Liquid level management system of liquid nitrogen tank group

Abstract

The invention relates to the technical field of liquid nitrogen management, and discloses a liquid nitrogen tank group liquid level management system which comprises a liquid level detection module, a control center module, a buzzer alarm module, a computer administrator end, a mobile phone common user end and an electric control lock module. The liquid level is converted into a level signal by utilizing the characteristic that different forward voltages immersed or not immersed in liquid nitrogen output high and low levels through a sampling and hysteresis comparison circuit when a light emitting diode works, the type of a sent broadcast packet is judged through a control center module, and when the monitored liquid level is lower than a threshold value, the control center module triggers a buzzer to give an alarm. When the computer administrator side monitors a broadcast packet with an alarm signal, an optimal allocation algorithm is triggered, and tasks are allocated to the mobile phone administrator side, so that the liquid level of the liquid nitrogen tank is automatically monitored, an alarm is given, meanwhile, optimal allocation of the management tasks is completed, the situation that too much liquid nitrogen volatilizes, irreversible damage is caused to cryopreserved specimens is avoided, and the cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of liquid nitrogen management technology, and in particular to a liquid nitrogen tank level management system. Background Technology

[0002] Liquid nitrogen (-196℃), as an ultra-low temperature medium, is widely used in biomedicine (such as cell, vaccine, and organ preservation), semiconductor manufacturing (cooling of superconducting materials), scientific research (low-temperature physics research), and industrial fields (deep cryogenic processing of materials). The storage and use of liquid nitrogen requires strict monitoring of the liquid level to ensure sample safety, stable equipment operation, and efficient resource utilization. Abnormal liquid levels may lead to the failure of stored samples, equipment damage, or waste of liquid nitrogen; therefore, real-time and accurate liquid level monitoring and management technology is crucial.

[0003] Traditional liquid level monitoring technologies have limitations and the following shortcomings: Mechanical sensors (float, pressure type): materials are prone to embrittlement at low temperatures, mechanical parts are prone to freezing and jamming, resulting in high maintenance costs and short lifespans; Capacitive sensors: the dielectric constant is significantly affected by temperature fluctuations, and density changes caused by liquid nitrogen vaporization reduce measurement accuracy; Ultrasonic sensors: extreme low temperatures may affect the speed of sound wave propagation, and condensation or fog interference can easily lead to signal attenuation; Manual inspection: relies on experience-based judgment, cannot monitor in real time, has the risk of missed detections, and has high labor costs. In practical application scenarios, there are also challenges such as different tank locations, actual changes in liquid nitrogen tank levels, and the importance and urgency of the projects supplied by the liquid nitrogen tanks. Liquid level management not only needs to consider the timeliness of liquid nitrogen tank level detection and maintenance for each individual tank, but also the rational allocation of maintenance tasks for the liquid nitrogen tank group within a region, which further increases the difficulty of liquid nitrogen tank group level detection and management.

[0004] Therefore, how to reduce the complexity and maintenance cost of liquid nitrogen tank level detection, improve the intelligence and efficiency of liquid level management, reduce the loopholes in existing liquid level detection technologies, and ensure the stable and safe operation of the system containing the liquid nitrogen tank while reducing labor costs is an urgent technical problem to be solved. Summary of the Invention

[0005] The present invention provides a liquid nitrogen tank group level management system, which aims to solve at least one of the above-mentioned technical problems.

[0006] To achieve the above objectives, the present invention provides a liquid nitrogen tank level management system, comprising: The liquid level detection module includes several diode sensors respectively disposed at different heights inside the liquid nitrogen tank, and is configured to output a level signal characterizing whether each diode sensor is submerged; The control center module, which connects the liquid level detection module and the computer administrator terminal, is configured to generate a Bluetooth broadcast packet containing liquid nitrogen tank data and detection analysis results from several level signals output by the liquid level detection module, and send the Bluetooth broadcast packet to the computer administrator terminal. The computer administrator terminal connects the control center module and the mobile phone ordinary user terminal. It is configured to continuously receive Bluetooth broadcast packets sent by the control center module, establish a liquid nitrogen database based on the liquid nitrogen tank data in the Bluetooth broadcast packets, and when the detection and analysis results in the Bluetooth broadcast packets contain alarm signals, it triggers the optimal allocation algorithm to match the target staff of the current alarm event, generates management tasks based on the liquid nitrogen tank data, and sends the management tasks to the target staff's mobile phone ordinary user terminal. The mobile phone client, which is a regular user terminal, connects to the computer administrator terminal and the control center module. It is configured to receive management tasks sent by the computer administrator terminal. After performing identification and authentication, it sends the unlocking command for the alarm event to the control center module via a key. The electric lock module is connected to the control center module and is configured to receive the unlocking command issued by the control center module and perform the unlocking action of the liquid nitrogen tank lid according to the unlocking command.

[0007] Optionally, the liquid level detection module further includes: a driving circuit and a level output circuit; The driving circuit includes a power supply, a first resistor connected in series in the main circuit, a Zener diode connected in parallel with the diode sensor, and a second resistor connected in series with the diode sensor. The level output circuit includes a sample-and-hold circuit for sampling the output signal of each diode sensor, a hysteresis comparator circuit for noise suppression of the sampled signal output by the sample-and-hold circuit and comparison with a preset voltage value, and converts the voltage judgment result output by the hysteresis comparator circuit into a level signal for output.

[0008] Optionally, the control center module is configured as a microprocessor, the microprocessor having a liquid level information sampling driver, the liquid level information sampling driver performing the following steps: The liquid level detection module is woken up at preset intervals to obtain the level signal of each diode sensor output by the liquid level detection module and form a binary status word; Based on the preset mapping relationship between the binary status word and the liquid level height in the liquid nitrogen tank, the liquid level height in the liquid nitrogen tank is restored and recorded as the liquid level status; Optionally, the control center module is configured as a microprocessor, the microprocessor having a liquid level information sampling driver, the liquid level information sampling driver performing the following steps: The liquid level detection module is woken up at preset intervals to obtain the level signal of each diode sensor output by the liquid level detection module and form a binary status word; Based on the preset mapping relationship between the binary status word and the liquid level height in the liquid nitrogen tank, the liquid level height in the liquid nitrogen tank is restored and recorded as the liquid level status; Based on the recorded liquid level status and the liquid level range, a linear regression method is used to dynamically generate the remaining time for the liquid level to drop to the lowest alarm liquid level threshold, and the frequency of the detection module being woken up is adjusted according to the remaining time.

[0009] Optionally, the liquid level status is configured as a liquid level percentage, and the liquid level range includes a first range of 90%-80%, a second range of 80%-60%, a third range of 60%-50%, and a fourth range of 50%-40%.

[0010] Optionally, based on the recorded liquid level status and the current liquid level range, a linear regression method is used to dynamically generate the remaining time for the liquid level to drop to the lowest alarm liquid level threshold, specifically including: When the liquid level drops from 80% in the second range and enters 60%: Based on the evaporation slopes in the first and second intervals of the historical liquid level status, the average value is taken to obtain the first liquid level evaporation slope k1. According to the linear regression formula T1=(L_60%-L_20%) / k1, the first estimated remaining time T1 required for the liquid level to drop from the current height L_current to the lowest alarm liquid level threshold L_20% is calculated. When the liquid level drops from 60% in the third zone and enters 50%: Based on the average of the evaporation slope in the third interval of the historical liquid level status and the evaporation slope k1 of the first liquid level, the evaporation slope k2 of the second liquid level is obtained. According to the linear regression formula T1=(L_50%-L_20%) / k2, the second estimated remaining time T2 required for the liquid level to drop from the current height L_50% to the minimum alarm liquid level threshold L_20% is calculated. When the liquid level drops from 50% in the fourth zone and enters 40%: Based on the average of the evaporation slope in the fourth interval and the evaporation slope k2 of the first liquid level in the historical liquid level status, the evaporation slope k3 of the third liquid level is obtained. According to the linear regression formula T1=(L_40%-L_20%) / k3, the second estimated remaining time T3 required for the liquid level to drop from the current height L_40% to the minimum alarm liquid level threshold L_20% is calculated.

[0011] Optionally, the power supply of the liquid level detection module is controlled by a MOSFET. The gate of the MOSFET is connected to the GPIO of the microprocessor through a third resistor, the source is connected to the power supply, and the drain is connected to the positive terminal of the diode sensor. The MOSFET is configured to supply power to the liquid level detection module during the sampling period when the microprocessor wakes up the liquid level detection module to perform liquid level acquisition, and to cut off the power supply to the liquid level detection module during the non-sampling period when the microprocessor does not wake up the liquid level detection module to perform liquid level acquisition.

[0012] Optionally, the liquid nitrogen tank level management system further includes a buzzer alarm module located locally on-site and connected to the control center module; wherein the output terminal of the control center module is connected to the base of an NPN transistor, the collector of the NPN transistor is connected to a bypass power supply, and the emitter of the NPN transistor is connected to the buzzer alarm module.

[0013] Optionally, the computer administrator terminal has a data monitoring mode and a connection initiation mode; The computer administrator terminal is normally in data monitoring mode. When it detects regular data, it initiates a connection with the control center module based on the time when the microprocessor wakes up the liquid level detection module. It receives Bluetooth broadcast packets sent by the control center module in batches, parses the liquid nitrogen tank data, and establishes a liquid nitrogen tank database. When the computer administrator detects an alarm signal, it switches to connection initiation mode, triggers the optimal allocation algorithm to match the target staff member of the current alarm event, generates a management task based on the liquid nitrogen tank data, initiates a connection between the computer administrator and the target staff member's mobile phone, and sends the management task to the target staff member's mobile phone.

[0014] Optionally, the optimal allocation algorithm is triggered to match the target staff member for the current alarm event, specifically including: Establish a three-dimensional evaluation model based on spatial, temporal, and resource dimensions to generate priority scoring expressions for management tasks when assigned to different staff members; The priority scoring expression is specifically as follows: ; In the formula, α represents the actual reachable distance from the tank location of the previous management task to the tank of the current management task, β represents the alarm level determined based on the alarm signal, γ represents the importance level of the current liquid nitrogen tank supply demand item, and A, B, and C are preset dynamic weights based on the urgency of the management task. Obtain the management task list for each staff member, and extract the task execution time period and task execution tank location for each management task to be executed recorded in the management task list; The different execution order positions of the current management task assigned to different staff members' management task lists are used as decision variables. The task execution duration is determined based on the task execution attributes of the current management task. Based on the task execution duration of the current management task and the task execution duration of each management task to be executed in the management task list, the task execution time period of each management task to be executed after the management task is assigned to the management task list is updated. Based on the updated management task list, α and β in the priority scoring expression of each management task to be executed are updated to obtain the updated priority score. The update of α is achieved by calculating the actual reachable distance from the tank position of the previous management task to the tank of the current management task when the current management task is assigned to the corresponding execution order position in the management task list of the corresponding staff member. Among them, the update of β is to estimate the liquid level height in the liquid nitrogen tank during the task execution period by using the latest calculated slope value κ, and convert the liquid level height in the liquid nitrogen tank into an alarm level according to preset rules; The first constraint is that after a management task is assigned to the corresponding execution order position in the management task list of the corresponding staff member, the execution waiting time between the completion time of the task execution period of each pending management task in the updated management task list of each staff member does not exceed the preset waiting time. The second constraint is that the priority score of each pending management task in the updated management task list of each staff member is not higher than the preset priority score value. The optimization objective is to minimize the sum of the priority scores of all pending management tasks in the updated management task list of each staff member. An optimization algorithm is used to solve for the optimal execution order position in the management task list of the corresponding staff member to which the management task is assigned.

[0015] Optionally, the system receives management tasks from the computer administrator and, after performing identification and authentication, sends the unlocking command for the alarm event to the control center module via a key, specifically including: After receiving a management task from the computer administrator, the mobile phone user terminal uses multispectral imaging to extract facial features and compares the extracted facial features with a pre-stored feature library to perform micro-expression recognition and blink detection for liveness assessment. Upon successful comparison, a one-time key is generated, and the unlocking command for the alarm event is sent to the control center module through the generated one-time key; When the comparison fails, a lock command is sent to the control center module to initiate a three-level lock action, including local locking, administrator alarm, and system log recording.

[0016] The beneficial effects of this invention are as follows: (1) Taking advantage of the significant change in electrical characteristics of six light-emitting diodes (LEDs) under low-temperature conditions, when liquid nitrogen covers the diodes, their temperature drops sharply, causing a significant change in the forward voltage of the diodes. By measuring this change in electrical signal, it can be determined whether the diodes are submerged in liquid nitrogen. The output level is encoded, and the time to reach the next liquid level is predicted according to the liquid level information represented by the encoding. The power supply to the liquid level detection circuit is completed by dynamically adjusting the liquid level detection frequency (low power mode → high frequency monitoring). Combined with the Bluetooth on-demand wake-up mechanism, the power consumption of the control center module is reduced. At the same time, the continuous power-on mode is replaced by pulse-driven magnetic relays (forward unlocking / reverse locking), reducing the energy consumption of the lock. This reduces the overall power consumption of the terminal device.

[0017] (2) Adopting an intelligent hierarchical response based on a coding alarm mechanism to achieve accurate fault judgment and hierarchical response, and adopting different response methods for different tasks to improve the system response speed.

[0018] (3) The optimal allocation algorithm for management tasks using a three-dimensional evaluation model and dynamic weight allocation is adopted. The algorithm utilizes the spatial dimension, time dimension and resource dimension included in the three-dimensional evaluation model, and executes the optimal allocation algorithm for management tasks using dynamic weight allocation when the task types reported by the control center module are different. This ensures the stable and safe operation of the system where the liquid nitrogen tank group is located. While considering the timeliness of liquid level detection and management maintenance of each individual liquid nitrogen tank, it also considers the rationality of the allocation of maintenance tasks for the liquid nitrogen tank group within the region, thereby improving the intelligence and efficiency of liquid level management and reducing the loopholes in the existing liquid level monitoring technology.

[0019] (4) Combining facial recognition biometric authentication with dynamic key technology and a secure two-factor authentication with a validity period of 300 seconds, it improves security and eliminates the risk of key reuse compared to traditional password verification methods. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the main modules of the liquid nitrogen tank level management system of the present invention; Figure 2 This is a circuit diagram of the control center module of the liquid nitrogen tank level management system of the present invention; Figure 3 This is a flowchart illustrating the triggering of the liquid level alarm in the liquid nitrogen tank group level management system of the present invention; Figure 4 This is a flowchart illustrating the hierarchical alarm process of the liquid nitrogen tank level management system of the present invention. Figure 5 This is a schematic diagram of the binary status word of the liquid nitrogen tank level management system of the present invention; Figure 6 This is a flowchart of the optimal allocation algorithm for the liquid nitrogen tank group level management system of the present invention; Figure 7 This is a block diagram of the electrically controlled lock of the liquid nitrogen tank level management system of the present invention.

[0021] Explanation of reference numerals in the attached figures: 10-Liquid level detection module; 20-Control center module; 30-Computer administrator terminal; 40-Mobile phone ordinary user terminal; 50-Electric lock module; 60-Buzzer alarm module. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0023] This invention provides a liquid nitrogen tank level management system, referring to... Figure 1 , Figure 1 This is a schematic diagram of the liquid nitrogen tank level management system according to an embodiment of the present invention.

[0024] In this embodiment, a liquid nitrogen tank level management system includes: The liquid level detection module 10 includes a plurality of diode sensors respectively disposed at different heights inside the liquid nitrogen tank, and is configured to output a level signal characterizing whether each of the diode sensors is submerged; The control center module 20, which connects the liquid level detection module 10 and the computer administrator terminal 30, is configured to generate a Bluetooth broadcast packet containing liquid nitrogen tank data and detection analysis results from a number of level signals output by the liquid level detection module 10, and send the Bluetooth broadcast packet to the computer administrator terminal 30. The computer administrator terminal 30 is connected to the control center module 20 and the mobile phone ordinary user terminal 40. It is configured to continuously receive Bluetooth broadcast packets sent by the control center module 20, establish a liquid nitrogen database based on the liquid nitrogen tank data in the Bluetooth broadcast packets, and when the detection and analysis results in the Bluetooth broadcast packets contain alarm signals, trigger the optimal allocation algorithm to match the target staff of the current alarm event, generate management tasks according to the liquid nitrogen tank data, and send the management tasks to the target staff's mobile phone ordinary user terminal 40. The mobile phone ordinary user terminal 40 is connected to the computer administrator terminal 30 and the control center module 20. It is configured to receive management tasks sent by the computer administrator terminal 30. After performing identification and authentication, it will send the unlocking command for the alarm event to the control center module 20 through the key. The electric lock module 50 is connected to the control center module 20 and is configured to receive the unlocking command issued by the control center module 20 and perform the unlocking action of the liquid nitrogen tank lid according to the unlocking command.

[0025] It should be noted that traditional liquid level monitoring technologies have limitations and the following shortcomings: Mechanical sensors (float, pressure type): materials are prone to embrittlement at low temperatures, mechanical parts are prone to freezing and jamming, resulting in high maintenance costs and short lifespans; Capacitive sensors: the dielectric constant is significantly affected by temperature fluctuations, and density changes caused by liquid nitrogen vaporization reduce measurement accuracy; Ultrasonic sensors: extreme low temperatures may affect the speed of sound wave propagation, and condensation or fog interference can easily lead to signal attenuation; Manual inspection: relies on experience-based judgment, cannot monitor in real time, has the risk of missed detections, and has high labor costs. In practical application scenarios, there are also challenges such as different tank locations, actual changes in liquid nitrogen tank levels, and the importance and urgency of the projects supplied by the liquid nitrogen tanks. Liquid level management not only needs to consider the timeliness of liquid nitrogen tank level detection and maintenance for each individual liquid nitrogen tank, but also the rationality of allocating maintenance tasks for the liquid nitrogen tank group within a region, which further increases the difficulty of liquid nitrogen tank group level detection and management.

[0026] To address the aforementioned issues, this embodiment proposes a liquid nitrogen tank level management system based on a liquid level sensor constructed from light-emitting diodes and a low-power microcontroller. The system includes a liquid level detection module, a control center module, a buzzer alarm module, a computer administrator terminal, a mobile phone user terminal, and an electric lock module. The liquid level detection module is installed inside the liquid nitrogen tank, and the control center module is installed at the tank opening. The output of the liquid level detection module is connected to the input of the microprocessor in the control center module, and the output of the microprocessor in the control center module is connected to the power supply of the liquid level detection module, the input of the electric lock, and the buzzer alarm module.

[0027] As is easily understood, liquid nitrogen tanks are used to store liquid nitrogen as well as biological samples.

[0028] For example, the liquid level detection module consists of six LED liquid level monitors that output liquid level detection voltages s1, s2, s3, s4, s5, and s6 from top to bottom at 15% (minimum liquid level alarm), 20% (low liquid level alarm), 40%, 60%, 80%, and 90% (high liquid level alarm). The control center module consists of a low-power microprocessor and a Bluetooth module. The computer administrator terminal communicates with the control center module and ordinary mobile phone terminals via Bluetooth to receive Bluetooth broadcast packets from the control center module in batches. The system receives data from the liquid nitrogen tank to establish a database. Upon receiving a Bluetooth broadcast packet with an alarm signal, it triggers an optimal allocation algorithm to achieve real-time fusion of multi-source data and simultaneously sends a task to a regular mobile user terminal. The mobile user terminal implements a dual-security authentication mechanism: it receives a task signal from the computer administrator, uploads its GPS location to the computer, performs facial recognition, and sends a one-time key to the control center module via Bluetooth to unlock the device. The electronic lock consists of a bolt and a latch; the bolt is located on the liquid nitrogen tank lid, and the latch is located on the outside of the tank opening. The control center module communicates remotely with both the computer administrator terminal and the mobile user terminal via Bluetooth.

[0029] Therefore, the liquid nitrogen tank level management system provided in this embodiment utilizes the characteristic that when a light-emitting diode (LED) is working, different positive voltages when it is immersed or not immersed in liquid nitrogen are sampled and output as high or low levels by a hysteresis comparison circuit. The liquid level is converted into a level signal, and the control center module determines the type of broadcast packet to be sent. When the current monitored liquid level is lower than the threshold, the control center module triggers a buzzer alarm. When the computer administrator listens for a broadcast packet with an alarm signal, it triggers the optimal allocation algorithm to allocate tasks to the mobile administrator. After completing facial recognition authentication, a one-time key is sent to the control center module. After verifying the key, the control center module sends a positive pulse to the electric lock module, thereby opening the liquid nitrogen tank. This achieves automatic monitoring of the liquid nitrogen tank level and alarm, while simultaneously achieving optimal allocation of management tasks, preventing excessive evaporation of liquid nitrogen and causing irreversible damage to frozen specimens, and reducing costs.

[0030] In a preferred embodiment, the liquid level detection module further includes: a driving circuit and a level output circuit; The driving circuit includes a power supply, a first resistor connected in series in the main circuit, a Zener diode connected in parallel with the diode sensor, and a second resistor connected in series with the diode sensor. The level output circuit includes a sample-and-hold circuit for sampling the output signal of each diode sensor, a hysteresis comparator circuit for noise suppression of the sampled signal output by the sample-and-hold circuit and comparison with a preset voltage value, and converts the voltage judgment result output by the hysteresis comparator circuit into a level signal for output.

[0031] In this embodiment, as Figure 2 As shown, the LED driving circuit includes an 18V power supply, a resistor connected in series in the main circuit, a Zener diode connected in parallel with the LED, and a resistor connected in series with the LED. The output signal of the LED is passed through a sample-and-hold circuit to output a more accurate signal. The voltage follower output of the sample-and-hold circuit is connected to the inverting input of the operational amplifier. A reference voltage is input to the non-inverting input of the operational amplifier, and a resistor is connected between the non-inverting input and output of the operational amplifier to introduce positive feedback and give the circuit a hysteresis phenomenon.

[0032] In a preferred embodiment, the control center module is configured as a microprocessor, the microprocessor having a liquid level information sampling driver, the liquid level information sampling driver performing the following steps: S11: Wake up the liquid level detection module at preset intervals, obtain the level signal of each diode sensor output by the liquid level detection module, and form a binary status word; S12: Based on the preset mapping relationship between the binary status word and the liquid level height in the liquid nitrogen tank, restore the liquid level height in the liquid nitrogen tank and record it as the liquid level status; S13: Based on the recorded liquid level status and the liquid level range, use linear regression to dynamically generate the remaining time for the liquid level to drop to the lowest alarm liquid level threshold, and adjust the frequency of the detection module being woken up based on the remaining time.

[0033] Specifically, the liquid level status is configured as a liquid level percentage, and the liquid level range includes a first range of 90%-80%, a second range of 80%-60%, a third range of 60%-50%, and a fourth range of 50%-40%.

[0034] Based on this, according to the recorded liquid level status and the current liquid level range, a linear regression method is used to dynamically generate the remaining time for the liquid level to drop to the lowest alarm liquid level threshold, specifically including: When the liquid level drops from 80% in the second range and enters 60%: Based on the evaporation slopes in the first and second intervals of the historical liquid level status, the average value is taken to obtain the first liquid level evaporation slope k1. According to the linear regression formula T1=(L_60%-L_20%) / k1, the first estimated remaining time T1 required for the liquid level to drop from the current height L_current to the lowest alarm liquid level threshold L_20% is calculated. When the liquid level drops from 60% in the third zone and enters 50%: Based on the average of the evaporation slope in the third interval of the historical liquid level status and the evaporation slope k1 of the first liquid level, the evaporation slope k2 of the second liquid level is obtained. According to the linear regression formula T1=(L_50%-L_20%) / k2, the second estimated remaining time T2 required for the liquid level to drop from the current height L_50% to the minimum alarm liquid level threshold L_20% is calculated. When the liquid level drops from 50% in the fourth zone and enters 40%: Based on the average of the evaporation slope in the fourth interval and the evaporation slope k2 of the first liquid level in the historical liquid level status, the evaporation slope k3 of the third liquid level is obtained. According to the linear regression formula T1=(L_40%-L_20%) / k3, the second estimated remaining time T3 required for the liquid level to drop from the current height L_40% to the minimum alarm liquid level threshold L_20% is calculated.

[0035] In practical applications, the frequency at which the detection module is woken up can be adjusted according to the remaining time. This frequency can be set to be negatively correlated with the remaining time, that is, the shorter the remaining time, the higher the frequency.

[0036] Therefore, through the frequency generation algorithm described above, the device can reduce the sampling frequency during normal operation, disconnect the power supply to the liquid level detection circuit module, and reduce power consumption; when the low liquid level warning is about to be reached, the sampling frequency can be increased, and it can be determined whether a minimum liquid level alarm needs to be triggered.

[0037] In a preferred embodiment, the power supply of the liquid level detection module is controlled by a MOSFET. The gate of the MOSFET is connected to the GPIO of the microprocessor through a third resistor, the source is connected to the power supply, and the drain is connected to the positive terminal of the diode sensor. The MOSFET is configured to supply power to the liquid level detection module during the sampling period when the microprocessor wakes up the liquid level detection module to perform liquid level acquisition, and to cut off the power supply to the liquid level detection module during the non-sampling period when the microprocessor does not wake up the liquid level detection module to perform liquid level acquisition.

[0038] In this embodiment, under the liquid level prediction algorithm of the control center module, the microprocessor in the control center module wakes up the Bluetooth module and the liquid level detection module in the control center module according to the predicted time to reach the next liquid level stage; after the monitoring is completed, the Bluetooth module in the control center module enters a sleep state, and at the same time, the power supply to the liquid level detection module is stopped; the power supply terminal of the liquid level detection module is controlled by a MOSFET, the gate of the MOSFET is connected to the MCU GPIO through a resistor, the source is connected to the power supply, and the drain is connected to the positive terminal of the sensor, which is used to completely cut off the power supply to the liquid level detection module during non-sampling periods.

[0039] In a preferred embodiment, the liquid nitrogen tank level management system further includes a buzzer alarm module 60 located locally on-site and connected to the control center module; wherein the output terminal of the control center module is connected to the base of an NPN transistor, the collector of the NPN transistor is connected to a bypass power supply, and the emitter of the NPN transistor is connected to the buzzer alarm module 60.

[0040] In this embodiment, when the liquid level detection module detects that the liquid nitrogen tank level is lower than the level 2 alarm value, it sends a pulse to the buzzer module to trigger the buzzer alarm, reminding the staff. At the same time, it sends a broadcast packet with the level 2 alarm to the computer. After the computer administrator detects the broadcast packet with the level 2 alarm, a desktop prompt pops up, triggering the optimal allocation algorithm. After completing the calculation, the algorithm automatically sends the task to the ordinary user's mobile phone. After the ordinary user's mobile phone completes face recognition, it sends a one-time key to the control center module. After the control center module verifies that the information is correct, it sends a pulse to the electric lock to unlock the liquid nitrogen tank.

[0041] It should be noted that the electronic lock module for the liquid nitrogen tank includes a latch and a buckle. The latch is located on the liquid nitrogen tank lid, and the buckle is located on the outside of the liquid nitrogen tank opening. Furthermore, the latch and buckle form a mechanical pin structure. This mechanical pin structure, together with the magnetic relay protector, constitutes the electronic lock module. The magnetic relay protector consists of an internal permanent magnet, a coil, normally open contacts, and normally closed contacts, and operates in two modes: set and reset. When the control center module outputs a high level to coil 1, the normally open contact closes, unlocking the tank; when the control center module outputs a high level to coil 2, the normally closed contact opens, locking the tank.

[0042] In a preferred embodiment, the computer administrator terminal has a data monitoring mode and a connection initiation mode; The computer administrator terminal is normally in data monitoring mode. When it detects regular data, it initiates a connection with the control center module based on the time when the microprocessor wakes up the liquid level detection module. It receives Bluetooth broadcast packets sent by the control center module in batches, parses the liquid nitrogen tank data, and establishes a liquid nitrogen tank database. When the computer administrator detects an alarm signal, it switches to connection initiation mode, triggers the optimal allocation algorithm to match the target staff member of the current alarm event, generates a management task based on the liquid nitrogen tank data, initiates a connection between the computer administrator and the target staff member's mobile phone, and sends the management task to the target staff member's mobile phone.

[0043] In this embodiment, as Figure 3As shown, six LEDs are installed inside the liquid nitrogen tank to monitor the liquid level. A buzzer alarm is triggered when the liquid level is above a certain threshold, and also when the liquid level is below a certain threshold. Simultaneously, the control center module transmits information to the computer administrator via a broadcast packet embedded with a secondary alarm signal. When the computer administrator detects a broadcast packet with an alarm signal, the optimal allocation algorithm is triggered, and the task is assigned to a regular mobile user. The regular mobile user switches from broadcast mode to connection mode to receive the task. After completing facial recognition, the regular mobile user sends a one-time key to the control center module. The control center module verifies the key. If verified, the control center module sends a positive pulse to the control coil to unlock the electric lock. The staff then proceeds to the liquid nitrogen tank, adds liquid nitrogen, closes the tank, and clicks "task complete." The control center module then sends a reverse DC pulse to the control coil to lock the electric lock.

[0044] In a preferred embodiment, triggering the optimal allocation algorithm to match the target staff member for the current alarm event specifically includes: S21: Establish a three-dimensional evaluation model based on spatial, temporal, and resource dimensions to generate priority scoring expressions for management tasks when assigned to different staff members; The priority scoring expression is specifically as follows: In the formula, α represents the actual reachable distance from the tank location of the previous management task to the tank of the current management task, β represents the alarm level determined based on the alarm signal, γ represents the importance level of the current liquid nitrogen tank supply demand item, and A, B, and C are preset dynamic weights based on the urgency of the management task. S22: Obtain the management task list for each staff member, and extract the task execution time period and task execution tank location for each management task to be executed recorded in the management task list; S23: Assign the current management task to different execution order positions in the management task lists of different staff as decision variables. Determine the task execution duration based on the task execution attributes of the current management task. Based on the task execution duration of the current management task and the task execution duration of each management task to be executed in the management task list, update the task execution time period of each management task to be executed after the management task is assigned to the management task list. Based on the updated management task list, update α and β in the priority scoring expression of each management task to be executed to obtain the updated priority score. The update of α is achieved by calculating the actual reachable distance from the tank position of the previous management task to the tank of the current management task when the current management task is assigned to the corresponding execution order position in the management task list of the corresponding staff member. Among them, the update of β is to estimate the liquid level height in the liquid nitrogen tank during the task execution period by using the latest calculated slope value κ, and convert the liquid level height in the liquid nitrogen tank into an alarm level according to preset rules; S24: The first constraint is that after a management task is assigned to the corresponding execution order position in the management task list of the corresponding staff member, the execution waiting time between the completion time of the task execution period of each pending management task in the updated management task list of each staff member does not exceed the preset waiting time. The second constraint is that the priority score of each pending management task in the updated management task list of each staff member is not higher than the preset priority score value. The optimization objective is to minimize the sum of the priority scores of all pending management tasks in the updated management task list of each staff member. An optimization algorithm is used to solve for the optimal execution order position in the management task list of the corresponding staff member to which the management task is assigned.

[0045] In this embodiment, a three-dimensional evaluation model based on spatial, temporal, and resource dimensions is first established. This three-dimensional evaluation model considers the following factors: Spatial dimension: Calculate the actual reachable distance between each ordinary mobile phone user terminal and the tank, denoted as α; Time dimension: Assess the urgency of the task, denoted as β, and the assessment method is as follows: like Figure 4 and Figure 5 As shown, the control center module detected the following output from the liquid level detection module: 011111: Level 1 warning, recorded locally in the control center module, with β=1; 111111: Level 2 alarm, recorded locally in the control center module, triggers the buzzer alarm, and simultaneously sends a broadcast packet with low-level alarm to the computer administrator terminal, with β=2; 000000: High-level alarm, recorded locally in the control center module, triggers a buzzer alarm, reminding the staff to stop the operation. If the operation exceeds the specified time by 30 seconds, it is recorded as an erroneous operation and can be used for staff assessment. Staff need to wait on the side when adding liquid nitrogen, so the optimal algorithm is not triggered. The combination of 000000, 000001, 000011, 000111, 001111, 011111, and 111111: Fault alarm, triggering the buzzer alarm, and simultaneously sending a broadcast packet with fault alarm to the computer administrator, with β=3. Resource dimension: Consider the importance assessment of the items currently stored in the liquid nitrogen tank, denoted as γ. Assessment method: classify the importance level of the items stored in the liquid nitrogen tank into 1, 2, 3, 4, and implement hierarchical management of the liquid nitrogen tank; The dynamic weight allocation is specifically as follows: when the task types reported by the control center module are different, the optimal allocation algorithm calculates the dynamic weight allocation, taking spatial weight as A, time weight as B, and resource weight as C (A+B+C=1): Urgent tasks: Time weight > Space weight > Resource weight; For routine tasks: Resource weight > Spatial weight > Time weight; Special task: Weighting ratios are manually specified; Subsequently, this embodiment uses the different execution order positions of the current management task assigned to different staff members' management task lists as decision variables. The task execution duration is determined based on the task execution attributes of the current management task (e.g., the estimated time for liquid nitrogen addition related to the amount of liquid nitrogen added, which can be estimated based on historical management task execution status). Based on the task execution duration of the current management task and the task execution duration of each pending management task in the management task list, the task execution time period of each pending management task after the management task is assigned to the management task list is updated. Based on the updated management task list, α and β in the priority scoring expression of each pending management task are updated to obtain the updated priority score. Then, the management task... After being assigned to the corresponding execution order position in the management task list of the corresponding staff member, the execution waiting time between the completion time of each pending management task in the updated management task list of each staff member and the allocation time of the management task does not exceed the preset waiting time as the first constraint condition. The priority score of each pending management task in the updated management task list of each staff member is not higher than the preset priority score value as the second constraint condition. The optimization objective is to minimize the sum of the priority scores of all pending management tasks in the updated management task list of each staff member. An optimization algorithm is used to solve for the optimal execution order position in the management task list of the corresponding staff member to which the management task is assigned.

[0046] Therefore, as Figure 6 and Figure 7 As shown, this embodiment employs an optimal management task allocation algorithm based on a three-dimensional evaluation model and dynamic weight allocation. It utilizes the spatial, temporal, and resource dimensions included in the three-dimensional evaluation model, and the dynamic weight allocation algorithm is executed when the task types reported by the control center module differ. Optimization algorithms (such as particle swarm optimization or genetic algorithms) are used to determine the optimal execution order of management tasks assigned to the corresponding personnel in their management task lists. This ensures the stable and safe operation of the liquid nitrogen tank group system. While considering the timeliness of level detection and maintenance for each individual liquid nitrogen tank, it also considers the rationality of the allocation of maintenance tasks for the liquid nitrogen tank group within a region, improving the intelligence and efficiency of level management and reducing the vulnerabilities of existing level monitoring technologies.

[0047] In a preferred embodiment, the system receives a management task from the computer administrator. After performing identification and authentication, it sends an unlocking command for the alarm event to the control center module via a key. Specifically, this includes: S31: After receiving the management task sent by the computer administrator, the mobile phone user terminal uses multispectral imaging to extract facial features, and uses the extracted facial features to perform micro-expression recognition and blink detection liveness judgment similarity comparison with the pre-stored feature library. S32: Upon successful comparison, a one-time key is generated, and the unlocking command for the alarm event is sent to the control center module through the generated one-time key; S33: When the comparison fails, a lock command is sent to the control center module to initiate a three-level lock action that includes local locking, administrator alarm, and system log recording.

[0048] In this embodiment, when the mobile administrator receives a task instruction, it uses multispectral imaging technology to acquire facial features. Liveness detection is achieved through micro-expression recognition and blink detection, and a similarity comparison is performed with a pre-stored feature library. Simultaneously, a dual security authentication mechanism is implemented: On success, a key generation algorithm is triggered, generating a one-time key. The key generation format includes: key=Hash(MAC address / timestamp / random number / device key), with a configurable validity period of 300 seconds by default. On failure, a three-level locking mechanism is activated (1. Local locking; 2. Administrator alarm; 3. System log recording).

[0049] Therefore, this embodiment can accurately monitor the liquid nitrogen tank level at multiple points in a low-temperature environment, issue tiered alarms, and forward the data to the computer administrator. The computer administrator then uses an optimal allocation algorithm to distribute tasks to ordinary users' mobile phones. These users switch from broadcast mode to connection mode to receive the tasks. After facial recognition, the user sends a one-time key to the control center module. The control center module verifies the key; if verified, it sends a positive pulse to the control coil to unlock the electric lock. The user then goes to the liquid nitrogen tank, adds liquid nitrogen, closes the tank, and clicks "task complete." The control center module then sends a reverse DC pulse to the control coil to lock the electric lock. This achieves hierarchical management, real-time fusion of multi-source data, discrete level estimation, and trend prediction; it links liquid nitrogen replenishment, fault alarms, and remote monitoring functions to build a closed-loop control system; it reduces system complexity and maintenance costs, minimizes the vulnerabilities of relying solely on manual inspection and experience, and lowers labor costs.

[0050] It is understood that in the description of this specification, references to terms such as "one embodiment," "another embodiment," "other embodiments," or "first embodiment to Nth embodiment," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0051] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0052] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A liquid nitrogen tank level management system, characterized in that, include: The liquid level detection module includes several diode sensors respectively disposed at different heights inside the liquid nitrogen tank, and is configured to output a level signal characterizing whether each diode sensor is submerged; The control center module, which connects the liquid level detection module and the computer administrator terminal, is configured to generate a Bluetooth broadcast packet containing liquid nitrogen tank data and detection analysis results from several level signals output by the liquid level detection module, and send the Bluetooth broadcast packet to the computer administrator terminal. The computer administrator terminal connects the control center module and the mobile phone ordinary user terminal. It is configured to continuously receive Bluetooth broadcast packets sent by the control center module, establish a liquid nitrogen database based on the liquid nitrogen tank data in the Bluetooth broadcast packets, and when the detection and analysis results in the Bluetooth broadcast packets contain alarm signals, it triggers the optimal allocation algorithm to match the target staff of the current alarm event, generates management tasks based on the liquid nitrogen tank data, and sends the management tasks to the target staff's mobile phone ordinary user terminal. The mobile phone client, which is a regular user terminal, connects to the computer administrator terminal and the control center module. It is configured to receive management tasks sent by the computer administrator terminal. After performing identification and authentication, it sends the unlocking command for the alarm event to the control center module via a key. The electric lock module is connected to the control center module and is configured to receive the unlocking command issued by the control center module and perform the unlocking action of the liquid nitrogen tank lid according to the unlocking command.

2. The liquid nitrogen tank level management system as described in claim 1, characterized in that, The liquid level detection module further includes: a driving circuit and a level output circuit; The driving circuit includes a power supply, a first resistor connected in series in the main circuit, a Zener diode connected in parallel with the diode sensor, and a second resistor connected in series with the diode sensor. The level output circuit includes a sample-and-hold circuit for sampling the output signal of each diode sensor, a hysteresis comparator circuit for noise suppression of the sampled signal output by the sample-and-hold circuit and comparison with a preset voltage value, and converts the voltage judgment result output by the hysteresis comparator circuit into a level signal for output.

3. The liquid nitrogen tank level management system as described in claim 2, characterized in that, The control center module is configured as a microprocessor, and the microprocessor has a liquid level information sampling driver program, which executes the following steps: The liquid level detection module is woken up at preset intervals to obtain the level signal of each diode sensor output by the liquid level detection module and form a binary status word; Based on the preset mapping relationship between the binary status word and the liquid level height in the liquid nitrogen tank, the liquid level height in the liquid nitrogen tank is restored and recorded as the liquid level status; Based on the recorded liquid level status and the liquid level range, a linear regression method is used to dynamically generate the remaining time for the liquid level to drop to the lowest alarm liquid level threshold, and the frequency of the detection module being woken up is adjusted according to the remaining time.

4. The liquid nitrogen tank level management system as described in claim 3, characterized in that, The liquid level status is configured as a liquid level percentage, and the liquid level range includes a first range of 90%-80%, a second range of 80%-60%, a third range of 60%-50%, and a fourth range of 50%-40%.

5. The liquid nitrogen tank level management system as described in claim 4, characterized in that, Based on the recorded liquid level status and the current liquid level range, a linear regression method is used to dynamically generate the remaining time for the liquid level to drop to the lowest alarm liquid level threshold, specifically including: When the liquid level drops from 80% in the second range and enters 60%: Based on the evaporation slopes in the first and second intervals of the historical liquid level status, the average value is taken to obtain the first liquid level evaporation slope k1. According to the linear regression formula T1=(L_60%-L_20%) / k1, the first estimated remaining time T1 required for the liquid level to drop from the current height L_current to the lowest alarm liquid level threshold L_20% is calculated. When the liquid level drops from 60% in the third zone and enters 50%: Based on the average of the evaporation slope in the third interval of the historical liquid level status and the evaporation slope k1 of the first liquid level, the evaporation slope k2 of the second liquid level is obtained. According to the linear regression formula T1=(L_50%-L_20%) / k2, the second estimated remaining time T2 required for the liquid level to drop from the current height L_50% to the minimum alarm liquid level threshold L_20% is calculated. When the liquid level drops from 50% in the fourth zone and enters 40%: Based on the average of the evaporation slope in the fourth interval and the evaporation slope k2 of the first liquid level in the historical liquid level status, the evaporation slope k3 of the third liquid level is obtained. According to the linear regression formula T1=(L_40%-L_20%) / k3, the second estimated remaining time T3 required for the liquid level to drop from the current height L_40% to the minimum alarm liquid level threshold L_20% is calculated.

6. The liquid nitrogen tank level management system as described in claim 5, characterized in that, The power supply of the liquid level detection module is controlled by a MOSFET. The gate of the MOSFET is connected to the GPIO of the microprocessor through a third resistor, the source is connected to the power supply, and the drain is connected to the positive terminal of the diode sensor. The MOSFET is configured to supply power to the liquid level detection module during the sampling period when the microprocessor wakes up the liquid level detection module to perform liquid level acquisition, and to cut off the power supply to the liquid level detection module during the non-sampling period when the microprocessor does not wake up the liquid level detection module to perform liquid level acquisition.

7. The liquid nitrogen tank level management system as described in claim 2, characterized in that, It also includes a buzzer alarm module located locally on-site and connected to the control center module; wherein, the output terminal of the control center module is connected to the base of an NPN transistor, the collector of the NPN transistor is connected to a bypass power supply, and the emitter of the NPN transistor is connected to the buzzer alarm module.

8. The liquid nitrogen tank level management system as described in claim 1, characterized in that, The computer administrator terminal has a data monitoring mode and a connection initiation mode; The computer administrator terminal is normally in data monitoring mode. When it detects regular data, it initiates a connection with the control center module based on the time when the microprocessor wakes up the liquid level detection module. It receives Bluetooth broadcast packets sent by the control center module in batches, parses the liquid nitrogen tank data, and establishes a liquid nitrogen tank database. When the computer administrator detects an alarm signal, it switches to connection initiation mode, triggers the optimal allocation algorithm to match the target staff member of the current alarm event, generates a management task based on the liquid nitrogen tank data, initiates a connection between the computer administrator and the target staff member's mobile phone, and sends the management task to the target staff member's mobile phone.

9. The liquid nitrogen tank level management system as described in claim 8, characterized in that, Trigger the optimal allocation algorithm to match the target staff member for the current alarm event, specifically including: Establish a three-dimensional evaluation model based on spatial, temporal, and resource dimensions to generate priority scoring expressions for management tasks when assigned to different staff members; The priority scoring expression is specifically as follows: In the formula, α represents the actual reachable distance from the tank location of the previous management task to the tank of the current management task, β represents the alarm level determined based on the alarm signal, γ represents the importance level of the current liquid nitrogen tank supply demand item, and A, B, and C are preset dynamic weights based on the urgency of the management task. Obtain the management task list for each staff member, and extract the task execution time period and task execution tank location for each management task to be executed recorded in the management task list; The different execution order positions of the current management task assigned to different staff members' management task lists are used as decision variables. The task execution duration is determined based on the task execution attributes of the current management task. Based on the task execution duration of the current management task and the task execution duration of each management task to be executed in the management task list, the task execution time period of each management task to be executed after the management task is assigned to the management task list is updated. Based on the updated management task list, α and β in the priority scoring expression of each management task to be executed are updated to obtain the updated priority score. The update of α is achieved by calculating the actual reachable distance from the tank position of the previous management task to the tank of the current management task when the current management task is assigned to the corresponding execution order position in the management task list of the corresponding staff member. Among them, the update of β is to estimate the liquid level height in the liquid nitrogen tank during the task execution period by using the latest calculated slope value κ, and convert the liquid level height in the liquid nitrogen tank into an alarm level according to preset rules; The first constraint is that after a management task is assigned to the corresponding execution order position in the management task list of the corresponding staff member, the execution waiting time between the completion time of the task execution period of each pending management task in the updated management task list of each staff member does not exceed the preset waiting time. The second constraint is that the priority score of each pending management task in the updated management task list of each staff member is not higher than the preset priority score value. The optimization objective is to minimize the sum of the priority scores of all pending management tasks in the updated management task list of each staff member. An optimization algorithm is used to solve for the optimal execution order position in the management task list of the corresponding staff member to which the management task is assigned. The liquid nitrogen tank level management system as described in claim 1 is characterized in that, Upon receiving management tasks from the computer administrator, and after performing identification and authentication, the unlocking command for the alarm event is sent to the control center module via a key, specifically including: After receiving the management task sent by the computer administrator, the mobile phone user terminal uses multispectral imaging to extract facial features and compares the extracted facial features with a pre-stored feature library to perform micro-expression recognition and blink detection for liveness judgment. Upon successful comparison, a one-time key is generated, and the unlocking command for the alarm event is sent to the control center module through the generated one-time key; When the comparison fails, a lock command is sent to the control center module to initiate a three-level lock action, including local locking, administrator alarm, and system log recording.

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