Sample tube device status detection method and apparatus

Abstract

Embodiments of the present application disclose a sample tube equipment state detection method and device. A specific embodiment of the method comprises: performing communication link detection on each sample tube equipment between laboratories; in response to determining that the communication link detection result indicates that the communication link is normal, updating a monitoring node of a sample tube equipment transportation relationship graph corresponding to each sample tube equipment; according to the updated sample tube equipment transportation relationship graph and each monitoring node, performing the following detection steps: performing transportation pipeline state detection on each sample tube equipment to obtain a set of transportation pipeline state detection results; performing power state detection on each sample tube equipment; and according to the set of transportation pipeline state detection results and a set of power state detection results, performing a marking operation on each sample tube equipment and the monitoring node. The embodiment improves the efficiency of sample tube equipment transportation anomaly monitoring and ensures the stability of the sample tube equipment transportation network.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the field of sample tube equipment state detection, and in particular, to a sample tube equipment state detection method and device. BACKGROUND

[0002] At present, sample tube equipment is arranged in each laboratory or building, and sample tubes are transported through pipelines (sample tubes are transported in time or closed transportation) to ensure the timeliness of sample tube transportation and avoid damage to sample tubes during manual transportation. When transporting sample tubes between various sample tube equipment, it is necessary to ensure that the sample tube equipment is in a stable state. At present, the detection of the state of the sample tube equipment is usually carried out by technical personnel periodically and the single sample tube equipment is detected. However, the single detection method is prone to have many unstable factors in detection (for example, some abnormalities can only be confirmed by comprehensive detection). Therefore, there is an urgent need for a comprehensive detection method for various sample tube equipment to improve the stability of sample tubes during transportation. SUMMARY

[0003] The summary section of the present application is used to introduce the concepts in a brief form, which will be described in detail in the specific embodiments section. The summary section of the present application is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0004] Some embodiments of the present application propose a sample tube equipment state detection method, device, electronic equipment and computer readable medium to solve the technical problems mentioned in the background section.

[0005] In a first aspect, some embodiments of the present application provide a sample tube device state detection method, which comprises: performing communication link detection on each sample tube device between laboratories to obtain a communication link detection result; in response to determining that the communication link detection result indicates that the communication link is normal, updating a monitoring node of a sample tube device transport relationship graph corresponding to each sample tube device to obtain an updated sample tube device transport relationship graph, wherein the sample tube device transport relationship graph represents the transport relationship of sample tubes between each sample tube device; and performing the following detection steps according to the updated sample tube device transport relationship graph and each monitoring node: performing transport pipeline state detection on each sample tube device through each monitoring node to obtain a set of transport pipeline state detection results, wherein one transport pipeline state detection result corresponds to one sample tube device; performing power state detection on each sample tube device through each monitoring node to obtain a set of power state detection results, wherein one power state detection result corresponds to one sample tube device; and performing marking operations on each sample tube device and monitoring node according to the set of transport pipeline state detection results and the set of power state detection results.

[0006] In a second aspect, some embodiments of the present application provide a sample tube device state detection apparatus, which comprises: a detection unit configured to perform communication link detection on each sample tube device between laboratories to obtain a communication link detection result; an update unit configured to, in response to determining that the communication link detection result indicates that the communication link is normal, update a monitoring node of a sample tube device transport relationship graph corresponding to each sample tube device to obtain an updated sample tube device transport relationship graph, wherein the sample tube device transport relationship graph represents the transport relationship of sample tubes between each sample tube device; a state detection unit configured to perform the following detection steps according to the updated sample tube device transport relationship graph and each monitoring node: perform transport pipeline state detection on each sample tube device through each monitoring node to obtain a set of transport pipeline state detection results, wherein one transport pipeline state detection result corresponds to one sample tube device; perform power state detection on each sample tube device through each monitoring node to obtain a set of power state detection results, wherein one power state detection result corresponds to one sample tube device; and a marking unit configured to perform marking operations on each sample tube device and monitoring node according to the set of transport pipeline state detection results and the set of power state detection results.

[0007] In a third aspect, some embodiments of the present application provide an electronic device, which comprises: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any of the implementations of the first aspect.

[0008] In a fourth aspect, some embodiments of the present application provide a computer readable medium having stored thereon a computer program, wherein the program, when executed by a processor, implements the method described in any implementation manner of the first aspect.

[0009] The above various embodiments of the present application have the following beneficial effects: through the sample tube equipment state detection method of some embodiments of the present application, the monitoring nodes are set for each node through the sample tube equipment transportation relationship diagram, so as to comprehensively monitor the sample tube equipment transportation network; thereby improving the efficiency of the sample tube equipment transportation abnormality monitoring, to ensure the stability of the sample tube equipment transportation network; in addition, the sample tube equipment transportation network is monitored from multiple angles such as communication link detection, pipeline state detection and power detection, to comprehensively improve the stability of the sample tube equipment transportation network. BRIEF DESCRIPTION OF DRAWINGS

[0010] The above and other features, aspects and advantages of the embodiments of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals will be understood to refer to the same or like elements, features and structures. It will be understood that the drawings are diagrammatic and schematic and are not drawn to scale nor to precise proportions.

[0011] Figure 1 is a flow chart of some embodiments of the sample tube equipment state detection method according to the present application;

[0012] Figure 2 is a layout schematic diagram of one laboratory;

[0013] Figure 3 is a connection layout schematic diagram of various sample tube equipment;

[0014] Figure 4 is a schematic diagram of a transfer node;

[0015] Figure 5 is a structural schematic diagram of some embodiments of the sample tube equipment state detection device according to the present application;

[0016] Figure 6 is a structural schematic diagram of an electronic device for implementing some embodiments of the present application. DETAILED DESCRIPTION

[0017] Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms, and should not be interpreted as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided so as to more thoroughly and completely understand the present application. It should be understood that the drawings and embodiments of the present application are only for exemplary purposes, and are not intended to limit the scope of protection of the present application.

[0018] In addition, it needs to be noted that only parts related to the present application are shown in the drawings for the convenience of description. The embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0019] It should be noted that the terms "first", "second" and the like in the present application are only used to distinguish different devices, modules or units, and do not limit the order or interdependence of the functions performed by these devices, modules or units.

[0020] It should be noted that the terms "one", "multiple" in the present application are illustrative and not restrictive, and those skilled in the art should understand that "one" or "multiple" should be understood as "one or more" unless otherwise explicitly indicated in the context.

[0021] The names of the messages or information exchanged between the devices in the embodiments of the present application are only for illustrative purposes, and are not used to limit the scope of the messages or information.

[0022] The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0023] Figure 1 Flow 100 of some embodiments of a sample tube equipment state detection method of some embodiments of the present application. The sample tube equipment state detection method comprises the following steps:

[0024] Step 101, communication link detection is performed on each sample tube equipment between each laboratory to obtain a communication link detection result.

[0025] In some embodiments, the execution subject (such as a computing device) of the sample tube equipment state detection method can perform communication link detection on each sample tube equipment between each laboratory to obtain a communication link detection result. The layout between each laboratory, as shown in the example, can include laboratory 1, laboratory 2, laboratory 3, laboratory 4, laboratory 5, and laboratory 6. Among them, each laboratory can be in the same building, the same floor; can be in the same building, different floors; or can be between different buildings. Each laboratory is arranged with a sample tube equipment. Each sample tube equipment is connected through a conveying pipeline for conveying sample tubes. Figure 2

[0026] Further reference is made to Figure 3 ​The connection layout between each sample tube device is shown, for example, including: sample tube device A, sample tube device B, ··· sample tube device N; and sample tube device 1, sample tube device 2, ···, sample tube device M. Here, sample tube device A, sample tube device B, ··· sample tube device N; and sample tube device 1, sample tube device 2, ···, sample tube device M can be the same device, or different devices, according to the needs of each laboratory, just distributed in different laboratories. Each two sample tube devices are connected by a conveying pipeline, and the conveying pipeline is directly provided with a transfer node for transferring the sample tube in the conveying pipeline. Here, the conveying pipeline can be a transparent pipeline. The transfer node can represent a conveying and transferring device, which can be translucent or transparent. The sample tube device can include but is not limited to: chromatograph, spectrometer, mass spectrometer, extractor, centrifugal concentrator, low-temperature liquid nitrogen circulating equipment, etc. Specifically, each laboratory can set the sample tube device according to the actual needs and experimental sequence.

[0027] Further referring to Figure 4 The transfer node can include: a sample tube transfer assembly 401, a conveying hole 402, a sample tube temporary storage hole 403, and a gas connection hole 404. The transfer node is disc-shaped, and the conveying holes 402 are uniformly arranged along the edge and connected with the pneumatic conveying pipeline. The sample tube transfer assembly 401 is arranged at the center of the transfer node and can rotate along the axis of the transfer node. The mechanism is connected with a gas generating device at the bottom and can generate negative pressure or positive pressure gas under control.

[0028] The conveying pipeline: the conveying pipeline is slightly larger in diameter than the sample tube, and a booster device is arranged along the conveying pipeline. The conveying pipeline at a specific position is transparent, and a temperature measuring device, a speed measuring device, and a camera are arranged at the transparent position. The temperature measuring device, the speed measuring device, and the camera on the conveying pipeline can detect the current pipeline pressure, temperature information, and image data in real time, and these information are all collected to the execution body.

[0029] In practice, the above execution body can detect the communication link of each sample tube device between each laboratory by the following steps:

[0030] First, a communication detection request is generated, and the communication detection request is packaged as a communication detection request message. The communication detection request can be a request for testing whether each sample tube device is communicatively connected. For example, the communication detection request can be packaged as a communication detection request message conforming to the HTTP / HTTPS protocol format. The communication detection request can be generated by the execution body at a regular time.

[0031] Secondly, for each of the sample tube devices, the following communication link detection step is performed:

[0032] 1. The communication detection request message is sent to the sample tube device to receive the message feedback information fed back by the sample tube device. The message feedback information can represent the response information of the sample tube device to the received communication detection request message.

[0033] 2. According to the message feedback information, the sample tube device audit result is generated. For example, the message feedback information can be checked with the preset feedback information to generate the sample tube device audit result. That is, the sample tube device audit result can represent that the message feedback information is consistent or inconsistent with the preset feedback information.

[0034] The second step can include the following sub-steps:

[0035] The first sub-step is to standardize the message feedback information to obtain standardized message feedback information. Standardization can include message structure standardization, data encoding standardization, semantic and content standardization, etc. The message structure standardization can refer to converting the message feedback information into a fixed format message. Data encoding standardization can refer to character encoding unification (using UTF-8 encoding), binary encoding (specifying the byte length of integer / floating point type). Semantic and content standardization can refer to enumeration value standardization (defining the explicit meaning of status code (such as HTTP status code: 200=OK, 404=Not Found)).

[0036] The second sub-step is to generate sample tube device communication success information according to the standardized message feedback information. The sample tube device communication success information represents the communication accuracy of the corresponding sample tube device. That is, first, determine whether the standardized message feedback information indicates a successful communication; if it indicates a successful communication, determine the total number of successful and failed communications of the sample tube device within a predetermined time period, and calculate the communication accuracy (sample tube device communication success information).

[0037] The third sub-step is to generate a sample tube device audit result representing an audit pass in response to determining that the sample tube device communication success information meets the target communication condition. The target communication condition can refer to the current communication success and the communication accuracy is greater than or equal to a predetermined threshold.

[0038] Thirdly, according to the generated sample tube device audit results, the communication link detection result is generated. That is, the sample tube device audit results can be combined into a communication link detection result.

[0039] At step 102, in response to determining that the communication link detection result indicates that the communication link is normal, the monitoring node update is performed on the sample tube device transportation relationship graph corresponding to each sample tube device to obtain an updated sample tube device transportation relationship graph.

[0040] In some embodiments, the execution subject can perform the monitoring node update on the sample tube device transportation relationship graph corresponding to each sample tube device in response to determining that the communication link detection result indicates that the communication link is normal, to obtain an updated sample tube device transportation relationship graph. The sample tube device transportation relationship graph indicates the sample tube transportation relationship between each sample tube device. The sample tube device transportation relationship graph can refer to Figures 2-3 The connection relationship between each sample tube device can be indicated. If each sample tube device audit result in the communication link detection result meets the target communication condition, it indicates that the communication link is normal.

[0041] For example, monitoring nodes can be arranged at each sample tube device, as well as each section of the transportation pipeline and the transfer node. The monitoring node can be the node where the intelligent agent is arranged, used to monitor the running state of the sample tube device, the transportation pipeline and the transfer node. In order to timely discover the abnormal running state of each node. For example, the identifier of the intelligent agent can be updated in each node in the sample tube device transportation relationship graph. Here, each node in the sample tube device transportation relationship graph can be a separate sample tube device or a transfer node; that is, one sample tube device / transfer node represents one node. The edge between each node can represent the transportation pipeline, and which nodes are interconnected.

[0042] It should be noted that various sensors (air pressure sensor, voltage sensor, current sensor), cameras need to be arranged at each monitoring node for the intelligent agent to control, for collecting the running data of the monitoring target (sample tube device / transportation pipeline / transfer node) corresponding to each monitoring node.

[0043] In practice, the execution subject can perform the monitoring node update on the sample tube device transportation relationship graph corresponding to each sample tube device to obtain an updated sample tube device transportation relationship graph by the following steps:

[0044] First, determine the device information corresponding to each sample tube device. The device information includes: sample tube device identifier and device location information. The sample tube device identifier can uniquely identify the sample tube device. The device location information can indicate the laboratory location where the device is located.

[0045] Secondly, template codes of the intelligent monitoring agents running in different running environments are obtained to obtain an intelligent monitoring agent code set. Here, the running environment can refer to a monitoring environment where the intelligent monitoring agent is located. For example, the running environment can include an indoor environment, an outdoor environment, and monitoring requirements / targets. The template code can represent a template of the running code of the intelligent monitoring agent. The intelligent monitoring agent can be an intelligent agent.

[0046] Thirdly, the intelligent monitoring agent code set is subjected to code logic reconstruction processing to obtain a reconstructed intelligent monitoring agent code set.

[0047] Fourthly, a monitoring strategy plug-in is added to the reconstructed intelligent monitoring agent code set to obtain a strategy intelligent monitoring agent code. The monitoring strategy plug-in can represent a plug-in of the monitoring strategy of the intelligent monitoring agent, and is used to control / update the monitoring strategy of the intelligent monitoring agent.

[0048] Fifthly, the strategy intelligent monitoring agent code is compiled to obtain a target number of strategy intelligent monitoring agents. That is, the target number can be consistent with the number of monitoring nodes.

[0049] Sixthly, according to the device information, the strategy intelligent monitoring agents are deployed to the corresponding monitoring nodes in the sample tube device conveying relationship graph. That is, according to the location information included in the device information, the strategy intelligent monitoring agents can be deployed to the corresponding monitoring nodes. For example, one strategy intelligent monitoring agent can be pre-set to correspond to one monitoring node.

[0050] Seventhly, according to the deployed strategy intelligent monitoring agents, the sample tube device conveying relationship graph is updated to obtain an updated sample tube device conveying relationship graph. That is, the intelligent agent identifier of the strategy intelligent monitoring agent can be marked at the monitoring node in the sample tube device conveying relationship graph.

[0051] Step 103, according to the updated sample tube device conveying relationship graph and the monitoring nodes, the following detection steps are performed:

[0052] Step 1031, the sample tube devices are subjected to conveying pipeline state detection by the monitoring nodes to obtain a conveying pipeline state detection result set.

[0053] In some embodiments, the execution subject can detect the state of the conveying pipeline of each sample tube device through each monitoring node to obtain a set of conveying pipeline state detection results. One conveying pipeline state detection result corresponds to one sample tube device. For example, the air pressure of the conveying pipeline corresponding to each sample tube device can be detected by the air pressure detection device arranged at each monitoring node to determine whether the pressure in the conveying pipeline is stable. For another example, the transportation data (conveying duration, whether broken, whether jammed) of each sample tube within a period of time can be obtained to determine whether each transportation data meets the preset requirement to obtain the conveying pipeline state detection result.

[0054] In practice, the execution subject can detect the state of the conveying pipeline of each sample tube device through the following steps:

[0055] Firstly, the strategy intelligent monitoring body of each monitoring node detects the air pressure of the conveying pipeline to obtain the pipeline air pressure detection result. The strategy intelligent monitoring body can be provided with a conveying pipeline state detection strategy for detecting the conveying pipeline. For example, the strategy intelligent monitoring body can be an intelligent body with a detection strategy built-in. The detection strategy can include but is not limited to detection period, detection item, etc.

[0056] The first step can include the following sub-steps:

[0057] 1. Collect the air pressure signal of the conveying pipeline and segment the air pressure signal to generate a first air pressure signal and a second air pressure signal. The first air pressure signal is the air pressure signal when the air extraction operation is performed on the conveying pipeline, and the second air pressure signal is the air pressure signal after the air extraction operation on the conveying pipeline is stopped. For example, the air pump arranged at the monitoring node can be controlled by the strategy intelligent monitoring body to extract air from the conveying pipeline. In practice, when the air pressure value in the conveying pipeline reaches the preset air pressure value, the air pump can be controlled to stop air extraction. The air pressure signal between the start of air extraction and the stop of air extraction is the first air pressure signal.

[0058] 2. Determine the mean value of the air pressure signal of the second air pressure signal. For example, the execution subject can take the ratio of the function integral value of the analog equation corresponding to the second air pressure signal in the signal interval corresponding to the second air pressure signal to the signal interval length as the mean value of the air pressure signal.

[0059] 3. Generate the air pressure change trend according to the mean value of the air pressure signal and the end point signal value of the first air pressure signal. The air pressure change trend includes no change trend and change trend. The no change trend represents that the air pressure in the conveying pipeline does not change or the change of the air pressure is less than a threshold value. The change trend represents that the change of the air pressure in the conveying pipeline is greater than or equal to the threshold value.

[0060] For example, the execution subject can determine the relationship between the signal difference between the air pressure signal mean value and the end point signal value and the threshold value, thereby determining the air pressure change trend. The end point signal value is the air pressure signal value of the end point of the first air pressure signal.

[0061] 4. In response to the air pressure change trend being the no change trend, an air pressure detection result of the pipeline satisfying the air tightness verification condition is generated. For example, the air tightness verification condition can be that the air pressure change trend indicates the no change trend.

[0062] Optionally, a transit node image set of a transit node corresponding to the pipeline is collected. The transit node image set is a monitoring image of the transit node region at a front view angle. For example, the transit node image set of the transit node corresponding to the pipeline can be collected by a camera or a camera arranged. The transit node image can be an image collected by the camera when the air pump starts to pump.

[0063] Optionally, in response to the air pressure change trend being the change trend, the following air tightness verification steps are performed:

[0064] Firstly, each transit node image in the transit node image set is subjected to negative film processing to generate a negative film transit node image, thereby obtaining a negative film transit node image set.

[0065] Secondly, each negative film transit node image in the negative film transit node image set is subjected to bubble detection by a pre-trained bubble detection model to generate a bubble confidence, thereby obtaining a bubble confidence set. The bubble detection model is a target detection model for detecting whether a sample tube has bubbles due to air tightness problems when there is a pressure difference between the pipeline and the sample tube. In practice, the bubble detection model can use a Faster R-CNN model. For example, the bubble detection model can be set as a special segmentation model (ECA-YOLACT) for bubble characteristics, that is, the edge feature extraction is strengthened by adding channel attention (ECA) and hollow convolution on the basis of YOLACT. Use BubGAN to generate synthetic data for training. For another example, the bubble detection model can also use YOLOv8 as the basic model, extract multi-scale features through the CSPDarknet backbone network and the SPPF layer, and realize bubble tracking by combining Kalman filtering. For another example, the bubble detection model can also introduce the CBAM attention mechanism to enhance feature correlation, use BiFPN to optimize multi-scale fusion, or combine the improved three-frame difference method (ITFD) to enhance small bubble detection, and optimize the results by IoU screening.

[0066] Thirdly, in response to the existence of a bubble confidence greater than or equal to the preset bubble confidence in the bubble confidence set and the average bubble confidence corresponding to the bubble confidence set being greater than or equal to the preset bubble confidence, a hermeticity check identifier indicating that the sample tube does not meet the hermeticity check condition is generated. Here, the reason for setting two judgment conditions is that: first, at least one bubble that looks like a leak is found; second, the bubbles found overall all look like leaks. That is, the conditions for judging that the sample tube is unqualified are as follows: Condition 1: there is one or more values greater than or equal to the preset threshold in the bubble confidence set. Condition 2: the average value of the bubble confidence set is greater than or equal to the preset threshold. Only when both conditions are met, the sample tube will be finally marked as "not leaking". Because it is currently impossible to achieve complete "no leakage" in the sample tube sealing process, unless it is in a vacuum state; but as long as the "leakage" is within the controllable range required by the experiment, it is acceptable.

[0067] The core technical idea is to combine the "existence of strong evidence" and "overall strong evidence" strategies to finally determine whether the sample tube meets the hermeticity requirement, thereby avoiding detection bias caused by single noise or misjudgment.

[0068] Fourthly, in response to the existence of a bubble confidence greater than or equal to the preset bubble confidence in the bubble confidence set and the average bubble confidence corresponding to the bubble confidence set being less than the preset bubble confidence, a pipeline air pressure detection result indicating that the transfer node meets the hermeticity check condition is generated.

[0069] Fifthly, in response to the absence of a bubble confidence greater than or equal to the preset bubble confidence in the bubble confidence set, a pipeline air pressure detection result indicating that the transfer node meets the hermeticity check condition is generated.

[0070] In practice, when the biological sample tube with infection exists is handled improperly by human, especially when the sample tube storing the biological sample has airtightness problem, the biological sample is prone to be leaked. Based on this, the application detects the airtightness in the way of combining air pressure and image. In practice, the hardware cost of vacuum pump is high. Based on this, the application uses a micro air pump to make the air pressure in the sample tube and the air pressure in the sample delivery pipeline have an air pressure difference, in other words, the air pressure in the sample delivery pipeline reaches a preset air pressure difference standard. And according to the second air pressure signal, it is directly observed whether the air pressure difference in the sample delivery pipeline is reduced. When it is reduced, it may be due to air leakage of the sample delivery pipeline or air overflow in the sample tube. At this time, the application further combines the bubble detection model to detect whether there is air bubble overflow in the sample tube. Whether the sample delivery pipeline has the problem of air bubble overflow due to air pressure difference in the air extraction stage and the non-air extraction stage is determined, so as to judge whether the sample delivery pipeline has the airtightness problem. In this way, whether the sample delivery pipeline has the airtightness problem can be effectively detected.

[0071] In the second step, the sample tube delivery data set collected by each strategy intelligent monitoring body is subjected to data anomaly detection to obtain a sample tube delivery data detection result set. One sample tube delivery data detection result corresponds to one sample tube delivery data, and one sample tube delivery data corresponds to one strategy intelligent monitoring body. The sample tube delivery data can be the delivery data of the monitoring node of the sample tube in a preset window time length collected by the strategy intelligent monitoring. For example, the sample tube delivery data can include the delivery time length of each sample tube, whether it is stuck, whether it is damaged, whether it is delivery error, etc. in the preset window time length. That is, it can be determined whether there is abnormal sample tube delivery data in the sample tube delivery data set. The abnormal sample tube delivery data can be one or more of the following: exceeding the preset delivery time length, having a jam, having a delivery damage, and having a delivery error (for example, the A sample tube should be delivered to the A device, but it is delivered to the B device).

[0072] In the third step, according to the above sample tube delivery data detection result set, the delivery relationship between each sample tube device in the above updated sample tube device delivery relationship diagram is updated, and each sample tube delivery data in the above sample tube delivery data set is clustered to obtain a sample tube delivery data group set. Each sample tube delivery data group corresponds to a delivery network composed of multiple sample tube devices. That is, it can be determined which delivery line has an abnormality. That is, each sample tube delivery data corresponding to the same delivery pipeline / monitoring node can be clustered into a class.

[0073] In the fourth step, the transport state of each sample tube transport data set in the sample tube transport data set is detected, and a set of transport state detection results characterizing the sample tube transport abnormality is generated in response to detecting each sample tube transport data set with an abnormal sample tube transport state. That is, the abnormal data in each sample tube transport data set is determined first, and the transport state of the monitoring node / transport pipeline is determined according to the abnormal data.

[0074] In the fifth step, the pipeline pressure detection result and the set of transport state detection results are determined as the set of transport state detection results.

[0075] In the step 1032, the power state of each sample tube device is detected by each monitoring node to obtain a set of power state detection results.

[0076] In some embodiments, the execution subject can detect the power state of each sample tube device by each monitoring node to obtain a set of power state detection results. One power state detection result corresponds to one sample tube device. For example, the voltage and current data of each sample tube device within a preset window length can be collected to determine whether the voltage and current of each sample tube device is in a normal state.

[0077] In the step 104, each sample tube device and monitoring node is marked according to the set of transport pipeline state detection results and the set of power state detection results.

[0078] In some embodiments, the execution subject can mark each sample tube device and monitoring node according to the set of transport pipeline state detection results and the set of power state detection results. That is, the transport pipeline state detection result characterizing the abnormality can be determined first, so that the corresponding transport pipeline of each sample tube device and monitoring node can be marked according to the abnormal transport pipeline state detection result. Secondly, the power state detection result characterizing the abnormality can be determined, so that the corresponding sample tube device can be marked. The marking here can be to mark the specific problem of the abnormality.

[0079] Thus, the maintenance personnel can be prompted to repair each marked sample tube device and monitoring node in time.

[0080] Further reference Figure 5 As an implementation of the method shown in the above figures, the present application provides some embodiments of a sample tube device state detection apparatus, which corresponds to the method embodiments shown in Figure 1 The sample tube device state detection apparatus can be applied to various electronic devices.

[0081] As Figure 5As shown, the sample tube equipment state detection apparatus 500 of some embodiments includes a detection unit 501, an updating unit 502, a state detection unit 503, and a marking unit 504. The detection unit 501 is configured to perform communication link detection on each sample tube equipment between laboratories to obtain a communication link detection result. The updating unit 502 is configured to, in response to determining that the communication link detection result indicates that the communication link is normal, update a monitoring node of a sample tube equipment transportation relationship graph corresponding to each sample tube equipment to obtain an updated sample tube equipment transportation relationship graph, where the sample tube equipment transportation relationship graph represents a sample tube transportation relationship between each sample tube equipment. The state detection unit 503 is configured to, according to the updated sample tube equipment transportation relationship graph and each monitoring node, perform the following detection steps: performing transportation pipeline state detection on each sample tube equipment through each monitoring node to obtain a set of transportation pipeline state detection results, where one transportation pipeline state detection result corresponds to one sample tube equipment; performing power state detection on each sample tube equipment through each monitoring node to obtain a set of power state detection results, where one power state detection result corresponds to one sample tube equipment. The marking unit 504 is configured to, according to the set of transportation pipeline state detection results and the set of power state detection results, mark each sample tube equipment and the monitoring node.

[0082] It can be understood that the units described in the sample tube equipment state detection apparatus 500 correspond to the steps in the method described above. Figure 1 Therefore, the operations, features, and advantages described above for the method also apply to the sample tube equipment state detection apparatus 500 and the units included therein, which will not be described here again.

[0083] The following refers to Figure 6 which shows a structural schematic diagram of an electronic device (such as a computing device) suitable for implementing some embodiments of the present application. Figure 6 The electronic device shown is merely an example and should not impose any limitation on the functions and use range of the embodiments of the present application. As Figure 6As shown, the computer device includes a processor, a memory and a network interface connected through a system bus, wherein the memory can include a non-volatile storage medium and an internal memory. The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions which, when executed, can cause the processor to perform any one of the sample tube device state detection methods. The processor is used to provide computing and control capabilities to support the operation of the entire computer device. The internal memory provides an environment for the computer program in the non-volatile storage medium to run, which, when executed by the processor, can cause the processor to perform any one of the sample tube device state detection methods. The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand, Figure 6 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0084] It should be understood that the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic components, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0085] In one embodiment, the processor is configured to run a computer program stored in the memory to implement the following steps: performing communication link detection on each sample tube device between laboratories to obtain a communication link detection result; in response to determining that the communication link detection result indicates that the communication link is normal, updating a monitoring node of a sample tube device transport relationship graph corresponding to each sample tube device to obtain an updated sample tube device transport relationship graph, wherein the sample tube device transport relationship graph represents a sample tube transport relationship between each sample tube device; and performing the following detection steps according to the updated sample tube device transport relationship graph and each monitoring node: performing transport pipeline state detection on each sample tube device through each monitoring node to obtain a set of transport pipeline state detection results, wherein one transport pipeline state detection result corresponds to one sample tube device; performing power state detection on each sample tube device through each monitoring node to obtain a set of power state detection results, wherein one power state detection result corresponds to one sample tube device; and performing a marking operation on each sample tube device and monitoring node according to the set of transport pipeline state detection results and the set of power state detection results.

[0086] The embodiments of the sample tube device state detection method also provide a computer readable storage medium, and the computer readable storage medium stores a computer program. The computer program includes program instructions, and the method implemented by the program instructions can refer to the embodiments of the sample tube device state detection method.

[0087] The computer readable storage medium can be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. The computer readable storage medium can also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, and the like.

[0088] It should be noted that, in this document, the terms "comprising", "including", or any other variant thereof are intended to cover a non-exclusive inclusion, so that a process, method, article, or system that includes a list of elements not only includes those elements, but also includes other elements not expressly listed, or inherent to such a process, method, article, or system. Without more limitations, an element defined by the statement "including a" does not exclude the presence of additional identical elements in the process, method, article, or system that includes the element.

[0089] The above description is merely some of the preferred embodiments of the application and a description of the technical principles of the application. It should be understood by those skilled in the art that the inventive scope of the embodiments of the application is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by the combinations of the above technical features or equivalent features without departing from the above inventive concept. For example, the technical solutions formed by the mutual replacement of the above features and the technical features with similar functions disclosed in the embodiments of the application (but not limited to) form the technical solutions.

Claims

1. A method for detecting the status of a sample tube device, characterized in that, include: The communication links between the various sample tube devices in each laboratory were tested, and the communication link test results were obtained. In response to the determination that the communication link detection result indicates that the communication link is normal, the monitoring node of the sample tube equipment transport relationship diagram corresponding to each sample tube equipment is updated to obtain an updated sample tube equipment transport relationship diagram, wherein the sample tube equipment transport relationship diagram represents the transport relationship of sample tubes between each sample tube equipment; Based on the updated sample tube equipment transport relationship diagram and each monitoring node, perform the following detection steps: By using each monitoring node, the status of the delivery pipeline of each sample tube device is detected, and a set of delivery pipeline status detection results is obtained, wherein one delivery pipeline status detection result corresponds to one sample tube device. By using each monitoring node, the power status of each sample tube device is detected, and a power status detection result set is obtained, wherein one power status detection result corresponds to one sample tube device. Based on the pipeline status detection result set and the power status detection result set, mark each sample tube device and monitoring node; The process of detecting the condition of the delivery pipeline for each sample tube device includes: The strategy of controlling each monitoring node is an intelligent monitoring body that performs pipeline air pressure detection on the delivery pipeline and obtains the pipeline air pressure detection results. Data anomaly detection is performed on the sample tube delivery datasets collected by each strategy intelligent monitoring body to obtain a sample tube delivery data detection result set. Here, one sample tube delivery data detection result corresponds to one sample tube delivery data, and one sample tube delivery data corresponds to one strategy intelligent monitoring body. Based on the sample tube delivery data detection result set, and according to the delivery relationship between each sample tube device and the updated sample tube device delivery relationship diagram, the sample tube delivery data in the sample tube delivery dataset is clustered to obtain sample tube delivery data set, wherein each sample tube delivery data set corresponds to a delivery network consisting of multiple sample tube devices. The delivery status of each sample tube delivery data group in the sample tube delivery data group set is detected, and in response to the detection of each sample tube delivery data group with abnormal delivery status, a delivery status detection result set characterizing the abnormal delivery status of the sample tube is generated. The air pressure detection results of each pipeline and the delivery status detection result set are determined as the delivery status detection result set; This includes conducting pipeline air pressure testing on the delivery pipeline, including: The air pressure signal of the delivery pipeline is collected, and the air pressure signal is segmented to generate a first air pressure signal and a second air pressure signal. The first air pressure signal is the air pressure signal when the air extraction operation of the delivery pipeline is performed, and the second air pressure signal is the air pressure signal after the air extraction operation of the delivery pipeline is stopped. Determine the average value of the second air pressure signal; Based on the average value of the air pressure signal and the terminal signal value of the first air pressure signal, an air pressure change trend is generated, wherein the air pressure change trend includes: no change trend and change trend; In response to the pressure change trend being the no-change trend, a pipeline pressure test result is generated to indicate that the delivery pipeline meets the airtightness verification conditions.

2. The method according to claim 1, characterized in that, The communication link detection between the various sample tube devices in each laboratory, and the resulting communication link detection results, include: Generate a communication detection request and encapsulate the communication detection request into a communication detection request message; For each of the sample tube devices, perform the following communication link detection steps: The communication detection request message is sent to the sample tube device to receive the message feedback information from the sample tube device. Based on the feedback information in the message, generate the sample tube equipment audit result; Based on the generated equipment review results for each sample tube, communication link detection results are generated.

3. The method according to claim 2, characterized in that, The step of generating the sample tube equipment audit result based on the message feedback information includes: The message feedback information is standardized to obtain standardized message feedback information; Based on the standardized message feedback information, a sample tube device communication success message is generated, wherein the sample tube device communication success message represents the communication accuracy of the corresponding sample tube device; In response to the determination that the communication success information of the sample tube device meets the target communication conditions, a sample tube device review result indicating that the characterization review has passed is generated.

4. The method according to claim 1, characterized in that, The step of updating the sample tube equipment transport relationship diagram corresponding to each sample tube equipment to obtain an updated sample tube equipment transport relationship diagram includes: Determine the equipment information corresponding to each sample tube device, wherein the equipment information includes: sample tube device identifier and device location information; Obtain the template code of each intelligent monitoring entity running in different operating environments to obtain the intelligent monitoring entity code set; The code logic of the intelligent monitoring entity code set is refactored to obtain the refactored intelligent monitoring entity code set; Add a monitoring strategy plugin to the reconstructed intelligent monitoring entity code set to obtain the strategy intelligent monitoring entity code; The code of the strategy intelligent monitoring body is compiled to obtain the target number of strategy intelligent monitoring bodies; Based on the information of each device, each strategy intelligent monitoring entity is deployed to the corresponding monitoring node in the sample tube device transport relationship diagram; Based on the deployed intelligent monitoring entities of various strategies, the sample tube equipment transport relationship diagram is updated to obtain an updated sample tube equipment transport relationship diagram.

5. A sample tube equipment status detection device, characterized in that, include: The detection unit is configured to detect the communication links between the sample tube devices in each laboratory and obtain the communication link detection results. The updating unit is configured to update the monitoring nodes of the sample tube device transport relationship diagram corresponding to each sample tube device in response to determining that the communication link detection result indicates that the communication link is normal, so as to obtain an updated sample tube device transport relationship diagram, wherein the sample tube device transport relationship diagram represents the transport relationship of sample tubes between each sample tube device; The status detection unit is configured to perform the following detection steps based on the updated sample tube device delivery relationship diagram and each monitoring node: performing delivery pipeline status detection on each sample tube device through each monitoring node to obtain a delivery pipeline status detection result set, wherein one delivery pipeline status detection result corresponds to one sample tube device; performing electrical status detection on each sample tube device through each monitoring node to obtain an electrical status detection result set, wherein one electrical status detection result corresponds to one sample tube device; the status detection unit is further configured to: The strategy of controlling each monitoring node is an intelligent monitoring body that performs pipeline air pressure detection on the delivery pipeline and obtains the pipeline air pressure detection results. Data anomaly detection is performed on the sample tube delivery datasets collected by each strategy intelligent monitoring body to obtain a sample tube delivery data detection result set. Here, one sample tube delivery data detection result corresponds to one sample tube delivery data, and one sample tube delivery data corresponds to one strategy intelligent monitoring body. Based on the sample tube delivery data detection result set, and according to the delivery relationship between each sample tube device and the updated sample tube device delivery relationship diagram, the sample tube delivery data in the sample tube delivery dataset is clustered to obtain sample tube delivery data set, wherein each sample tube delivery data set corresponds to a delivery network consisting of multiple sample tube devices. The delivery status of each sample tube delivery data group in the sample tube delivery data group set is detected, and in response to the detection of each sample tube delivery data group with abnormal delivery status, a delivery status detection result set characterizing the abnormal delivery status of the sample tube is generated. The air pressure detection results of each pipeline and the delivery status detection result set are determined as the delivery status detection result set; This includes conducting pipeline air pressure testing on the delivery pipeline, including: The air pressure signal of the delivery pipeline is collected, and the air pressure signal is segmented to generate a first air pressure signal and a second air pressure signal. The first air pressure signal is the air pressure signal when the air extraction operation of the delivery pipeline is performed, and the second air pressure signal is the air pressure signal after the air extraction operation of the delivery pipeline is stopped. Determine the average value of the second air pressure signal; Based on the average value of the air pressure signal and the terminal signal value of the first air pressure signal, an air pressure change trend is generated, wherein the air pressure change trend includes: no change trend and change trend; In response to the pressure change trend being the no-change trend, a pipeline pressure test result is generated to characterize that the delivery pipeline meets the airtightness verification conditions; The marking unit is configured to mark each sample tube device and monitoring node according to the delivery pipeline status detection result set and the power status detection result set.

6. An electronic device, characterized in that, include: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1 to 4.

7. A computer-readable medium, characterized in that, It stores a computer program thereon, wherein the computer program, when executed by a processor, implements the method as described in any one of claims 1 to 4.

Images