017] While it is possible to compile statistics on all sensor outputs acquired during operation of the automated analyzer, it is preferable to compile statistics on sensor outputs extracted under specified conditions as needed. For example, some automated analyzers are equipped with a function that issues an alarm if an abnormality is detected during measurement, cleaning, or conditioning. For example, an alarm is recorded if the measured value (concentration of the analyte) is higher or lower than the appropriate range, if the EV (effective value) of the current generated when a control voltage is applied to the electrode is higher than the appropriate value, or if the EV of the luminescence of the reaction product during measurement is lower than the appropriate value. The sensor output obtained at each measurement time when an alarm is issued can be suitably used as the basis for statistical values.

[0018] Through extensive research, the present inventors discovered that sensor output values, such as the current generated at the electrodes, change significantly during measurements that trigger alarms in automated analyzers. If a malfunction in the liquid delivery system interferes with the replacement of liquid in the flow cell, preventing the proper liquid from being present in the flow cell, this can trigger an alarm. It can be said that there is a causal relationship between the occurrence of an alarm and a malfunction in the liquid delivery system. Therefore, diagnosing components based on statistical values ​​using sensor output from measurements that trigger an alarm can improve the accuracy of component anomaly detection. Furthermore, if a false anomaly is detected even when a component in the liquid delivery system is functioning normally, the automated analyzer must be shut down unnecessarily to confirm the anomaly. From the perspective of avoiding unnecessary shutdowns of the automated analyzer, it can be advantageous to exclude sensor output from measurements that do not trigger an alarm and diagnose components by statistically analyzing only sensor output (electrical signal at the time of the alarm) that may be correlated with a malfunction in the liquid delivery system.

[0019] Furthermore, when collecting statistics on sensor outputs related to measurements that have been given alarms, the processing device may be configured to select the type of alarm related to the sensor output to be collected and adjust the anomaly detection sensitivity. For example, when sensitivity is set as an anomaly detection condition on a user interface (monitor or input device) of the component anomaly detection system, the processing device may select an alarm type according to the set sensitivity and collect statistics on the sensor outputs related to the selected alarm to detect component anomalies. From the perspective of adjusting the anomaly detection sensitivity, a configuration is also conceivable in which the processing device adjusts a set value (a value to be compared with a statistical value to determine an anomaly) to adjust the anomaly detection sensitivity. Specifically, a configuration is exemplified in which when sensitivity is set on a user interface, the processing device changes the set value according to the set sensitivity. Of course, a configuration is also conceivable in which the sensitivity is adjusted by changing both the alarm type and the set value. For example, a configuration is exemplified in which data on combinations of alarm types and set values ​​is linked to the set sensitivity and stored in a storage device, and the processing device changes the alarm type and set value according to the set sensitivity.

[0020] Furthermore, the concept of component anomaly detection described above is not necessarily limited to a computer system, but can also be embodied as a method. For example, a user can view log data of sensor outputs and determine whether an anomaly exists in a component of a liquid transport system based on the sensor outputs selected by noting whether an alarm is present or not.

[0021] (First embodiment) The present invention can be applied to an automated analyzer. Examples of detection units installed in an automated analyzer include biochemical analyzers and immunoanalyzers. However, this is merely an example, and the present invention is not limited to the embodiments described below. The present invention can be widely applied to automated analyzers equipped with detection units that analyze samples based on the results of reactions with reagents. For example, automated analyzers equipped with mass spectrometers used in clinical testing and coagulation analyzers that measure blood clotting time can also be included as application targets. The present invention can also be applied to a composite automated analyzer equipped with multiple types of these various detection units, and to an automated analysis system including at least one automated analyzer. Specific embodiments of the component abnormality detection system of the present invention will be described below with reference to the drawings.

[0022] -Automatic analyzer- 1 is a plan view schematically illustrating an example of the configuration of an automatic analyzer to which the component abnormality detection system according to the first embodiment is applied. The automatic analyzer 1 in the figure includes a transport line 2, an incubator (reaction disk) 3, a first transport mechanism 4, a tray 5, a sample dispensing nozzle 6, a reagent disk 7, a reagent dispensing nozzle 8, a second transport mechanism 9, a detection unit 10, a controller 21, an operation device 22, and a control device 30.

[0023] The transport line 2 is a device that transports the rack R, and transports the rack R to a sample dispensing position using a sample dispensing nozzle 6. A plurality of sample containers C1 for holding samples can be installed on the rack R. The example in Figure 1 illustrates a configuration for transporting samples along a line, but there is also a case where a disk-shaped transport unit that rotates to transport the samples is provided.

[0024] The incubator 3 is a turntable-like device in which the reaction vessels C2 are placed, and multiple reaction vessels C2 can be placed in a circle. The incubator 3 is driven to rotate by a drive unit (not shown), and can move any reaction vessel C2 to multiple predetermined positions, such as the dispensing position by the sample dispensing nozzle 6.

[0025] The first transport mechanism 4 is a device that transports sample dispensing tips T and reaction vessels C2. This first transport mechanism 4 is movable in three axes (X, Y, and Z) along rails, and transports sample dispensing tips T and reaction vessels C2 between the incubator 3, the stirring mechanism M, the disposal position D, the tip mounting position P, and the tray 5. The stirring mechanism M is a device that stirs the sample contained in the reaction vessel C2. The disposal position D is a position equipped with a disposal hole for disposing of used sample dispensing tips T and reaction vessels C2. The tip mounting position P is a position for mounting the sample dispensing tip T on the sample dispensing nozzle 6.

[0026] The tray 5 is a container that accommodates a plurality of unused sample dispensing tips T and a plurality of unused reaction vessels C2. An unused reaction vessel C2 is picked up from the tray 5 and placed at a predetermined position in the incubator 3 by the first transport mechanism 4. Similarly, an unused sample dispensing tip T picked up from the tray 5 is transported to the first transport mechanism 4 and placed at the tip mounting position P.

[0027] The sample dispensing nozzle 6 is a device that aspirates and dispenses samples. This sample dispensing nozzle 6 is configured to be rotatable and move up and down. The nozzle tip is moved above the tip mounting position P and then lowered. A sample dispensing tip T prepared at the tip mounting position P is then pressed into the nozzle tip. After the sample dispensing tip T is mounted on the nozzle tip, the sample dispensing nozzle 6 moves its nozzle tip above the sample container C1 placed in the rack R and lowers it, and aspirates a predetermined amount of sample from the sample container C1. After aspirating the sample, the sample dispensing nozzle 6 moves its nozzle tip above the incubator 3 and lowers it, and dispenses the sample into an unused reaction container C2 placed in the incubator 3. After dispensing the sample, the sample dispensing nozzle 6 moves its nozzle tip above the disposal position D and discards the used sample dispensing tip T into a disposal hole.

[0028] The reagent disk 7 is a turntable-like device on which multiple reagent containers C3 are placed. The top of this reagent disk 7 is covered with a disk cover 7a (shown partially cut away in FIG. 1), and the inside is kept at a predetermined temperature. The disk cover 7a has an opening (not shown) at a reagent suction position 7b set near the incubator 3.

[0029] The reagent dispensing nozzle 8 is a device that aspirates and dispenses reagent. Like the sample dispensing nozzle 6, this reagent dispensing nozzle 8 can rotate and move up and down, and moves its nozzle tip to and lowers it at the reagent aspirating position 7b on the reagent disk 7, where it aspirates a predetermined amount of reagent from a predetermined reagent container C3 that has been transported to the reagent aspirating position 7b. Next, the reagent dispensing nozzle 8 lifts its nozzle tip from the reagent container C3, moves it to and lowers it to a predetermined position in the incubator 3, and dispenses the reagent into a reaction container C2 containing a sample that has been transported to this position.

[0030] The reaction vessel C2 into which the sample and reagent have been poured is transported to a predetermined position by the rotation of the incubator 3, and then transferred to the stirring mechanism M by the first transport mechanism 4. The stirring mechanism M stirs and mixes the sample and reagent inside the reaction vessel C2, for example, by rotating the reaction vessel C2. After stirring, the reaction vessel C2 is again transferred to a predetermined position in the incubator 3 by the first transport mechanism 4.

[0031] The second transport mechanism 9 is a device that transfers the reaction vessel C2 between the incubator 3 and the detection unit 10, and is configured to be able to rotate and move up and down. This second transport mechanism 9 picks up the reaction vessel C2 containing the reaction liquid that has been returned to the incubator 3 after mixing the sample and reagent and after a predetermined reaction time has elapsed, and transfers it to the detection unit 10.

[0032] The detection unit 10 is a measuring instrument that measures measurement items such as specific biological components and chemical substances contained in the reaction liquid inside the reaction vessel C2. In this embodiment, the object of abnormality detection is a component of a liquid transport system (described later) used in this detection unit 10.

[0033] The controller 21 is a computer associated with (forming a unit with) the mechanism section 91 (the disk, transport mechanism, dispensing nozzle, detection unit 10, etc. described above) of the automatic analyzer 1. The controller 21 controls the mechanism section 91 of the automatic analyzer 1 in response to signals input from the operation device 22 in response to user operations and signals input from the control device 30.

[0034] The control device 30 is a computer configured to include a storage device 31 such as a RAM, a ROM, an HDD, or an SSD, a processing device 32 such as a CPU, and the like, and is connected to a mechanical section 91 of the automatic analyzer 1 via a controller 21. This control device 30 controls each device of the mechanical section 91 of the automatic analyzer 1, and records and processes data input from the detection unit 10, etc. The control device 30 may be formed as a unit with the mechanical section 91 or controller 21 of the automatic analyzer 1, for example, or it may be installed separately from the mechanical section 91 of the automatic analyzer 1 and directly connected to the controller 21 via a wired or wireless connection.

[0035] In this embodiment, the control device 30 is connected to the server 40 via the communication interface 33, the network NW, and the communication interface 43. The server 40 is also a computer configured to include a storage device 41 such as a RAM, a ROM, an HDD, or an SSD, a processing device 42 such as a CPU, etc. In this embodiment, the server 40 is equipped with a function for detecting abnormalities in components of the liquid transport system used in the automatic analyzer 1. The server 40 records data of electrical signals output by the sensors 11 of the automatic analyzer 1 in the storage device 41, processes the data recorded in the storage device 41 in the processing device 42, and detects abnormalities in components of the liquid transport system of the automatic analyzer 1 based on the sensor output (described below).

[0036] -Liquid transport system- Figure 2 is a schematic diagram of a liquid transport system provided in the automatic analyzer shown in Figure 1. The detection unit 10 of the automatic analyzer 1 is provided with a flow cell type sensor 11 (described below), a liquid transport system 12, and a turntable 13. Here, the configurations of the turntable 13 and the liquid transport system 12 will be described.

[0037] The turntable 13 is equipped with an auxiliary reagent container RG for storing an auxiliary reagent and a detergent container CL for storing a cleaning liquid, and is also equipped with a standby position SP and a reaction container installation position SM. The auxiliary reagent is a chemical liquid for causing a luminescent reaction of the reaction product in the reaction liquid. The cleaning liquid is a liquid for cleaning the flow path of the liquid transport system 12 and the flow cell of the sensor 11. The reaction container C2 transferred from the incubator 3 is installed at the reaction container installation position SM. The turntable 13 is equipped with a drive device (not shown), and is driven to rotate and move up and down by the drive device controlled by signals from the controller 21. The turntable 13 transports, for example, the reaction container C2, detergent container CL, or auxiliary reagent container RG to the liquid suction position of the liquid transport system 12 in a timely manner, and adjusts the standby position SP.

[0038] The liquid delivery system 12 includes flow paths F1-F6 through which the liquid flows, multiple valves V1 and V2 that open and close these flow paths, and a syringe SY that generates a pressure difference in the flow paths to suck and discharge the liquid. Flow path F1 is a flow path (tube) that sends the sucked liquid to the sensor 11. A suction nozzle (not shown) is attached to one end of the flow path F1, and the other end is connected to the sensor 11. Flow path F2 is connected to the opposite side of the sensor 11 from flow path F1, connecting the sensor 11 to valve V1. Flow path F3 connects valves V1 and V2. Flow path F4 connects valve V2 to a drain tank (not shown). Flow path F5 branches off from flow path F3 and connects flow path F3 to syringe SY. Flow path F6 connects syringe SY to a system water supply pump (not shown). The valves V1 and V2 are, for example, solenoid valves. While normally open solenoid valves can also be used, normally closed solenoid valves are used in this embodiment.

[0039] For example, if reaction vessel C2, auxiliary reagent vessel RG, or detergent vessel CL is transported to the suction position of liquid transport system 12, and valve V1 is opened with valve V2 closed and syringe SY is driven for suction, liquid is sucked from a container such as reaction vessel C2 through the suction nozzle. This causes the liquid to be sucked into sensor 11 via flow path F1 and further into flow paths F3 and F5. Also, if valve V1 is opened with the valve closed and syringe SY is driven for discharge, the liquid sucked into flow paths F3 and F5 is discharged into the drain tank.

[0040] -Sensor- Figure 3 is a schematic diagram of a sensor used to measure samples in the automatic analyzer shown in Figure 1. The detection unit 10 of the automatic analyzer 1 is equipped with a flow cell type sensor 11. The sensor 11 is composed of a flow cell FC, three electrodes (reference electrode E1, counter electrode E2, and working electrode E3) provided inside the flow cell FC, and a photoelectric conversion sensor (e.g., a photomultiplier tube) PT that measures the luminescence intensity of the reaction product RP.

[0041] The three electrodes are controlled to the desired voltage by potentiostat 15. When a reaction product RP between the sample and reagent in the reaction solution is collected on reference electrode E1 and a specific voltage is applied between reference electrode E1 and working electrode E3 by potentiostat 15, the reaction product RP emits light. A photoelectric conversion sensor PT is placed on the opposite side of the flow cell FC from the reference electrode E1 (upper side in Figure 3), and this photoelectric conversion sensor PT detects the luminescence intensity of the reaction product RP.

[0042] The luminescence intensity detected by the photoelectric conversion sensor PT is digitized by the A / D converter 18 and recorded as raw data of the measurement value of the measurement item in the storage device 31 (or the storage device of the sensor 11) together with the measurement date and time through a raw data recording process P1. At this time, the potentiostat 15 measures the current value, voltage value, and resistance value generated between the counter electrode E2 and the working electrode E3 by applying a voltage between the reference electrode E1 and the working electrode E3. In this embodiment, not only the output of the photoelectric conversion sensor PT but also the voltage value applied to the reference electrode E1 and the working electrode E3, and the current value, voltage value, and resistance value generated between the counter electrode E2 and the working electrode E3 are recorded in the raw data recording process P1.

[0043] -Operation of automatic analyzer- In order to perform qualitative and quantitative analysis of the analyte components contained in unknown patient samples with high accuracy, calibration and QC measurements are performed in a timely manner. For example, in the case of quantitative analysis, the automated analyzer 1 is operated daily according to the following work procedures (1)-(5).

[0044] (1) Equipment startup First, power is turned on to start up the automatic analyzer 1. Then, reagent container C3 is installed and initially filled with reagent, the temperature inside the reagent disk 7 is adjusted, a constant voltage is applied to the electrode to continuously measure the internal standard solution, and the potential of the electrode of sensor 11 is checked to see if it is stable, and maintenance is performed as necessary.

[0045] (2) Calibration High-concentration standard samples and low-concentration standard samples with known concentrations of the measurement item (analyte component) are measured. From these measurements, a relationship equation (calibration curve) between the concentration of the measurement item and the output of the sensor 11 (photoelectric conversion sensor PT) is created. However, the frequency of calibration differs depending on the measurement item, and for example, calibration for each measurement item is performed periodically (for example, monthly) in turn.

[0046] (3) QC measurement Multiple QC samples with different concentration levels, each with a known range of possible concentrations for the measurement item, are measured, and the concentration of the measurement item in the QC sample is calculated using the calibration curve created during calibration. The appropriateness of the calibration curve is confirmed by checking whether the calculated concentration is within the known concentration range of the QC sample. QC measurements are performed frequently, as they are positioned as a condition check to ensure the measurement results of patient samples. For example, QC measurements are performed 1-3 times per day for multiple measurement items in parallel.

[0047] (4) Measurement of patient samples A patient sample with an unknown concentration of a measurement item is measured, and the concentration of the measurement item is calculated using a calibration curve. Prior to this patient sample measurement, a so-called background measurement or dummy measurement may be performed to check the state of the automatic analyzer 1.

[0048] (5) Shutdown of the device If necessary, each part of the automatic analyzer 1 is cleaned or inspected, and the automatic analyzer 1 is shut down by turning off the power.

[0049] -Measurement cycle- FIG. 4 is a timing chart showing a measurement cycle in the automatic analyzer shown in FIG. As described above, calibration, QC measurement, and patient sample measurement are performed as appropriate from the time the instrument is started up to the time it is shut down, and samples (patient samples, standard samples, QC samples, dummy samples, etc.) are measured at each step. The measurement operations at each step are performed in a series of cycles: electrode conditioning, sample introduction, measurement, and cleaning, as shown in Figure 4.

[0050] For example, in the electrode conditioning process, as shown in Figure 4, auxiliary reagent container RG is transported to the suction position of liquid transport system 12 by the operation of turntable 13. Once auxiliary reagent container RG reaches the suction position, valve V1 is opened with valve V2 closed, and syringe SY is driven to aspirate auxiliary reagent from auxiliary reagent container RG and introduce it into flow cell FC. In parallel with this aspirating operation of auxiliary reagent by syringe SY, potentiostat 15 applies a specific pattern of voltage to the electrode for a certain period of time, bringing the electrode into a state suitable for measurement. Once electrode conditioning is completed in this way, both valves V1 and V2 are closed, and the aspirating operation by syringe SY and the application of voltage to the electrode are stopped. In addition, the sensor output while voltage is applied to the electrode is recorded.

[0051] In the subsequent sample introduction step, reaction vessel C2, which is placed at reaction vessel placement position SM, is transported to the suction position of liquid transfer system 12 by the operation of turntable 13. Once reaction vessel C2 has reached the suction position, valve V1 opens while valve V2 remains closed, and syringe SY is actuated to aspirate the reaction liquid from reaction vessel C2, which is then introduced into flow cell FC. Furthermore, auxiliary reagent vessel RG is transported to the suction position of liquid transfer system 12 by the operation of turntable 13 while valve V1 remains open. Once auxiliary reagent vessel RG has reached the suction position, syringe SY is actuated to aspirate auxiliary reagent from auxiliary reagent vessel RG, which is then introduced into flow cell FC. Once the sample introduction step is completed in this manner, valves V1 and V2 are closed, and the suction operation of syringe SY is stopped.

[0052] In the measurement step, the turntable 13 moves the standby position SP to the suction position of the liquid transport system 12, and the voltage required for the luminescence reaction of the reaction product RP captured by the reference electrode E1 in the sample introduction step is applied by the potentiostat 15. In addition, the sensor output while the voltage is applied to the electrode is recorded.

[0053] In the subsequent cleaning process, valve V1 remains closed while valve V2 opens, and syringe SY is activated to discharge auxiliary reagents and other reagents into the drain tank. Then, both valves V1 and V2 close, and the turntable 13 moves the detergent container CL to the suction position of the liquid delivery system 12. Once the detergent container CL reaches the suction position, valve V1 opens while valve V2 remains closed, and syringe SY is activated to aspirate cleaning fluid from the detergent container CL and introduce it into the flow cell FC. During this process, a voltage pattern different from that used in the electrode conditioning process is applied to the electrodes for a certain period of time while cleaning fluid is flowing through the flow cell FC to prevent reaction products RP from remaining on the flow cell FC. Applying a voltage to the electrodes peels off reaction products RP and other materials adhering to the electrodes, which are then washed away with cleaning fluid and discharged from the flow cell FC. During the cleaning process, the sensor output is recorded while voltage is applied to the electrodes, and once the suction of cleaning fluid is complete, valves V1 and V2 close. Then, the turntable 13 moves the standby position SP to the suction position of the liquid transfer system 12, valve V2 opens while valve V1 is closed, and the cleaning liquid is discharged into the drain tank by the syringe SY. Finally, valve V2 closes, restoring the state to that before the start of the electrode conditioning process.

[0054] Because the set values ​​of the voltages applied to the electrodes differ during each of the electrode conditioning, measurement, and cleaning processes, the voltages applied to the electrodes at multiple times during the same measurement cycle are controlled in a complex manner by potentiostat 15. In sensor 11, complex voltage patterns are precisely and repeatedly applied to the electrodes as samples (patient specimens, standard samples, QC samples, dummy samples, etc.) are measured, and electrical signals such as voltage, current, and resistance generated at the electrodes, as well as measured values ​​of the concentrations of the components to be analyzed, are output.

[0055] -Data processing flow (automatic analyzer)- The automated analyzer 1 records an alarm if an abnormality is detected during the electrode conditioning, measurement, or cleaning steps. Specifically, an alarm is recorded if the measured value (concentration of the analyte component) is outside the appropriate range (high or low), if the EV value of the current generated when voltage is applied is higher than the appropriate value, or if the EV value of the luminescence of the reaction product RP is lower than the appropriate value. For example, if the liquid inside the flow cell FC is not replaced from the cleaning liquid to the auxiliary reagent, the detected current value measured during the electrode conditioning step may increase (e.g., to about 15 mA) from a normal value (e.g., about 10 mA). The component abnormality detection system of this embodiment detects abnormalities in components of the liquid delivery system 12 based on the output of the sensor 11 during the measurement for which the alarm was issued. In particular, in this embodiment, abnormalities in components of the liquid delivery system 12 are detected based only on the sensor output of the sensor 11 related to the measurement for which the alarm was issued.

[0056] Figure 5 is a block diagram showing the processing flow in the automatic analyzer shown in Figure 1. Data is input to the control device 30 of the automatic analyzer 1 from the sensor 11, a mechanical unit 91, a sample data reader 92, a reagent data reader 93, and a UI (user interface) 94.

[0057] The control device 30 receives data recorded in the raw data recording process P1 (FIG. 3) as input from the sensor 11. The data input from the sensor 11 to the control device 30 includes not only data on the measurement cycle of the patient sample measurement, but also data on the measurement cycle of each measurement type, such as QC measurement and calibration, and even dummy measurement, which is performed as a preparation operation immediately before the measurement of the patient sample.

[0058] As mentioned above, the mechanical unit 91 is a collective term for each piece of hardware (such as the sample dispensing nozzle 6 and the incubator 3) mounted on the automatic analyzer 1. Data input from this mechanical unit 91 to the control device 30 is, for example, log data such as the operation timing, operation amount, and current value of each motor, signals from sensors used to control each motor, and the opening / closing timing and current value of fluid valves (such as valves V1 and V2).

[0059] The sample data reader 92 is a device that reads registered data of samples (for example, a barcode or RFID reader) and is provided in the automatic analyzer 1. A storage medium such as a barcode or RFID is attached to the sample container C1, and the sample data recorded on the storage medium is read by the sample data reader 92. The data read by the sample data reader 92 and input to the control device 30 is, for example, a sample ID.

[0060] The reagent data reader 93 is a device that reads registered data of reagents (for example, a barcode or RFID reader), and is provided in the automatic analyzer 1. A storage medium such as a barcode or RFID is attached to the reagent container C3, and the reagent data recorded on the storage medium is read by the reagent data reader 93. The data read by the reagent data reader 93 and input to the control device 30 includes, for example, the reagent ID, lot number, expiration date, etc.

[0061] The UI 94 is comprised of a monitor and input device provided in the automatic analyzer 1, and is used by the user to view data and input data into the control device 30. Various types of data can be input into the control device 30 using the UI 94, and examples of data related to reagents and auxiliary reagents include reagent IDs, lot numbers, expiration dates, onboard expiration dates, and required remaining amounts. Examples of data related to samples include sample IDs, measurement types for the sample IDs (patient sample measurement, QC measurement, calibration, dummy measurement, etc.), measurement items, etc.

[0062] The various data input to the control device 30 from the sensors 11 and the like is processed in real time by the processing device 32 and transmitted as a log file to the server 40 via the communication interface 33. The processing executed by the processing device 32 includes, for example, with respect to sensor output, processes such as a sensor output conversion process P2 and a sensor output recording process P3. Other processes executed by the processing device 32 include an operation log recording process P4, a reagent data recording process P5, a sample data recording process P6, an alarm data recording process P7, and a log file generation process P8. Each process will be explained in turn below.

[0063] Sensor output conversion processing In the sensor output conversion process P2, the processing device 32 converts the sensor output (raw data) input from the sensor 11 into an effective value. The sensor output input from the sensor 11 is raw data of emission intensity, current value, voltage value, and resistance value.

[0064] FIG. 6 shows an example of time-series data of luminescence intensity measured during sample measurement, FIG. 7 shows an example of time-series data of voltage values, FIG. 8 shows an example of time-series data of current values, and FIG. 9 shows an example of time-series data of resistance values. The horizontal axis of each diagram corresponds to time, and the change in each value over time is shown. During sample measurement, the control device 30 applies voltage to the electrodes at a specific timing from the start of measurement to obtain data. In the examples shown in FIGS. 6 to 9, a predetermined voltage is applied to the reference electrode E1 and the working electrode E3 at the timing of the 41st sensor output from the start of measurement, counting in the sensor output cycle.

[0065] Under this control characteristic, in the sensor output conversion process P2, the processing device 32 converts the sensor output (raw data) input from the sensor 11 for each measurement into an EV value (effective value) using the following two formulas pre-stored in the memory device 31 (e.g., ROM).

[0066]

number

[0067]

number

[0068] Sensor output recording processing In the sensor output recording process P3, the processing device 32 assigns a measurement ID to each measurement, and records the raw data and valid values ​​of the measurement values ​​in the storage device 31 in association with the measurement ID.

[0069] Operation log recording process In operation log recording processing P4, the processing device 32 records the operation logs input from the mechanism unit 91 and the sensor 11 in the storage device 31. The operation logs input from the mechanism unit 91 etc. include, for example, the operation timing and operation amount of each motor, the current value of the motor, the signal of the sensor for controlling the operation of the motor, the opening / closing timing and current value of the fluid valves (valves V1, V2 etc.), etc.

[0070] Reagent data recording and processing In the reagent data recording process P5, the processing device 32 compares the reagent data input from the reagent data reader 93 with condition data previously recorded in the storage device 31, and if the condition data matches, records the reagent as a usable reagent in the storage device 31. The condition data with which the reagent data is compared includes the reagent ID, lot number, expiration date, onboard expiration date, required remaining amount, etc., and is input by the UI 94 or another computer, input to the control device 30 via the communication interface 33, and recorded in the storage device 31. Also, in the reagent data recording process P5, the processing device 32 records the history of reagents used for each measurement ID in the storage device 31. This links the raw data and valid values ​​of the measurement values ​​with the data of the reagent used in the measurement via the measurement ID.

[0071] Sample data recording and processing In the sample data recording process P6, the processing device 32 compares the sample data input from the sample data reader 92 with the condition data previously recorded in the storage device 31, and if the condition data matches, records the sample in the storage device 31 as a measurable sample and performs the measurement at the appropriate time. The condition data with which the sample data is compared includes the sample ID, measurement type (QC measurement, measurement of a patient sample, etc.), measurement items, etc., and is input by the UI 94 or by another computer, input to the control device 30 via the communication interface 33, and recorded in the storage device 31.

[0072] Alarm data recording and processing In the alarm data recording process P7, the processing device 32 determines whether or not there is an abnormality in the measurement each time a measurement is performed (each time a control voltage is applied between the reference electrode E1 and the working electrode E3 of the sensor 11). If there is an abnormality in the measurement, alarm data is added to the data set related to the measurement determined to be abnormal and recorded in the storage device 31. The presence or absence of an abnormality in the measurement is determined, for example, by comparing the measured value (the concentration of the analyte component), the EV of the current generated when a control voltage is applied to the electrode, and the EV of the amount of luminescence of the reaction product with respective preset values. For example, if the measured value is higher than the set value (the upper limit of the appropriate range) or lower than the set value (the lower limit of the appropriate range), it is determined that there is an abnormality in the measurement, and an alarm is added to the data set of the output of the sensor 11 acquired in this measurement. Furthermore, if the EV of the current generated between the counter electrode E2 and the working electrode E3 is higher than the set value or the amount of luminescence of the reaction product RP is lower than the set value, it is also determined that there is an abnormality in the measurement, and an alarm is added to the data set of the sensor output acquired in this measurement. The alarm data includes information about the abnormality (measured value too high / measured value too low / current EV value too high / light emission EV value too low).

[0073] Log file generation process In the log file generation process P8, the processing device 32 aggregates data necessary for detecting abnormalities in components of the liquid transport system, such as raw data and alarm data output from the sensor 11, measurement types, etc., from the data stored in the storage device 31 for each measurement (each measurement timing in a measurement cycle) to generate a log file. The processing device 32 also transmits the log file to the server 40 via the communication interface 33 and the network NW. A log file is created for each measurement, uploaded sequentially, and accumulated in the server 40.

[0074] -Component abnormality detection processing flow (server)- 10 is a block diagram showing the processing flow of component abnormality detection by the server. In this embodiment, the component abnormality detection function is executed by the server 40, and the server 40 constitutes a component abnormality detection system for the liquid transport system 12. Upon receiving a log file from the automatic analyzer 1, the processing device 42 records the log file in the storage device 41 in a log file storage process P21. In the subsequent diagnostic data extraction process P22, the processing device 42 extracts diagnostic data, specifically data with an alarm attached, from the log file stored in the storage device 41 to serve as the basis for detecting abnormalities in the components of the liquid transport system 12. In the subsequent diagnostic data storage process P23, the processing device 42 sequentially stores the extracted diagnostic data in the storage device 41.

[0075] Thereafter, in a data counting process P24, the processing device 42 counts the number of alarms during a set period based on the extracted diagnostic data. The set period is a period ending at the present time (e.g., the most recent 24 hours). The set number is a preset value (e.g., 20). When the number of alarms during the set period reaches the set number, the processing device 42 diagnoses the condition of the components of the liquid transfer system 12 based on the diagnostic data related to the set period in a component abnormality diagnosis process P25. The diagnosis results (presence or absence of component abnormalities) are transmitted to the automatic analyzer 1 via the communication interface 43 and the network NW and notified to a user or the like via the display on the UI 94. The diagnosis results can also be displayed on the UI (user interface) 44 of the server 40. The UI 44 of the server 40 is similar to the UI 94 of the control device 30 of the automatic analyzer 1.

[0076] -Decision calculation processing- FIG. 11 is a flowchart showing the detailed procedure of the flow of FIG.

[0077] 11, the processing device 42 acquires a data set of the sensor output from the automatic analyzer 1 and sequentially records the acquired data set in the storage device 41 (step S11). The procedure of step S11 corresponds to the log file storage process P21 described in FIG.

[0078] When a new data set is recorded in the storage device 41, the processing device 42 determines whether the data set includes alarm data (step S12). If alarm data is added, the processing device 42 extracts the data as diagnostic data and stores it in the storage device 41 (step S13). The procedures of steps S12 and S13 correspond to the diagnostic data extraction process P22 and the diagnostic data storage process P23 described in FIG. 10.

[0079] The processing device 42 also counts the number of alarms that have occurred during a set period (the most recent 24 hours) based on the extracted diagnostic data, and determines whether the number of alarms during the set period has reached a set number (20) or more (step S14). If the number of alarms that have occurred during the set period does not reach the set number and it is assumed that the components of the liquid transport system 12 are normal, the processing device 42 continues to repeat the processing of steps S11-S14. Conversely, if the number of alarms that have occurred during the set period reaches or exceeds the set number and it is suspected that there is an abnormality in a component of the liquid transport system 12, the processing device 42 proceeds to a procedure for diagnosing the components of the liquid transport system 12. The procedure of step S14 corresponds to the data counting process P24 described in FIG. 10.

[0080] When the process moves to the procedure for diagnosing the components of the liquid delivery system 12, the processing device 42 first calculates statistical values ​​for evaluating the condition of the components based on the sensor output data. While the statistical method can be changed as appropriate, in this embodiment, the sensor output data extracted from a set period is read from the storage device 42, and the variability of the data for the set period is calculated as a statistical value. As a specific example, FIG. 11 illustrates an algorithm in which the extracted diagnostic data for the set period is statistically calculated (step S15), and a variation coefficient CV is calculated as the statistical value (variability) based on the calculated value (step S16).

[0081] In the procedure of step S15, the standard deviation of the sensor output (EV value of the current in FIG. 8) is calculated using the following equation.

[0082]

number

[0083] In the subsequent procedure of step S16, the processor 42 divides the calculated standard deviation by the average value of the EV values ​​to calculate a variation coefficient CV (the following equation).

[0084]

number

[0085] After calculating the statistical value (fluctuation coefficient CV in this embodiment) for evaluating the condition of the component, the processing device 42 detects an abnormality in the component of the liquid delivery system 12 based on the statistical value. Specifically, in this embodiment, the processing device 42 compares the fluctuation coefficient CV with a preset value and determines whether the fluctuation coefficient CV is equal to or greater than the preset value (step S17). If the statistical value is less than the preset value, it is assumed that the component of the liquid delivery system 12 is functioning normally. However, if the fluctuation coefficient CV is equal to or greater than the preset value, an abnormality in the component of the liquid delivery system 12 is suspected. The component abnormality detection system is configured with this in mind. If the fluctuation coefficient CV is equal to or greater than the preset value, the processing device 42 sends display data to the UI 44 or UI 94 and notifies the user that an abnormality in the component of the liquid delivery system 12 is suspected (step S18), and then ends the flow. If the fluctuation coefficient CV is less than the preset value, the processing device 42 returns to step S11 and continues the processing of steps S11-S17.

[0086] - Judgment condition setting screen - FIG. 12 is a diagram showing an example of a setting screen for anomaly detection conditions. The setting screen shown in the figure is displayed on the UI 44 (FIG. 10) of the server 40, and the UI 44 can be used to set and save anomaly detection conditions for components of the liquid transport system 12. The setting screen can also be displayed on the UI of a computer that can access the server 40, such as the UI 94 of the control device 30 of the automatic analyzer 1, so that anomaly detection conditions can be set from the UI 94 or the like. The setting screen of FIG. 12 is just an example, and it is also possible to set condition items other than those shown in the figure. Furthermore, the setting screen of FIG. 12 can be shared by all automatic analyzers connected to the server 40, or it can be prepared for each ID of an automatic analyzer.

[0087] Detection target / detection mode On the setting screen shown in Figure 12, the target components for abnormality detection in the liquid transport system 12 can be set in the area labeled "Target of abnormality detection." One or more of the three items "flow path," "solenoid valve," and "syringe" can be selected as the target components for abnormality detection. "Flow path" corresponds to flow paths F1-F6, "solenoid valve" corresponds to valves V1 and V2, and "syringe" corresponds to syringe SY.

[0088] Additionally, on the setting screen in the same figure, the anomaly detection method can be set in the area labeled "Detection Mode." As the anomaly detection method, one or more of two options can be selected: "Abnormal Mode Detection" and "Abnormal Location Detection." "Abnormal Mode Detection" is a method for detecting the type of anomaly that has been detected, and "Abnormal Location Detection" is a method for detecting which component in the liquid transfer system 12 is abnormal. "Abnormal Mode" refers to the nature of the anomaly (the type of anomaly), and for example, in the case of valves V1 and V2, this could be a malfunction in opening or closing.

[0089] As explained above with reference to Figure 4, the automatic analyzer 1 can acquire sensor output data at multiple times (electrode conditioning / measurement / cleaning) during the measurement cycle of the same sample. Depending on which of these multiple times the acquired data is used to issue an alarm, it is possible to estimate the component in which an abnormality is observed and the abnormal mode.

[0090] For example, if an alarm occurs during electrode conditioning measurement in one measurement cycle, it is suspected that valve V1 was not opened and the flow cell FC was not filled with the auxiliary reagent (the measurement was performed without the auxiliary reagent remaining inside the flow cell FC). If an alarm occurs during concentration measurement, it is also suspected that valve V1 was not opened and the reaction solution was not introduced into the flow cell FC. In these cases, an abnormality is observed in valve V1, and a malfunction in the opening of valve V1 is suspected as the abnormal mode. If an alarm occurs during cleaning measurement, it is possible that valve V2 was not opened and syringe SY was operated while auxiliary reagent or reaction solution was still sealed between valves V1 and V2, causing pressure to build up between valves V1 and V2. As a result, when valve V1 was opened, liquid flowed back, preventing the cleaning solution from being drawn in. In this case, an abnormality is observed in valve V2, and a malfunction in the opening of valve V2 is suspected as the abnormal mode. If a liquid leak occurs in the flow paths F1-F6 or if the syringe SY malfunctions, the liquid replacement operation inside the flow cell FC will not be performed normally, which may affect the sensor output.

[0091] Patterns can be identified by experiments, simulations, etc. to determine what type of abnormality in which component of the liquid delivery system 12 would affect data acquired at what timing, and the patterns can be stored in, for example, the storage device 41. This allows the processing device 42 to determine the abnormal component of the liquid delivery system 12 and its abnormal mode based on the sensor output data acquired at least at one of a plurality of timings, for example, in step S18 of Fig. 11.

[0092] Detection sensitivity Additionally, on the settings screen in the figure, the anomaly detection sensitivity can be set in the area labeled "Detection Sensitivity." The anomaly detection sensitivity can be set to one of three levels: "High," "Medium," or "Low."

[0093] Regarding the setting of anomaly detection conditions, for example, detection sensitivity, the processing device 42 adjusts the sensitivity of anomaly detection by changing the set period for counting the number of alarms in step S14 of FIG. 11. In this case, the longer the set period, the higher the detection sensitivity. For example, if the set period for "high" detection sensitivity is set to 48 hours, the set period for "medium" detection sensitivity is set to 24 hours, and the set period for "low" detection sensitivity is set to 12 hours, the processing device 42 selects one of the set periods from 48 hours, 24 hours, or 12 hours depending on the set detection sensitivity.

[0094] The detection sensitivity can also be adjusted depending on the type of alarm associated with the sensor output being the statistical target. As previously described with reference to Figures 6-9, in the automated analyzer 1, multiple types of electrical signals, such as the amount of light emitted, current, voltage, and resistance, are output from the sensor 11 during the same measurement session. A predetermined judgment is made based on these values, and alarm data is issued if an abnormality is detected. Specifically, as previously illustrated, an alarm is recorded when the measured value is higher than the appropriate value, when the measured value is lower than the appropriate value, when the EV of the current generated in the electrode is higher than the appropriate value, or when the EV of the amount of light emitted by the reaction product is lower than the appropriate value. For example, in step S13 of Figure 11, the test sensitivity can be changed depending on which of the multiple alarms is selected as diagnostic data. For example, a configuration is conceivable in which a total of four types of alarms are set for "high" detection sensitivity, two or three predetermined types of alarms are set for "medium" detection sensitivity, and one or two predetermined types of alarms are set for "low" detection sensitivity, and the processing device 42 selects and adjusts the detection sensitivity according to the detection sensitivity setting. It is also possible to configure the system so that the type of alarm is combined with a set period, and the processing unit 42 selects the alarm and the set period according to the setting of the detection sensitivity, and adjusts the detection sensitivity.

[0095] In addition, diagnostic data can be extracted from the measurement of at least one type of sample, such as a specimen, a calibration sample, a QC sample, or a dummy sample, and sensitivity adjustment can also be performed by selecting the type of sample related to the diagnostic data.

[0096] -effect- (1) According to this embodiment, it is possible to detect an abnormality in a component of the liquid transport system 12 that draws in and discharges liquid to the sensor 11 based on an electrical signal output by the sample testing sensor 11 of the automatic analyzer 1. This makes it possible to prevent downtime of the automatic analyzer 1 due to a malfunction of the liquid transport system 12 or the like.

[0097] Another major advantage is that there is no need to add new hardware components such as new sensors, because abnormalities in the components of the liquid transport system 12 are detected based on the output of the sample inspection sensor 11. Since no new hardware components are required, it can be easily applied to existing automatic analyzers.

[0098] (2) It is also possible to simply compare the sensor output with a set value and determine that a component of the liquid transport system 12 is abnormal when a measurement is performed that, based on the comparison with the set value, suggests that a component of the liquid transport system 12 is abnormal, or when a predetermined number of measurements suggest that a component is abnormal. However, because there is an error in the sensor output, if it is determined that a component of the liquid transport system 12 is abnormal simply because a predetermined number of sensor outputs suggesting a component abnormality have been obtained, there is a possibility that an abnormality will be falsely detected even when the component of the liquid transport system 12 is normal. In this case, the automatic analyzer 1 must be stopped unnecessarily to inspect the liquid transport system 12.

[0099] In contrast, in this embodiment, the sensor output extracted as diagnostic data is statistically analyzed before diagnosing the components of the liquid transport system 12, thereby reducing false detection of abnormalities and reducing the number of times the automatic analyzer 1 is stopped unnecessarily.

[0100] (3) Furthermore, the variance in the sensor output data extracted from a set period (CV value in this example) is calculated as a statistical value, and if the statistical value is equal to or greater than a set value, it is determined that there is an abnormality in a component of the liquid transport system 12, which is expected to enable early detection of an abnormality in the component of the liquid transport system 12. For example, if valve V1 begins to malfunction and valve V1 does not open during a measurement that should be performed with valve V1 open, the variance in the diagnostic data will increase. In this embodiment, by diagnosing the component using the variance in the diagnostic data as an index, an abnormality in the component of the liquid transport system 12 can be detected at an early stage.

[0101] (4) By extracting diagnostic data from a set period ending at the present time, abnormalities in the liquid transport system 12 can be detected in a timely and appropriate manner.

[0102] (5) The sensitivity of anomaly detection can be set in UI 44 or 94, so that the automatic analyzer 1 can be operated flexibly, for example, by setting the test sensitivity high when sample measurement accuracy is important, or by setting the test sensitivity low when reduced inspection frequency is important. In addition, since the anomaly detection target and detection mode can also be set, it is possible to detect anomalies or abnormal modes by targeting specific parts whose condition is of particular concern, or to investigate the durability of each part and optimize the interval between regular inspections.

[0103] (6) Through careful study, the inventors of the present application have found that there is a certain correlation that can be utilized to detect abnormalities in components between the alarms generated during measurement by the functions of the automatic analyzer 1 and the state of the components of the liquid transport system 12. By detecting abnormalities in components using the sensor output during measurement in which an alarm is generated, as in this embodiment, abnormalities in components of the liquid transport system 12 can be detected rationally.

[0104] (7) In particular, in this embodiment, the risk of false detection of an abnormality can be reduced by using only the output of sensor 11 during sample measurement for which an alarm has been issued as diagnostic data. For example, if sensor output indicating a normal value is mixed in with the diagnostic data, and an alarm is occasionally issued due to factors other than an abnormality in liquid transport system 12, the data may vary greatly regardless of the state of liquid transport system 12, leading to a false detection of an abnormality. In contrast, by extracting only the sensor output for which an alarm has been issued as diagnostic data, the risk of false detection of an abnormality in a component of liquid transport system 12 can be reduced, and unnecessary shutdowns of the automatic analyzer 1 can be prevented while increasing the reliability of abnormality detection in the component of liquid transport system 12.

[0105] (8) By making it possible to include in the diagnostic data the output of the sensor 11 not only when the sample is measured (when the concentration of the component to be analyzed is measured) but also when the sensor 11 is cleaned or when the electrode is conditioned, it is possible to secure opportunities to acquire data and improve the accuracy of abnormality detection. Also, as mentioned above, the component in which the abnormality occurred and the abnormality mode can be determined depending on when the alarm is issued.

[0106] (9) By utilizing data from measurements of not only patient samples but also calibration samples, QC samples, dummy samples, and other samples, it is possible to secure opportunities to acquire data and improve the accuracy of anomaly detection. QC samples, calibration samples, and dummy samples are all measured under conditions similar to or close to those of patient samples. Therefore, by utilizing data from these samples, it is possible to accurately diagnose components of the liquid transport system 12.

[0107] (Second embodiment) This embodiment differs from the first embodiment in that the automatic analyzer 1 is equipped with an abnormality detection system for components of the liquid transport system 12. The processing displayed in the abnormality detection function F in the figure is a series of processes related to the function that was handled by the server 40 (FIG. 10) in the first embodiment. Data and processing related to the abnormality detection function that was allocated to the memory device 41 and processing device 42 in the first embodiment are allocated to, for example, the memory device 31 and processing device 32 of the control device 30 in this embodiment. The diagnostic algorithm for detecting abnormalities in components of the liquid transport system 12 is the same as in the first embodiment, and the detection results are notified to the user, etc., via the UI 94.

[0108] In other respects, this embodiment is similar to the first embodiment, and can provide the same effects as the first embodiment.

[0109] (Variation) The above describes an example in which data to which an alarm is issued is selectively extracted as diagnostic data, and abnormalities in components of the liquid transport system 12 are detected based on this data. However, to obtain the basic effect (1) described in the first embodiment, it is not necessarily necessary to make the issuance of an alarm a condition for the diagnostic data. For example, it is also possible to apply an algorithm in which sensor output is extracted under predetermined conditions, randomly, or uniformly for a set period, regardless of whether an alarm is issued, and abnormalities in components of the liquid transport system 12 are detected based on this extracted data.

[0110] In addition, an example has been described in which abnormalities in components of the liquid transport system 12 are detected based on the statistical values ​​of a set number of diagnostic data items, but as mentioned above, an algorithm can also be applied to detect abnormalities in components of the liquid transport system 12 by simply comparing the sensor output with the corresponding set value without obtaining statistical values.

[0111] Furthermore, the set period for extracting diagnostic data does not necessarily have to end at the present time. If there is a period of particular interest, it is possible to specify a predetermined period up to a certain point in the past as the set period, and perform anomaly detection based on the log data of the sensor output.

[0112] Furthermore, the functions for setting the abnormality detection target, detection mode, and detection sensitivity are not necessarily required to obtain the basic effect (1), and unnecessary functions can be omitted as appropriate.

[0113] Although the above example illustrates the extraction of diagnostic data from all data obtained at multiple times during a measurement cycle, this setting can also be changed as appropriate. For example, diagnostic data may be extracted from only data related to one or two of the following: sample measurement, cleaning of the sensor 11, and electrode conditioning.

[0114] Although an example has been described in which data from sample measurement occasions is extracted as diagnostic data regardless of whether the sample is a patient sample, calibration sample, QC sample, or dummy sample, this setting can also be changed as appropriate. For example, data from one, two, or three specified sample measurement occasions from among patient samples, calibration sample, QC sample, and dummy sample may be extracted as diagnostic data. [Explanation of symbols]

[0115] 1...automatic analyzer, 11...sensor, 12...liquid transport system, 31...storage device, 32...processing device, 40...server (component abnormality detection system), 41...storage device, 42...processing device, 44, 94...user interface, E1...reference electrode (electrode), E2...counter electrode (electrode), E3...working electrode (electrode), F...abnormality detection function, F1-F6...flow path, FC...flow cell, PT...photoelectric conversion sensor, SY...syringe, V1, V2...valve

Claims

1. A component abnormality detection system that detects abnormalities in components of a liquid transport system that draws in and discharges liquid to a sensor for sample testing in an automatic analyzer, a storage device that stores data of the electrical signal output by the sensor; a processing device for processing data recorded in the storage device, The processing device includes: An abnormality in a component of the liquid transport system is detected based on the electrical signal. Parts abnormality detection system.

2. 2. The component abnormality detection system according to claim 1, The processing device includes: calculating statistical values ​​of the data of the electrical signal; Detecting an abnormality in a component of the liquid transport system based on the statistical value. Parts abnormality detection system.

3. 3. The component abnormality detection system according to claim 2, The processing device includes: reading out the electrical signal data extracted from the set period from the storage device; calculating the variance of the data for the set period as the statistical value; If the statistical value is equal to or greater than a set value, it is determined that there is an abnormality in a component of the liquid transport system. Parts abnormality detection system.

4. 4. The component abnormality detection system according to claim 3, The set period is a period ending at the present time.

5. 4. The component abnormality detection system according to claim 3, The processing device is a component abnormality detection system that adjusts the sensitivity of abnormality detection by changing the set value.

6. 3. The component abnormality detection system according to claim 2, A component abnormality detection system, wherein the statistical value is a statistical value obtained using an electrical signal output by the sensor at the time of measurement for which an alarm is issued.

7. 7. The component abnormality detection system according to claim 6, The processing device is a component abnormality detection system that adjusts sensitivity of abnormality detection by selecting the type of alarm related to the electrical signal to be statistically analyzed.

8. 3. The component abnormality detection system according to claim 2, A component abnormality detection system, wherein the statistical value is a statistical value obtained using only the electrical signal output by the sensor when measuring the sample for which an alarm has been issued.

9. 2. The component abnormality detection system according to claim 1, The processing device is a component abnormality detection system that estimates an abnormality mode indicating an abnormal component or abnormality state of the liquid transport system based on at least one of the electrical signals output by the sensor at multiple times during the measurement cycle of the same sample.

10. 10. The component abnormality detection system according to claim 9, The component abnormality detection system, wherein the plurality of timings are when a sample is measured, when the sensor is cleaned, and when an electrode is conditioned.

11. 2. The component abnormality detection system according to claim 1, The sensor A flow cell; a reference electrode, a counter electrode, and a working electrode provided in the flow cell; a photoelectric conversion sensor disposed on the opposite side of the reference electrode across the flow cell; A component abnormality detection system comprising:

12. The component abnormality detection system according to claim 11, The component abnormality detection system, wherein the electrical signal is a current value, a voltage value, or a resistance value that occurs between the counter electrode and the working electrode when a voltage is applied between the reference electrode and the working electrode.

13. 2. The component abnormality detection system according to claim 1, The component abnormality detection system, wherein the electrical signal is a signal output by the sensor when a sample is measured, when the sensor is cleaned, or when an electrode is conditioned.

14. 2. The component abnormality detection system according to claim 1, The component anomaly detection system, wherein the sample is a specimen, a calibration sample, a quality control sample, or a dummy sample.

15. 2. The component abnormality detection system according to claim 1, The liquid delivery system comprises: a flow path for passing the liquid; a plurality of valves for opening and closing the flow paths; a syringe that generates a pressure difference in the flow path for sucking and discharging the liquid; A component abnormality detection system comprising:

16. The component abnormality detection system according to claim 15, The component abnormality detection system, wherein the component is the valve.

17. 2. The component abnormality detection system according to claim 1, A component abnormality detection system having a user interface configured to enable setting of abnormality detection conditions.

18. a sensor for measuring an analyte; a liquid transport system that draws in and discharges liquid to the sensor; a component abnormality detection system that detects abnormalities in components of the liquid transport system; An automatic analyzer comprising: The component abnormality detection system includes: a storage device that stores data of the electrical signal output by the sensor; a processing device for processing data recorded in the storage device, The processing device includes: An abnormality in a component of the liquid transport system is detected based on the electrical signal. Automatic analyzer.

19. A component abnormality detection method for detecting an abnormality in a component of a liquid transport system that draws in and discharges liquid to a sample measurement sensor of an automatic analyzer, comprising: Recording data of the electrical signal output by the sensor; An abnormality in a component of the liquid transport system is detected based on the electrical signal. Component abnormality detection method.

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