A method and system for intelligently monitoring cargo hold working data

Abstract

The present application relates to the technical field of ship engineering, and discloses a method and system for intelligent monitoring of cargo hold working data. The method first uses a camera to obtain a cargo hold image, extracts specific features through an edge detection algorithm, divides the sub-regions to count the number of pixels, and calculates the distribution uniformity to determine the type of cargo distribution. If it is a uniformly distributed target, the first infrared camera device and the temperature sensor are used to obtain data, and the uniform temperature is weighted and calculated. If it exceeds the first threshold, the corresponding cooling fan speed is adjusted; if it is a non-uniformly distributed target, the data is obtained in the same way to calculate the non-uniform temperature, and the corresponding cooling fan speed is adjusted if it exceeds the second threshold. Finally, the weighted comprehensive difference of the uniform temperature, non-uniform temperature and the corresponding threshold difference is calculated within a set period. When it is higher than the set threshold, the first and second thresholds of the next period are adjusted in the opposite direction. The above method can realize precise and intelligent control of cargo hold temperature to ensure cargo safety.

Description

Technical Field

[0001] The present application relates to the technical field of ship engineering, and in particular to a method and system for intelligently monitoring cargo hold working data. Background Art

[0002] In the operation and management of cargo holds, it is crucial to monitor the working data in the cargo hold. Traditional cargo hold monitoring methods may rely mainly on manual inspections or simple sensor monitoring, which has many limitations. For example, manual inspections are difficult to achieve real-time, comprehensive and accurate monitoring of cargo holds, prone to monitoring loopholes, and inefficient. At the same time, for the distribution status and temperature information of cargo in the cargo hold, only overall data may be obtained, lacking detailed analysis and targeted monitoring of cargo distribution.

[0003] However, in a complex cargo hold environment, cargo is usually placed in a variety of ways and may present different distribution states, including uniform distribution and non-uniform distribution. Different distribution states will have different effects on the temperature field in the cargo hold, which in turn affects the storage conditions and safety of the cargo. At the same time, the temperature in the cargo hold is affected by many factors, such as the thermal characteristics of the cargo itself, ambient temperature, ventilation conditions, etc. The traditional single threshold temperature control method is difficult to adapt to different cargo distributions and complex temperature changes. Therefore, a more intelligent, accurate and adaptive monitoring method is needed to ensure the storage safety of cargo in the cargo hold and the normal operation of the cargo hold. Summary of the invention

[0004] In order to improve the accuracy of monitoring cargo hold working data, the present application provides a method and system for intelligent monitoring of cargo hold working data.

[0005] In a first aspect, the present application provides a method for intelligently monitoring cargo hold working data, which adopts the following technical solution: A method for intelligently monitoring cargo hold working data comprises the following steps: Acquire a cargo hold image in the cargo hold based on a camera, and extract multiple specific features from the cargo hold image using an edge detection algorithm; Dividing the cargo hold image etc. into a plurality of sub-regions, and counting the number of pixels of the specific feature in each sub-region; Calculate the variance of the number of pixels as the distribution uniformity of the coordinates corresponding to the plurality of specific features in the cargo hold image; If the distribution uniformity is greater than the set uniform threshold, the specific feature is judged to be a uniform distribution target; otherwise, it is a non-uniform distribution target; If the target is evenly distributed, an infrared image of the evenly distributed target obtained by the first infrared camera device is the first image; calculating, according to the first image, a first infrared temperature corresponding to the first image; Acquiring the ambient temperature of the uniformly distributed target based on the first temperature sensor as the first ambient temperature; Obtaining a uniform temperature by weighted calculation according to the first infrared temperature and the first ambient temperature; If the uniform temperature exceeds the first threshold, the wind speed of the cooling fan corresponding to the uniform distribution target is adjusted according to the uniform temperature, the higher the uniform temperature, the higher the wind speed of the cooling fan; the lower the uniform temperature, the lower the wind speed of the cooling fan; If the target is non-uniformly distributed, an infrared image of the non-uniformly distributed target obtained by the second infrared camera device is the second image; calculating, according to the second image, a second infrared temperature corresponding to the second image; Acquiring the ambient temperature of the non-uniformly distributed target based on the second temperature sensor as a second ambient temperature; Obtaining a non-uniform temperature by weighted calculation according to the second infrared temperature and the second ambient temperature; If the non-uniform temperature exceeds a second threshold, the wind speed of the cooling fan corresponding to the non-uniform distribution target is adjusted according to the non-uniform temperature, the greater the non-uniform temperature, the greater the wind speed of the cooling fan corresponding to the non-uniform distribution target; the smaller the non-uniform temperature, the smaller the wind speed of the cooling fan corresponding to the non-uniform distribution target; Within a set time period, the sum of the absolute values ​​of the differences between the uniform temperature and the first threshold is calculated as a first difference, and the sum of the absolute values ​​of the differences between the non-uniform temperature and the second threshold is calculated as a second difference; weighted calculation of the first difference and the second difference as a comprehensive difference, and if the comprehensive difference is higher than a set threshold, adjusting the first threshold and the second threshold in a next time period; The larger the comprehensive difference is, the smaller the first threshold and the second threshold are; and the smaller the comprehensive difference is, the larger the first threshold and the second threshold are.

[0006] By adopting the above technical solution, the cargo hold image is first obtained through the camera, and the edge detection algorithm is used to extract specific features, which can accurately identify the key features of the objects in the cargo hold, providing a basis for the subsequent in-depth analysis of the cargo hold situation. The cargo hold image is divided into sub-areas and the number of specific feature pixels is counted, and then the distribution uniformity is calculated to determine the feature distribution type, and the distribution state of the objects in the cargo hold is fully grasped, so that different control strategies can be adjusted according to different distribution uniformity conditions. For uniformly distributed targets, they are generally cargo in the cargo hold; while for non-uniformly distributed targets, they are generally thermal equipment in the cargo hold. For uniformly distributed targets and non-uniformly distributed targets, different infrared cameras and temperature sensors are used for temperature monitoring, so that the temperature information of targets under different distribution states can be obtained more accurately, and the accuracy of temperature monitoring can be improved. According to the acquired infrared temperature and ambient temperature, the actual temperature is calculated by weight, including uniform temperature and non-uniform temperature, and the corresponding cooling fan speed is adjusted according to the temperature, so as to realize the intelligent and precise control of the temperature of different distribution targets in the cargo hold, effectively avoiding the problems of cargo damage and safety hazards caused by excessive temperature, and ensuring the quality of cargo and the safe operation of cargo holds. In the set time period, the sum of the absolute values ​​of the difference between the uniform temperature and the first threshold, and the difference between the non-uniform temperature and the second threshold is calculated, and the weighted difference is obtained. The first threshold and the second threshold in the next time period are adjusted according to the comprehensive difference, realizing the dynamic adjustment of the threshold. This dynamic adjustment mechanism can continuously optimize the temperature control standard according to the actual temperature changes in the cargo hold, making the adjustment of the cooling fan more reasonable and efficient, improving the adaptive ability of the entire monitoring system, and better adapting to the complex and changing environment in the cargo hold.

[0007] Optionally, if the second infrared camera device is disposed on a side of the cargo hold top, the method further includes: acquiring the second infrared image; identifying a characteristic object from the second infrared image according to a set characteristic threshold; Calculating the matching degree between the shape of the feature object and the feature shape in a preset feature library; If the matching degree is greater than a first matching threshold and lower than a second matching threshold, then calculating the radian value of the area corresponding to the feature object, the radian value being the radian value of the arc curve after fitting the shape of the feature object; If the radian value is greater than the set radian value, the wind direction and power of the cooling fan corresponding to the non-uniformly distributed target are adjusted; the larger the radian value, the greater the power of the cooling fan, and the cooling fan is directed toward the area where the characteristic object corresponding to the radian value is located; the smaller the radian value, the smaller the power of the cooling fan.

[0008] By adopting the above technical solution, since if the temperature in the cargo hold is too high, the heat will rise and gather in the middle, the camera is installed on the side instead of the top, which helps to reduce the impact of heat rise on the camera device. For non-uniform targets, that is, the images of thermal equipment, although there will be obstructions when shooting from the side, the heating situation of the thermal equipment can be more accurately understood from the side; the regional curvature value is mainly used to judge the obstruction, so as to estimate the actual temperature value. By calculating the curvature value of the characteristic object area, the possible heat collection situation in the middle of the cargo can be accurately judged. When the curvature value is greater than the set curvature value, the power of the heat dissipation fan is increased and the wind direction is adjusted to directly dissipate the heat in the heat collection area, effectively preventing heat from accumulating in the middle of the cargo, preventing the quality of the cargo from being affected by the high temperature in the middle, ensuring that the cargo can be in a suitable temperature environment in the entire cargo hold, and ensuring the safety of cargo storage. Since the rising heat will gather at the top in the middle, the camera device installed on the side can avoid the impact of heat on the camera device. Timely adjustment of the cooling fan power and wind direction to dissipate the intermediate heat can prevent problems such as blurred images and inaccurate data obtained by the camera device due to heat interference, and ensure that the second infrared camera device continuously and stably obtains clear images, providing reliable data support for subsequent feature recognition, matching degree calculation, and arc value calculation, etc., to ensure the normal operation of the entire intelligent monitoring system.

[0009] Optionally, the method for calculating the matching degree between the shape of the feature object and the feature shape in a preset feature library further includes the following sub-steps: If the matching degree is less than or equal to a first matching threshold, then setting a heat value corresponding to an area within a pixel range around the feature object; If the heat value is greater than the preset heat threshold, the wind direction and power of the cooling fan corresponding to the non-uniformly distributed target are adjusted; the larger the heat value, the greater the power of the cooling fan, and the cooling branch fan is directed toward the area where the characteristic object corresponding to the heat value is located; the smaller the heat value, the smaller the power of the cooling fan.

[0010] By adopting the above technical solution, when the shape of the feature object matches the shape in the preset feature library less than or equal to the first matching threshold, by analyzing the heat value of the area within the set pixel range around the feature object, the potential hidden danger area with abnormal heat can be accurately located. For example, although the device with abnormal heat is blocked by the device in front of the camera, the heat radiation area around the blocked device can be seen in the thermal imaging image. The area showing heat. This method makes up for the deficiency of relying solely on shape matching judgment, provides a more comprehensive monitoring perspective from the heat dimension, and does not miss any potential risk points that may affect the safety of cargo storage in the cargo hold. The wind direction and power of the cooling fan corresponding to the non-uniformly distributed target are adjusted in real time according to the size of the heat value, realizing the dynamic optimization of the heat dissipation strategy. When the heat value is larger, the power is increased and the wind is directed to the hidden danger area, which can quickly and effectively dissipate the heat; the smaller the heat value, the power is reduced to avoid energy waste. This precise heat dissipation control improves energy utilization efficiency and ensures that the temperature in the cargo hold is always kept within a safe range. By promptly discovering and handling areas of abnormal heat, we can effectively avoid problems such as damage and deterioration of cargo caused by local excessive heat, comprehensively guarantee the storage safety of cargo in the cargo hold, maintain the normal operation order of the cargo hold, and reduce economic losses and operational risks caused by temperature problems.

[0011] Optionally, the method for calculating the radian value of the area corresponding to the feature object includes the following sub-steps: Calculating an image area corresponding to the cargo hold image; Counting the number of multiple specific features extracted from the cargo hold image as the number of features, and calculating the distribution density of the specific features; The distribution density=image area / feature quantity; According to the distribution density, adjusting the value of the set arc value; The greater the distribution density, the smaller the set arc value; the smaller the distribution density, the greater the set arc value.

[0012] By adopting the above technical solution, the distribution density is determined by calculating the cargo hold image area and the number of specific features, and then the set arc value is adjusted according to the distribution density, so that the system can flexibly adjust the judgment standard according to the actual distribution status of the cargo in the cargo hold. Different cargo holds have different loading conditions. This method of dynamically adjusting the set arc value can better adapt to various complex and changeable cargo hold environments and improve the accuracy of monitoring. Adjusting the set arc value according to the cargo distribution density helps to more accurately judge whether the feature object is abnormal. When the distribution density is large, it means that the cargo distribution is relatively dense. At this time, lowering the set arc value can keenly capture the subtle anomalies that may exist in the dense area; while the distribution density is small and the cargo distribution is sparse, increasing the set arc value can avoid misjudging the normal situation due to overly strict standards, thereby realizing accurate identification of abnormal conditions in the cargo hold. This mechanism of automatically adjusting the set arc value according to the distribution density greatly improves the flexibility and adaptability of the entire monitoring system. Without frequent manual intervention to adjust parameters, the system can automatically optimize the judgment standard according to real-time monitoring data, effectively respond to the dynamic changes in the distribution of cargo in the cargo hold, ensure the continuous and stable operation of the monitoring system, and provide strong support for cargo hold safety.

[0013] Optionally, the method for calculating the matching degree between the shape of the feature object and the feature shape in a preset feature library further includes the following sub-steps: Calculating the spatial volume of the cargo hold according to the cargo hold image; According to a plurality of specific features extracted from the cargo hold image, matching the power of the device corresponding to the specific features; Calculate the spatial power density = spatial volume / the sum of the power of all devices corresponding to specific characteristics; adjusting the heat threshold according to the spatial power density; The greater the spatial power density, the smaller the heat threshold; the smaller the spatial power density, the greater the heat threshold.

[0014] By adopting the above technical solution, the spatial power density is obtained by calculating the cargo hold space volume and the equipment power corresponding to specific characteristics, and the heat threshold is adjusted accordingly, which changes the limitations of the previous fixed threshold. This method can dynamically and reasonably set the heat threshold according to the actual equipment power distribution and space size of the cargo hold to ensure the accuracy of heat monitoring. When the spatial power density is large, it means that the total power of the equipment in the unit space is large, and the heat may be more. At this time, lowering the heat threshold can timely detect potential overheating risks and make heat dissipation adjustments in advance; on the contrary, when the spatial power density is small, the heat threshold is increased to avoid frequent startup of heat dissipation equipment due to excessive sensitivity, achieving accurate and efficient temperature control and ensuring the stability of the cargo storage environment. This technical solution enables the system to automatically adjust the heat threshold according to the real-time status of the cargo hold, without the need for manual setting according to different cargo hold conditions. This greatly enhances the adaptability of the monitoring system, effectively responds to complex situations such as changes in equipment power in the cargo hold and changes in cargo storage layout, ensures the reliable operation of the entire cargo hold monitoring system, and provides strong protection for cargo hold safety and cargo storage.

[0015] Optionally, a ventilation pipe is provided inside the uniform distribution target, and the ventilation pipe is connected to an external ventilator; the ventilation pipe is a hard pipe, or the ventilation pipe is a semi-hose; the semi-hose includes a hard hollow annular or mesh-shaped supporting structure, and a ventilated cloth bag covering the hollow part of the supporting structure; The method comprises the following sub-steps: If the average temperature exceeds a first threshold, the ventilator operates at a first power for a first period of time; The first power and the first duration are adjusted in real time according to the uniform temperature. The larger the uniform temperature is, the larger the first power is and the longer the first duration is; the smaller the uniform temperature is, the smaller the first power is and the shorter the first duration is.

[0016] By adopting the above technical solution, ventilation hard tubes and / or hoses are added to the evenly distributed goods. The hoses include a supporting structure and dense side walls to achieve a certain ventilation effect and help dissipate heat.

[0017] Ventilation pipes are set inside the uniformly distributed target. Whether it is a hard pipe or a semi-hose with both a support structure and a ventilated bag, a ventilation channel can be directly constructed inside the cargo to enhance air circulation and accelerate heat dissipation. Compared with the traditional external heat dissipation method, this internal ventilation and heat dissipation is more targeted, which can effectively reduce the temperature in the core area of ​​the cargo, avoid damage to the cargo due to heat accumulation, greatly improve the heat dissipation efficiency, and ensure the safety of cargo storage. The first power and the first working time of the ventilator are adjusted in real time according to the uniform temperature to achieve precise heat dissipation control. When the uniform temperature is higher, the power and working time of the ventilator are increased to enhance the ventilation and heat dissipation effect; when the temperature is lowered, the power and working time are reduced accordingly to avoid energy waste. This flexible control mechanism can not only meet the heat dissipation needs of the cargo under different temperature conditions, but also improve energy utilization efficiency. The semi-hose adopts a hard hollow ring or mesh support structure with a ventilated bag. While ensuring the ventilation effect, it reduces the material cost and installation difficulty compared to the full rigid pipe. At the same time, by precisely controlling the working status of the ventilator, unnecessary energy consumption is reduced, and operating costs are further controlled, making the entire cargo hold cooling system more economical while ensuring its functionality.

[0018] Optionally, the method for adjusting the humidity of ventilation gas in the ventilation duct comprises the following steps: Obtaining a humidity parameter in the cargo hold during the first period of time; Calculating the average humidity in the cargo hold during the first period of time; If the average humidity exceeds a set threshold, the dryness of the ventilation air of the ventilator is adjusted according to the average humidity; The greater the humidity parameter, the higher the dryness of the ventilated air of the ventilator; the smaller the humidity parameter, the lower the dryness of the ventilated air of the ventilator.

[0019] By adopting the above technical solution, the humidity in the cargo hold can be effectively controlled by obtaining the humidity parameters of the cargo hold in the first time period and calculating the average humidity, and adjusting the dryness of the ventilation gas of the ventilator according to the comparison between the average humidity and the set threshold. When the average humidity exceeds the set threshold, the dryness of the ventilation gas is increased to absorb excess moisture; when the humidity is low, the dryness is reduced to prevent the cargo hold from being too dry, maintain the humidity of the cargo hold stable, and avoid affecting the cargo storage environment due to excessive or too low humidity. Different goods have different requirements for humidity, and precise adjustment of the humidity of the ventilation gas can meet the storage needs of various types of goods. Excessive humidity may cause the goods to become damp, moldy, and deteriorate, while too low humidity may cause the goods to crack and dehydrate. Through this technical solution, the ventilation gas can be flexibly adjusted according to the actual humidity of the cargo hold, providing a suitable humidity environment for the goods, protecting the quality of the goods to the greatest extent, and reducing the loss of goods caused by humidity problems. Reasonable adjustment of the humidity of the ventilation gas avoids rust and corrosion of equipment in the cargo hold due to excessive humidity, prolongs the service life of the equipment, and reduces the cost of equipment maintenance and replacement. At the same time, it prevents static electricity generated by low humidity from damaging the electronic components of the equipment, ensures the stable operation of the equipment in the cargo hold, and improves the operating efficiency of the entire cargo hold.

[0020] In the second aspect, the present application provides a cargo hold working data intelligent monitoring system, which adopts the following technical solution: A cargo hold operating data intelligent monitoring system comprises a processor, wherein the processor executes the steps of any one of the above-mentioned cargo hold operating data intelligent monitoring methods.

[0021] In summary, the present application includes at least one of the following beneficial technical effects: The camera is used to obtain cargo hold images, and specific features are extracted through edge detection algorithms. The image is divided into sub-areas to calculate the uniformity of feature distribution, so as to determine the type of cargo distribution. For uniform and non-uniform distribution targets, different infrared cameras and temperature sensors are used to measure the temperature, and the actual temperature is weighted and the cooling fan speed is adjusted accordingly. The threshold is dynamically adjusted by calculating the difference between the temperature and the threshold, so as to accurately monitor the cargo hold and intelligently control the temperature.

[0022] If the second infrared camera is installed on the top side of the cargo hold, the heat collection and heat abnormality of the cargo can be judged by calculating the matching degree between the feature object and the preset feature shape, the curvature value and the surrounding heat value, and the wind direction and power of the cooling fan can be flexibly adjusted accordingly. At the same time, the curvature value can be set according to the cargo distribution density, and the heat threshold can be adjusted according to the spatial power density to improve monitoring accuracy and adaptability.

[0023] Ventilation pipes (rigid or semi-flexible) are set inside the uniformly distributed target, and the fan power and duration are adjusted in real time according to the uniform temperature to dissipate heat. At the same time, the dryness of the ventilation gas is adjusted according to the average humidity in the cargo hold to ensure that the temperature and humidity of the cargo storage environment are appropriate, improve heat dissipation efficiency and energy utilization, protect cargo quality, and extend equipment life. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The invention is a step diagram of a method for intelligently monitoring cargo hold working data if the target is uniformly distributed.

[0025] Figure 2 The invention is a step diagram of a method for intelligently monitoring cargo hold working data if the target is non-uniformly distributed.

[0026] Figure 3 This is a method step diagram when the second infrared camera device is set on the side of the cargo hold top.

[0027] Figure 4 It is a graphically simplified diagram of different radian values. DETAILED DESCRIPTION

[0028] Embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings.

[0029] The present application embodiment discloses a method for intelligently monitoring cargo hold working data, referring to Figure 1 and Figure 2 , including the following steps: First, the camera is used to shoot the interior of the cargo hold to obtain the cargo hold image. Then, the edge detection algorithm is used to analyze and process the cargo hold image to extract multiple specific features from the image. For example, in an inland river transport cargo hold, the edge detection algorithm can identify key features such as the outline of the cargo packaging and the structure of the shelves in the cargo hold. This feature extraction method based on image recognition can accurately identify the key features of objects in the cargo hold, laying a solid foundation for subsequent in-depth analysis of the cargo hold situation.

[0030] Next, the acquired cargo hold image is divided into multiple sub-areas, and then for each sub-area, the number of pixels of specific features is counted. Taking a large cargo hold as an example, assume that its image is divided into 100 sub-areas of equal size, and the number of pixels of cargo contour features in each sub-area is counted. In this way, the distribution of specific features in different areas can be understood in detail. After that, based on the number of pixels obtained by statistics, its variance is calculated to determine the distribution uniformity of the coordinates corresponding to multiple specific features in the cargo hold image. The distribution uniformity can quantitatively reflect the distribution status of specific features in the cargo hold.

[0031] When the calculated distribution uniformity is greater than the set uniform threshold, the corresponding specific feature can be judged as a uniform distribution target. Generally speaking, the goods in the warehouse tend to be evenly distributed under normal stacking conditions, so the uniform distribution target usually refers to the goods in the warehouse. On the contrary, if the distribution uniformity is less than or equal to the set uniform threshold, it is judged as a non-uniform distribution target. In the cargo hold, some heat-generating equipment, such as lighting fixtures, ventilation equipment, etc., often have uneven heat distribution, and these heat equipment belong to non-uniform distribution targets.

[0032] For the uniformly distributed target, its infrared image is obtained based on the first infrared camera device, and the image is defined as the first image. The infrared camera device can capture the infrared rays emitted by the object, thereby obtaining the temperature information of the object. According to the first image, the first infrared temperature corresponding to the first image is calculated by a specific algorithm. At the same time, the ambient temperature of the uniformly distributed target is obtained based on the first temperature sensor, and it is defined as the first ambient temperature. Then, the uniform temperature is obtained by weighted calculation according to the first infrared temperature and the first ambient temperature. For example, when calculating the uniform temperature, according to the actual situation, a weight of 05 is assigned to the first infrared temperature and a weight of 0.5 is assigned to the first ambient temperature, so as to comprehensively consider the influence of the target's own temperature and the ambient temperature on it. If the calculated uniform temperature exceeds the first threshold, then it is necessary to adjust the wind speed of the cooling fan corresponding to the uniformly distributed target according to the uniform temperature. Specifically, the larger the uniform temperature, the larger the wind speed of the cooling fan; the smaller the uniform temperature, the smaller the wind speed of the cooling fan. Such an adjustment mechanism can effectively control the temperature of the goods and avoid damage to the goods due to excessive temperature. Assuming that the first threshold is 10°C, when the uniform temperature reaches 12°C, the cooling fan starts. When the temperature rises to 15°C, the fan speed is adjusted from low to high to enhance heat dissipation. When the temperature drops to 11°C, the wind speed is reduced to maintain a suitable temperature and protect the goods from high temperature damage.

[0033] If it is determined to be a non-uniformly distributed target, an infrared image of the non-uniformly distributed target is obtained based on the second infrared camera device and defined as a second image. Similarly, a second infrared temperature corresponding to the second image is calculated based on the second image, and the ambient temperature of the non-uniformly distributed target, i.e., the second ambient temperature, is obtained based on the second temperature sensor. The non-uniform temperature is then obtained by weighted calculation. In practical applications, for non-uniformly distributed thermal devices, the weight setting of the weighted calculation may be different from that of the uniformly distributed target to more accurately reflect its temperature characteristics. If the non-uniform temperature exceeds the second threshold, the wind speed of the cooling fan corresponding to the non-uniformly distributed target is adjusted according to the non-uniform temperature in a similar adjustment method to the uniformly distributed target. The larger the non-uniform temperature, the larger the wind speed of the cooling fan corresponding to the non-uniformly distributed target; the smaller the non-uniform temperature, the smaller the wind speed of the cooling fan corresponding to the non-uniformly distributed target. If the second threshold is 40°C, when the thermal device has been running for a period of time, the non-uniform temperature reaches 43°C, and the cooling fan starts and runs at a certain wind speed. If the thermal equipment continues to work and the non-uniform temperature rises to 48°C, the cooling fan will increase the wind speed to prevent the thermal equipment from malfunctioning due to overheating and ensure that the thermal equipment is transported in a safe temperature environment.

[0034] In a set time period, for example, one hour as a time period, the sum of the absolute values ​​of the difference between the uniform temperature and the first threshold is calculated, which is defined as the first difference; at the same time, the sum of the absolute values ​​of the difference between the non-uniform temperature and the second threshold is calculated, which is defined as the second difference. Then, the first difference and the second difference are weighted to obtain a comprehensive difference. If the comprehensive difference is higher than the set threshold, this indicates that there is a large deviation between the current temperature control situation and the expected standard. At this time, it is necessary to adjust the size of the first threshold and the second threshold in the next time period. The specific adjustment rule is that the larger the comprehensive difference, the smaller the first threshold and the second threshold; the smaller the comprehensive difference, the larger the first threshold and the second threshold. This dynamic adjustment mechanism can continuously optimize the temperature control standard according to the actual temperature changes in the cargo hold, make the adjustment of the cooling fan more reasonable and efficient, improve the adaptive ability of the entire monitoring system, and better adapt to the complex and changing environment in the cargo hold.

[0035] For example, the time period is set to 1 hour, and the first threshold is set to 10°C for monitoring the uniformly distributed temperature of goods; the second threshold is set to 40°C for monitoring the non-uniformly distributed temperature of thermal equipment.

[0036] During the first hour: The average temperatures are 8°C, 9°C, 11°C, 10°C, 12°C, and 11°C, respectively. The absolute values ​​of the differences from the first threshold value of 10°C are 2, 1, 1, 0, 2, and 1, respectively. The first difference is 2+1+1+0+2+1=7.

[0037] The non-uniform temperatures are 38°C, 42°C, 45°C, 40°C, 43°C, and 41°C, respectively. The absolute values ​​of the differences from the second threshold value of 40°C are 2, 2, 5, 0, 3, and 1, respectively. The second difference is 2+2+5+0+3+1=13.

[0038] Assume that the weight of the first difference is 0.4, and the weight of the second difference is 0.6, the comprehensive difference = 7×0.4+13×0.6=2.8+7.8=10.6. Set the threshold to 8, and the comprehensive difference 10.6 is higher than the set threshold, so the first threshold and the second threshold of the next time period need to be adjusted. Since the comprehensive difference is large, the first threshold and the second threshold should be reduced accordingly, for example, the first threshold is adjusted to 9°C, and the second threshold is adjusted to 38°C.

[0039] During the second hour: The average temperatures are 8°C, 9°C, 8°C, 9°C, 9°C, and 8°C respectively. The absolute values ​​of the differences between them and the adjusted first threshold value of 9°C are 1, 0, 1, 0, 0, and 1 respectively. The first difference is 1+0+1+0+0+1=3.

[0040] The non-uniform temperatures are 37°C, 39°C, 38°C, 37°C, 39°C, and 38°C, respectively, and the absolute values ​​of the differences between them and the adjusted second threshold value of 38°C are 1, 1, 0, 1, 1, and 0, respectively. The second difference is 1+1+0+1+1+0=4.

[0041] The comprehensive difference = 3×0.4+4×0.6=1.2+2.4=3.6. 3.6 is less than the set threshold value of 8, indicating that the current temperature control is relatively ideal, so in the next time period, the first threshold and the second threshold can be appropriately increased, for example, the first threshold is adjusted back to 10°C, and the second threshold is adjusted back to 40°C. In this way, the threshold is dynamically adjusted according to the comprehensive difference to ensure that the cargo hold temperature is always in a reasonable range.

[0042] In summary, the method for intelligent monitoring of cargo hold working data first obtains cargo hold images through a camera, and uses edge detection algorithms to extract specific features, providing a basis for subsequent analysis. By dividing the cargo hold image into sub-areas and counting the number of specific feature pixels, the distribution uniformity is calculated to determine the feature distribution type and fully grasp the distribution state of objects in the cargo hold. Then, according to different distribution uniformity conditions, different infrared camera devices and temperature sensors are used to monitor the temperature of uniformly distributed targets and non-uniformly distributed targets, accurately obtain the temperature information of targets under different distribution states, and improve the accuracy of temperature monitoring. The actual temperature is calculated by weighting the acquired infrared temperature and ambient temperature, and the corresponding cooling fan speed is adjusted according to the temperature, realizing intelligent and precise control of the temperature of different distribution targets in the cargo hold, effectively avoiding cargo damage and safety hazards caused by excessive temperature, and ensuring the quality of cargo and safe operation of the cargo hold. At the same time, by calculating the difference within a set time period and weighting the comprehensive difference, the threshold value is adjusted according to the comprehensive difference, realizing dynamic adjustment of the threshold, and further improving the performance of the entire monitoring system.

[0043] Reference Figure 3 If the second infrared camera device is disposed on the side of the cargo hold top, the method further includes: First, obtain the second infrared image. The second infrared camera captures infrared rays and converts the thermal radiation information of the non-uniformly distributed targets in the cargo hold, that is, the thermal equipment, into image data. These images contain rich thermal information and are an important basis for subsequent analysis of the working status of the thermal equipment and the temperature distribution in the cargo hold.

[0044] Next, based on the set feature threshold, the feature object is identified from the second infrared image. The feature threshold is pre-set based on a large amount of experimental data and practical experience, and is used to distinguish different thermal signal features. For example, in a cargo hold where goods are stored, the thermal equipment is the heat dissipation component of the refrigeration unit, etc. The feature threshold can accurately identify these key thermal equipment parts and exclude other irrelevant thermal interference signals.

[0045] Subsequently, the matching degree between the shape of the feature object and the feature shape in the preset feature library is calculated. The preset feature library stores the standard shape features of various common thermal devices under different working conditions. By comparing the shape of the identified feature object with the shape in the feature library, it is possible to preliminarily determine the type of thermal device to which the feature object belongs and its approximate working state. For example, if the shape of the identified feature object has a high matching degree with the shape of the heat sink of the refrigeration unit in the feature library, it can be preliminarily determined that the feature object is related to the heat dissipation of the refrigeration unit.

[0046] Reference Figure 4,For different occlusion situations, schematic diagrams of 3 different arc values ​​are shown. Different boxes represent different thermal devices. There are overlapping parts. The oblique shaded part is located in the rear thermal device. The heating area shown by the thermal imaging after the front device is blocked is matched in the preset feature library based on the heating area.

[0047] If the matching degree is greater than the first matching threshold and lower than the second matching threshold, this indicates that the shape of the feature object is similar to the standard shape in the feature library to a certain extent, but not completely consistent, and there may be some special cases or anomalies. At this time, it is necessary to further calculate the radian value of the area corresponding to the feature object. The radian value here is the radian value of the arc curve after fitting the shape of the feature object. For example, when a component of a thermal device changes the shape of its heat radiation area due to local overheating, by calculating the radian value of the area, this change can be quantified more accurately. Figure 4 In the figure, the arc value is the fitting arc value of the oblique line shaded part. Among them, the first two cases from left to right are that the matching degree is greater than the first matching threshold and lower than the second matching threshold.

[0048] If the calculated arc value is greater than the set arc value, this means that there may be abnormal heat accumulation in the cargo hold, especially in the middle of the cargo. At this time, it is necessary to adjust the wind direction and power of the cooling fan corresponding to the non-uniform distribution target. The specific adjustment method is: the larger the arc value, the more serious the heat accumulation, the greater the power of the cooling fan needs to be, and the cooling fan should be directed to the area where the characteristic object corresponding to the arc value is located, so as to concentrate the heat dissipation in the heat collection area; conversely, the smaller the arc value, the lower the degree of heat accumulation, and the smaller the power of the cooling fan.

[0049] It is assumed that the radian value of the heating area of ​​a normal server has a relatively stable range, and the radian value calculated this time is 1.5.

[0050] The radian value is set to 1.2. Since the calculated radian value of 1.5 is greater than the set radian value of 1.2, it indicates that the heating situation in this area may be abnormal, and the wind direction and power of the cooling fan corresponding to the non-uniform distribution target need to be adjusted. Because the radian value is large, the power of the cooling fan is increased, and the wind direction is adjusted so that the cooling fan is directly facing the area where the characteristic object corresponding to the radian value is located. If the subsequent monitoring shows that the radian value gradually decreases, for example, it drops to 1.0, which is less than the set radian value, the power of the cooling fan will be reduced accordingly to avoid excessive heat dissipation and energy waste, while continuing to ensure the normal operation of the equipment.

[0051] The reason why the second infrared camera is installed on the side instead of the top is based on the characteristics of heat transfer in the cargo hold. In the cargo hold, if the temperature is too high, the hot air will rise due to its low density and gather in the middle top area of ​​the cargo hold. Installing the camera on the side can effectively reduce the direct impact of heat rise on the camera, reduce the damage to the performance of the camera caused by high temperature, and extend its service life. For non-uniform targets, that is, the images of thermal equipment, although shooting from the side may cause some information to be missing due to the obstruction of other objects in the cargo hold, it can more accurately understand the heating conditions of the thermal equipment from the side. For example, for some vertical thermal equipment, shooting from the side can clearly show the heating differences in different parts of its side, while shooting from the top may be difficult to fully capture these details due to viewing angle problems.

[0052] The regional curvature value is mainly used to determine the situation where the thermal equipment or cargo is blocked, and then estimate the actual temperature value. Because when part of the thermal equipment or cargo area is blocked, the distribution shape of its thermal radiation will change. By calculating the curvature value, this shielding situation can be quantitatively analyzed, so as to more accurately estimate the actual temperature distribution. By calculating the curvature value of the characteristic object area, it is possible to accurately determine the possible heat collection in the middle of the cargo. When the curvature value is greater than the set curvature value, the power of the cooling fan is increased and the wind direction is adjusted in time to directly dissipate the heat in the heat collection area. This measure can effectively prevent heat from accumulating in the middle of the cargo, prevent the quality of the cargo from being affected by the high temperature in the middle, and ensure that the cargo can be in a suitable temperature environment throughout the cargo hold, effectively ensuring the safety of cargo storage.

[0053] In addition, since rising hot air will gather at the top in the middle, the camera device installed on the side can avoid the influence of hot air on the camera device. Timely adjustment of the heat dissipation fan power and wind direction to dissipate the hot air in the middle can prevent the camera device from obtaining blurred images and inaccurate data due to hot air interference. This ensures that the second infrared camera device can continuously and stably obtain clear images, providing reliable data support for subsequent feature recognition, matching degree calculation, and arc value calculation, fundamentally ensuring the normal operation of the entire intelligent monitoring system.

[0054] The method for calculating the matching degree between the shape of the feature object and the feature shape in the preset feature library also includes the following sub-steps: When the matching degree is less than or equal to the first matching threshold, this indicates that the shape of the feature object has a low similarity with the standard shape in the preset feature library. At this time, it is difficult to accurately judge its state based on shape matching alone. In order to grasp the situation more comprehensively and accurately, it is necessary to conduct in-depth analysis based on the heat value corresponding to the area within the set pixel range around the feature object. For example, in a large logistics cargo hold, various types of equipment are installed, and one of the new cargo handling robots has abnormal heating during operation. Due to the unique appearance design of the robot, its shape does not have a highly matching standard shape in the preset feature library, resulting in a shape matching degree less than or equal to the first matching threshold. However, by analyzing the heat value of the area within the set pixel range around it, signs of abnormal heating can be found. Figure 4 In the figure, the arc value is the fitting arc value of the oblique line shaded part. The last case from left to right is the case where the matching degree is less than or equal to the first matching threshold.

[0055] Specifically, if the heat value is greater than the preset heat threshold, this means that there may be abnormal heat accumulation in the area, posing a potential safety hazard. At this time, it is particularly important to adjust the wind direction and power of the cooling fan corresponding to the non-uniformly distributed target. Suppose the heat value of the surrounding area exceeds the preset heat threshold. At this time, the power of the cooling fan needs to be adjusted according to the size of the heat value. The larger the heat value, the greater the power of the cooling fan, and the air outlet of the cooling fan should be adjusted to the area where the characteristic object corresponding to the heat value is located, so as to quickly and effectively dissipate the heat, reduce the equipment temperature, and avoid equipment damage due to overheating. On the contrary, the smaller the heat value, the smaller the power of the cooling fan, which can avoid unnecessary waste of energy.

[0056] Assume that the set pixel range is a circular area with a radius of 50 pixels centered on the feature object. After detection, the heat value of the area is 80 (the unit is set according to the actual heat detection standard).

[0057] The preset heat threshold is 60. 80 is greater than 60, indicating that the heat in the area is abnormal and the cooling fan needs to be adjusted. Because the heat value is large, the cooling fan power is increased from the original 30% to 70%, and the wind direction is adjusted so that it blows directly to the area where the feature object is located.

[0058] As the heat dissipation progresses, the heat value of the area is tested again. If it drops to 50, which is less than the preset heat threshold, the cooling fan power will be reduced accordingly, for example, to 20%, to maintain appropriate heat dissipation intensity, ensure stable operation of the equipment, and avoid energy waste.

[0059] When the degree of matching between the shape of the feature object and the shape in the preset feature library is less than or equal to the first matching threshold, the potential hidden danger area of ​​thermal anomaly can be accurately located by analyzing the calorific value of the area within the set pixel range around the feature object. Even if the device with abnormal heating is blocked by the device in front of the camera, the thermal radiation area around the blocked device can still be seen in the thermal imaging image as an area with abnormal heating. For example, in a food refrigeration cargo hold, a key component of the refrigeration equipment is blocked by other goods, but by analyzing the calorific value of the surrounding area through thermal imaging, the abnormal heating of the component can still be discovered in time. This method makes up for the shortcomings of relying solely on shape matching judgment, provides a more comprehensive monitoring perspective from the thermal dimension, and does not miss any potential risk points that may affect the storage safety of cargo in the cargo hold.

[0060] The wind direction and power of the cooling fan corresponding to the non-uniform distribution target are adjusted in real time according to the calorific value, realizing the dynamic optimization of the cooling strategy. In actual cargo hold operations, the types of cargo, the placement of cargo, and the operating status of equipment are constantly changing. This dynamically optimized cooling strategy can respond promptly according to real-time heat changes. When the calorific value is larger, increasing the power and directing the wind to the potential danger area can quickly and effectively dissipate the heat; when the calorific value is smaller, reducing the power to avoid energy waste.

[0061] By promptly detecting and handling abnormal heat areas, problems such as damage and deterioration of goods caused by local excessive heat can be effectively avoided.

[0062] The method for calculating the radian value of the area corresponding to the feature object includes the following sub-steps: First, calculate the image area corresponding to the cargo hold image. In actual operation, this step is equivalent to defining a "benchmark range" for subsequent analysis. For example, on a certain voyage, a large number of containers were loaded in the cargo hold. In order to monitor the cargo in the cargo hold, a high-definition camera installed on the top of the cargo hold acquired the cargo hold image. After being processed by the image analysis software, the image has 3000 horizontal pixels and 2000 vertical pixels, and it is known that each pixel corresponds to an actual physical size of 0.02 square meters. According to the area calculation formula, the image area corresponding to the cargo hold image is 3000×0.02×2000×0.02=2400 square meters.

[0063] Next, we counted the number of specific features extracted from the cargo hold image, defined it as the number of features, and then calculated the distribution density of the specific features. The specific features here have different meanings in different cargo hold scenarios. For example, in a cargo hold full of containers, these specific features may be the corners and edges of the containers; while in a cargo hold stacked with grain, the specific features may be the key points of the ups and downs of the contours formed by the grain stacking. From the cargo hold image, we extracted the corner points of the container as specific features. Through the image recognition algorithm, the number of these corner points was counted to be 150. According to the formula of "distribution density = image area / number of features", the distribution density of specific features is calculated to be 2400÷150=16 square meters / piece.

[0064] After that, the size of the set arc value is adjusted according to the distribution density. The initial set arc value is 1.3. In the subsequent voyages, due to the change in the type of goods transported, it is changed to transport mechanical equipment with larger volume but fewer quantity. After acquiring and analyzing the cargo hold image again, it is found that the number of specific features extracted (key contour points of mechanical equipment) is only 50. The distribution density is recalculated to 2400÷50=48 square meters / piece, and the distribution density is significantly increased at this time. According to the rules, the set arc value needs to be reduced, for example, adjusted to 1.0, so that the subtle abnormal arc that may occur when the mechanical equipment is placed in the cargo hold or the state changes can be more accurately detected. On the contrary, if the transported goods are changed again, small and densely stacked goods are used, resulting in the number of specific features extracted to increase to 300. The distribution density is recalculated to 2400÷300=8 square meters / piece. The distribution density becomes smaller, and the set arc value is increased accordingly, such as adjusted to 1.6, to avoid misjudging the normal cargo stacking situation as abnormal due to overly strict standards.

[0065] The distribution density is determined by calculating the cargo hold image area and the number of specific features, and then the set arc value is adjusted according to the distribution density, so that the system can flexibly adjust the judgment criteria according to the actual distribution status of the cargo in the cargo hold. This method of dynamically adjusting the set arc value can better adapt to various complex and changeable cargo hold environments and improve the accuracy of monitoring. The mechanism of automatically adjusting the set arc value according to the distribution density greatly improves the flexibility and adaptability of the entire monitoring system. Without the need for frequent manual intervention to adjust parameters, the system can automatically optimize the judgment criteria based on real-time monitoring data, effectively respond to the dynamic changes in the distribution of cargo in the cargo hold, ensure the continuous and stable operation of the monitoring system, and provide strong support for cargo hold safety.

[0066] The method for calculating the matching degree between the shape of the feature object and the feature shape in the preset feature library also includes the following sub-steps: First, the spatial volume of the cargo hold is calculated based on the cargo hold image. In actual operation, the structure of the ship cargo hold is relatively complex and may have irregular shapes. Taking a common container transport ship cargo hold as an example, the cargo hold image is obtained by installing high-definition cameras in different corners of the hold. Due to the complex light conditions in the ship cargo hold, it may be necessary to combine light auxiliary lighting to obtain a clear image. The image stitching technology is used to integrate images from multiple perspectives into a complete cargo hold view. Then, with the help of a three-dimensional modeling algorithm designed specifically for ship cargo holds, combined with the camera installation angle, position parameters and pre-set distance measurement markers in the image, the length, width, height and volume of irregular parts of the cargo hold are accurately calculated. For example, a river cargo hold is a regular rectangular parallelepiped. Through the image taken by the camera in the cabin, combined with the known camera parameters and the internal size mark of the cargo hold, it is measured and calculated that the cargo hold is 30 meters long, 8 meters wide and 5 meters high. According to the rectangular parallelepiped volume formula, the volume of the cargo hold space is 30×8×5=1200 cubic meters.

[0067] Next, according to the multiple specific features extracted from the cargo hold image, the power of the equipment corresponding to the specific features is matched. In the ship cargo hold, these specific features are closely related to various types of equipment. For example, in a comprehensive ship cargo hold, the specific features extracted by image recognition technology may include the shape of the air outlet of the ship ventilation system, the mechanical structure characteristics of the cargo lifting equipment, and the shell outline of the power supply equipment. With the help of a pre-established database covering the characteristics and power information of various types of ship equipment, the power of the equipment corresponding to each specific feature can be quickly and accurately matched. From the cargo hold image, the features of lighting fixtures, ventilation equipment, and cargo lifting equipment are extracted. Through the pre-established equipment feature and power database, the power of the lighting fixture is 200 watts, with a total of 5 lamps; the power of the ventilation equipment is 1000 watts, with a total of 2 units; the power of the cargo lifting equipment is 5000 watts, with a total of 1 unit. The sum of the power of all equipment is 200×5+1000×2+5000×1=8000 watts.

[0068] Then, calculate the spatial power density, and its calculation formula is "spatial power density = spatial volume / the sum of the powers of all devices corresponding to specific characteristics".

[0069] Afterwards, the heat threshold is adjusted according to the spatial power density. This adjustment method breaks the limitations of the previous fixed heat threshold. It can dynamically and reasonably set the heat threshold according to the actual equipment power distribution and space size of the ship's cargo hold to ensure the accuracy of heat monitoring. When the spatial power density is large, it means that the total power of the equipment in the unit space is large, and the heat may be more. For example, in a ship cargo hold that specializes in transporting precision electronic instruments, the spatial power density is high because it is equipped with a large number of high-precision temperature control equipment and detection equipment to ensure the stable operation of the instruments. At this time, lowering the heat threshold can timely detect potential overheating risks, and perform heat dissipation adjustments in advance to avoid damage to electronic instruments due to overheating. On the contrary, when the spatial power density is small, such as in a ship cargo hold that transports ordinary building materials, the number of equipment is small and the power is relatively low. At this time, raising the heat threshold can avoid frequent startup of heat dissipation equipment due to excessive sensitivity, which not only saves energy, but also achieves accurate and efficient temperature control to ensure the stability of the cargo storage environment. According to the formula, the spatial power density is 1200÷8000=0.15 cubic meters / watt. Assuming that the initial heat threshold is 50°C, when the cargo hold is transported for the next time, multiple high-power electromechanical equipment are added for use on the construction site. After recalculation, the total power of the equipment rises to 20,000 watts, and the spatial power density becomes 1200÷20,000=0.06 cubic meters / watt, and the density increases. At this time, in order to detect potential overheating risks in a timely manner, the heat threshold is reduced to 40°C. If the subsequent transportation is changed to lightweight building materials, only basic lighting and ventilation equipment are retained, the total power is reduced to 3,000 watts, and the spatial power density becomes 1200÷3000=0.4 cubic meters / watt. The density decreases and the heat threshold is increased to 60°C to avoid frequent startup of equipment.

[0070] This technical solution enables the system to automatically adjust the heat threshold according to the real-time status of the ship's cargo hold, without the need for manual setting according to the different cargo hold conditions of the ship. This greatly enhances the adaptability of the monitoring system and effectively copes with complex situations such as changes in equipment power in the ship's cargo hold and changes in cargo storage layout. For example, in a multi-purpose ship cargo hold that constantly adjusts the type of cargo and equipment configuration as the transportation mission changes, the system can automatically adjust the heat threshold in real time according to changes in spatial power density to ensure the reliable operation of the entire cargo hold monitoring system, providing strong protection for the safety of the ship's cargo hold and cargo storage. Whether in professional special cargo transport ships or in the cargo hold scenarios of common comprehensive transport ships, this method of adjusting the heat threshold based on spatial power density has shown significant advantages and greatly improved the level of intelligence in ship cargo hold temperature monitoring and control.

[0071] A ventilation duct is arranged inside the uniformly distributed target, and the ventilation duct is connected to an external ventilator; the ventilation duct is a hard pipe, or the ventilation duct is a semi-hose; the semi-hose includes a hard hollow annular or mesh-shaped supporting structure, and a ventilated cloth bag covering the hollow part of the supporting structure.

[0072] Hard pipes are usually made of metal or high-strength plastic. They are strong and durable, can withstand high ventilation pressure, are not easily deformed during long-term use, and ensure ventilation stability. For example, in large grain storage cargo holds, hard ventilation pipes can be stably installed inside the piles of grain, providing reliable ventilation and heat dissipation support for long-term storage of grain.

[0073] The semi-hose is a cleverly designed ventilation component, which consists of a hard hollow ring or mesh support structure and a breathable cloth bag covering the hollow part of the support structure. Taking the ring support structure as an example, it is like a series of closely arranged metal or hard plastic rings, which are connected to each other to form the basic skeleton of the semi-hose, ensuring that the semi-hose will not collapse due to air flow pressure during ventilation. The breathable cloth bag is made of textile materials with good air permeability, such as special cotton or chemical fiber materials. Its densely distributed small pores can not only ensure the smooth flow of air, but also prevent dust, impurities, etc. from entering the ventilation system and affecting the ventilation effect. In a cargo hold storing light electronic products, the semi-hose can shuttle between the goods more flexibly, which not only meets the ventilation needs but also does not cause damage to the goods.

[0074] The ventilation and heat dissipation method includes the following sub-steps: If the uniform temperature exceeds the first threshold, it indicates that the temperature of the cargo in the cargo hold has reached a level that requires heat dissipation intervention. At this time, the ventilator works at the first power for the first duration. In actual operation, this process needs to be precisely controlled. For example, in a refrigerated cargo hold that transports fresh fruits and vegetables, when the temperature sensor detects that the uniform temperature inside the fruit and vegetable pile exceeds the first threshold suitable for storage, the ventilator starts quickly and starts working at the preset first power, continuously delivering external cold air to the inside of the fruit and vegetable pile to take away the heat.

[0075] In addition, the system will adjust the first power and the first duration in real time according to the uniform temperature. The higher the uniform temperature, the more serious the heat accumulation of the cargo. At this time, it is necessary to increase the first power and extend the first duration to enhance the ventilation and heat dissipation effect. For example, in the hot summer, in the cargo hold where chocolate and other easily melted goods are transported, as the ambient temperature rises, the temperature of the goods gradually rises, and the uniform temperature continues to increase. The power and working time of the ventilator will increase accordingly to ensure that the quality of the chocolate is not affected by high temperature. On the contrary, the lower the uniform temperature, the lower the first power and the shorter the first duration, so as to avoid excessive consumption of energy.

[0076] Assume that the first threshold is set to 10°C, the default first power of the ventilator is 50%, and the first duration is 30 minutes.

[0077] When the cargo hold monitoring system shows that the average temperature reaches 12°C, exceeding the first threshold, the ventilator immediately starts working at 50% power for 30 minutes.

[0078] After a period of time, the average temperature rises to 15°C. The system determines that the temperature is too high and increases the first power of the fan to 70% and the first duration to 45 minutes to increase ventilation and heat dissipation to prevent fruits and vegetables from rotting due to high temperature.

[0079] After continuous ventilation and cooling, the average temperature dropped to 11°C, the first power of the fan was reduced to 60%, and the first duration was shortened to 35 minutes to maintain moderate ventilation and heat dissipation.

[0080] When the temperature drops back to 9°C, which is lower than the first threshold, the ventilator stops working until the temperature exceeds the standard again. This dynamic adjustment ensures that fruits and vegetables are transported at an appropriate temperature.

[0081] Adding ventilation hard pipes and / or hoses to evenly distributed cargo can achieve good ventilation effects and greatly benefit heat dissipation. Ventilation pipes are set inside evenly distributed targets. Whether they are hard pipes or semi-hose pipes that have both support structures and breathable bags, ventilation channels can be directly built inside the cargo to enhance air circulation and accelerate heat dissipation. Compared with traditional external heat dissipation methods, this internal ventilation and heat dissipation is more targeted and can effectively reduce the temperature in the core area of ​​the cargo, avoid damage to the cargo due to heat accumulation, greatly improve heat dissipation efficiency, and ensure cargo storage safety.

[0082] According to the uniform temperature, the first power and the first working time of the ventilator are adjusted in real time to achieve precise heat dissipation control. When the uniform temperature is higher, the power and working time of the ventilator are increased to enhance the ventilation and heat dissipation effect; when the temperature is lowered, the power and working time are reduced accordingly to avoid energy waste. This flexible control mechanism can not only meet the heat dissipation needs of goods under different temperature conditions, but also improve energy utilization efficiency.

[0083] The semi-hose adopts a hard hollow ring or mesh support structure with a breathable cloth bag. While ensuring the ventilation effect, it reduces the material cost and installation difficulty compared to the full rigid pipe. For example, in the cargo holds of some small cargo ships, the semi-hose can be more conveniently installed between the cargoes, reducing the manpower and material investment in the installation process. At the same time, by accurately controlling the working state of the ventilator, unnecessary energy consumption is reduced, and the operating cost is further controlled, so that the entire cargo hold cooling system has better economy while ensuring the function. In the long-term operation of the cargo hold, this economical and efficient heat dissipation method can save a lot of costs for the enterprise and improve economic benefits.

[0084] The method for adjusting the humidity of ventilation gas in the ventilation duct comprises the following steps: First, the humidity parameters in the cargo hold within the first time period are obtained. In actual operation, multiple high-precision humidity sensors need to be reasonably distributed in the cargo hold. These sensors can capture the humidity data of different positions in the cargo hold in real time and accurately. For example, in a large river cargo hold, in order to fully grasp the humidity conditions, humidity sensors are installed at different positions such as the front, middle, rear, top, and bottom of the cargo hold. At regular intervals, such as 10 minutes, these sensors will transmit the collected humidity data to the central control system, thereby obtaining the humidity parameters at each time and location within the first time period (assuming 1 hour).

[0085] Next, the average humidity in the cargo hold during the first period is calculated. The central control system will summarize and analyze the large amount of humidity data received. Using mathematical statistical methods, the data collected by all humidity sensors during the first period are summed up and then divided by the total number of data to obtain the average humidity of the cargo hold during this period. For example, within 1 hour, a total of 100 humidity data at different times and locations are received. These data are added up and divided by 100 to obtain the average humidity value.

[0086] If the average humidity exceeds the set threshold, it means that the humidity in the cargo hold has exceeded the appropriate range for cargo storage. At this time, it is necessary to adjust the dryness of the ventilation gas of the ventilator according to the average humidity. In the ventilation system, a special gas drying device is usually equipped, such as a desiccant adsorption device or a condensation dehumidification device. When the average humidity is higher, it means that the moisture content in the cargo hold is higher. At this time, it is necessary to increase the dryness of the ventilation gas of the ventilator. For example, in a cargo hold for transporting Chinese medicinal materials, Chinese medicinal materials are more sensitive to humidity, and the appropriate humidity range is between 40% and 60%. If the calculated average humidity reaches 70%, which exceeds the set threshold of 60%, it is necessary to increase the amount of desiccant or increase the working intensity of the condensation dehumidification device to increase the dryness of the ventilation gas, so that it can absorb excess moisture in the cargo hold during ventilation. Conversely, the smaller the humidity parameter, the lower the dryness of the ventilation gas of the ventilator. For example, when the average humidity is only 30%, which is lower than the set threshold, it is necessary to appropriately reduce the amount of desiccant or reduce the working intensity of the condensation dehumidification device to prevent the cargo hold from being too dry.

[0087] By obtaining the humidity parameters of the cargo hold in the first period of time and calculating the average humidity, the dryness of the ventilation air from the ventilator is adjusted according to the comparison between the average humidity and the set threshold, and the humidity in the cargo hold can be effectively controlled. When the average humidity exceeds the set threshold, the dryness of the ventilation air is increased to absorb excess moisture; when the humidity is low, the dryness is reduced to prevent the cargo hold from being too dry, maintain the humidity of the cargo hold stable, and avoid the impact of excessive or low humidity on the cargo storage environment.

[0088] Different goods have different requirements for humidity. Accurately adjusting the humidity of ventilation gas can meet the storage needs of various types of goods. Too high humidity may cause the goods to get damp, moldy, and deteriorate. For example, in a cargo hold that transports food, too high humidity can make biscuits soft and cakes moldy, seriously affecting the taste and safety of the food. Too low humidity may cause the goods to dry out and dehydrate. For example, in a cargo hold that transports solid wood furniture, too low humidity can cause the wood to lose moisture too quickly, causing the furniture to dry out, deform, and have other problems. Through this technical solution, the ventilation gas can be flexibly adjusted according to the actual humidity of the cargo hold, providing a suitable humidity environment for the goods, protecting the quality of the goods to the greatest extent, and reducing the loss of goods caused by humidity problems.

[0089] Reasonable adjustment of ventilation gas humidity can avoid rust and corrosion of equipment in the cargo hold due to excessive humidity, extend the service life of the equipment, and reduce equipment maintenance and replacement costs. For example, metal ventilation ducts and electrical equipment in the cargo hold are prone to rust and corrosion in a high humidity environment, and by controlling humidity, the occurrence of this situation can be effectively reduced. At the same time, static electricity generated by low humidity can be prevented from damaging the electronic components of the equipment, ensuring the stable operation of the equipment in the cargo hold and improving the operating efficiency of the entire cargo hold. In a cargo hold equipped with an advanced electronic control system, static electricity generated by low humidity may interfere with the normal operation of electronic equipment and even damage electronic components. Reasonable adjustment of humidity can avoid these problems and ensure the smooth operation of the entire cargo hold.

[0090] An embodiment of the present application also discloses a system for intelligently monitoring cargo hold operating data, comprising a processor, wherein the processor executes the steps of any of the above-described methods for intelligently monitoring cargo hold operating data.

[0091] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for intelligent monitoring of cargo hold working data, characterized in that: The steps include: Acquire a cargo hold image in the cargo hold based on a camera, and extract multiple specific features from the cargo hold image using an edge detection algorithm; Dividing the cargo hold image etc. into a plurality of sub-regions, and counting the number of pixels of the specific feature in each sub-region; Calculate the variance of the number of pixels as the distribution uniformity of the coordinates corresponding to the plurality of specific features in the cargo hold image; If the distribution uniformity is greater than the set uniform threshold, the specific feature is judged to be a uniform distribution target; otherwise, it is a non-uniform distribution target; If the target is evenly distributed, an infrared image of the evenly distributed target obtained by the first infrared camera device is the first image; calculating, according to the first image, a first infrared temperature corresponding to the first image; Acquiring the ambient temperature of the uniformly distributed target based on the first temperature sensor as the first ambient temperature; Obtaining a uniform temperature by weighted calculation according to the first infrared temperature and the first ambient temperature; If the uniform temperature exceeds the first threshold, the wind speed of the cooling fan corresponding to the uniform distribution target is adjusted according to the uniform temperature, the higher the uniform temperature, the higher the wind speed of the cooling fan; the lower the uniform temperature, the lower the wind speed of the cooling fan; If the target is non-uniformly distributed, an infrared image of the non-uniformly distributed target obtained by the second infrared camera device is the second image; calculating, according to the second image, a second infrared temperature corresponding to the second image; Acquiring the ambient temperature of the non-uniformly distributed target based on the second temperature sensor as a second ambient temperature; Obtaining a non-uniform temperature by weighted calculation according to the second infrared temperature and the second ambient temperature; If the non-uniform temperature exceeds a second threshold, the wind speed of the cooling fan corresponding to the non-uniform distribution target is adjusted according to the non-uniform temperature. The greater the non-uniform temperature, the greater the wind speed of the cooling fan corresponding to the non-uniform distribution target; the smaller the non-uniform temperature, the smaller the wind speed of the cooling fan corresponding to the non-uniform distribution target.

2. The method for intelligent monitoring of cargo hold working data according to claim 1, characterized in that: The method further comprises the steps of: Within a set time period, calculating the sum of the absolute values ​​of the differences between the uniform temperature and the first threshold as a first difference, and calculating the sum of the absolute values ​​of the differences between the non-uniform temperature and the second threshold as a second difference; weighted calculation of the first difference and the second difference as a comprehensive difference, and if the comprehensive difference is higher than a set threshold, adjusting the first threshold and the second threshold in a next time period; The larger the comprehensive difference is, the smaller the first threshold and the second threshold are; and the smaller the comprehensive difference is, the larger the first threshold and the second threshold are.

3. The method for intelligent monitoring of cargo hold working data according to claim 1, characterized in that: If the second infrared camera device is disposed on the side of the cargo hold top, the method further includes: acquiring the second infrared image; identifying a characteristic object from the second infrared image according to a set characteristic threshold; Calculating the matching degree between the shape of the feature object and the feature shape in a preset feature library; If the matching degree is greater than a first matching threshold and lower than a second matching threshold, then calculating the radian value of the area corresponding to the feature object, the radian value being the radian value of the arc curve after fitting the shape of the feature object; If the radian value is greater than the set radian value, the wind direction and power of the cooling fan corresponding to the non-uniformly distributed target are adjusted; the larger the radian value, the greater the power of the cooling fan, and the cooling fan is directed toward the area where the characteristic object corresponding to the radian value is located; the smaller the radian value, the smaller the power of the cooling fan.

4. The method for intelligently monitoring cargo hold working data according to claim 3, characterized in that: The method for calculating the matching degree between the shape of the feature object and the feature shape in the preset feature library also includes the following sub-steps: If the matching degree is less than or equal to a first matching threshold, then setting a heat value corresponding to an area within a pixel range around the feature object; If the heat value is greater than the preset heat threshold, the wind direction and power of the cooling fan corresponding to the non-uniformly distributed target are adjusted; the larger the heat value, the greater the power of the cooling fan, and the cooling branch fan is directed toward the area where the characteristic object corresponding to the heat value is located; the smaller the heat value, the smaller the power of the cooling fan.

5. The method for intelligently monitoring cargo hold working data according to claim 3, characterized in that: The method for calculating the radian value of the area corresponding to the feature object comprises the following sub-steps: Calculating an image area corresponding to the cargo hold image; Counting the number of multiple specific features extracted from the cargo hold image as the number of features, and calculating the distribution density of the specific features; The distribution density=image area / feature quantity; According to the distribution density, adjusting the value of the set arc value; The greater the distribution density, the smaller the set arc value; the smaller the distribution density, the greater the set arc value.

6. The method for intelligently monitoring cargo hold working data according to claim 4, characterized in that: The method for calculating the matching degree between the shape of the feature object and the feature shape in the preset feature library also includes the following sub-steps: Calculating the spatial volume of the cargo hold according to the cargo hold image; According to a plurality of specific features extracted from the cargo hold image, matching the power of the device corresponding to the specific features; Calculate the spatial power density = spatial volume / the sum of the power of all devices corresponding to specific characteristics; adjusting the heat threshold according to the spatial power density; The greater the spatial power density, the smaller the heat threshold; the smaller the spatial power density, the greater the heat threshold.

7. The method for intelligently monitoring cargo hold working data according to claim 1, characterized in that: A ventilation pipe is arranged inside the uniform distribution target, and the ventilation pipe is connected to an external ventilator; the ventilation pipe is a hard pipe, or the ventilation pipe is a semi-hose; the semi-hose includes a hard hollow annular or net-shaped supporting structure, and a ventilated cloth bag covering the hollow part of the supporting structure; The method comprises the following sub-steps: If the average temperature exceeds a first threshold, the ventilator operates at a first power for a first period of time; The first power and the first duration are adjusted in real time according to the uniform temperature. The larger the uniform temperature is, the larger the first power is and the longer the first duration is; the smaller the uniform temperature is, the smaller the first power is and the shorter the first duration is.

8. The method for intelligently monitoring cargo hold operating data according to claim 7, characterized in that: The method for adjusting the humidity of ventilation gas in the ventilation duct comprises the following steps: Obtaining a humidity parameter in the cargo hold during the first period of time; Calculating the average humidity in the cargo hold during the first period of time; If the average humidity exceeds a set threshold, the dryness of the ventilation air of the ventilator is adjusted according to the average humidity; The greater the humidity parameter, the higher the dryness of the ventilated air of the ventilator; the smaller the humidity parameter, the lower the dryness of the ventilated air of the ventilator.

9. An intelligent monitoring system for cargo hold working data, characterized in that: It includes a processor, in which the steps of the method for intelligent monitoring of cargo hold working data as described in any one of claims 1 to 8 are executed.

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