Ultra-low temperature freezer temperature control system and method

Abstract

The present invention discloses a temperature control system and method for an ultra-low temperature freezer, which relates to the technical field of temperature control. The temperature data of the ultra-low temperature freezer is collected by a temperature acquisition module, and then a temperature analysis control module is used to analyze whether the temperature of the ultra-low temperature freezer is within a temperature control range. If so, the device data acquisition module collects device-related data, and then the device data processing module calculates and processes the device state comprehensive evaluation coefficient, and then uses the device data analysis module to analyze and calculate the device state comprehensive evaluation coefficient to evaluate the set fault level, and then displays the operating status of the device and the fault level of the faulty device through a control center, thereby realizing the function of accurately controlling and adjusting the temperature of the ultra-low temperature freezer, and then performing fault detection, analysis, and processing on the equipment in the ultra-low temperature freezer after the temperature is adjusted.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature control, and in particular to a temperature control system and method for an ultra-low temperature freezer. Background Art

[0002] With the continuous advancement of science and technology, people's requirements for cryogenic storage equipment are becoming increasingly higher. Traditional temperature control technology can no longer meet the requirements for precision and stability of ultra-low temperature freezer temperature control in modern industry, medicine, scientific research and other fields. Therefore, the development of new ultra-low temperature freezer temperature controllers is an inevitable result of technological progress.

[0003] With the rapid development of life sciences, biotechnology, and other fields, ultra-low temperature freezers are increasingly used in sample storage and vaccine preservation. The market's requirements for ultra-low temperature freezers' temperature control accuracy, stability, and energy efficiency are becoming increasingly stringent, which has also driven the research and development of ultra-low temperature freezer temperature controllers.

[0004] With the continuous improvement of global environmental awareness, energy conservation and emission reduction have become the focus of attention in various industries. As ultra-low temperature freezers are high-energy-consuming equipment, the development of their temperature controllers must also fully consider energy efficiency issues to achieve the goal of energy conservation and emission reduction.

[0005] Ultra-low temperature freezers are usually used to store important samples or items, and their temperature control affects the safety of equipment operation. Summary of the Invention

[0006] In order to address the deficiencies mentioned in the above background technology, the purpose of the present invention is to provide an ultra-low temperature freezer temperature control system and method, which can accurately control and adjust the temperature of the ultra-low temperature freezer, and then perform fault detection, analysis and processing on the equipment in the ultra-low temperature freezer after the temperature is adjusted.

[0007] In a first aspect, the purpose of the present invention can be achieved by the following technical solution: a temperature control system for an ultra-low temperature freezer, comprising:

[0008] The temperature acquisition module is used to collect the temperature data of the ultra-low temperature freezer and send the collected ultra-low temperature freezer temperature data to the temperature analysis and control module;

[0009] The temperature analysis and control module is used to mark the temperature data of the ultra-low temperature freezer, set the temperature control range, and determine whether the temperature of the ultra-low temperature freezer is within the temperature control range. If so, it sends a device data acquisition signal to the device data acquisition module. If not, it sets the adjustment accuracy value and the number of adjustments. After the ultra-low temperature freezer temperature is within the temperature control range, it stops and sends a device data acquisition signal to the device data acquisition module.

[0010] The equipment data acquisition module collects equipment-related data and sends the equipment-related data to the equipment data processing module, wherein the equipment-related data includes: equipment basic data, equipment operation data, equipment production data and equipment maintenance data;

[0011] The equipment data processing module is used to pre-process the equipment-related data to obtain the pre-processed equipment-related data, mark the pre-processed equipment-related data, use the marked equipment-related data to perform a comprehensive evaluation calculation of the equipment status to obtain a comprehensive evaluation coefficient of the equipment status, set an equipment status evaluation threshold, compare the comprehensive evaluation coefficient of the equipment status with the equipment status evaluation threshold, and determine whether there is a problem with the equipment status based on the comparison result. If there is no problem, a no-problem signal is sent to the control center. If there is a problem, the comprehensive evaluation coefficient of the equipment status is sent to the equipment data analysis module for analysis;

[0012] The equipment data analysis module is used to obtain the equipment fault judgment model pre-established in the control center, input the equipment status comprehensive evaluation coefficient into the pre-established equipment fault judgment model, output the equipment fault judgment coefficient, use the obtained equipment fault judgment coefficient to perform judgment score calculation to obtain the equipment fault judgment score, set the equipment fault judgment proportional coefficient, use the equipment fault judgment score and the equipment fault judgment proportional coefficient to perform a ratio calculation, determine whether the equipment is faulty and the fault level of the equipment based on the ratio result, and send different fault signals to the control center;

[0013] The control center is used to store pre-established equipment fault judgment models, and after receiving a no-problem signal sent by the equipment data processing module, it reminds through the display screen that the equipment is running without problems; after receiving a no-fault signal sent by the equipment data analysis module, it reminds through the display screen that there is a problem with the equipment operation but it is not a fault; after receiving various levels of fault signals sent by the equipment data analysis module, it displays the equipment fault level on the display screen according to the signal level.

[0014] In conjunction with the first aspect, in certain implementations of the first aspect, the system further includes: the temperature analysis control module marking the ultra-low temperature freezer temperature data, marking it as Tj, where j is the number of times the temperature acquisition module collects data, j=1, 2, 3, ..., m, and m is the total number of times the temperature acquisition module collects data;

[0015] Set the temperature control range [Tmin, Tmax];

[0016] If Tmin≤Tj≤Tmax, there is no need to control and adjust the temperature of the ultra-low temperature freezer at this time; the temperature analysis control module sends the device data acquisition signal to the device data acquisition module;

[0017] If Tj < Tmin, set the adjustment precision value Δt, the temperature analysis and control module adjusts the temperature according to the adjustment precision value Δt, and the adjustment times are a. When Tmin ≤ Tj + aΔt ≤ Tmax, the device data acquisition signal is sent to the device data acquisition module;

[0018] If Tj>Tmax, the temperature analysis and control module adjusts the temperature according to the adjustment accuracy value Δt, and the number of adjustments is b, until Tmin≤Tj+bΔt≤Tmax, and sends the device data acquisition signal to the device data acquisition module.

[0019] In combination with the first aspect, in certain implementations of the first aspect, the system further includes: in the equipment data processing module, the equipment basic data is marked as Bi, the equipment operation data is marked as Yi, the equipment production data is marked as Si, and the equipment maintenance data is marked as Wi, where i is the collection number of the equipment data collection module, and i=1, 2, 3, ..., n, and n is the total number of collection times of the equipment data collection module.

[0020] In conjunction with the first aspect, in certain implementations of the first aspect, the system further includes: a calculation formula for comprehensive evaluation of the device status of the device data processing module is as follows:

[0021]

[0022] Where Zgi is the comprehensive evaluation coefficient of equipment status, S0 is the preset production standard coefficient, Y0 is the preset operation standard coefficient, W0 is the preset maintenance standard coefficient, α is the equipment production impact coefficient, β is the equipment operation impact coefficient, ε is the equipment maintenance impact coefficient, p1, p2 and p3 are all preset related evaluation coefficients, and ln() is the logarithmic function.

[0023] In conjunction with the first aspect, in certain implementations of the first aspect, the system further includes: an analysis process of the device data processing module:

[0024] Set the equipment status assessment threshold Zg0;

[0025] If Zgi≤Zg0, a no-problem signal is sent to the control center;

[0026] If Zgi>Zg0, the comprehensive evaluation coefficient of the equipment status is sent to the equipment data analysis module for analysis.

[0027] In conjunction with the first aspect, in certain implementations of the first aspect, the system further includes: the equipment data analysis module inputting the equipment status comprehensive evaluation coefficient Zgi into a pre-established equipment fault determination model, outputting an equipment fault determination coefficient, and marking the equipment fault determination coefficient as Rgi;

[0028] The process of calculating the judgment score using the obtained equipment failure judgment coefficient Rgi is as follows:

[0029]

[0030] Where Rpi is the equipment fault judgment score, Umax is the preset maximum score coefficient, and Umin is the preset minimum score coefficient.

[0031] In conjunction with the first aspect, in certain implementations of the first aspect, the system further includes: an analysis process of the device data analysis module:

[0032] Set the equipment fault judgment proportional coefficient Rp0;

[0033] like Then send a no-fault signal to the control center;

[0034] like If it is determined to be a low-level fault, the equipment data analysis module sends a low-level fault signal to the control center;

[0035] like If it is determined to be a medium fault, the equipment data analysis module sends a medium fault signal to the control center;

[0036] like It is determined to be a high-level fault, and the equipment data analysis module sends a high-level fault signal to the control center.

[0037] In a second aspect, in order to achieve the above-mentioned object, the present invention discloses a method for controlling the temperature of an ultra-low temperature freezer, the method comprising the following steps:

[0038] Acquire the ultra-low temperature freezer temperature data, process and mark the ultra-low temperature freezer temperature data, set the temperature control range, determine whether the ultra-low temperature freezer temperature is within the temperature control range, if not, set the adjustment accuracy value and the number of adjustments, and stop adjusting the ultra-low temperature freezer temperature after it is within the temperature control range;

[0039] When the temperature of the ultra-low temperature freezer is within the temperature control range, equipment-related data is obtained, pre-processed and marked, and a comprehensive equipment status evaluation calculation is performed on the marked equipment-related data to obtain a comprehensive equipment status evaluation coefficient, wherein the equipment-related data includes: basic equipment data, equipment operation data, equipment production data, and equipment maintenance data;

[0040] Set the equipment status assessment threshold, use the equipment status comprehensive assessment coefficient to compare with the equipment status assessment threshold, and determine whether there is a problem with the equipment status based on the comparison result. If there is a problem, continue to use the equipment status comprehensive assessment coefficient for analysis;

[0041] Input the comprehensive evaluation coefficient of the equipment status into the pre-established equipment fault judgment model, output the equipment fault judgment coefficient, and use the equipment fault judgment coefficient to calculate the judgment score to obtain the equipment fault judgment score;

[0042] Set the equipment fault judgment proportional coefficient, use the equipment fault judgment score and the equipment fault judgment proportional coefficient to calculate the ratio, and determine whether the equipment is faulty and the equipment fault level based on the ratio result. The equipment fault level includes low, medium and high levels, and is finally displayed according to the different status of the equipment, so that the equipment can be repaired.

[0043] Beneficial effects of the present invention:

[0044] The present invention collects temperature data of an ultra-low temperature freezer through a temperature acquisition module, and then uses a temperature analysis and control module to analyze whether the temperature of the ultra-low temperature freezer is within a temperature control range. If so, the device data acquisition module collects device-related data, and then the device data processing module obtains a comprehensive evaluation coefficient of the device status through processing and calculation. The device data analysis module then analyzes and calculates the comprehensive evaluation coefficient of the device status to evaluate the set fault level, and then displays the operating status of the device and the fault level of the faulty device through a control center, thereby realizing the function of accurately controlling and adjusting the temperature of the ultra-low temperature freezer, and then performing fault detection, analysis, and processing on the equipment in the ultra-low temperature freezer after the temperature is adjusted. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0046] Figure 1 It is a schematic flow chart of the method of the present invention;

[0047] Figure 2 This is a schematic diagram of the hardware system flow of an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of the flyback conversion circuit principle according to an embodiment of the present invention;

[0049] Figure 4 This is a schematic diagram of the PT100 signal conditioning principle according to an embodiment of the present invention;

[0050] Figure 5 This is a schematic diagram of the NTC acquisition principle of an embodiment of the present invention;

[0051] Figure 6 This is a schematic diagram of the charging circuit principle of an embodiment of the present invention;

[0052] Figure 7 This is a schematic diagram of an over-discharge protection circuit according to an embodiment of the present invention.

[0053] Figure 8 This is a flowchart of the software startup program according to an embodiment of the present invention.

[0054] Figure 9 This is a schematic diagram of the software application process of an embodiment of the present invention

[0055] Figure 10 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0057] Example 1:

[0058] The following is an introduction to the relevant terms involved in the embodiments of this application:

[0059] Ultra-low temperature freezer (ultra-low temperature freezer) generally refers to ultra-low temperature frozen storage box

[0060] Ultra-low temperature refrigerated storage boxes, also known as ultra-low temperature freezers, ultra-low temperature preservation boxes, ultra-low temperature laboratory chambers, ultra-low temperature freezers, medical low-temperature refrigerators, and medical low-temperature preservation boxes, utilize an internationally advanced single-unit automatic cascade refrigeration system. While conventional refrigerators using compressors of the same power can only reach temperatures of -40°C, these refrigerators utilize automatic cascade refrigeration to reach temperatures below -60°C. All products utilize a fluorine-free, environmentally friendly refrigerant formula and are manufactured using internationally renowned brand components. This unique refrigeration method is adaptable to harsh environments.

[0061] Convolutional Neural Networks (CNNs) are a type of feedforward neural network with a deep structure that incorporates convolutional computations. They are one of the representative algorithms for deep learning. CNNs possess representational learning capabilities and can perform shift-invariant classification of input information according to their hierarchical structure, hence their nickname, "Shift-Invariant Artificial Neural Networks (SIANN)." Research on CNNs began in the 1980s and 1990s, with time delay networks and LeNet-5 being the earliest examples. Since the 21st century, with the advent of deep learning theory and improvements in numerical computing equipment, CNNs have rapidly developed and have been applied to fields such as computer vision and natural language processing. Convolutional neural networks are modeled after biological visual perception mechanisms and can perform both supervised and unsupervised learning. The shared convolution kernel parameters within the hidden layer and the sparsity of inter-layer connections enable convolutional neural networks to learn grid-like topology features, such as pixels and audio, with minimal computational effort, with stable results and without requiring additional feature engineering.

[0062] like Figure 1 As shown, a temperature control system for an ultra-low temperature freezer includes:

[0063] Temperature acquisition module, temperature analysis and control module, equipment data acquisition module, equipment data processing module, equipment data analysis module and control center;

[0064] The temperature acquisition module is used to collect the temperature data of the ultra-low temperature freezer, and send the collected ultra-low temperature freezer temperature data to the temperature analysis and control module for temperature analysis and control;

[0065] The temperature analysis and control module is used to analyze and control the temperature after receiving the ultra-low temperature freezer temperature data sent by the temperature acquisition module. Specifically, the analysis and control process of the temperature analysis and control module is as follows:

[0066] The ultra-low temperature freezer temperature data is marked as Tj, where j is the number of times the temperature acquisition module collects data, j = 1, 2, 3, ..., m, and m is the total number of times the temperature acquisition module collects data;

[0067] Set the temperature control range [Tmin, Tmax];

[0068] If Tmin≤Tj≤Tmax, it indicates that the temperature of the ultra-low temperature freezer is within the temperature control range and there is no need to control and adjust the temperature of the ultra-low temperature freezer; the temperature analysis control module sends a device data acquisition signal to the device data acquisition module;

[0069] If Tj < Tmin, it indicates that the temperature of the ultra-low temperature freezer is too low. The adjustment accuracy value Δt is set. The temperature analysis and control module adjusts the temperature according to the adjustment accuracy value Δt, and the adjustment number is a. When Tmin ≤ Tj + aΔt ≤ Tmax, the temperature analysis and control module sends a device data acquisition signal to the device data acquisition module;

[0070] If Tj>Tmax, it indicates that the temperature of the ultra-low temperature freezer is too high. The temperature analysis and control module adjusts the temperature according to the adjustment accuracy value Δt, and the adjustment number is b. Until Tmin≤Tj+bΔt≤Tmax, the temperature analysis and control module sends a device data acquisition signal to the device data acquisition module;

[0071] After receiving the device data acquisition signal sent by the temperature analysis control module, the device data acquisition module collects the device data. The acquisition process is as follows:

[0072] The equipment data acquisition module acquires equipment-related data, wherein the equipment-related data includes: equipment basic data, equipment operation data, equipment production data and equipment maintenance data;

[0073] The basic data of the equipment includes: equipment model, manufacturer, date of manufacture, service life, maintenance records and other basic information, providing necessary reference for equipment management;

[0074] Equipment production data includes information such as equipment production efficiency, output, and product quality, providing a basis for production management and quality control;

[0075] Equipment maintenance data includes equipment maintenance records, repair records, parts replacement records and other information, providing reference and basis for equipment maintenance;

[0076] The equipment operation data is obtained by comprehensive operation calculation of equipment temperature, equipment pressure, equipment load and equipment power;

[0077] Specifically, in this embodiment, the calculation process is as follows:

[0078] Take this method as an example to obtain the equipment operation data once;

[0079] The temperature of the primary equipment is marked as A1, the pressure of the primary equipment is marked as A2, the load of the primary equipment is marked as A3, and the power of the primary equipment is marked as A4;

[0080] Use the marked data to perform comprehensive operation calculations on the equipment and obtain the equipment operation data. The calculation formula is as follows:

[0081]

[0082] Where A is the primary equipment operating data, q1 is the temperature influence coefficient, q2 is the pressure influence coefficient, q3 is the load influence coefficient, q4 is the power influence coefficient, and A0 is the preset operation correlation coefficient;

[0083] Send the collected device-related data to the device data processing module for processing;

[0084] After receiving the device-related data sent by the device data acquisition module, the device data processing module performs data processing. Specifically, the processing process of the device data processing module includes the following steps:

[0085] Preprocess the equipment-related data to obtain preprocessed equipment-related data, and mark the preprocessed equipment-related data, wherein the equipment basic data is marked as Bi, the equipment operation data is marked as Yi, the equipment production data is marked as Si, and the equipment maintenance data is marked as Wi, where i is the collection number of the equipment data collection module, and i=1, 2, 3, ..., n, and n is the total number of collection times of the equipment data collection module;

[0086] The pre-processing of the equipment-related data includes data cleaning, data conversion and data integration to improve the data quality of the equipment-related data.

[0087] The equipment status comprehensive evaluation calculation is performed using the marked equipment-related data to obtain the equipment status comprehensive evaluation coefficient. Specifically, the calculation formula for the equipment status comprehensive evaluation calculation is as follows:

[0088]

[0089] Where Zgi is the comprehensive evaluation coefficient of equipment status, S0 is the preset production standard coefficient, Y0 is the preset operation standard coefficient, W0 is the preset maintenance standard coefficient, α is the equipment production impact coefficient, β is the equipment operation impact coefficient, ε is the equipment maintenance impact coefficient, p1, p2 and p3 are all preset related evaluation coefficients, and ln() is the logarithmic function;

[0090] Set the equipment status assessment threshold Zg0;

[0091] The comprehensive evaluation coefficient Zgi of the equipment status is compared with the equipment status evaluation threshold Zg0, and the comparison result is used to determine whether there is a problem with the equipment status. The specific process is as follows:

[0092] If Zgi≤Zg0, it means that there is no problem with the device status, and the device data processing module sends a no-problem signal to the control center;

[0093] If Zgi>Zg0, it means that there is a problem with the equipment status. The equipment data processing module sends the equipment status comprehensive evaluation coefficient to the equipment data analysis module for analysis;

[0094] After receiving the comprehensive evaluation coefficient of the equipment status sent by the equipment data processing module, the equipment data analysis module performs equipment data analysis. Specifically, the analysis process of the equipment data analysis module includes the following steps:

[0095] Obtain the equipment fault judgment model pre-established in the control center;

[0096] Input the equipment status comprehensive evaluation coefficient Zgi into the pre-established equipment fault judgment model, and output the equipment fault judgment coefficient, which is marked as Rgi;

[0097] The obtained equipment failure determination coefficient Rgi is used to calculate the determination score to obtain the equipment failure determination score. Specifically, the determination score is calculated as follows:

[0098]

[0099] Where Rpi is the equipment fault judgment score, Umax is the preset maximum score coefficient, and Umin is the preset minimum score coefficient;

[0100] Set the equipment fault judgment proportional coefficient Rp0, use the equipment fault judgment score Rpi and the equipment fault judgment proportional coefficient Rp0 to calculate the ratio, determine whether the equipment is faulty and the fault level of the equipment based on the ratio result, and send different fault signals to the control center; the specific process is as follows:

[0101] like If the device has a problem but is not faulty, the device data analysis module sends a non-fault signal to the control center;

[0102] like If the device has failed and it is determined to be a low-level failure, the device data analysis module sends a low-level failure signal to the control center;

[0103] like If the device has failed and is judged to be a medium-level failure, the device data analysis module sends a medium-level failure signal to the control center;

[0104] like If the device has failed and is judged to be a high-level failure, the device data analysis module sends a high-level failure signal to the control center;

[0105] After receiving the no-problem signal sent by the equipment data processing module, the control center reminds the user through the display screen that the equipment is running without any problems. After receiving the no-fault signal sent by the equipment data analysis module, the control center reminds the user through the display screen that the equipment has problems but is not faulty. After receiving various levels of fault signals sent by the equipment data analysis module, the control center displays the equipment fault level through the display screen according to the signal level.

[0106] The training process of the pre-established equipment fault determination model stored in the control center is based on artificial intelligence model training; wherein the process of training the equipment fault determination model based on the artificial intelligence model is as follows:

[0107] Integrate and obtain equipment usage status related data through the server, where the equipment usage status related data includes equipment production related data, equipment operation related data, and equipment maintenance related data;

[0108] Divide the device usage status related data into primary usage status related data and secondary usage status related data;

[0109] The artificial intelligence model is trained by using status-related data once to obtain and store a device fault judgment model; wherein the artificial intelligence model includes a deep convolutional neural network model and an RBF neural network model.

[0110] The primary equipment fault judgment model is trained using secondary use status related data, and the secondary equipment fault judgment model is obtained and stored; the primary use status related data and the secondary use status related data are input into the secondary equipment fault judgment model for training, and the equipment fault judgment model is output.

[0111] Specifically, the present invention will be further described below through examples:

[0112] The temperature control range set by this system is -86℃~0℃, with an accuracy of 1℃; the temperature adjustment accuracy is ±0.1℃;

[0113] System power supply: AC power is input and converted to 15V, 5V, and 3.3V outputs. Operating voltage range: 164V to 256V, frequency: 50Hz. TOP244YN is used as the ACDC control chip.

[0114] System power design

[0115] The device's operating voltage range is 186V to 256V, requiring the system power supply to properly output 15V, 5V, and 3.3V within this range. Considering system power requirements and manufacturing costs, a flyback converter circuit is used to convert the external AC input voltage to 15V, with an output current of up to 2A. This voltage is then converted to 5V via a DC-DC circuit, and finally input to 3.3V using an LDO chip.

[0116] The flyback converter circuit uses TOP244YN as the controller. The schematic diagram is as follows Figure 3

[0117] Key design points for a flyback converter circuit include overvoltage and undervoltage protection point design, voltage feedback loop design, and protection circuit design. Pin 2 (L) of the TOP244YN enables line voltage overvoltage and undervoltage detection.

[0118] U ov =R4×I ov =2MΩ×225μA=445V

[0119] U uv =R4×I uv =2MΩ×50μA=100V

[0120] The overvoltage protection can be set to 445V and the undervoltage protection to 100V, which meet the equipment operation requirements.

[0121] The voltage feedback loop, consisting of the EL817, TL431C, and its peripheral components, converts the output voltage signal and feeds it back to Pin 1 (C) of the TOP244YN. The TL431C's R pin collects the output voltage, divides it by R21 and R22, and compares it with the reference voltage to control the on and off state of the C pin, thereby driving the optocoupler EL817 and feeding the result back to the TOP244YN. The voltage is calculated as follows:

[0122] The TL431C reference voltage V is known. ref =2.5V

[0123]

[0124] Meet design requirements.

[0125] In the schematic diagram, fuse F1, varistor ZER1, and thermistor RP1 form the input protection circuit. In the event of a short circuit in the downstream stage, fuse F1 instantly opens to prevent further damage. The varistor conducts during input surges and induced lightning strikes, releasing high voltage to protect the downstream stage from damage. Furthermore, D2 (RS1N), D1 (P6SMB200A), C2 (4.7µF 1kV), and R24 (120Ω) form an RC circuit to absorb spikes during the transformer's primary switching process, preventing the switch from failing due to breakdown. C7 (22pF) and R9 (68Ω) form an RC circuit to absorb switching spikes in the transformer's secondary and protect the Schottky diode.

[0126] Microcontroller: It is the control core of the entire system. The APM32F407RGT6 single-chip microcomputer is selected to complete temperature acquisition, input voltage acquisition, communication interface data interaction, compressor controller, alarm events, and data access.

[0127] Temperature acquisition unit: The device uses PT100 and NTC as temperature conversion elements. The temperature acquisition unit contains a signal amplification circuit, which amplifies the signal to a suitable range and then inputs it into the ADC port of the microcontroller.

[0128] Temperature acquisition is divided into two parts according to the sensor type: PT100 acquisition circuit and NTC acquisition circuit.

[0129] PT100 uses a three-wire system, and the signal conditioning schematic is as follows Figure 4

[0130] PT100 passes through the resistor network composed of RA36, RA37, and RA38 and then enters the operational amplifier for differential amplification.

[0131]

[0132]

[0133]

[0134] get

[0135]

[0136] Calculate PT100 resistance

[0137]

[0138] The temperature can be calculated using the approximate formula

[0139]

[0140] NTC acquisition principle diagram is as follows Figure 5 .

[0141]

[0142] The NTC resistance value can be obtained

[0143]

[0144] Finally, the NTC temperature can be obtained

[0145]

[0146] Battery Management Unit (BMU): The device's internal battery is used to maintain the device controller during power outages and allows viewing or exporting historical device data. The BMU includes battery charge management and undervoltage protection circuits.

[0147] The battery management circuit is used to control the charging and discharging of the built-in lead-acid battery. The circuit consists of two parts: charging control and over-discharge protection.

[0148] The charging control is implemented using the CN3768 chip. The CN3768 is a 12V lead-acid battery dedicated charging management chip in PWM buck mode, with trickle, constant current, overcharge and float charge modes. The input voltage is wide and the charging current can be set. The schematic diagram is as follows Figure 6

[0149] The charging current is determined by the resistor RC7. The current detection voltage V can be obtained from the manual. csp is 120mV, so the charging current

[0150]

[0151] The schematic diagram of the over-discharge protection circuit is as follows: Figure 7

[0152] The over-discharge protection circuit consists of a TL431C and a MOS AO4459. The TL431C detects current and voltage. When the voltage is less than the set value, the MOS transistor is turned off, stopping battery discharge. Resistor RC4 is added to the detection network to form a hysteresis interval.

[0153] Protection voltage

[0154]

[0155] V BAT =10.12V

[0156] Release protection voltage

[0157]

[0158] V BAT =11V

[0159] Data storage unit: used to save device setting parameters, device operation records, event records, etc. Data storage is divided into two parts, namely the external Flash chip and the internal Flash of the microcontroller.

[0160] Data communication unit: The communication unit mainly includes RS232, RS485, UART TTL, and USB. It can be connected to communication modules such as 4G modules and WIFI modules. The USB can be connected to a USB flash drive to copy and store data and software upgrades.

[0161] Human-computer interaction unit: A 7-inch touch screen is used to display the device status and enter setting parameters.

[0162] Software design includes the design of the startup program and the application program. The startup program is the first program to be run after the microcontroller is powered on. After the startup program is completed, the PC is updated to point to the application start address and the application begins running.

[0163] The main functions of the startup program include USB device enumeration, U disk file system loading, upgrade file identification, verification loading, program upgrade, and main program loading. The program flow chart is as follows Figure 8

[0164] The application includes USB interface processing, Modbus protocol processing, temperature and main voltage acquisition, alarm event detection, periodic data storage, compressor and heat exchange fan control. The specific flow chart is as follows Figure 9

[0165] An efficient flyback switching power supply is used as the main power source of the system, providing effective guarantee for the stable operation of the system.

[0166] The startup program and application program run independently, allowing the device to update the program automatically via USB, which is convenient for device maintenance and personalized customization.

[0167] Equipment operation data is saved regularly and can be copied to a USB flash drive via USB, which facilitates equipment operation status tracing and fault analysis. Especially in high-reliability applications, regular data verification can improve the detection of equipment failure hazards.

[0168] Example 2: The second aspect, as Figure 10 As shown, a method for controlling the temperature of an ultra-low temperature freezer comprises the following steps:

[0169] Acquire the ultra-low temperature freezer temperature data, process and mark the ultra-low temperature freezer temperature data, set the temperature control range, determine whether the ultra-low temperature freezer temperature is within the temperature control range, if not, set the adjustment accuracy value and the number of adjustments, and stop adjusting the ultra-low temperature freezer temperature after it is within the temperature control range;

[0170] When the temperature of the ultra-low temperature freezer is within the temperature control range, equipment-related data is obtained, pre-processed and marked, and a comprehensive equipment status evaluation calculation is performed on the marked equipment-related data to obtain a comprehensive equipment status evaluation coefficient, wherein the equipment-related data includes: basic equipment data, equipment operation data, equipment production data, and equipment maintenance data;

[0171] Set the equipment status assessment threshold, use the equipment status comprehensive assessment coefficient to compare with the equipment status assessment threshold, and determine whether there is a problem with the equipment status based on the comparison result. If there is a problem, continue to use the equipment status comprehensive assessment coefficient for analysis;

[0172] Input the comprehensive evaluation coefficient of the equipment status into the pre-established equipment fault judgment model, output the equipment fault judgment coefficient, and use the equipment fault judgment coefficient to calculate the judgment score to obtain the equipment fault judgment score;

[0173] Set the equipment fault judgment proportional coefficient, use the equipment fault judgment score and the equipment fault judgment proportional coefficient to calculate the ratio, and determine whether the equipment is faulty and the equipment fault level based on the ratio result. The equipment fault level includes low, medium and high levels, and is finally displayed according to the different status of the equipment, so that the equipment can be repaired.

[0174] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors and a memory for storing one or more computer programs; the program includes program instructions, and the processor is used to execute the program instructions stored in the memory. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is used to implement one or more instructions, specifically for loading and executing one or more instructions in a computer storage medium to implement the above method.

[0175] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium having a computer program stored thereon, which executes the above method when executed by a processor. The storage medium can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or component.

[0176] The above formulas are all calculated by removing dimensions and taking their numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technicians in this field according to actual conditions or obtained by simulating a large amount of data.

[0177] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of these 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 any one or more embodiments or examples.

[0178] The above shows and describes the basic principles, main features and advantages of the present disclosure. Those skilled in the art should understand that the present disclosure is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present disclosure. Various changes and improvements may be made to the present disclosure without departing from the spirit and scope of the present disclosure, and such changes and improvements shall fall within the scope of the present disclosure.

Claims

1. A temperature control system for an ultra-low temperature freezer, characterized in that: include: The temperature acquisition module is used to collect the temperature data of the ultra-low temperature freezer and send the collected ultra-low temperature freezer temperature data to the temperature analysis and control module; The temperature analysis and control module is used to mark the temperature data of the ultra-low temperature freezer, set the temperature control range, and determine whether the temperature of the ultra-low temperature freezer is within the temperature control range. If so, it sends a device data acquisition signal to the device data acquisition module. If not, it sets the adjustment accuracy value and the number of adjustments. After the ultra-low temperature freezer temperature is within the temperature control range, it stops and sends a device data acquisition signal to the device data acquisition module. The temperature analysis and control module marks the ultra-low temperature freezer temperature data as Tj, where j is the number of times the temperature acquisition module collects data, j=1, 2, 3, ..., m, and m is the total number of times the temperature acquisition module collects data; Set the temperature control range [Tmin, Tmax]; If Tmin≤Tj≤Tmax, there is no need to control and adjust the temperature of the ultra-low temperature freezer at this time; the temperature analysis control module sends the device data acquisition signal to the device data acquisition module; If Tj < Tmin, set the adjustment precision value Δt, the temperature analysis and control module adjusts the temperature according to the adjustment precision value Δt, and the adjustment times are a. When Tmin ≤ Tj + aΔt ≤ Tmax, the device data acquisition signal is sent to the device data acquisition module; If Tj>Tmax, the temperature analysis and control module adjusts the temperature according to the adjustment accuracy value Δt, and the number of adjustments is b, until Tmin≤Tj+bΔt≤Tmax, and sends the device data acquisition signal to the device data acquisition module; The equipment data acquisition module collects equipment-related data and sends the equipment-related data to the equipment data processing module, wherein the equipment-related data includes: equipment basic data, equipment operation data, equipment production data and equipment maintenance data; The equipment data processing module is used to preprocess the equipment-related data to obtain the preprocessed equipment-related data, mark the preprocessed equipment-related data, perform a comprehensive equipment status evaluation calculation using the marked equipment-related data, obtain a comprehensive equipment status evaluation coefficient, set an equipment status evaluation threshold, compare the comprehensive equipment status evaluation coefficient with the equipment status evaluation threshold, and determine whether there is a problem with the equipment status based on the comparison result. If there is no problem, a no-problem signal is sent to the control center. If there is a problem, the comprehensive equipment status evaluation coefficient is sent to the equipment data analysis module for analysis; In the equipment data processing module, the equipment basic data is marked as Bi, the equipment operation data is marked as Yi, the equipment production data is marked as Si, and the equipment maintenance data is marked as Wi, where i is the collection number of the equipment data collection module, and i=1, 2, 3, ..., n, and n is the total number of collection times of the equipment data collection module; The calculation formula for the comprehensive evaluation calculation of the equipment status of the equipment data processing module is as follows: Zgi=\frac {\sqrt {\alpha {(Si-S0)}^{2}+\beta {(Yi-Y0)}^{2}}} {1+\varepsilon {(Wi-W0)}^{2}}ln[Bi{({p}_{1}+{p}_{2}+{p}_{3})}^{2}] Where Zgi is the comprehensive evaluation coefficient of equipment status, S0 is the preset production standard coefficient, Y0 is the preset operation standard coefficient, W0 is the preset maintenance standard coefficient, α is the equipment production impact coefficient, β is the equipment operation impact coefficient, ε is the equipment maintenance impact coefficient, p1, p2 and p3 are all preset related evaluation coefficients, and ln() is the logarithmic function; The equipment data analysis module is used to obtain the equipment fault judgment model pre-established in the control center, input the equipment status comprehensive evaluation coefficient into the pre-established equipment fault judgment model, output the equipment fault judgment coefficient, use the obtained equipment fault judgment coefficient to perform judgment score calculation to obtain the equipment fault judgment score, set the equipment fault judgment proportional coefficient, use the equipment fault judgment score and the equipment fault judgment proportional coefficient to perform a ratio calculation, determine whether the equipment is faulty and the fault level of the equipment based on the ratio result, and send different fault signals to the control center; The control center is used to store pre-established equipment fault judgment models, and after receiving a no-problem signal sent by the equipment data processing module, it reminds through the display screen that the equipment is running without problems; after receiving a no-fault signal sent by the equipment data analysis module, it reminds through the display screen that there is a problem with the equipment operation but it is not a fault; after receiving various levels of fault signals sent by the equipment data analysis module, it displays the equipment fault level on the display screen according to the signal level.

2. The ultra-low temperature freezer temperature control system according to claim 1, characterized in that: Analysis process of the device data processing module: Set the equipment status assessment threshold Zg0; If Zgi≤Zg0, a no-problem signal is sent to the control center; If Zgi>Zg0, the comprehensive evaluation coefficient of the equipment status is sent to the equipment data analysis module for analysis.

3. The ultra-low temperature freezer temperature control system according to claim 1, characterized in that: The equipment data analysis module inputs the equipment status comprehensive evaluation coefficient Zgi into a pre-established equipment fault judgment model, outputs the equipment fault judgment coefficient, and marks the equipment fault judgment coefficient as Rgi; The process of calculating the judgment score using the obtained equipment failure judgment coefficient Rgi is as follows: Where Rpi is the equipment fault judgment score, Umax is the preset maximum score coefficient, and Umin is the preset minimum score coefficient.

4. The ultra-low temperature freezer temperature control system according to claim 3, characterized in that: The analysis process of the device data analysis module: Set the equipment fault judgment proportional coefficient Rp0; If 0< ≤1, a no-fault signal is sent to the control center; If 1< If the value is less than or equal to 2, it is judged as a low-level fault, and the equipment data analysis module sends a low-level fault signal to the control center; If 2< If the value is less than or equal to 3, it is judged as a medium fault, and the equipment data analysis module sends a medium fault signal to the control center; like >3, it is determined to be a high-level fault, and the equipment data analysis module sends a high-level fault signal to the control center.

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