Profound hypothermia intelligent micro-positive pressure working cabin control system

Abstract

The invention belongs to the technical field of cabin pressure control, and provides a deep hypothermia intelligent micro-positive pressure working cabin control system which comprises a working cabin body, a detection integration box, a pressure release valve, a nitrogen recovery device and a control module. The detection integration box is used for collecting pressure data and dew point temperature in the working cabin body, and sending the pressure data and the dew point temperature to the control module after analog-to-digital conversion; the control module is used for comparing the pressure data with a preset safe pressure range, if it is detected that the pressure data exceed the safe pressure range, the pressure release valve is controlled to be opened, the nitrogen recovery device is used for temporarily storing redundant nitrogen in the working cabin body, and the control module controls the pressure release valve to be closed when it is detected that the pressure data is reduced to the safe pressure range; the control module is further used for triggering the liquid nitrogen gasification dehumidification action after it is detected that the dew point temperature is higher than the temperature set value. The system gives consideration to control precision and control cost, and can better meet the application requirements of cabin scenes of different scales.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cabin pressure control, and particularly relates to a deep low-temperature intelligent micro-positive pressure working cabin control system. BACKGROUND

[0002] The micro-positive pressure working cabin can effectively prevent the invasion of external dust, moisture and flammable gas by maintaining the cabin pressure slightly higher than the external environment, and is widely used in explosion-proof laboratories, equipment protection cabins, drug isolators and other scenes.

[0003] In the related art, the micro-positive pressure working cabin relies on a single pressure relief valve for pressure regulation in the pressure control link. When the cabin pressure suddenly rises due to gas input fluctuations or changes in sealing performance, the pressure relief valve needs to bear the entire pressure relief load alone, which is prone to cause pressure overshoot due to delayed response. At the same time, in the existing system, the excess inert gas (such as nitrogen) in the cabin is usually directly discharged to the external environment during pressure relief. In the long-term running scene, this non-recycling pressure relief mode leads to high consumption of inert gas, which not only increases the operating cost, but also does not meet the energy-saving and environmentally-friendly technical development trend.

[0004] Therefore, the traditional micro-positive pressure working cabin has the technical problems of low control precision and high operating cost in the pressure control link. SUMMARY

[0005] The present application provides a deep low-temperature intelligent micro-positive pressure working cabin control system to solve the defects of low control precision and high operating cost of the traditional micro-positive pressure working cabin in the pressure control link.

[0006] In one aspect, the present application provides a deep low-temperature intelligent micro-positive pressure working cabin control system, comprising: a working cabin body, a detection integrated box, a pressure relief valve, a nitrogen recovery device and a control module. The detection integrated box, the pressure relief valve and the nitrogen recovery device are all installed on the working cabin body. The detection integrated box is used to collect pressure data and dew point temperature in the working cabin body, and send the pressure data and dew point temperature to the control module after analog-to-digital conversion. The control module is used to compare the pressure data with a preset safe pressure range after receiving the pressure data and dew point temperature, and control the pressure relief valve to open if it is detected that the pressure data exceeds the safe pressure range. The nitrogen recovery device is used to temporarily store excess nitrogen in the working cabin body, and the control module controls the pressure relief valve to close when it is detected that the pressure data drops to the safe pressure range. The control module is also used to trigger a liquid nitrogen gasification dehumidification action when it is detected that the dew point temperature is higher than a pre-set temperature setting value.

[0007] According to the cryogenic intelligent micro-positive pressure working chamber control system provided by the present invention, the working chamber body includes: a first chamber and a second chamber; The first cabin is installed on the second cabin. The first cabin is assembled from multiple transparent viewing panels, and the second cabin is assembled from multiple mounting side panels.

[0008] According to the cryogenic intelligent micro-positive pressure working chamber control system provided by the present invention, the detection integration box includes: a pressure sensor and a dew point sensor; The pressure sensor is used to collect pressure data within the working chamber body; The dew point sensor is used to collect the dew point temperature inside the working chamber.

[0009] The cryogenic intelligent micro-positive pressure working chamber control system provided by the present invention further includes: image acquisition equipment, lighting equipment, and remote monitoring terminal; The image acquisition device is connected to the remote monitoring terminal; The image acquisition device is used to acquire full-scene images of the working chamber and upload the full-scene images to the remote monitoring terminal; The lighting equipment is used to illuminate the interior of the working compartment body; The remote monitoring terminal is used to receive and display the full-scene image in real time.

[0010] According to the cryogenic intelligent micro-positive pressure working chamber control system provided by the present invention, the remote monitoring terminal is further used for: The full-scene image is preprocessed and multi-dimensional feature is extracted to obtain multi-dimensional image features; Hierarchical anomaly identification is performed on the multidimensional image features to obtain anomaly identification results; If the anomaly identification result indicates that there is an anomaly within the cabin, a warning message will be generated and displayed.

[0011] The cryogenic intelligent micro-positive pressure working chamber control system provided by the present invention preprocesses the full-scene images, including: The full-scene image is subjected to illumination equalization processing to obtain an equalized image; The equalized image is subjected to noise filtering to obtain a denoised image; The denoised image is pixel-level aligned with a pre-established standard cabin scene image, and invalid regions in the aligned denoised image are cropped.

[0012] The cryogenic intelligent micro-positive pressure working chamber control system provided by the present invention performs multi-dimensional feature extraction on the full-scene images to obtain multi-dimensional image features, including: Extract the equipment outlines of the fixed equipment in the cabin from the full-scene image, and calculate the outline parameters of each equipment outline to obtain static structural features; Calculate the pixel difference between two consecutive full-scene images to obtain dynamic change features; Extract texture features from key areas inside the cabin in the full-scene image; The static structural features, dynamic change features, and texture features are used as multidimensional image features.

[0013] The cryogenic intelligent micro-positive pressure working chamber control system provided by the present invention performs hierarchical anomaly identification on the multi-dimensional image features to obtain anomaly identification results, including: Anomaly feature template matching is performed on the multidimensional image features to obtain preliminary identification results; The abnormal image features in the preliminary identification results are prioritized to obtain the abnormal feature levels; Based on the aforementioned anomaly feature level, the abnormal image features in the preliminary identification results are continuously verified across multiple frames to obtain the anomaly identification results.

[0014] According to the cryogenic intelligent micro-positive pressure working chamber control system provided by the present invention, abnormal feature template matching is performed on the multi-dimensional image features to obtain preliminary identification results, including: Establish an anomaly feature library containing templates for various anomaly features; The multidimensional image features are matched with various abnormal feature templates in the abnormal feature library to determine the feature similarity. The feature similarity obtained under each dimension is compared with the pre-set similarity threshold under the corresponding dimension, and the preliminary identification result is determined based on the comparison result.

[0015] According to the cryogenic intelligent micro-positive pressure working chamber control system provided by the present invention, based on the anomaly characteristic level, the abnormal image features in the preliminary identification results are continuously verified across multiple frames to obtain anomaly identification results, including: Based on the aforementioned anomaly characteristic level, determine the target number of verification frames; The abnormal image features in the preliminary identification results are continuously verified according to the target verification frame number. If the abnormal image features are all determined to be abnormal under the consecutive target verification frame number, the abnormal identification result is that there is an abnormal state corresponding to the abnormal image features in the cabin.

[0016] The cryogenic intelligent micro-positive pressure working chamber control system provided by this invention comprises a working chamber body, a detection integration box, a pressure relief valve, a nitrogen recovery device, and a control module. The detection integration box collects pressure data and dew point temperature within the working chamber body and sends the pressure data and dew point temperature to the control module after analog-to-digital conversion. Upon receiving the pressure data and dew point temperature, the control module compares the pressure data with a preset safe pressure range. If the pressure data exceeds the safe pressure range, it controls the pressure relief valve and nitrogen recovery device to open. When the pressure data drops to the safe pressure range, it controls the pressure relief valve and nitrogen recovery device to close. Simultaneously, the control module also triggers liquid nitrogen vaporization dehumidification after detecting that the dew point temperature is higher than a preset temperature setting value. This system integrates a nitrogen recovery device and a pressure relief valve into a coordinated control mechanism, ensuring pressure regulation accuracy while achieving efficient recovery and utilization of inert gas. By leveraging the real-time analysis of pressure signals by the control module, the coordinated drive of dual actuators, and the liquid nitrogen vaporization dehumidification function, it solves the problems of delayed pressure relief and excessive fluctuations in traditional systems. By simplifying the control logic and optimizing the component coordination, it balances control accuracy and cost, better meeting the application needs of different sized cabin scenarios. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is one of the structural schematic diagrams of the cryogenic intelligent micro-positive pressure working chamber control system provided in the embodiments of the present invention; Figure 2 This is a schematic diagram showing the connection relationship between the detection integrated box, the pressure relief valve, and the control module; Figure 3 This is the second schematic diagram of the structure of the cryogenic intelligent micro-positive pressure working chamber control system provided in the embodiment of the present invention; Figure 4 This is the third schematic diagram of the structure of the cryogenic intelligent micro-positive pressure working chamber control system provided in this embodiment of the invention; Figure 5 This is the fourth structural schematic diagram of the cryogenic intelligent micro-positive pressure working chamber control system provided in this embodiment of the invention; Figure 6 This is the fifth schematic diagram of the structure of the cryogenic intelligent micro-positive pressure working chamber control system provided in the embodiments of the present invention; Figure 7This is the sixth schematic diagram of the structure of the cryogenic intelligent micro-positive pressure working chamber control system provided in this embodiment of the invention; Figure 8 This is the seventh structural schematic diagram of the cryogenic intelligent micro-positive pressure working chamber control system provided in the embodiments of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] The following is combined with Figures 1-8 This invention describes the detailed scheme of the cryogenic intelligent micro-positive pressure working chamber control system provided in the embodiments of the present invention.

[0021] like Figure 1 , Figure 2 , Figure 7 and Figure 8 As shown, the cryogenic intelligent micro-positive pressure working chamber control system provided in this embodiment of the invention mainly includes: a working chamber body 110, a detection integration box 120, a pressure relief valve 130, a nitrogen recovery device 140, and a control module 150.

[0022] The detection integration box 120, the pressure relief valve 130, and the nitrogen recovery device 140 are all installed on the working chamber body 110.

[0023] The detection integration box 120 is used to collect pressure data and dew point temperature inside the working chamber body 110, and then send the pressure data and dew point temperature to the control module 150 after analog-to-digital conversion.

[0024] The control module 150 is used to compare the pressure data with the preset safe pressure range after receiving the pressure data and dew point temperature. If the pressure data is detected to exceed the safe pressure range, the pressure relief valve 130 is controlled to open. The nitrogen recovery device 140 is used to temporarily store excess nitrogen in the working chamber body 110 and to control the pressure relief valve 130 to close when the pressure data is detected to drop to the safe pressure range. The control module is also used to trigger liquid nitrogen vaporization dehumidification after detecting that the dew point temperature is higher than the preset temperature setting value.

[0025] Understandably, cryogenics typically refers to lowering the temperature inside a working chamber to a specific range far below conventional low temperatures. The core purpose is to achieve specific functions through extreme low temperatures, such as preservation of items or industrial processing.

[0026] In this embodiment, a pressure sensor is installed inside the detection integration box 120, which can monitor the pressure data inside the working chamber body 110 in real time and continuously, convert the pressure data into electrical signals, and transmit them to the control module 150 through a communication interface, providing data basis for the control module 150 to determine whether pressure relief is needed. During installation, the positive pressure end of the pressure sensor inside the detection integration box 120 is connected to the inside of the working chamber body 110, while the negative pressure end is exposed to the external atmospheric environment.

[0027] Meanwhile, the aforementioned control system also features an automatic dehumidification function. The detection integration box 120 is equipped with a dew point sensor to detect the dew point temperature inside the working chamber body 110. When the dew point temperature detected by the dew point sensor is higher than the preset temperature setting value, liquid nitrogen will be automatically vaporized. The vaporized nitrogen will carry away the moisture, thereby achieving the dehumidification function.

[0028] In this embodiment, the pressure relief valve 130 is a one-way pressure relief valve. The pressure relief valve 130 and the nitrogen recovery device 140 can work together. When the control module 150 detects that the pressure inside the chamber is too high, the pressure relief valve 130 is automatically opened under the instruction of the control module 150. At the same time, the nitrogen recovery device 140 can temporarily store the excess nitrogen in the chamber, reduce nitrogen waste, and help alleviate the sudden rise in pressure inside the chamber, providing a buffer for the pressure relief valve 130 to release the excess pressure inside the chamber. When the pressure inside the chamber drops to a safe range, such as 15Pa-50Pa, the pressure relief valve 130 and the nitrogen recovery device 140 are automatically closed, thereby maintaining a stable slightly positive pressure inside the chamber.

[0029] In this embodiment, the control module 150 uses a programmable logic controller as its core processor. It can analyze and judge the pressure data through the internally written control logic program. When the pressure inside the chamber is too high, it sends an opening command to the pressure relief valve 130 to achieve automatic pressure relief. After the pressure returns to normal, it sends a closing command to the pressure relief valve 130 to ensure that the pressure inside the chamber is maintained in a slightly positive pressure range of 15-50 Pa.

[0030] In one embodiment, such as Figure 3 As shown, the main body of the working compartment specifically includes: a first compartment 210 and a second compartment 220.

[0031] The first compartment 210 is installed on the second compartment 220. The first compartment 210 is assembled from multiple transparent viewing panels, and the second compartment 220 is assembled from multiple mounting side panels.

[0032] In this embodiment, the second compartment 220 at the bottom is formed by mounting side plates made of aluminum alloy or stainless steel plates, which are surrounded on all four sides and have high strength and corrosion resistance, providing stable support for the entire working compartment.

[0033] The top first compartment 210 is made of U-shaped transparent viewing panels. Specifically, 5-20mm thick PC boards can be used as transparent viewing panels, which are processed by hot-melt splicing process. This makes it easy for staff to observe the working conditions inside the working compartment. At the same time, a high sealing design is adopted to ensure that there is no leakage in the compartment under 300Pa pressure and to maintain a stable slightly positive pressure environment.

[0034] In practical applications, screws and nuts can be used to firmly connect the mounting side plate to the transparent viewing window plate, preventing the connection from loosening due to changes in cabin pressure, thereby ensuring the stability and sealing of the cabin structure.

[0035] like Figure 3 As shown, a sealing door 230 is provided on one side mounting plate of the second compartment 220. The sealing door 230 is fixedly installed on the mounting plate by multiple embossed knobs 240. After the mounting plate and the transparent window plate are installed and connected as a whole, the pressure remains within a range of not less than 100 Pa after 10 hours under a static pressure of 200 Pa.

[0036] In practical applications, the sealing door 230 is fixed to the mounting side plate with an embossed knob 240, serving as an emergency maintenance window to facilitate disassembly and entry by maintenance personnel.

[0037] In one embodiment, such as Figure 3 and Figure 4 As shown, the above-mentioned cryogenic intelligent micro-positive pressure working chamber control system may also include: image acquisition device 310, lighting device 320 and remote monitoring terminal.

[0038] The image acquisition device 310 is connected to the remote monitoring terminal.

[0039] The image acquisition device 310 is used to acquire full-scene images inside the working chamber and upload the full-scene images to the remote monitoring terminal.

[0040] Lighting equipment 320 is used to illuminate the interior of the working compartment.

[0041] The remote monitoring terminal is used to receive and display full-scene images in real time.

[0042] In this embodiment, the image acquisition device 310 can be a network camera, installed inside the first cabin, which can capture the working scene inside the cabin in real time, making it convenient for staff to remotely monitor the situation inside the cabin and promptly detect abnormal problems.

[0043] The lighting equipment 320 can be fluorescent lamps, installed inside the first compartment to provide sufficient lighting for the compartment, ensuring that staff can clearly observe the working status inside the compartment through the transparent viewing window or network camera, especially in low-light environments.

[0044] In some embodiments, such as Figure 5 As shown, a handle 410 is also installed on the outside of the transparent viewing window panel to facilitate the movement or adjustment of the cabin position by the staff and improve the ease of operation.

[0045] In practical applications, such as Figure 6 As shown, a pressure strip-type sealing gasket 510 can also be filled at the connection gap between the mounting side panel and the transparent window panel. When used with sealant, it can further improve the sealing performance of the cabin.

[0046] In one embodiment, the remote monitoring terminal can also be used for: First, the entire scene image is preprocessed and multi-dimensional features are extracted to obtain multi-dimensional image features.

[0047] In this embodiment, the acquisition frequency of the full-scene image is synchronized with the lighting cycle of the lighting equipment to ensure that clear full-scene images are obtained under stable lighting conditions. The acquired raw image data needs to be preprocessed to eliminate environmental interference and equipment noise.

[0048] For possible anomalies within the cabin, such as abnormal displacement of the detection integration box or foreign object intrusion caused by sealing failure of the sealing door, multi-dimensional image features can be extracted from the pre-processed image information to provide data basis for anomaly identification.

[0049] Then, hierarchical anomaly identification is performed on the multidimensional image features to obtain the anomaly identification results.

[0050] In this embodiment, a hierarchical anomaly identification mechanism can be used to accurately identify abnormal situations inside the cabin.

[0051] Finally, if the anomaly identification result indicates that there is an anomaly within the cabin, a warning message will be generated and displayed.

[0052] In practical applications, when an abnormal situation is detected, early warning information can be generated and displayed in a timely manner to remind relevant personnel to take timely measures to prevent the abnormal situation from deteriorating further and causing safety problems.

[0053] In one embodiment, preprocessing of the entire scene image specifically includes: First, the entire scene image is subjected to illumination equalization processing to obtain an equalized image.

[0054] In this embodiment, an adaptive histogram equalization algorithm is used to adjust the grayscale values ​​of image pixels to address the potential problem of uneven brightness in local areas of fluorescent lighting. This makes the brightness of different areas inside the cabin, such as the edge area near the sealed door and the equipment area near the detection integration box, more consistent, thus avoiding the problem of misjudgment of subsequent anomaly identification due to differences in lighting.

[0055] Then, noise filtering is performed on the equalized image to obtain a denoised image.

[0056] In this embodiment, an algorithm combining Gaussian filtering and median filtering can be used to filter out various noises in the equalized image, such as noise generated by interference from the image acquisition equipment circuit, while preserving key details such as the outline of the equipment inside the cabin and the direction of the cables, laying the foundation for subsequent feature extraction.

[0057] Finally, the denoised image is pixel-level aligned with a pre-established standard cabin scene image, and invalid regions in the aligned denoised image are cropped.

[0058] In practical applications, given the fixed structural characteristics of the working chamber itself, such as the fixed positions of the mounting side panels and transparent viewing windows, a standard scene image of the chamber can be pre-established as a reference template. After real-time acquisition and equalization and denoising processing of the denoised image, the standard scene image is aligned pixel-level with the image. Invalid areas in the image that have no actual monitoring significance, such as the border of the transparent viewing window, are cropped out, and the focus is placed on the core monitoring areas inside the chamber, such as the perimeter of the detection integration box, the connection of the nitrogen recovery device, and the sealing of the sealed door. This provides more accurate data for subsequent feature extraction.

[0059] In one embodiment, multi-dimensional feature extraction is performed on the entire scene image to obtain multi-dimensional image features, specifically including: On the one hand, the equipment outlines of the fixed equipment in the cabin are extracted from the full scene image, and the outline parameters of each equipment outline are calculated to obtain static structural features.

[0060] In this embodiment, an edge detection algorithm can be used to extract the contour features of the fixed equipment in the cabin, such as the detection integrated box, nitrogen recovery device, and sealing door. Contour parameters of each device contour can be calculated, such as the aspect ratio of the rectangular contour of the detection integrated box and the radius range of the circular contour of the nitrogen recovery device, thereby obtaining the static structural features. In practical applications, the contour parameters can be compared with preset normal contour parameter thresholds. If the real-time contour parameters exceed the safety threshold range, such as the detection integrated box tilting due to vibration and a change in its aspect ratio exceeding 5%, it can be marked as a potential anomaly.

[0061] On the other hand, the pixel difference between two consecutive full-scene images is calculated to obtain dynamic change features.

[0062] In this embodiment, the pixel difference between two consecutive full-scene images can be calculated using the inter-frame difference method to generate a dynamic change heatmap, i.e., dynamic change features. For areas on the cabin that should be static, such as the joint between the sealed door and the mounting side panel, or the connection seam between the pressure strip and the transparent window, if the dynamic change heatmap shows pixel changes for more than three consecutive frames, such as when the sealed door fails and external dust intrudes, resulting in dynamic grayscale changes, the dynamic change features of that area can be extracted, and parameters such as the area, grayscale value, and change amplitude of the changed area can be recorded.

[0063] On the other hand, texture features of key parts inside the cabin are extracted from the full-scene images.

[0064] In this embodiment, a local binary mode algorithm can be used to extract the texture features of key parts inside the cabin, such as the inner wall of the transparent window panel and the surface of the sealing gasket. Under normal circumstances, the texture of the inner wall of the transparent window panel is uniform, and the surface of the sealing gasket has no obvious scratches or damage, and the texture feature values ​​are in a stable range. If the transparent window panel cracks due to abnormal pressure or the sealing gasket ages and breaks, the texture feature values ​​will deviate from the normal range, and this will be used as a basis for judging anomalies.

[0065] Finally, static structural features, dynamic change features, and texture features are used as multidimensional image features.

[0066] In one embodiment, hierarchical anomaly identification is performed on multidimensional image features to obtain anomaly identification results, specifically including: First, abnormal feature template matching is performed on the multidimensional image features to obtain preliminary recognition results.

[0067] In one specific implementation, anomaly feature template matching is performed on multidimensional image features to obtain preliminary recognition results, which include: The first step is to establish an anomaly feature library containing templates for various anomaly features.

[0068] It is understandable that the abnormal feature library stores various abnormal feature templates, including template information such as threshold values ​​for various device contour parameters, threshold values ​​for static area change parameters, and standard texture features.

[0069] The second step is to perform similarity matching between the multidimensional image features and various abnormal feature templates in the abnormal feature library to determine the feature similarity.

[0070] The third step is to compare the feature similarity obtained under each dimension with the pre-set similarity threshold under the corresponding dimension, and determine the preliminary recognition result based on the comparison result.

[0071] In the similarity matching process, the cosine similarity algorithm can be used to calculate the feature similarity between various features in the multidimensional image features and the template features. If the feature similarity exceeds the preset similarity threshold, such as exceeding 85%, it is initially determined that the corresponding type of feature is abnormal.

[0072] Then, the abnormal image features in the preliminary identification results are prioritized to obtain the abnormal feature levels.

[0073] In this step, the abnormal image features in the preliminary identification results can be classified and prioritized according to the degree of impact of the cabin anomaly on the stability of the micro-positive pressure environment. For example, the bulging and deformation of the nitrogen recovery device may lead to nitrogen leakage, which directly affects the stability of the cabin pressure and can be classified as a high-priority anomaly; slight scratches on the surface of the sealing door do not affect the sealing performance and can be classified as a low-priority anomaly. Different priorities correspond to different subsequent processing strategies.

[0074] Finally, based on the level of abnormal features, the abnormal image features in the preliminary identification results are continuously verified across multiple frames to obtain the abnormal identification results.

[0075] In one specific implementation, based on the anomaly feature level, the anomaly image features in the preliminary identification results are continuously verified across multiple frames to obtain the anomaly identification results, which specifically include: The first step is to determine the target number of verification frames based on the level of abnormal characteristics.

[0076] The second step is to continuously verify the abnormal image features in the preliminary identification results according to the target verification frame number. If the abnormal image features are all determined to be abnormal under the consecutive target verification frame number, the abnormal identification result is that there is an abnormal state corresponding to the abnormal image features in the cabin.

[0077] In this embodiment, a time series analysis algorithm can be introduced to perform multi-frame continuous verification of abnormal image features in the preliminary identification results. For high-priority abnormal image features, the target verification frame count can be set to 10 frames. This verifies whether all 10 consecutive frames of images acquired meet the abnormal feature matching conditions and whether the abnormal feature parameters show a continuous changing trend. If the above conditions are met, the abnormality can be confirmed to exist. For low-priority abnormal image features, the target verification frame count can be set to 5 frames. This verifies whether all 5 consecutive frames of images acquired meet the abnormal feature matching conditions, avoiding misjudgment problems caused by accidental factors (such as brief shaking of the network camera).

[0078] In practical applications, once an abnormal situation is confirmed within the cabin, multiple methods can be used to provide early warnings and visual feedback, helping staff to respond quickly.

[0079] Specifically, different types of early warning signals can be generated based on the level of abnormal characteristics. For example, high-priority abnormalities trigger audible and visual alarms, while low-priority abnormalities trigger system pop-up alarms. At the same time, abnormal information, including the type of abnormality, location of occurrence, confirmation time, and abnormal image characteristics, is transmitted to the remote monitoring terminal and control module through the communication interface. The control module can analyze the pressure data collected by the pressure sensor in the detection integration box in conjunction with the data. For example, when the nitrogen recovery device bulges abnormally, the pressure change curve of the pressure sensor in the detection integration box can be retrieved simultaneously to determine whether the abnormality has affected the cabin pressure.

[0080] Meanwhile, image overlay technology can be used to add highlighted boxes to the areas where anomalies occur. For example, high-priority anomalies are marked with solid red boxes, and low-priority anomalies with dashed yellow boxes. The anomaly type and key parameters are also marked next to the boxes. For example, if the nitrogen recovery device is bulging abnormally with a current radius of 12cm, the normal range is 8-10cm. Staff can observe this directly through a transparent viewing window or remotely retrieve on-site images for remote monitoring, thereby quickly locating the anomaly and its core information.

[0081] In addition, the full-scene images, abnormal feature parameters, and processing results of each anomaly can be stored in the database to build an anomaly traceability archive. Association rule mining algorithms can be used to analyze the correlation between different anomaly types, such as the correlation between sealing door failure and cabin pressure fluctuations, to provide data support for cabin maintenance. Subsequently, anomalies can be predicted in advance based on historical data to avoid the recurrence of the same anomaly.

[0082] In summary, the cryogenic intelligent micro-positive pressure working chamber control system provided by this invention provides a stable and sealed foundation through the working chamber body. Relying on the pressure sensor and dew point sensor in the detection integration box, it accurately collects the pressure data and dew point temperature inside the chamber, and transmits them to the control module after analog-to-digital conversion. The control module compares the pressure data with the safe pressure range and then controls the pressure relief valve in conjunction with the nitrogen recovery device to release pressure. When the dew point temperature exceeds the limit, it uses liquid nitrogen vaporization to achieve dehumidification.

[0083] On the one hand, the precise coordination between the detection integration box and the control module can capture changes in cabin pressure in real time, avoiding the problem of pressure monitoring lag in traditional systems. Combined with the coordinated work of the pressure relief valve and the nitrogen recovery device, it can quickly divert and relieve pressure when the pressure exceeds the limit, preventing cabin seal failure or equipment damage caused by sudden pressure rise. On the other hand, it can shut down components in time when the pressure reaches the standard, avoiding excessive pressure relief and damage to the micro-positive pressure environment. This effectively ensures that the cabin pressure is always stable within the preset safe range, significantly improving the accuracy and reliability of pressure control.

[0084] On the other hand, the nitrogen recovery device breaks away from the traditional depressurization system's direct discharge of inert gas, allowing for the recovery and reuse of excess nitrogen in the chamber, significantly reducing nitrogen waste and lowering gas consumption costs during long-term operation, aligning with the technological development trend of energy conservation and environmental protection. Simultaneously, it achieves automatic dehumidification through dew point temperature control and liquid nitrogen vaporization. The entire system has a simple structure, strong component synergy, and is applicable to various scenarios such as equipment protection chambers and drug isolators, with a wide range of applications and high practicality. It can effectively meet the multiple needs of micro-positive pressure chambers of different sizes for pressure stability, gas conservation, and operational economy.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A cryogenic intelligent micro-positive pressure working chamber control system, characterized in that, include: The main body of the working compartment, the detection integration box, the pressure relief valve, the nitrogen recovery device, and the control module; The detection integration box, the pressure relief valve, and the nitrogen recovery device are all installed on the main body of the working chamber; The detection integration box is used to collect pressure data and dew point temperature inside the working chamber, and send the pressure data and dew point temperature to the control module after analog-to-digital conversion. The control module is used to compare the pressure data with a preset safe pressure range after receiving the pressure data and dew point temperature. If the pressure data is detected to exceed the safe pressure range, the control module controls the pressure relief valve to open. The nitrogen recovery device is used to temporarily store excess nitrogen in the working chamber. When the control module detects that the pressure data has dropped to the safe pressure range, it controls the pressure relief valve to close. The control module is also used to trigger liquid nitrogen vaporization dehumidification after detecting that the dew point temperature is higher than the preset temperature setting value.

2. The cryogenic intelligent micro-positive pressure working chamber control system according to claim 1, characterized in that, The working compartment body includes: a first compartment and a second compartment; The first cabin is installed on the second cabin. The first cabin is assembled from multiple transparent viewing panels, and the second cabin is assembled from multiple mounting side panels.

3. The cryogenic intelligent micro-positive pressure working chamber control system according to claim 1, characterized in that, The detection integration box includes: a pressure sensor and a dew point sensor; The pressure sensor is used to collect pressure data within the working chamber body; The dew point sensor is used to collect the dew point temperature inside the working chamber.

4. The cryogenic intelligent micro-positive pressure working chamber control system according to claim 1, characterized in that, The system also includes: image acquisition equipment, lighting equipment, and remote monitoring terminal; The image acquisition device is connected to the remote monitoring terminal; The image acquisition device is used to acquire full-scene images of the working chamber and upload the full-scene images to the remote monitoring terminal; The lighting equipment is used to illuminate the interior of the working compartment body; The remote monitoring terminal is used to receive and display the full-scene image in real time.

5. The cryogenic intelligent micro-positive pressure working chamber control system according to claim 4, characterized in that, The remote monitoring terminal is also used for: The full-scene image is preprocessed and multi-dimensional feature is extracted to obtain multi-dimensional image features; Hierarchical anomaly identification is performed on the multidimensional image features to obtain anomaly identification results; If the anomaly identification result indicates that there is an anomaly within the cabin, a warning message will be generated and displayed.

6. The cryogenic intelligent micro-positive pressure working chamber control system according to claim 5, characterized in that, Preprocessing of the full-scene image includes: The full-scene image is subjected to illumination equalization processing to obtain an equalized image; The equalized image is subjected to noise filtering to obtain a denoised image; The denoised image is pixel-level aligned with a pre-established standard cabin scene image, and invalid regions in the aligned denoised image are cropped.

7. The cryogenic intelligent micro-positive pressure working chamber control system according to claim 5, characterized in that, Multi-dimensional feature extraction is performed on the full-scene image to obtain multi-dimensional image features, including: Extract the equipment outlines of the fixed equipment in the cabin from the full-scene image, and calculate the outline parameters of each equipment outline to obtain static structural features; Calculate the pixel difference between two consecutive full-scene images to obtain dynamic change features; Extract texture features from key areas inside the cabin in the full-scene image; The static structural features, dynamic change features, and texture features are used as multidimensional image features.

8. The cryogenic intelligent micro-positive pressure working chamber control system according to claim 5, characterized in that, Hierarchical anomaly identification is performed on the multidimensional image features to obtain anomaly identification results, including: Anomaly feature template matching is performed on the multidimensional image features to obtain preliminary identification results; The abnormal image features in the preliminary identification results are prioritized to obtain the abnormal feature levels; Based on the aforementioned anomaly feature level, the abnormal image features in the preliminary identification results are continuously verified across multiple frames to obtain the anomaly identification results.

9. The cryogenic intelligent micro-positive pressure working chamber control system according to claim 8, characterized in that, Anomaly feature template matching is performed on the multidimensional image features to obtain preliminary identification results, including: Establish an anomaly feature library containing templates for various anomaly features; The multidimensional image features are matched with various abnormal feature templates in the abnormal feature library to determine the feature similarity. The feature similarity obtained under each dimension is compared with the pre-set similarity threshold under the corresponding dimension, and the preliminary identification result is determined based on the comparison result.

10. The cryogenic intelligent micro-positive pressure working chamber control system according to claim 8, characterized in that, Based on the aforementioned anomaly feature level, the abnormal image features in the preliminary identification results are continuously verified across multiple frames to obtain anomaly identification results, including: Based on the aforementioned anomaly characteristic level, determine the target number of verification frames; The abnormal image features in the preliminary identification results are continuously verified according to the target verification frame number. If the abnormal image features are all determined to be abnormal under the consecutive target verification frame number, the abnormal identification result is that there is an abnormal state corresponding to the abnormal image features in the cabin.

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