An intelligent monitoring method and system for cargo hold working data

Abstract

The present application relates to the technical field of ship engineering, and discloses an intelligent monitoring method and system for 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 sub-regions to count the number of pixels, calculates the distribution uniformity, and thereby determines the type of cargo distribution. If it is a uniformly distributed target, data is obtained using a first infrared camera device and a temperature sensor, and the uniform temperature is calculated by weighting. When the first threshold is exceeded, the wind speed of the corresponding cooling fan is adjusted; if it is a non-uniformly distributed target, data is obtained in the same way to calculate the non-uniform temperature, and when the second threshold is exceeded, the wind speed of the corresponding cooling fan is adjusted. Finally, within a set period, the weighted comprehensive difference between the uniform temperature, the non-uniform temperature and the corresponding threshold difference is calculated. When it is higher than the set threshold, the first and second thresholds of the next period are adjusted in the reverse direction. Through the above method, precise and intelligent control of the cargo hold temperature can be achieved, ensuring the safety of the cargo.

Description

Technical Field

[0001] This application relates to the technical field of ship engineering, and particularly to an intelligent monitoring method and system for cargo hold working data. Background Art

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

[0003] However, in a complex cargo hold environment, the placement of goods is usually diverse and may exhibit different distribution states, including uniform distribution and non-uniform distribution. Different distribution states will have different effects on the temperature field inside the cargo hold, thereby affecting the storage conditions and safety of the goods. At the same time, the temperature inside the cargo hold is affected by various factors, such as the thermal characteristics of the goods themselves, the ambient temperature, ventilation conditions, etc. Traditional single-threshold temperature control methods are difficult to adapt to different goods distributions and complex temperature change situations. Therefore, a more intelligent, accurate, and adaptive monitoring method is needed to ensure the storage safety of the goods inside the cargo hold and the normal operation of the cargo hold. Summary of the Invention

[0004] To improve the accuracy of monitoring cargo hold working data, this application provides an intelligent monitoring method and system for cargo hold working data.

[0005] In a first aspect, this application provides an intelligent monitoring method for cargo hold working data, adopting the following technical solution:

[0006] An intelligent monitoring method for cargo hold working data includes the following steps:

[0007] Based on a camera, obtain a cargo hold image inside the cargo hold, and use an edge detection algorithm to extract multiple specific features from the cargo hold image;

[0008] Divide the cargo hold image into multiple sub-regions equally, and count the number of pixels of the specific features in each sub-region;

[0009] Calculate the variance of the number of pixels, and determine the distribution uniformity of the coordinates corresponding to the multiple specific features in the cargo hold image according to the variance;

[0010] If the distribution uniformity is greater than a set uniformity threshold, then determine that the specific feature is a uniformly distributed target; otherwise, it is a non-uniformly distributed target;

[0011] If it is a uniformly distributed target, the infrared image of the uniformly distributed target obtained based on the first infrared imaging device is the first image;

[0012] According to the first image, calculate the first infrared temperature corresponding to the first image;

[0013] Based on the first temperature sensor, obtain the ambient temperature of the uniformly distributed target as the first ambient temperature;

[0014] According to the first infrared temperature and the first ambient temperature, calculate the uniform temperature by weighted calculation;

[0015] If the uniform temperature exceeds the first threshold, adjust the wind speed of the cooling fan corresponding to the uniformly distributed target according to the uniform temperature. The greater the uniform temperature, the greater the wind speed of the cooling fan; the smaller the uniform temperature, the smaller the wind speed of the cooling fan;

[0016] If it is a non-uniformly distributed target, the infrared image of the non-uniformly distributed target obtained based on the second infrared imaging device is the second image;

[0017] According to the second image, calculate the second infrared temperature corresponding to the second image;

[0018] Based on the second temperature sensor, obtain the ambient temperature of the non-uniformly distributed target as the second ambient temperature;

[0019] According to the second infrared temperature and the second ambient temperature, calculate the non-uniform temperature by weighted calculation;

[0020] If the non-uniform temperature exceeds the second threshold, adjust the wind speed of the cooling fan corresponding to the non-uniformly distributed target 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-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;

[0021] Within a set time period, calculate the sum of the absolute values of the differences between the uniform temperature and the first threshold as the first difference, and calculate the sum of the absolute values of the differences between the non-uniform temperature and the second threshold as the second difference;

[0022] Calculate the weighted sum of the first difference and the second difference as the comprehensive difference. If the comprehensive difference is higher than the set threshold, adjust the magnitudes of the first threshold and the second threshold in the next time period;

[0023] The greater the comprehensive difference, the smaller the first threshold and the second threshold; the smaller the comprehensive difference, the greater the first threshold and the second threshold.

[0024] By adopting the above technical solutions, first, the cargo hold image is obtained through a camera, and specific features are extracted using an edge detection algorithm, which can accurately identify the key features of the objects in the cargo hold and provide a basis for subsequent in-depth analysis of the cargo hold situation. The cargo hold image is divided into sub-regions and the number of specific feature pixels is counted, and then the distribution uniformity is calculated to judge the type of feature distribution, comprehensively master the distribution state of the objects in the cargo hold, and thus adjust different control strategies according to different distribution uniformity situations. For uniformly distributed targets, they are generally the goods in the cargo hold; while for non-uniformly distributed targets, they are generally the thermal equipment in the cargo hold. For uniformly distributed targets and non-uniformly distributed targets, different infrared imaging devices and temperature sensors are used for temperature monitoring respectively, so that the temperature information of the targets in different distribution states can be obtained more accurately, and the accuracy of temperature monitoring is improved. The actual temperature is calculated by weighted calculation of the obtained infrared temperature and the ambient temperature, including the uniform temperature and the non-uniform temperature, and the corresponding cooling fan speed is adjusted according to this temperature, realizing the intelligent and precise control of the temperatures of different distributed targets in the cargo hold, effectively avoiding problems such as possible damage to goods and potential safety hazards caused by too high temperature, and ensuring the quality of goods and the safe operation of the cargo hold. Within a set time period, the sum of the absolute values of the differences between the uniform temperature and the first threshold, and between the non-uniform temperature and the second threshold is calculated, and a comprehensive difference is obtained by weighting. The sizes of 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 thresholds. This dynamic adjustment mechanism can continuously optimize the temperature control standard according to the actual temperature change situation 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 changeable environment in the cargo hold.

[0025] Optionally, if the second infrared imaging device is arranged on the side of the top of the cargo hold, the method further includes:

[0026] Obtain the second infrared image;

[0027] Identify a feature object from the second infrared image according to a set feature threshold;

[0028] Calculate the matching degree between the shape of the feature object and the feature shape in a preset feature library;

[0029] If the matching degree is greater than the first matching threshold and lower than the second matching threshold, calculate the radian value of the region corresponding to the feature object, where the radian value is the radian value of the arc curve after fitting the shape of the feature object;

[0030] If the radian value is greater than the set radian value, adjust the wind direction and power of the cooling fan corresponding to the non-uniformly distributed target; the greater the radian value, the greater the power of the cooling fan, and the cooling fan is directed towards the region where the feature object corresponding to the radian value is located; the smaller the radian value, the smaller the power of the cooling fan.

[0031] By adopting the above technical solution, if the temperature in the cargo hold is too high, the heat will rise and accumulate in the middle. Therefore, the camera is installed on the side instead of the top, which helps to reduce the impact of heat rise on the imaging device. For non-uniform targets, that is, the thermal images of thermal equipment, although there will be occlusion when shooting from the side, the heat generation situation of the thermal equipment can be more accurately understood from the side; the regional radian value is mainly used to judge the occlusion situation, so as to estimate the actual temperature value. By calculating the regional radian value of the feature object, the heat accumulation situation that may occur in the middle of the goods can be accurately judged. When the radian value is greater than the set radian value, increase the power of the cooling fan and adjust the wind direction to directly dissipate the heat in the heat accumulation area, effectively preventing the heat from accumulating in the middle of the goods, preventing the goods quality from being affected by the too high temperature in the middle, ensuring that the goods can be in a suitable temperature environment throughout the cargo hold, and guaranteeing the safety of goods storage. Since the hot air will rise and accumulate at the middle top, the imaging device installed on the side can avoid the influence of the hot air on the imaging device. Adjust the power and wind direction of the cooling fan in time to disperse the hot air in the middle. The timely dissipation of the hot air can prevent problems such as blurred images and inaccurate data obtained by the imaging device due to the interference of the hot air, ensuring that the second infrared imaging device continuously and stably obtains clear images, providing reliable data support for subsequent feature recognition, matching degree calculation, and radian value calculation, etc., and guaranteeing the normal operation of the entire intelligent monitoring system.

[0032] Optionally, the method for calculating the matching degree between the shape of the feature object and the feature shapes in the preset feature library further includes the following sub-steps:

[0033] If the matching degree is less than or equal to the first matching threshold, then according to the heat value corresponding to the area within the set pixel range around the feature object;

[0034] If the heat value is greater than the preset heat threshold, then adjust the wind direction and power of the cooling fan corresponding to the non-uniformly distributed target; the greater the heat value, the greater the power of the cooling fan, and make the cooling fan face the area where the feature object corresponding to the heat value is located; the smaller the heat value, the smaller the power of the cooling fan.

[0035] By adopting the above technical solution, when the shape matching degree between the feature object and the shape in the preset feature library is less than or equal to the first matching threshold, by analyzing the heat values in the area within a set number of pixels around the feature object, it is possible to accurately locate the potential hazard areas where heat anomalies may exist. For example, although the device with abnormal heat generation is blocked by the device in front of the imaging device, the heat radiation area around the blocking device can be seen as an area with heat in the thermal imaging image. 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 storage safety of the goods in the cargo hold. According to the magnitude of the heat value, the wind direction and power of the cooling fan corresponding to the non-uniformly distributed target are adjusted in real time, realizing the dynamic optimization of the cooling strategy. When the heat value is larger, the power is increased and the wind is directed to the hazard area, which can quickly and effectively disperse the heat; when the heat value is smaller, the power is reduced to avoid energy waste. This precise heat dissipation control improves the energy utilization efficiency and ensures that the temperature in the cargo hold always remains within the safe range. By promptly detecting and handling the heat anomaly areas, it effectively avoids problems such as damage and deterioration of the goods caused by excessive local heat, comprehensively guarantees the storage safety of the goods in the cargo hold, maintains the normal operation order of the cargo hold, and reduces the economic losses and operation risks caused by temperature problems.

[0036] Optionally, the method for calculating the radian value of the area corresponding to the feature object includes the following sub-steps:

[0037] Calculate the image area corresponding to the cargo hold image;

[0038] Count the number of multiple specific features extracted from the cargo hold image as the feature quantity, and calculate the distribution density of the specific features;

[0039] The distribution density = image area / feature quantity;

[0040] According to the distribution density, adjust the magnitude of the set radian value;

[0041] The larger the distribution density, the smaller the set radian value; the smaller the distribution density, the larger the set radian value.

[0042] By adopting the above technical solution, the distribution density is determined by calculating the area of the cargo hold image and the number of specific features, and then the set radian value is adjusted according to the distribution density, so that the system can flexibly adjust the judgment standard according to the actual distribution state of the goods in the cargo hold. Different cargo holds have different loading conditions. This way of dynamically adjusting the set radian value can better adapt to various complex and changeable cargo hold environments and improve the accuracy of monitoring. Adjusting the set radian 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 goods are more densely distributed. At this time, reducing the set radian value can sensitively capture the possible subtle abnormalities in the dense area; while when the distribution density is small and the goods are sparsely distributed, increasing the set radian value can avoid misjudging normal situations due to overly strict standards, so as to achieve accurate identification of abnormal situations in the cargo hold. This mechanism of automatically adjusting the set radian value according to the distribution density greatly improves the flexibility and self-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 cope with the dynamic changes in the cargo distribution in the cargo hold, ensure the continuous and stable operation of the monitoring system, and provide strong support for the safety of the cargo hold.

[0043] Optionally, the method for calculating the matching degree between the shape of the feature object and the feature shape in the preset feature library further includes the following sub-steps:

[0044] Calculate the space volume of the cargo hold according to the cargo hold image;

[0045] Match the power of the device corresponding to the specific feature according to a plurality of specific features extracted from the cargo hold image;

[0046] Calculate the space power density = space volume / sum of the powers of the devices corresponding to all specific features;

[0047] Adjust the heat threshold according to the space power density;

[0048] The greater the space power density, the smaller the heat threshold; the smaller the space power density, the greater the heat threshold.

[0049] By adopting the above technical solution, by calculating the volume of the cargo hold space and the power of the equipment corresponding to specific features, the space power density is obtained, and based on this, the heat threshold is adjusted, changing the limitation of the previous fixed threshold. In this way, according to the actual equipment power distribution and space size of the cargo hold, the heat threshold can be dynamically and reasonably set to ensure the accuracy of heat monitoring. When the space power density is large, it means that the total power of the equipment in the unit space is relatively large and more heat may be generated. At this time, lowering the heat threshold can promptly detect potential overheating risks and adjust heat dissipation in advance; on the contrary, when the space power density is small, the heat threshold is increased to avoid frequent activation of heat dissipation equipment due to excessive sensitivity, achieving precise 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 state of the cargo hold without manual setting according to different cargo hold situations. 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 the cargo storage layout, ensures the reliable operation of the entire cargo hold monitoring system, and provides strong guarantee for the safety of the cargo hold and the storage of goods.

[0050] Optionally, 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 rigid pipe, or the ventilation pipe is a semi-soft pipe; the semi-soft pipe includes a rigid hollowed-out ring-shaped or net-shaped support structure, and a ventilation cloth bag covering the hollowed-out places on the support structure;

[0051] The method includes the following sub-steps:

[0052] If the uniform temperature exceeds the first threshold, the ventilator operates at the first power for the first duration;

[0053] The first power and the first duration are adjusted in real time according to the uniform temperature. The greater the uniform temperature, the greater the first power and the longer the first duration; the smaller the uniform temperature, the smaller the first power and the shorter the first duration.

[0054] By adopting the above technical solution, a ventilation hard pipe and / or a hose are added to the uniformly distributed goods. The hose includes a support structure and a densely arranged side wall, achieving a certain ventilation effect and contributing to heat dissipation.

[0055] A ventilation pipe is arranged inside the uniformly distributed target. Whether it is a rigid pipe or a semi-flexible pipe with both a support structure and a breathable cloth bag, a ventilation channel can be directly constructed inside the goods, enhancing air circulation and accelerating heat dissipation. Compared with the traditional external heat dissipation method, this internal ventilation and heat dissipation is more targeted, can effectively reduce the temperature of the core area of the goods, avoid damage to the goods caused by heat accumulation, greatly improve the heat dissipation efficiency, and ensure the safety of goods storage. By adjusting the first power of the ventilator and the first working duration in real time according to the uniform temperature, precise heat dissipation control is achieved. When the uniform temperature is higher, the power and working duration of the ventilator are increased to strengthen the ventilation and heat dissipation effect; when the temperature decreases, the power and duration are correspondingly reduced to avoid energy waste. This flexible regulation mechanism can not only meet the heat dissipation requirements of the goods under different temperature conditions but also improve the energy utilization efficiency. The semi-flexible pipe adopts a rigid hollow circular or net-shaped support structure with a breathable cloth bag, which reduces the material cost and installation difficulty compared with the fully rigid pipe while ensuring the ventilation effect. At the same time, by precisely regulating the working state of the ventilator, unnecessary energy consumption is reduced, further controlling the operating cost, and making the entire cargo hold heat dissipation system more economical on the premise of ensuring its functions.

[0056] Optionally, the method for adjusting the humidity of the ventilation gas in the ventilation pipe includes the following steps:

[0057] Obtain the humidity parameter in the cargo hold during the first duration;

[0058] Calculate the average humidity in the cargo hold during the first duration;

[0059] If the average humidity exceeds the set threshold, adjust the dryness of the ventilation gas of the ventilator according to the average humidity;

[0060] The greater the humidity parameter, the higher the dryness of the ventilation gas of the ventilator; the smaller the humidity parameter, the lower the dryness of the ventilation gas of the ventilator.

[0061] By adopting the above technical solution, by obtaining the humidity parameter of the cargo hold within the first duration and calculating the average humidity, and adjusting the dryness degree of the ventilation gas of the ventilator according to the comparison between the average humidity and the set threshold, the humidity in the cargo hold can be effectively controlled. When the average humidity exceeds the set threshold, the dryness degree of the ventilation gas is increased to absorb the excess moisture; when the humidity is low, the dryness degree is reduced to prevent the cargo hold from being too dry, maintain the stability of the humidity in the cargo hold, and avoid affecting the cargo storage environment due to too high or too low humidity. Different goods have different requirements for humidity. Precisely adjusting the humidity of the ventilation gas can meet the storage needs of various goods. Too high humidity may cause the goods to get 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. Reasonably adjusting the humidity of the ventilation gas avoids the rusting and corrosion of the equipment in the cargo hold due to too high humidity, extends the service life of the equipment, and reduces the equipment maintenance and replacement costs. At the same time, it prevents the damage to the electronic components of the equipment caused by static electricity due to too low humidity, ensures the stable operation of the equipment in the cargo hold, and improves the operation efficiency of the entire cargo hold.

[0062] In a second aspect, the present application provides an intelligent monitoring system for cargo hold working data, adopting the following technical solution:

[0063] An intelligent monitoring system for cargo hold working data includes a processor, and the processor executes the steps of the method for intelligent monitoring of cargo hold working data as described in any one of the above.

[0064] In summary, the present application includes at least one of the following beneficial technical effects:

[0065] The camera is used to obtain the image of the cargo hold, and through the edge detection algorithm, specific features are extracted, the image sub-regions are divided to calculate the uniformity of the feature distribution, and thus the type of cargo distribution is judged. For uniformly and non-uniformly distributed targets, different infrared imaging devices and temperature sensors are respectively used to measure the temperature, the actual temperature is calculated by weighting, and the wind speed of the cooling fan is adjusted accordingly. Also, by calculating the difference between the temperature and the threshold, the dynamic adjustment of the threshold is realized to accurately monitor the cargo hold and intelligently control the temperature.

[0066] If the second infrared imaging device is arranged on the side of the top of the cargo hold, by calculating the matching degree, radian value and surrounding heat value of the feature object with the preset feature shape, the heat collection and heat anomaly conditions of the goods can be judged, and accordingly, the wind direction and power of the cooling fan are flexibly adjusted. At the same time, the set radian value is adjusted according to the cargo distribution density, and the heat threshold is adjusted according to the spatial power density, improving the monitoring accuracy and adaptability.

[0067] Install a ventilation pipe (rigid or semi-flexible) inside the uniformly distributed target, and adjust the power and duration of the ventilator in real time according to the uniform temperature for heat dissipation. At the same time, adjust the dryness of the ventilation gas according to the average humidity in the cargo hold to ensure that the temperature and humidity of the cargo storage environment are appropriate, improve the heat dissipation efficiency and energy utilization rate, protect the quality of the goods, and extend the service life of the equipment. Description of the Drawings

[0068] Figure 1 It is a step diagram of an intelligent monitoring method for cargo hold working data when it is a uniformly distributed target.

[0069] Figure 2 It is a step diagram of an intelligent monitoring method for cargo hold working data when it is a non-uniformly distributed target.

[0070] Figure 3 It is a step diagram of the method when the second infrared imaging device is set on the side of the top of the cargo hold.

[0071] Figure 4 It is a simplified schematic diagram of figures with different radian values. Detailed Embodiment

[0072] The following details the embodiments of the present application, and the examples of the embodiments are shown in the drawings.

[0073] The embodiments of the present application disclose an intelligent monitoring method for cargo hold working data. Referring to Figure 1 and Figure 2 , the method includes the following steps:

[0074] First, use a camera to take pictures of the interior of the cargo hold to obtain the cargo hold image. Subsequently, use an edge detection algorithm to analyze and process the cargo hold image, and extract multiple specific features from the image. For example, in a cargo hold of inland waterway transportation, key features such as the contour of the cargo packaging and the structure of the shelves in the cargo hold can be identified through the edge detection algorithm. This feature extraction method based on image recognition can accurately identify the key features of the objects in the cargo hold, laying a solid foundation for subsequent in-depth analysis of the cargo hold situation.

[0075] Next, divide the obtained cargo hold image into multiple sub-regions, and then for each sub-region, count the number of pixels of specific features therein. Taking a large cargo hold as an example, assume that its image is divided into 100 sub-regions of equal size, and count the number of pixels of the cargo contour features in each sub-region respectively. In this way, the distribution of specific features in different regions can be understood in detail. Then, according to the counted number of pixels, calculate its variance 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 state of specific features in the cargo hold.

[0076] When the calculated distribution uniformity is greater than the set uniformity threshold, it can be determined that the corresponding specific feature is a uniformly distributed target. Generally speaking, the goods in the warehouse tend to present a uniform distribution state under normal stacking conditions, so the uniformly distributed target usually refers to the goods in the warehouse. On the contrary, if the distribution uniformity is less than or equal to the set uniformity threshold, it is determined as a non-uniformly distributed target. In the cargo hold, some heating equipment, such as lighting fixtures, ventilation equipment, etc., often have uneven heat distribution, and these heat-generating devices belong to non-uniformly distributed targets.

[0077] For the uniformly distributed target, based on the first infrared imaging device, its infrared image is obtained and defined as the first image. The infrared imaging 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 through a specific algorithm. At the same time, based on the first temperature sensor, the ambient temperature where the uniformly distributed target is located is obtained and defined as the first ambient temperature. Then, according to the first infrared temperature and the first ambient temperature, the uniform temperature is obtained by means of weighted calculation. For example, when calculating the uniform temperature, according to the actual situation, a weight of 0.5 is assigned to the first infrared temperature and a weight of 0.5 is assigned to the first ambient temperature 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 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. Such an adjustment mechanism can effectively control the temperature of the goods and avoid damage to the goods caused by 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 the low gear to the high gear to strengthen heat dissipation. When the temperature drops to 11 °C, the wind speed decreases to maintain a suitable temperature and protect the goods from high-temperature damage.

[0078] 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 imaging device and defined as the second image. Similarly, the second infrared temperature corresponding to the second image is calculated according to 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. Then, the non-uniform temperature is obtained through weighted calculation. In practical applications, for non-uniformly distributed thermal equipment, the weight settings for its weighted calculation may be different from those of uniformly distributed targets to more accurately reflect their temperature characteristics. If the non-uniform temperature exceeds the second threshold, in a similar adjustment manner as for uniformly distributed targets, the wind speed of the cooling fan corresponding to the non-uniformly distributed 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-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, after the thermal equipment has been operating for a period of time, when the non-uniform temperature reaches 43°C, the cooling fan starts and operates at a certain wind speed. If the thermal equipment continues to operate and the non-uniform temperature rises to 48°C, the cooling fan will increase its 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.

[0079] Within a set time period, for example, with one hour as a time period, calculate the sum of the absolute values of the differences between the uniform temperature and the first threshold, and define it as the first difference; at the same time, calculate the sum of the absolute values of the differences between the non-uniform temperature and the second threshold, and define it as the second difference. Then, perform a weighted calculation on the first difference and the second difference to obtain the 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 magnitudes of the first threshold and the second threshold in the next time period. The specific adjustment rule is that the greater the comprehensive difference, the smaller the first threshold and the second threshold; the smaller the comprehensive difference, the greater 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, 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 changeable environment in the cargo hold.

[0080] For example, the set time period is 1 hour, the first threshold is set to 10°C for monitoring the temperature of uniformly distributed goods; the second threshold is set to 40°C for monitoring the temperature of non-uniformly distributed thermal equipment.

[0081] In the first hour:

[0082] The uniform temperatures are 8°C, 9°C, 11°C, 10°C, 12°C, 11°C respectively, and the absolute values of the differences from the first threshold of 10°C are 2, 1, 1, 0, 2, 1 respectively. The first difference is 2 + 1 + 1 + 0 + 2 + 1 = 7.

[0083] The non-uniform temperatures are 38°C, 42°C, 45°C, 40°C, 43°C, 41°C respectively, and the absolute values of the differences from the second threshold of 40°C are 2, 2, 5, 0, 3, 1 respectively. The second difference is 2 + 2 + 5 + 0 + 3 + 1 = 13.

[0084] Assume 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. The set threshold is 8. Since the comprehensive difference of 10.6 is higher than the set threshold, it is necessary to adjust the first threshold and the second threshold for the next time period. Since the comprehensive difference is relatively 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.

[0085] Within the second hour:

[0086] The uniform temperatures are 8°C, 9°C, 8°C, 9°C, 9°C, 8°C respectively, and the absolute values of the differences from the adjusted first threshold of 9°C are 1, 0, 1, 0, 0, 1 respectively. The first difference is 1 + 0 + 1 + 0 + 0 + 1 = 3.

[0087] The non-uniform temperatures are 37°C, 39°C, 38°C, 37°C, 39°C, 38°C respectively, and the absolute values of the differences from the adjusted second threshold of 38°C are 1, 1, 0, 1, 1, 0 respectively. The second difference is 1 + 1 + 0 + 1 + 1 + 0 = 4.

[0088] The comprehensive difference = 3×0.4 + 4×0.6 = 1.2 + 2.4 = 3.6. Since 3.6 is less than the set threshold of 8, it indicates that the current temperature control is relatively ideal. Therefore, for 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. By cycling in this way and continuously adjusting the thresholds dynamically according to the comprehensive difference, the temperature in the cargo hold can always be kept within a reasonable range.

[0089] In summary, the intelligent monitoring method for the cargo hold working data first obtains the cargo hold images through a camera and uses an edge detection algorithm to extract specific features, providing a basis for subsequent analysis. By dividing the cargo hold images into sub-regions and counting the number of pixels with specific features, the distribution uniformity is then calculated to determine the type of feature distribution, comprehensively grasping the distribution state of the objects in the cargo hold. Then, according to different distribution uniformity situations, different infrared camera devices and temperature sensors are respectively used to monitor the temperature of uniformly distributed targets and non-uniformly distributed targets, accurately obtaining the temperature information of the targets in different distribution states and improving the accuracy of temperature monitoring. The actual temperature is calculated by weighted calculation of the obtained infrared temperature and the ambient temperature, and the corresponding cooling fan speed is adjusted according to this temperature, realizing the intelligent and precise control of the temperature of different distributed targets in the cargo hold, effectively avoiding problems such as potential damage to goods and safety hazards caused by excessive temperature, and ensuring the quality of goods and the safe operation of the cargo hold. At the same time, by calculating the difference and weighting within a set time period to obtain a comprehensive difference, and adjusting the threshold size according to the comprehensive difference, the dynamic adjustment of the threshold is realized, further improving the performance of the entire monitoring system.

[0090] Referring to Figure 3 , if the second infrared camera device is set on the side of the top of the cargo hold, the method further includes:

[0091] First, obtain the second infrared image. The second infrared camera device 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 important bases for subsequent analysis of the working state of the thermal equipment and the temperature distribution in the cargo hold.

[0092] Next, according to the set feature threshold, identify the feature objects from the second infrared image. The feature threshold is preset 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 storing goods, if the thermal equipment is the heat dissipation component of a refrigeration unit, etc., the key parts of these thermal equipment can be accurately identified through the feature threshold, excluding other irrelevant thermal interference signals.

[0093] Subsequently, calculate the matching degree between the shape of the feature object and the feature shape in the preset feature library. The preset feature library stores the standard shape features of various common thermal equipment under different working conditions. By comparing the shape of the identified feature object with the shape in the feature library, the type of thermal equipment to which the feature object belongs and its approximate working state can be initially judged. For example, if the matching degree between the shape of the identified feature object and the shape of the heat dissipation fins of the refrigeration unit in the feature library is relatively high, it can be initially determined that the feature object is related to the heat dissipation situation of the refrigeration unit.

[0094] Referring to Figure 4, for different occlusion situations, schematic diagrams of 3 different radian values are shown. Different boxes represent different thermal devices, and there are overlapping parts. The slanted shaded part is the heat generation area shown by the thermal imaging after the front device occludes the rear thermal device. Matching is performed in a preset feature library according to this heat generation area.

[0095] If the matching degree is greater than the first matching threshold and lower than the second matching threshold, this indicates that there is a certain degree of similarity between the shape of the feature object and the standard shape in the feature library, but they are not exactly the same, and there may be some special situations or abnormalities. At this time, it is necessary to further calculate the radian value of the corresponding area of 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 certain component of a thermal device causes a change in the shape of its thermal radiation area due to local overheating, by calculating the radian value of this area, this change situation can be more accurately quantified. Figure 4 In [the figure], the radian value is the fitted radian value of the slanted shaded part. Among them, for the first two situations from left to right, the matching degree is greater than the first matching threshold and lower than the second matching threshold.

[0096] If the calculated radian value is greater than the set radian value, this means that there may be abnormal heat accumulation in the cargo hold, especially in the middle part 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 radian value, the more serious the heat accumulation, and the greater the power of the cooling fan is required, and the cooling fan should be directed towards the area where the feature object corresponding to this radian value is located to concentrate the heat dissipation of the heat collection area; conversely, the smaller the radian value, the lower the degree of heat accumulation, and the smaller the power of the cooling fan.

[0097] Assume that the radian value of the normal server heat generation area has a relatively stable range, and the calculated radian value this time is 1.5.

[0098] The set radian value is 1.2. Since the calculated radian value of 1.5 is greater than the set radian value of 1.2, it indicates that the heat generation situation in this area may be abnormal, and it is necessary to adjust the wind direction and power of the cooling fan corresponding to the non-uniform distribution target. Because the radian value is relatively large, the power of the cooling fan is increased, and the wind direction is adjusted so that the cooling fan is directly directed towards the area where the feature object corresponding to this radian value is located. If it is subsequently monitored that the radian value gradually decreases, for example, drops to 1.0, which is less than the set radian value, the power of the cooling fan is correspondingly reduced to avoid excessive heat dissipation and energy waste, while continuously ensuring the normal operation of the equipment.

[0099] The reason for installing the second infrared imaging device on the side instead of the top is based on the characteristics of heat propagation in the cargo hold. In the cargo hold, if the temperature is too high, the hot air will rise due to its lower density and accumulate 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 imaging device, reduce the damage to the performance of the imaging device caused by high temperature, and extend its service life. For non-uniform targets, that is, the captured images of heat equipment, although shooting from the side may result in partial information loss due to the occlusion of other objects in the cargo hold, it can more accurately understand the heat generation situation of the heat equipment from the side. For example, for some vertical heat equipment, shooting from the side can clearly show the heat generation differences in different parts of its side, while shooting from the top may be difficult to comprehensively capture these details due to the perspective problem.

[0100] The regional radian value is mainly used to judge the occlusion situation of heat equipment or goods, and then estimate the actual temperature value. Because when part of the area of heat equipment or goods is occluded, the distribution shape of its thermal radiation will change. By calculating the radian value, this occlusion situation can be quantitatively analyzed, so as to more accurately estimate the actual temperature distribution. By calculating the radian value of the characteristic object area, the possible heat collection situation in the middle of the goods can be accurately judged. When the radian value is greater than the set radian value, the power of the cooling fan is increased in time and the wind direction is adjusted to directly dissipate heat from the heat collection area. This measure can effectively prevent heat from accumulating in the middle of the goods, prevent the goods quality from being affected by too high temperature in the middle, ensure that the goods can be in a suitable temperature environment throughout the cargo hold, and effectively guarantee the safety of goods storage.

[0101] In addition, since the hot air will rise and accumulate in the middle top, the imaging device installed on the side can avoid the influence of the hot air on the imaging device. Adjust the power and wind direction of the cooling fan in time to disperse the hot air in the middle. The timely dissipation of the hot air can prevent problems such as blurred images and inaccurate data obtained by the imaging device due to the interference of the hot air. This ensures that the second infrared imaging device continuously and stably obtains clear images, provides reliable data support for subsequent feature recognition, matching degree calculation, and radian value calculation, etc., and fundamentally guarantees the normal operation of the entire intelligent monitoring system.

[0102] The method for calculating the matching degree between the shape of the characteristic object and the characteristic shape in the preset characteristic library further includes the following sub-steps:

[0103] When the matching degree is less than or equal to the first matching threshold, it indicates that the shape of the feature object has a low similarity to the standard shape in the preset feature library. At this time, it is difficult to accurately judge its state based solely on shape matching. To comprehensively and accurately understand the situation, 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. A new type of cargo handling robot shows abnormal heat generation during operation. Due to the unique design of the robot's appearance, there is no highly matching standard shape in the preset feature library, resulting in the matching degree being 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 heat generation can be discovered. Figure 4 In it, the radian value is the fitted radian value of the slanted shaded part. Among them, the last case from left to right belongs to the situation where the matching degree is less than or equal to the first matching threshold.

[0104] Specifically, if the heat value is greater than the preset heat threshold, it means that there may be abnormal heat accumulation in this area, presenting 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-uniform distribution 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 face the area where the feature object corresponding to this heat value is located, so as to quickly and effectively disperse the heat, reduce the equipment temperature, and avoid equipment damage caused by overheating. On the contrary, the smaller the heat value, the smaller the power of the cooling fan, which can avoid unnecessary waste of energy.

[0105] Suppose 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 this area is 80 (the unit is set according to the actual heat detection standard).

[0106] The preset heat threshold is 60, and 80 is greater than 60, indicating that the heat in this area is abnormal and the cooling fan needs to be adjusted. Because the heat value is relatively large, the power of the cooling fan is increased from the original 30% power to 70%, and the wind direction is adjusted so that it blows directly at the area where the feature object is located.

[0107] As the heat dissipation progresses, the heat value of this area is detected again. If it drops to 50, which is less than the preset heat threshold, the power of the cooling fan is correspondingly reduced, for example, to 20%, to maintain an appropriate heat dissipation intensity, ensure the stable operation of the equipment, and avoid energy waste at the same time.

[0108] When the shape matching degree between the feature object and the shapes in the preset feature library is less than or equal to the first matching threshold, by analyzing the heat values in the area within a set number of pixels around the feature object, it is possible to accurately locate the potential hazard areas where heat anomalies may exist. Even if the device with abnormal heat generation is blocked by the devices in front of the camera device, in the thermal imaging image, it is still possible to see that the thermal radiation area around the blocking device shows an area with abnormal heat. For example, in a food refrigerated cargo hold, a certain key component of the refrigeration equipment is blocked by other goods, but by analyzing the heat values in the surrounding area through thermal imaging, it is still possible to timely detect the abnormal heat generation of this component. 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 storage safety of the goods in the cargo hold.

[0109] According to the size of the heat value, the wind direction and power of the cooling fan corresponding to the non-uniform distribution target are adjusted in real time, realizing the dynamic optimization of the heat dissipation strategy. In the actual operation of the cargo hold, the types of goods, the placement methods, and the operating states of the equipment are constantly changing. This dynamically optimized heat dissipation strategy can make timely responses according to the real-time heat changes. When the heat value is larger, increase the power and direct the wind to the hazard area to quickly and effectively disperse the heat; when the heat value is smaller, reduce the power to avoid energy waste.

[0110] By timely discovering and dealing with the heat anomaly areas, it effectively avoids problems such as damage and deterioration of goods caused by excessive local heat.

[0111] The method for calculating the radian value of the area corresponding to the feature object includes the following sub-steps:

[0112] First, calculate the image area corresponding to the cargo hold image. In actual operation, this step is equivalent to delimiting a "reference range" for subsequent analysis. For example, in a certain voyage, the cargo hold is loaded with a large number of containers. To monitor the goods in the cargo hold, a high-definition camera installed on the top of the cargo hold obtains the cargo hold image. After being processed by the image analysis software, the horizontal pixels of this image are 3000, the vertical pixels are 2000, 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.

[0113] Next, count the number of multiple specific features extracted from the cargo hold image, define it as the feature quantity, and then calculate the distribution density of the specific features. Here, the specific features have different references in different cargo hold scenarios. For example, in a cargo hold full of containers, these specific features may be the corner points, edges, etc. of the containers; while in a cargo hold stacked with grains, the specific features may be the key points of the undulating contour formed by the grain stacking. From the cargo hold image, we extract the corner points of the containers as specific features. Through the image recognition algorithm, the number of these corner points is counted as 150. According to the formula "distribution density = image area / feature quantity", the distribution density of the specific features is calculated as 2400÷150 = 16 square meters per piece.

[0114] After that, according to the distribution density, adjust the size of the set radian value. The initially set radian value is 1.3. In subsequent voyages, due to the change in the types of goods transported, it is changed to transport mechanical equipment with a larger volume but a smaller quantity. After obtaining and analyzing the cargo hold image again, it is found that the number of specific features (key contour points of the mechanical equipment) extracted is only 50. Recalculate the distribution density as 2400÷50 = 48 square meters per piece. At this time, the distribution density increases significantly. According to the rule, the set radian value needs to be decreased, for example, adjusted to 1.0, so that the subtle abnormal radian that may occur when the mechanical equipment is placed or its state changes in the cargo hold can be detected more accurately. On the contrary, if the transported goods are changed again to small and densely stacked commodities, resulting in the number of specific features extracted increasing to 300. Recalculate the distribution density as 2400÷300 = 8 square meters per piece. The distribution density becomes smaller, and the set radian value is correspondingly increased, for example, adjusted to 1.6, to avoid misjudging the normal cargo stacking situation as abnormal because the standard is too strict.

[0115] Determine the distribution density by calculating the cargo hold image area and the quantity of specific features, and then adjust the set radian value according to the distribution density, so that the system can flexibly adjust the judgment criteria according to the actual distribution state of the goods in the cargo hold. This way of dynamically adjusting the set radian 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 radian value according to the distribution density greatly enhances the flexibility and self - adaptability of the entire monitoring system. Without frequent manual intervention to adjust parameters, the system can automatically optimize the judgment criteria according to real - time monitoring data, effectively cope with the dynamic changes in the cargo distribution in the cargo hold, ensure the continuous and stable operation of the monitoring system, and provide strong support for the safety of the cargo hold.

[0116] The method for calculating the matching degree between the shape of the feature object and the feature shapes in the preset feature library further includes the following sub - steps:

[0117] First, calculate the space volume of the cargo hold based on the cargo hold image. In actual operation, for a ship's cargo hold, its structure is relatively complex and may have irregular shapes. Taking the cargo hold of a common container shipping ship as an example, obtain the cargo hold image through high-definition cameras installed in different corners of the hold. Since the lighting conditions in the ship's cargo hold are complex, it may be necessary to combine with lighting auxiliary lighting to obtain clear images. Use image stitching technology to integrate images from multiple perspectives into a complete view of the cargo hold, and then, with the help of a three-dimensional modeling algorithm specifically designed for ship cargo holds, combined with the installation angles and position parameters of the cameras and the distance measurement markers preset in the image, accurately calculate the length, width, height of the cargo hold and the volume of the irregular parts. For example, a river transport cargo hold is in the shape of a regular cuboid. Through the image taken by the camera in the hold, combined with the known camera parameters and the internal dimension markers of the cargo hold, it is measured and calculated that the length of the cargo hold is 30 meters, the width is 8 meters, and the height is 5 meters. According to the cuboid volume formula, the space volume of the cargo hold is 30×8×5 = 1200 cubic meters.

[0118] Next, based on multiple specific features extracted from the cargo hold image, match the power of the equipment corresponding to the specific features. In a ship's cargo hold, these specific features are closely related to various types of equipment. For example, in a comprehensive ship's cargo hold, the specific features extracted through image recognition technology may include the shape of the air outlet of the ship's ventilation system, the mechanical structure features of the cargo handling equipment, and the outer shell contour of the power supply equipment, etc. With the help of a pre-established database covering the feature and power information of various ship equipment, it is possible to quickly and accurately match the power of the equipment corresponding to each specific feature. From the cargo hold image, extract the features of the lighting fixtures, ventilation equipment, and cargo handling equipment. Through the pre-established database of equipment features and power, match that the power of the lighting fixtures is 200 watts, with a total of 5; the power of the ventilation equipment is 1000 watts, with a total of 2; the power of the cargo handling equipment is 5000 watts, with a total of 1. The sum of the power of all equipment is 200×5 + 1000×2 + 5000×1 = 8000 watts.

[0119] Then, calculate the space power density, and its calculation formula is "space power density = space volume / sum of the power of all equipment corresponding to specific features".

[0120] After that, adjust the heat threshold according to the spatial power density. This adjustment method breaks the limitations of the previous fixed heat threshold and can dynamically and reasonably set the heat threshold according to the actual equipment power distribution and space size in the ship's cargo hold, ensuring the accuracy of heat monitoring. When the spatial power density is high, it means that the total equipment power in the unit space is relatively large and more heat may be generated. For example, in the cargo hold of a ship dedicated to transporting precision electronic instruments, due to the installation of a large number of high-precision temperature control equipment and detection equipment for ensuring the stable operation of the instruments, the spatial power density is relatively high. At this time, lowering the heat threshold can promptly detect potential overheating risks and perform heat dissipation adjustment in advance to avoid damage to the electronic instruments caused by overheating. On the contrary, when the spatial power density is low, such as in the cargo hold of a ship transporting 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 activation of the heat dissipation equipment due to excessive sensitivity, saving energy and achieving precise 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 per watt. Suppose the initial heat threshold is 50°C. When the cargo hold is transported next time, several high-power electromechanical devices are added for the construction site. After recalculation, the total equipment power rises to 20000 watts, and the spatial power density becomes 1200÷20000 = 0.06 cubic meters per watt, with the density increasing. At this time, to promptly detect potential overheating risks, the heat threshold is lowered to 40°C. If the subsequent transportation is changed to light building materials and only basic lighting and ventilation equipment are retained, the total power drops to 3000 watts, and the spatial power density becomes 1200÷3000 = 0.4 cubic meters per watt, with the density decreasing, and the heat threshold is then raised to 60°C to avoid frequent activation of the equipment.

[0121] 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 manual setting according to the conditions of different ship's cargo holds. This greatly enhances the self-adaptability of the monitoring system and effectively responds to complex situations such as changes in equipment power and cargo storage layout in the ship's cargo hold. For example, in the cargo hold of a multi-purpose ship that continuously adjusts the cargo types and equipment configurations according to different transportation tasks, the system can automatically adjust the heat threshold according to the change in the spatial power density in real time to ensure the reliable operation of the entire cargo hold monitoring system and provide strong guarantee for the safety of the ship's cargo hold and cargo storage. Whether in the cargo hold scenarios of professional special cargo transport ships or common comprehensive transport ships, this method of adjusting the heat threshold based on the spatial power density demonstrates significant advantages and greatly improves the intelligent level of temperature monitoring and control in the ship's cargo hold.

[0122] A ventilation pipe is provided inside the uniformly distributed target, and the ventilation pipe is connected to an external ventilator; the ventilation pipe is a rigid pipe, or the ventilation pipe is a semi-flexible pipe; the semi-flexible pipe includes a rigid hollow annular or net-shaped support structure, and a ventilation cloth bag covering the hollow parts on the support structure.

[0123] The rigid pipe is usually made of metal or high-strength plastic, has the characteristics of being strong and durable, can withstand a large ventilation pressure, is not easy to deform during long-term use, and ensures the stability of ventilation. For example, in a large grain storage cargo hold, the rigid ventilation pipe can be stably installed inside the mountainous pile of grains, providing reliable ventilation and heat dissipation support for the long-term storage of grains.

[0124] The semi-flexible pipe is a ventilation component with a clever design. It consists of a rigid hollow annular or net-shaped support structure and a ventilation cloth bag covering the hollow parts on the support structure. Taking the annular support structure as an example, it is like a series of closely arranged metal or rigid plastic rings, which are connected to form the basic framework of the semi-flexible pipe, ensuring that the semi-flexible pipe will not collapse due to air flow pressure during ventilation. The ventilation cloth bag is made of a textile material 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-flexible pipe can shuttle flexibly among the goods, meeting the ventilation requirements without damaging the goods.

[0125] The ventilation and heat dissipation method includes the following sub-steps:

[0126] If the uniform temperature exceeds the first threshold, it indicates that the temperature of the goods in the cargo hold has reached the level where heat dissipation intervention is required. At this time, the ventilator works at the first power for the first duration. In actual operation, this process needs to be accurately controlled. For example, in a refrigerated cargo hold transporting fresh fruits and vegetables, when the temperature sensor detects that the uniform temperature inside the fruit and vegetable pile exceeds the first threshold for suitable storage, the ventilator is quickly started and begins to work at the preset first power, continuously transporting the external cold air into the fruit and vegetable pile to take away the heat.

[0127] Moreover, the system will adjust the magnitudes of the first power and the first duration in real time according to the uniform temperature. When the uniform temperature is higher, it means that the heat accumulation of the goods is more serious. 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 a cargo hold transporting easily melted goods such as chocolates, as the ambient temperature rises, the temperature of the goods also gradually increases, and the uniform temperature continues to rise. The power and working duration of the ventilator will increase accordingly to fully ensure the quality of chocolates is not affected by high temperatures. On the contrary, the smaller the uniform temperature, the smaller the first power and the shorter the first duration, to avoid excessive energy consumption.

[0128] Assume that the first threshold is set at 10°C, the default first power of the ventilator is 50%, and the first duration is 30 minutes.

[0129] When the cargo hold monitoring system shows that the uniform temperature reaches 12°C, exceeding the first threshold, the ventilator immediately starts working at 50% power for 30 minutes.

[0130] After a period of time, the uniform temperature rises to 15°C. The system determines that the temperature is too high, increases the first power of the ventilator to 70%, and extends the first duration to 45 minutes to enhance the ventilation and heat dissipation efforts and prevent the fruits and vegetables from rotting due to high temperature.

[0131] After continuous ventilation and cooling, when the uniform temperature drops to 11°C, the first power of the ventilator is reduced to 60%, and the first duration is shortened to 35 minutes to maintain appropriate ventilation and heat dissipation.

[0132] When the temperature drops back to 9°C, below the first threshold, the ventilator stops working until the temperature exceeds the standard again. Such dynamic adjustment ensures that the fruits and vegetables are transported at a suitable temperature.

[0133] Adding ventilation hard pipes and / or hoses to the uniformly distributed goods can achieve good ventilation effects, which is of great benefit to heat dissipation. Installing ventilation pipes inside the uniformly distributed target, whether they are rigid pipes or semi-hoses with both support structures and breathable cloth bags, can directly build ventilation channels inside the goods, enhance air circulation, and accelerate heat dissipation. Compared with traditional external heat dissipation methods, this internal ventilation and heat dissipation is more targeted, can effectively reduce the temperature of the core area of the goods, avoid damage to the goods caused by heat accumulation, greatly improve the heat dissipation efficiency, and ensure the safety of goods storage.

[0134] Adjusting the first power of the ventilator and the first working duration in real time according to the uniform temperature realizes precise heat dissipation control. When the uniform temperature is higher, increase the power and working duration of the ventilator to strengthen the ventilation and heat dissipation effect; when the temperature decreases, reduce the power and duration accordingly to avoid energy waste. This flexible regulation mechanism can not only meet the heat dissipation requirements of the goods under different temperature states but also improve the energy utilization efficiency.

[0135] The semi-hose adopts a rigid hollowed-out ring-shaped or net-shaped support structure with a breathable cloth bag. While ensuring the ventilation effect, compared with fully rigid pipes, it reduces the material cost and installation difficulty. For example, in the cargo holds of some small freight ships, the semi-hose can be more conveniently installed between the goods, reducing the labor and material inputs during the installation process. At the same time, by precisely regulating the working state of the ventilator, unnecessary energy consumption is reduced, further controlling the operating cost, making the entire cargo hold heat dissipation system more economical on the premise of ensuring its functions. In the long-term operation of the cargo hold, this economical and efficient heat dissipation method can save a large amount of costs for enterprises and improve economic benefits.

[0136] The method for adjusting the humidity of the ventilation gas in the ventilation duct includes the following steps:

[0137] First, obtain the humidity parameters in the cargo hold within the first time period. During actual operation, a number of high-precision humidity sensors need to be reasonably distributed in the cargo hold. These sensors can capture the humidity data at different positions in the cargo hold in real time and accurately. For example, in a large river transport cargo hold, in order to comprehensively grasp the humidity situation, humidity sensors are installed at different positions such as the front, middle, rear, top, and bottom of the cargo hold. Every certain period of time, such as 10 minutes, these sensors will transmit the collected humidity data to the central control system, so as to obtain the humidity parameters at each moment and each position within the first time period (assumed to be 1 hour).

[0138] Next, calculate the average humidity in the cargo hold within the first time period. 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 within the first time period are summed up and then divided by the total number of data, so as to obtain the average humidity in the cargo hold during this time period. For example, within 1 hour, a total of 100 humidity data at different times and different positions are received. After adding these data and dividing by 100, the average humidity value is obtained.

[0139] If the average humidity exceeds the set threshold, it indicates that the humidity in the cargo hold has exceeded the suitable 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, there are usually special gas drying devices, such as desiccant adsorption devices or condensation dehumidification devices. The greater the average humidity, the higher the moisture content in the cargo hold. At this time, it is necessary to increase the dryness of the ventilation gas of the ventilator. For example, in a cargo hold transporting traditional Chinese medicine, traditional Chinese medicine is sensitive to humidity, and the suitable humidity range is between 40% - 60%. If the calculated average humidity reaches 70%, exceeding the set threshold of 60%, at this time, it is necessary to increase the dosage of desiccant or enhance the working intensity of the condensation dehumidification device to increase the dryness of the ventilation gas, so that the excess moisture in the cargo hold can be absorbed during the ventilation process. On the contrary, 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%, lower than the set threshold, it is necessary to appropriately reduce the dosage of desiccant or weaken the working intensity of the condensation dehumidification device to prevent the cargo hold from being too dry.

[0140] By obtaining the humidity parameters of the cargo hold within the first duration and calculating the average humidity, and adjusting the dryness degree of the ventilation gas based on the comparison between the average humidity and the set threshold, the humidity in the cargo hold can be effectively controlled. When the average humidity exceeds the set threshold, the dryness degree of the ventilation gas is increased to absorb the excess moisture; when the humidity is low, the dryness degree is reduced to prevent the cargo hold from being too dry, maintaining the stability of the humidity in the cargo hold and avoiding affecting the cargo storage environment due to too high or too low humidity.

[0141] Different goods have different requirements for humidity. Precisely adjusting the humidity of the ventilation gas can meet the storage needs of various goods. Excessive humidity may cause goods to become damp, moldy, and deteriorate. For example, in the cargo hold for transporting food, too high humidity will make biscuits soft and pastries moldy, seriously affecting the taste and safety of food. Too low humidity may cause goods to crack and dehydrate. Like in the cargo hold for transporting solid wood furniture, too low humidity will cause the wood to lose moisture too quickly, resulting in problems such as cracking and deformation of the furniture. Through this technical solution, the ventilation gas can be flexibly adjusted according to the actual humidity in 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.

[0142] Reasonably adjusting the humidity of the ventilation gas avoids the rusting and corrosion of equipment in the cargo hold due to too high humidity, extends the service life of the equipment, and reduces the equipment maintenance and replacement costs. For example, metal ventilation ducts and electrical equipment in the cargo hold are prone to rusting and corrosion in a high-humidity environment, and by controlling the humidity, this situation can be effectively reduced. At the same time, it prevents damage to the electronic components of the equipment caused by static electricity due to too low humidity, ensures the stable operation of the equipment in the cargo hold, and improves the operation efficiency of the entire cargo hold. In a cargo hold equipped with an advanced electronic control system, static electricity generated by too low humidity may interfere with the normal operation of electronic equipment and even damage electronic components, while reasonably adjusting the humidity can avoid these problems and ensure the smooth operation of the entire cargo hold.

[0143] The embodiment of the present application also discloses an intelligent monitoring system for cargo hold working data, including a processor, and the processor executes the steps of the intelligent monitoring method for cargo hold working data as described in any one of the above.

[0144] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to 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; Calculating the variance of the number of pixels, and determining the distribution uniformity of the coordinates corresponding to the plurality of specific features in the cargo hold image according to the variance; If the distribution uniformity is greater than the set uniformity threshold, the specific feature is judged to be a uniformly distributed target; otherwise, it is a non-uniformly distributed 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 the 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.

2. 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.

3. The method for intelligent monitoring of cargo hold working data according to claim 2, 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.

4. The method for intelligently monitoring cargo hold working data according to claim 2, 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.

5. 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: 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.

6. 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.

7. The method for intelligently monitoring cargo hold working data according to claim 6, 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.

8. 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 7 are executed.

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