CN-121981638-A - Monitoring method, equipment, storage medium and program product for gas-phase liquid nitrogen transfer box

CN121981638ACN 121981638 ACN121981638 ACN 121981638ACN-121981638-A

Abstract

The application discloses a monitoring method, equipment, a storage medium and a program product for a gas-phase liquid nitrogen transfer box. The method comprises the steps of establishing a dynamic threshold system for abnormality judgment based on comparison analysis of historical monitoring data and current monitoring data, automatically adjusting the dynamic threshold according to actual running characteristics of a box, carrying out risk assessment on the current transportation state based on the dynamic threshold system, determining risk grades, adjusting the collection frequency and uploading strategy of the monitoring data according to the risk grades, adopting a low-frequency collection mode when the risk is low, switching to an intermediate-frequency collection mode when the risk is high, switching to a high-frequency collection mode when the risk is high, and sending grading early warning information to a responsible person through a cloud server when the monitoring data triggers the dynamic threshold, wherein an early warning pushing mode and the emergency degree are matched with the risk grades. According to the application, through a dynamic threshold system and a self-adaptive monitoring strategy, false alarm and missing alarm are reduced, and the monitoring accuracy and the resource utilization efficiency are improved.

Inventors

ZHOU JIANGUO
WANG KAI
LI GUANGZHU
WANG PING

Assignees

北京融京科技发展有限公司

Dates

Publication Date: 20260505
Application Date: 20260124

Claims (10)

1. A method for monitoring a gas-phase liquid nitrogen transfer box, which is applied to the gas-phase liquid nitrogen transfer box and is used for transferring biological samples, the method comprising: Based on the comparative analysis of the historical monitoring data and the current monitoring data, establishing a dynamic threshold system for abnormality judgment, wherein the dynamic threshold system automatically adjusts a dynamic threshold according to the actual operation characteristics of the box body, and the dynamic threshold comprises a temperature fluctuation threshold and a residual quantity threshold; based on the dynamic threshold system, carrying out risk assessment on the current transportation state and determining a risk level, wherein the risk level is comprehensively assessed by the following factors of the ratio of the residual heat preservation time to the task residual time, the deviation degree of temperature data relative to the temperature fluctuation threshold, the change rate of consumption rate and the change amplitude of environmental temperature parameters; according to the risk level, adjusting the acquisition frequency and uploading strategy of monitoring data, wherein the monitoring data comprises temperature data and weight data: when the risk level is low risk, adopting a low-frequency acquisition mode, acquiring monitoring data at a first time interval and uploading the monitoring data to a remote cloud server at a second time interval; when the risk level rises to the risk of middle frequency, automatically switching to a middle frequency acquisition mode, and shortening an acquisition time interval and an uploading time interval; When the risk level is increased to a high risk, automatically switching to a high-frequency acquisition mode, continuously acquiring at the shortest time interval and uploading in real time; When the monitoring data trigger the dynamic threshold value, the cloud server sends grading early warning information to a preset responsibility person, and the pushing mode and the emergency degree of the grading early warning information are matched with the risk grade.
2. The method of claim 1, further comprising multi-bin co-monitoring: Associating a plurality of gas-phase liquid nitrogen transfer boxes in the same transportation task into a batch task, wherein each box is configured with sample type attributes in the batch task, and the sample type attributes comprise temperature sensitivity level of the samples, storage aging requirements and association dependency relations with other boxes; taking the sample type attribute as a weight factor for calculating the risk level, so that different sample type boxes calculate differentiated risk levels under the same monitoring data, wherein the higher the temperature sensitivity level is, the larger the influence weight of temperature fluctuation on the risk level is; When the risk level of a certain box body is increased or early warning is triggered, automatically identifying and marking a corresponding association box body based on the association dependency relationship, wherein the association dependency relationship comprises a pairing sample relationship, a complete detection sample relationship and a comparison group and experiment group relationship; when a certain box triggers early warning, the cloud server sends batch early warning information to the responsibility person, wherein the batch early warning information comprises abnormal box IDs and sample types, an affected associated box list and a suggested emergency treatment scheme.
3. The method of claim 1, wherein the monitoring data further comprises: The obtained box body posture data are continuously monitored through a posture sensor; Continuously acquiring the obtained position information through a positioning module; The dynamic threshold values further include an imbalance threshold value and a deviation threshold value; the trigger dynamic threshold includes: The fluctuation of the temperature data is greater than the temperature fluctuation threshold, the residual amount is less than the residual amount threshold, the tank posture data reaches the unbalance threshold, and the position information exceeds the deviation threshold.
4. A method according to claim 3, further comprising an adsorbent material status assessment: Based on the fusion analysis of the temperature data and the weight data, establishing a desorption characteristic curve of the adsorption material, wherein the desorption characteristic curve is used for representing the correspondence between the desorption rate and the weight change of liquid nitrogen in different temperature intervals; calculating the deviation degree of the current desorption characteristic and the desorption characteristic curve in real time, and judging that the adsorption material has abnormal performance when the deviation degree exceeds a preset deviation threshold value; When the performance abnormality of the adsorption material is judged, correcting the liquid nitrogen consumption rate parameter, recalculating the residual heat preservation duration, simultaneously improving the risk grade weight in the risk assessment model, and sending the corrected prediction result and the abnormality reason to the responsible person through the cloud server.
5. The method according to claim 4, wherein the method further comprises: and continuously recording the temperature data, the weight data, the box posture data, the position information, the risk level change record and the early warning trigger record in a time stamp form during the execution of the transportation task to form a tamper-proof tracking data chain for generating a compliance report after the transportation task is finished.
6. The method of claim 5, wherein the method further comprises: calculating performance attenuation indexes of each box body based on all monitoring data recorded in a detection period by taking the preset detection period as a unit, wherein the performance attenuation indexes comprise an increasing trend of consumption rate, a decreasing trend of heat preservation duration under the same environment temperature, an increasing trend of temperature fluctuation amplitude and an increasing trend of early warning trigger frequency; Comparing the performance attenuation index with a theoretical performance benchmark of the box body, and judging that the corresponding box body enters a performance attenuation early warning state when the consumption rate is increased by more than a preset first percentage threshold value than an initial value or the heat preservation duration is reduced by more than a preset second percentage threshold value than the initial value; And summarizing the box body in the performance attenuation early warning state and the corresponding performance attenuation index, sending the box body to the responsible person through the cloud server, and giving maintenance suggestions.
7. The method of claim 1, wherein the hierarchical early warning information comprises an early warning level and a push strategy: The early warning level is comprehensively determined according to the risk level and the triggered dynamic threshold type, and is yellow early warning when the risk level is low in risk and only a single threshold is triggered, orange early warning when the risk level is medium in risk or a plurality of thresholds are triggered simultaneously, and red early warning when the risk level is high in risk or a key safety threshold is triggered; Different message pushing strategies are set according to different early warning levels, yellow early warning is notified through an application message pushing mode, orange early warning is notified through an application message pushing mode and a short message mode, and red early warning is notified through an application message pushing mode, a short message mode, a mail mode and a telephone voice mode.
8. A monitoring device comprising one or more processors and memory coupled to the one or more processors, the memory to store computer program code comprising computer instructions that the one or more processors invoke to cause the monitoring device to perform the method of any of claims 1-7.
9. A computer readable storage medium comprising instructions which, when run on a monitoring device, cause the monitoring device to perform the method of any of claims 1-7.
10. A computer program product, characterized in that the computer program product, when run on a monitoring device, causes the monitoring device to perform the method according to any of claims 1-7.

Description

Monitoring method, equipment, storage medium and program product for gas-phase liquid nitrogen transfer box Technical Field The application relates to the technical field of intelligent monitoring, in particular to a monitoring method, equipment, a storage medium and a program product for a gas-phase liquid nitrogen transfer box. Background The gas phase liquid nitrogen transfer box is a special container for preserving biological samples, vaccines, cells and other temperature sensitive substances by utilizing the low temperature characteristic of liquid nitrogen. In the medical, scientific and biopharmaceutical fields, such samples often need to be transported over long distances in a cryogenic environment to ensure sample activity and assay effectiveness. The gas-phase liquid nitrogen transfer box is usually used for absorbing liquid nitrogen through an adsorption material, and continuously releases low-temperature gas in the transfer process to maintain the temperature in the box body, so that the low-temperature preservation of a sample is realized. In the related art, a part of gas-phase liquid nitrogen transfer box is provided with sensors such as temperature, pressure and the like, and is used for recording the state change in the box body. Real-time transfer box state detection is carried out in the transportation task process through data transmission, so that the change of the state of the transfer box can be timely grasped, and early warning protection measures can be timely carried out on possible risk accidents. However, in a practical working environment, different batches and different service lives of the transfer boxes behave differently under the same transportation conditions. The system has the advantages that the performance of part of the box body is stable, the temperature fluctuation range is small, the consumption of liquid nitrogen is stable, the temperature fluctuation is larger and the consumption is faster due to the aging of adsorption materials or the difference of environmental adaptability, false alarm and missing alarm easily occur in actual use, the accuracy is damaged, the system gives out early warning when the system normally fluctuates, the resource waste and the fatigue of responsible persons are caused, and the system does not give early warning when the temperature of the box body with the performance being attenuated is obviously abnormal, and the optimal treatment time is missed. Disclosure of Invention The application provides a monitoring method, equipment, a storage medium and a program product for a gas-phase liquid nitrogen transfer box, which are used for improving the effectiveness of safety monitoring of the gas-phase liquid nitrogen transfer box. The application provides a monitoring method of a gas-phase liquid nitrogen transfer box, which is applied to the gas-phase liquid nitrogen transfer box, wherein the gas-phase liquid nitrogen transfer box is used for transferring biological samples; based on a dynamic threshold system, risk assessment is carried out on the current transportation state, and a risk level is determined, wherein the risk level is comprehensively assessed through the following factors of the ratio of the residual heat preservation time to the task residual time, the deviation degree of temperature data relative to a temperature fluctuation threshold, the change rate of consumption rate and the change amplitude of environmental temperature parameters, the collection frequency and uploading strategy of monitoring data are adjusted according to the risk level, the monitoring data comprise temperature data and weight data, when the risk level is low risk, a low-frequency collection mode is adopted, the monitoring data are collected at a first time interval and uploaded to a remote cloud server at a second time interval, when the risk level is increased to a middle-frequency collection mode, the collection time interval and the uploading time interval are shortened, when the risk level is increased to a high risk level, the high-frequency collection mode is automatically switched, the monitoring data are continuously collected at the shortest time interval and uploaded in real time, when the monitoring data trigger the dynamic threshold, the cloud server is used for triggering classification early warning information to preset responsibility person, and the pushing mode and the emergency degree of classification early warning information are matched with the risk level. According to the embodiment, the temperature fluctuation threshold and the residual quantity threshold can be automatically adjusted according to the actual operation characteristics of the box body by establishing a dynamic threshold system based on the comparison analysis of the historical monitoring data and the current monitoring data, the early warning judgment basis is converted into a dynamic base line reflecting the individual performance of the box body from a fixe