Container rapid assessment method and system based on intelligent gas analysis and sniffing

Abstract

The present invention discloses a container rapid assessment method and system based on intelligent gas analysis and sniffing, which relates to the technical field of container safety assessment. By monitoring the real-time concentration of various gases inside the container and the corresponding gas concentration change rate, the obtained various gas concentrations and gas concentration change rates are comprehensively calculated to obtain a gas hazard score, the air pressure and radiation dose inside the container are monitored, and the air pressure warning period and the radiation dose warning period are recorded. The air pressure warning period and the radiation dose warning period are integrated to obtain the radiation fluctuation coefficient, and the radiation fluctuation coefficient and the gas hazard score are weighted to obtain the evaluation coefficient of the container. The container is classified according to the comparison result of the evaluation coefficient and the evaluation threshold, and the corresponding management strategy is generated according to the classification result. The evaluation system combines multi-source data to conduct a comprehensive and integrated analysis of the container and conducts corresponding management, thereby improving the detection effect and the comprehensiveness of the evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of container safety assessment, and in particular to a method and system for rapid container assessment based on intelligent gas analysis and sniffing. Background Art

[0002] Containers play an important role in global logistics and trade and are widely used to transport a variety of commodities, including food, chemicals, electronic products, and pharmaceuticals. However, the environment inside the container may be affected by a variety of factors, such as changes in temperature and humidity, which may cause cargo deterioration, contamination, or other safety issues. Therefore, real-time monitoring and evaluation of the environment inside the container becomes particularly important.

[0003] The prior art has the following deficiencies:

[0004] The existing method of conducting safety inspections on containers is usually to use X-ray scanners or infrared thermal imagers. First, the container usually needs to be opened for inspection, which will cause delays and additional costs for the goods. Second, if the container is not opened, only the surface or local areas of the container can be inspected, and the situation inside the container cannot be fully assessed. Summary of the invention

[0005] The purpose of the present invention is to provide a container rapid assessment method and system based on intelligent gas analysis and sniffing to address the deficiencies in the background technology.

[0006] In order to achieve the above object, the present invention provides the following technical solution: a container rapid assessment method based on intelligent gas analysis sniffing, the assessment method comprising the following steps:

[0007] The assessment system obtains information about containers transported in the same batch, marks each container, and regularly monitors the real-time concentration of various gases inside the container and the corresponding gas concentration change rate through several gas sensors installed inside the container. The edge computing device performs a comprehensive calculation on the obtained gas concentrations and gas concentration change rates to obtain a gas hazard score.

[0008] The evaluation system monitors the air pressure and radiation dose inside the container through the air pressure sensor and the radiation detector respectively, and records the air pressure warning period and the radiation dose warning period, and integrates the air pressure warning period and the radiation dose warning period to obtain the radiation fluctuation coefficient;

[0009] The radiation fluctuation coefficient and the gas hazard score are weightedly calculated to obtain the assessment coefficient of the container, which is sent to the remote management platform based on the 4G / 5G signal. The remote management platform classifies the containers based on the comparison results between the assessment coefficient and the assessment threshold, and generates corresponding management strategies based on the classification results.

[0010] In a preferred embodiment, the evaluation system monitors the real-time oxygen concentration and the rate of change of the oxygen concentration through an oxygen sensor, monitors the real-time carbon monoxide concentration and the rate of change of the carbon monoxide concentration through a carbon monoxide sensor, monitors the real-time carbon dioxide concentration and the rate of change of the carbon dioxide concentration through a carbon dioxide sensor, and monitors the volatile organic compound concentration and the rate of change of the volatile organic compound concentration through a volatile organic compound sensor.

[0011] In a preferred embodiment, the gas hazard score is obtained by comprehensively calculating the obtained gas concentrations and gas concentration change rates through an edge computing device, including the following steps:

[0012] The edge computing device first normalizes the concentrations of various gases and the rates of change of gas concentrations, maps the values ​​of the concentrations of various gases and the rates of change of gas concentrations to [0,1], obtains the normalized values ​​of the concentrations of various gases and the normalized values ​​of the rates of change of gas concentrations, and adds the normalized values ​​of the concentrations of various gases to the normalized values ​​of the rates of change of gas concentrations to obtain the indexes of various gases;

[0013] The gas hazard score is obtained by summing up the gas indexes. The function expression is: Where G_index j is the j-th gas index, G_hazards is the gas hazard score, and m is the number of gas types.

[0014] In a preferred embodiment, recording the air pressure warning period and the radiation dose warning period comprises the following steps:

[0015] The monitored air pressure deviation is compared with the deviation threshold, and the radiation dose is compared with the dose threshold. If the air pressure deviation is greater than the deviation threshold, it is judged that there is a risk of leakage or high pressure in the container. If the radiation dose is greater than the dose threshold, it is judged that there is a radiation hazard in the container.

[0016] The logic for obtaining the air pressure warning period is as follows: multiply the deviation threshold by 0.9 to obtain the warning deviation threshold, compare the real-time air pressure with the warning deviation threshold, and record the period when the air pressure is greater than the warning deviation threshold as the air pressure warning period;

[0017] The logic for obtaining the radiation dose warning period is as follows: multiply the dose threshold by 0.9 to obtain the warning dose threshold, compare the radiation dose obtained in real time with the warning dose threshold, and record the period when the radiation dose is greater than the warning dose threshold as the radiation dose warning period.

[0018] In a preferred embodiment, performing an integral operation on the air pressure warning period and the radiation dose warning period to obtain the radiation fluctuation coefficient includes the following steps:

[0019] The logic for obtaining the air pressure warning period is as follows: multiply the deviation threshold by 0.9 to obtain the warning deviation threshold, compare the real-time air pressure with the warning deviation threshold, and record the period when the air pressure is greater than the warning deviation threshold as the air pressure warning period;

[0020] The logic for obtaining the radiation dose warning period is as follows: multiply the dose threshold by 0.9 to obtain the warning dose threshold, compare the radiation dose obtained in real time with the warning dose threshold, and record the period when the radiation dose is greater than the warning dose threshold as the radiation dose warning period;

[0021] The radiation fluctuation coefficient is obtained by integrating the air pressure warning period and the radiation dose warning period. The expression is: FBZ is the radiation fluctuation coefficient, S(t) is the real-time change of the container radiation level, [t x , t y ] is the air pressure warning period, [t i , t j ] is the radiation dose warning period.

[0022] In a preferred embodiment, the remote management platform classifies containers according to the comparison result between the evaluation coefficient and the evaluation threshold, and generates corresponding management strategies according to the classification result, including the following steps:

[0023] The evaluation threshold includes a first gradient threshold and a second gradient threshold, and the first gradient threshold is less than the second gradient threshold. The obtained evaluation coefficient is compared with the first gradient threshold and the second gradient threshold. The first gradient threshold is used to determine whether there is an abnormality in the container, and the second gradient threshold is used to determine the severity of the abnormality in the container.

[0024] If the evaluation coefficient is less than or equal to the first gradient threshold, it is determined that the container is not abnormal and the container is classified into the normal set;

[0025] If the evaluation coefficient is greater than the first gradient threshold and the evaluation coefficient is less than or equal to the second gradient threshold, it is determined that the container is slightly abnormal and the container is classified into the slightly abnormal set;

[0026] If the evaluation coefficient is greater than the second gradient threshold, it is determined that the container is severely abnormal and the container is classified into a severely abnormal set;

[0027] If at least one container in the same batch of transport containers is included in the severe abnormality set, the remote management platform issues a timely management strategy, which requires transshipment inspection of the containers in the severe abnormality set;

[0028] If all the transport containers of the same batch are classified into normal collection, no management will be carried out;

[0029] If there are two or more containers in the same batch of transport containers that are classified into the mild anomaly set, the average evaluation coefficient and standard deviation of the evaluation coefficient of all containers in the mild anomaly set are calculated;

[0030] If the average evaluation coefficient is less than or equal to the benchmark threshold, and the standard deviation of the evaluation coefficient is less than or equal to the standard deviation threshold, it is analyzed that there is no obvious abnormality in the overall container in the mild abnormality set, and no management is performed;

[0031] If the average evaluation coefficient is less than or equal to the benchmark threshold, and the standard deviation of the evaluation coefficient is greater than the standard deviation threshold, it is analyzed that there is no obvious abnormality in the containers in the mild abnormality set, but some containers are abnormal, and a management prompt is sent to the management personnel, who decide whether to manage it;

[0032] If the average evaluation coefficient is greater than the benchmark threshold, and the standard deviation of the evaluation coefficient is greater than the standard deviation threshold, the containers in the slightly abnormal set are analyzed to be obviously abnormal, but some containers are not abnormal, and a mitigation management strategy is issued;

[0033] If the average evaluation coefficient is greater than the benchmark threshold, and the standard deviation of the evaluation coefficient is less than or equal to the standard deviation threshold, the overall container in the mild anomaly set is analyzed for obvious anomalies, and an emergency management strategy is issued.

[0034] In a preferred embodiment, the logic for obtaining the gas concentration change rate is: obtaining the initial gas concentration and the final gas concentration through a gas sensor at the start time point and the end time point of the monitoring time period, and obtaining the absolute value of the concentration difference by subtracting the initial gas concentration from the final gas concentration, and obtaining the gas concentration change rate by dividing the absolute value of the concentration difference by the monitoring time.

[0035] A container rapid assessment system based on intelligent gas analysis and sniffing, including a container marking module, a gas analysis module, a radiation analysis module, a calculation module, and a remote management module;

[0036] Container marking module: obtains container information of the same batch of transportation and marks each container;

[0037] Gas analysis module: The real-time concentration of various gases in the container and the corresponding gas concentration change rate are monitored in real time through several gas sensors installed inside the container. The gas sensors include oxygen sensors, carbon monoxide sensors, carbon dioxide sensors, and volatile organic compound sensors. The edge computing device performs a comprehensive calculation on the obtained gas concentrations and gas concentration change rates to obtain a gas hazard score;

[0038] Radiation analysis module: monitors the air pressure and radiation dose inside the container through air pressure sensors and radiation detectors respectively, records the air pressure warning period and radiation dose warning period, and performs integral calculations on the air pressure warning period and radiation dose warning period to obtain the radiation fluctuation coefficient;

[0039] Calculation module: weighted calculation of radiation fluctuation coefficient and gas hazard score to obtain container assessment coefficient;

[0040] Remote management module: classifies containers based on the comparison results between the evaluation coefficient and the evaluation threshold, and generates corresponding management strategies based on the classification results.

[0041] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0042] The present invention monitors the real-time concentration of various gases and the corresponding gas concentration change rate inside the container in real time by means of several gas sensors arranged inside the container, performs comprehensive calculation on the obtained gas concentrations and gas concentration change rates through edge computing equipment to obtain gas hazard scores, monitors the air pressure and radiation dose inside the container respectively through air pressure sensors and radiation detectors, and records the air pressure warning period and radiation dose warning period, performs integral calculation on the air pressure warning period and radiation dose warning period to obtain the radiation fluctuation coefficient, performs weighted calculation on the radiation fluctuation coefficient and the gas hazard score to obtain the evaluation coefficient of the container, and the remote management platform classifies the container according to the comparison result of the evaluation coefficient and the evaluation threshold, and generates corresponding management strategies according to the classification results. The evaluation system combines multi-source data to conduct comprehensive and integrated analysis of the container and performs corresponding management, thereby improving the detection effect and the comprehensiveness of the evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0044] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Example 1: Please refer to Figure 1 As shown, the container rapid assessment method based on intelligent gas analysis and sniffing described in this embodiment includes the following steps:

[0047] The assessment system obtains the information of containers transported in the same batch and marks each container. It regularly monitors the real-time concentration of various gases inside the container and the corresponding gas concentration change rate through several gas sensors installed inside the container. The gas sensors include oxygen sensors, carbon monoxide sensors, carbon dioxide sensors, volatile organic compounds (VOCs) sensors, etc. The acquired gas concentrations and gas concentration change rates are comprehensively calculated through edge computing devices to obtain the gas hazard score. The assessment system monitors the air pressure and radiation dose inside the container through air pressure sensors and radiation detectors respectively, and records the air pressure warning period and radiation dose warning period. The air pressure warning period and radiation dose warning period are integrated to obtain the radiation fluctuation coefficient. The radiation fluctuation coefficient and the gas hazard score are weighted to obtain the assessment coefficient of the container, and sent to the remote management platform based on the 4G / 5G signal. The remote management platform classifies the containers according to the comparison results between the assessment coefficient and the assessment threshold, and generates corresponding management strategies based on the classification results.

[0048] This application uses several gas sensors installed inside the container to monitor the real-time concentration of various gases inside the container and the corresponding gas concentration change rate in real time. The edge computing device performs a comprehensive calculation of the obtained gas concentrations and gas concentration change rates to obtain a gas hazard score. The air pressure sensor and radiation detector monitor the air pressure and radiation dose inside the container respectively, and record the air pressure warning period and radiation dose warning period. The air pressure warning period and radiation dose warning period are integrated to obtain the radiation fluctuation coefficient. The radiation fluctuation coefficient and the gas hazard score are weighted to obtain the evaluation coefficient of the container. The remote management platform classifies the container based on the comparison result of the evaluation coefficient and the evaluation threshold, and generates a corresponding management strategy based on the classification result. The evaluation system combines multi-source data to conduct a comprehensive and integrated analysis of the container and conducts corresponding management, thereby improving the detection effect and the comprehensiveness of the evaluation.

[0049] Embodiment 2: The evaluation system obtains information of containers transported in the same batch and marks each container, including the following steps:

[0050] The assessment system obtains information about containers shipped in the same batch through the logistics information system or other data sources, including the type of products loaded in the container, the number of containers, the name of the transport ship, the voyage number, the starting and ending ports, the transport company, etc., and initially marks each container. The mark can be in English letters or Arabic numerals.

[0051] The real-time concentration of various gases in the container and the corresponding gas concentration change rate are monitored in real time by several gas sensors installed inside the container. The gas sensors include oxygen sensors, carbon monoxide sensors, carbon dioxide sensors, volatile organic compound (VOCs) sensors, etc., including the following steps:

[0052] The evaluation system monitors the real-time concentration of oxygen and the rate of change of oxygen concentration through an oxygen sensor, monitors the real-time concentration of carbon monoxide and the rate of change of carbon monoxide concentration through a carbon monoxide sensor, monitors the real-time concentration of carbon dioxide and the rate of change of carbon dioxide concentration through a carbon dioxide sensor, and monitors the concentration of volatile organic compounds and the rate of change of volatile organic compound concentration through a volatile organic compound sensor;

[0053] The logic for obtaining the gas concentration change rate is as follows: the initial gas concentration and the final gas concentration are obtained through the gas sensor at the start and end time points of the monitoring period, and the absolute value of the concentration difference is obtained by subtracting the initial gas concentration from the final gas concentration. The gas concentration change rate is obtained by dividing the absolute value of the concentration difference by the monitoring time.

[0054] The gas hazard score is obtained by comprehensively calculating the concentrations of various gases and the gas concentration change rates obtained through edge computing devices, including the following steps:

[0055] The edge computing device first normalizes the concentrations of various gases and the rates of change of gas concentrations, maps the values ​​of the concentrations of various gases and the rates of change of gas concentrations to [0,1], obtains the normalized values ​​of the concentrations of various gases and the normalized values ​​of the rates of change of gas concentrations, adds the normalized values ​​of the concentrations of various gases to the normalized values ​​of the rates of change of gas concentrations to obtain the indexes of various gases, and sums the indexes of various gases to obtain the gas hazard score. The function expression is: Where G_index j is the j-th gas index, G_hazards is the gas hazard score, and m is the number of gas types.

[0056] The higher the gas hazard score, the higher the concentration of one or more gases inside the container, and the faster the concentration increases or decreases, indicating that the container may have the following abnormalities:

[0057] 1) Leakage or spillage:

[0058] Higher concentrations: If the concentration of one or more gases is higher, it may mean that some substances in the container have leaked or spilled, causing the gas concentration to exceed the normal level;

[0059] Faster increase or decrease: An increase in the rate at which concentrations increase or decrease may mean that the severity of the leak or spill is increasing, the gas is being released more rapidly, or the location of the leak source has changed;

[0060] 2) Abnormal cargo:

[0061] The greater the concentration: High concentrations of gas may be volatile substances in certain cargoes, and their increased concentrations may indicate abnormal cargo or improper storage conditions of the cargo;

[0062] The faster the increase or decrease: A rapid increase or decrease in concentration may indicate a change in the state of the cargo, perhaps due to spoilage, leakage or chemical reaction;

[0063] 3) Security risks:

[0064] The greater the concentration: High concentrations of harmful gases may pose a threat to personnel health, such as carbon monoxide and ammonia, so the presence of high concentrations may lead to increased safety risks;

[0065] The faster the increase or decrease: A rapid increase or decrease in concentration may cause the gas concentration to exceed the safe limit, increasing the risk of poisoning or suffocation of personnel.

[0066] The evaluation system monitors the air pressure and radiation dose inside the container through air pressure sensors and radiation detectors, respectively, and includes the following steps:

[0067] The air pressure sensor regularly collects the air pressure data inside the container, and the radiation detector regularly collects the radiation dose data inside the container. The evaluation system processes and analyzes the received air pressure data, including data cleaning, outlier detection, data calibration, etc., to ensure the accuracy and reliability of the data. Similarly, the received radiation dose data is processed and analyzed, including outlier detection, radiation level calculation, data calibration, etc., to obtain accurate radiation dose information, and the monitored air pressure deviation is compared with the preset deviation threshold, and the radiation dose is compared with the preset dose threshold. If the air pressure deviation is greater than the deviation threshold, it is judged that the container has leakage or high pressure risks, and if the radiation dose is greater than the dose threshold, it is judged that the container has radiation hazards;

[0068] The difference between the actual air pressure and the standard air pressure is the air pressure deviation.

[0069] Recording the air pressure warning period and the radiation dose warning period, and performing integral calculation on the air pressure warning period and the radiation dose warning period to obtain the radiation fluctuation coefficient, including the following steps:

[0070] The logic for obtaining the air pressure warning period is as follows: multiply the deviation threshold by 0.9 to obtain the warning deviation threshold, compare the real-time air pressure with the warning deviation threshold, and record the period when the air pressure is greater than the warning deviation threshold as the air pressure warning period;

[0071] The logic for obtaining the radiation dose warning period is as follows: multiply the dose threshold by 0.9 to obtain the warning dose threshold, compare the radiation dose obtained in real time with the warning dose threshold, and record the period when the radiation dose is greater than the warning dose threshold as the radiation dose warning period.

[0072] The radiation fluctuation coefficient is obtained by integrating the air pressure warning period and the radiation dose warning period. The expression is: FBZ is the radiation fluctuation coefficient, S(t) is the real-time change of the container radiation level, [t x , t y ] is the air pressure warning period, [t i , t j ] is the radiation dose warning period;

[0073] When there is a radiation source or radiation leakage inside the container, the radiation level will increase, increasing the radiation dose inside the container. This may be caused by the increased activity of the radiation source itself, damage or leakage of the radiation source, interaction between the radiation source and other substances, etc.

[0074] Abnormal pressure may cause the gas diffusion rate inside the container to increase or decrease. When the air pressure increases, the gas diffusion rate may increase, speeding up the propagation of radiation;

[0075] Suppose a batch of containers contains radioactive materials, and one of the containers has a damaged radiation source, resulting in an abnormally high radiation level. At the same time, due to an abnormal pressure on the transport ship, the air pressure inside the container increases. In this case, the abnormal pressure increases the diffusion rate of the gas inside the container and may cause the gas flow to be blocked, making it easier for radiation to gather and diffuse inside the container, thereby exacerbating the abnormal radiation level.

[0076] The radiation fluctuation coefficient and the gas hazard score are weighted to obtain the container assessment coefficient, which is sent to the remote management platform based on the 4G / 5G signal, including the following steps:

[0077] The evaluation coefficient of the container is obtained by weighted calculation of the radiation fluctuation coefficient and the gas hazard score. The function expression is: E_coefficient = ω1·G_hazards+ω2·FBZ, where E_coefficient is the evaluation coefficient, G_hazards is the gas hazard score, FBZ is the radiation fluctuation coefficient, ω1 and ω2 are the weights of the gas hazard score and the radiation fluctuation coefficient, respectively, and ω1+ω2=1. The evaluation coefficient calculated by the edge computing device is sent to the remote management platform based on the 4G / 5G signal;

[0078] It should be noted that the evaluation coefficient in this application is obtained by combining the radiation, air pressure, gas concentration and gas concentration change rate inside the container. The larger the evaluation coefficient, the more serious the overall abnormality of the container is, and the more management is needed.

[0079] The remote management platform classifies containers based on the comparison results between the evaluation coefficient and the evaluation threshold, and generates corresponding management strategies based on the classification results, including the following steps:

[0080] The evaluation threshold includes a first gradient threshold and a second gradient threshold, and the first gradient threshold is less than the second gradient threshold. The obtained evaluation coefficient is compared with the first gradient threshold and the second gradient threshold. The first gradient threshold is used to determine whether there is an abnormality in the container, and the second gradient threshold is used to determine the severity of the abnormality in the container.

[0081] If the evaluation coefficient is less than or equal to the first gradient threshold, it is determined that the container is not abnormal and the container is classified into the normal set;

[0082] If the evaluation coefficient is greater than the first gradient threshold and the evaluation coefficient is less than or equal to the second gradient threshold, it is determined that the container is slightly abnormal and the container is classified into the slightly abnormal set;

[0083] If the evaluation coefficient is greater than the second gradient threshold, it is determined that the container is severely abnormal and the container is classified into a severely abnormal set;

[0084] If at least one container in the same batch of transport containers is included in the severe abnormality set, the remote management platform issues a timely management strategy, which requires transshipment inspection of the containers in the severe abnormality set;

[0085] If all the transport containers of the same batch are classified into normal collection, no management will be carried out;

[0086] If there are more than two containers in the same batch of transport containers that are classified into the mild anomaly set, the average evaluation coefficient and standard deviation of the evaluation coefficient of all containers in the mild anomaly set are calculated;

[0087] If the average evaluation coefficient is less than or equal to the benchmark threshold, and the standard deviation of the evaluation coefficient is less than or equal to the standard deviation threshold, it is analyzed that there is no obvious abnormality in the overall container in the mild abnormality set, and no management is performed;

[0088] If the average evaluation coefficient is less than or equal to the benchmark threshold, and the standard deviation of the evaluation coefficient is greater than the standard deviation threshold, it is analyzed that there is no obvious abnormality in the containers in the mild abnormality set, but some containers are abnormal (that is, the average evaluation coefficient of some containers is greater than the benchmark threshold), and a management prompt is sent to the management personnel, who decide whether to manage it;

[0089] If the average evaluation coefficient is greater than the benchmark threshold, and the standard deviation of the evaluation coefficient is greater than the standard deviation threshold, the containers in the slightly abnormal set are analyzed to be obviously abnormal, but some containers are not abnormal (that is, the average evaluation coefficient of some containers is less than or equal to the benchmark threshold), and a mitigation management strategy is issued;

[0090] If the average evaluation coefficient is greater than the benchmark threshold, and the standard deviation of the evaluation coefficient is less than or equal to the standard deviation threshold, the overall container in the mild anomaly set is analyzed for obvious anomalies, and an emergency management strategy is issued.

[0091] The first gradient threshold is added to the second gradient threshold to obtain a threshold sum, and the threshold sum is divided by 2 to obtain a reference threshold.

[0092] The calculation expressions of the average evaluation coefficient and the standard deviation of the evaluation coefficient are:

[0093]

[0094] Where n represents the number of containers in the mild anomaly set, n is a positive integer, and E_coefficient i represents the evaluation coefficient of the i-th container in the mild anomaly set, represents the average evaluation coefficient.

[0095] Embodiment 3: The container rapid assessment system based on intelligent gas analysis and sniffing described in this embodiment includes a container marking module, a gas analysis module, a radiation analysis module, a calculation module, and a remote management module;

[0096] Container marking module: obtains container information of the same batch of transportation and marks each container. The marking information is sent to the remote management module based on 4G / 5G signals;

[0097] Gas analysis module: Regularly monitors the real-time concentration of various gases and the corresponding gas concentration change rate inside the container through several gas sensors installed inside the container. The gas sensors include oxygen sensors, carbon monoxide sensors, carbon dioxide sensors, volatile organic compound (VOCs) sensors, etc. The edge computing device performs a comprehensive calculation on the obtained gas concentrations and gas concentration change rates to obtain the gas hazard score, which is sent to the calculation module;

[0098] Radiation analysis module: monitors the air pressure and radiation dose inside the container through air pressure sensors and radiation detectors respectively, and records the air pressure warning period and radiation dose warning period, integrates the air pressure warning period and radiation dose warning period to obtain the radiation fluctuation coefficient, and sends the radiation fluctuation coefficient to the calculation module;

[0099] Calculation module: The radiation fluctuation coefficient and the gas hazard score are weighted to obtain the container's assessment coefficient, which is sent to the remote management module based on the 4G / 5G signal;

[0100] Remote management module: classifies containers based on the comparison results between the evaluation coefficient and the evaluation threshold, and generates corresponding management strategies based on the classification results.

[0101] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0102] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0103] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A container rapid assessment method based on intelligent gas analysis and sniffing, characterized by: The evaluation method comprises the following steps: The assessment system obtains information about containers transported in the same batch, marks each container, and regularly monitors the real-time concentration of various gases inside the container and the corresponding gas concentration change rate through several gas sensors installed inside the container. The edge computing device performs a comprehensive calculation on the obtained gas concentrations and gas concentration change rates to obtain a gas hazard score. The evaluation system monitors the air pressure and radiation dose inside the container through the air pressure sensor and the radiation detector respectively, and records the air pressure warning period and the radiation dose warning period, and integrates the air pressure warning period and the radiation dose warning period to obtain the radiation fluctuation coefficient; The radiation fluctuation coefficient and the gas hazard score are weighted to obtain the container's assessment coefficient, which is sent to the remote management platform based on the 4G / 5G signal. The remote management platform classifies the containers based on the comparison between the assessment coefficient and the assessment threshold, and generates corresponding management strategies based on the classification results. The gas hazard score is obtained by comprehensively calculating the obtained gas concentrations and gas concentration change rates through edge computing devices, including the following steps: The edge computing device first normalizes the concentrations of various gases and the rates of change of gas concentrations, maps the values ​​of the concentrations of various gases and the rates of change of gas concentrations to [0,1], obtains the normalized values ​​of the concentrations of various gases and the normalized values ​​of the rates of change of gas concentrations, and adds the normalized values ​​of the concentrations of various gases to the normalized values ​​of the rates of change of gas concentrations to obtain the indexes of various gases; The gas hazard score is obtained by summing up the gas indexes. The function expression is: Where G_index j is the jth gas index, G_hazards is the gas hazard score, and m is the number of gas types; Recording the air pressure warning period and the radiation dose warning period includes the following steps: The monitored air pressure deviation is compared with the deviation threshold, and the radiation dose is compared with the dose threshold. If the air pressure deviation is greater than the deviation threshold, it is judged that there is a risk of leakage or high pressure in the container. If the radiation dose is greater than the dose threshold, it is judged that there is a radiation hazard in the container. The logic for obtaining the air pressure warning period is as follows: multiply the deviation threshold by 0.9 to obtain the warning deviation threshold, compare the real-time air pressure with the warning deviation threshold, and record the period when the air pressure is greater than the warning deviation threshold as the air pressure warning period; The logic for obtaining the radiation dose warning period is as follows: multiply the dose threshold by 0.9 to obtain the warning dose threshold, compare the radiation dose obtained in real time with the warning dose threshold, and record the period when the radiation dose is greater than the warning dose threshold as the radiation dose warning period; Integrating the air pressure warning period and the radiation dose warning period to obtain the radiation fluctuation coefficient includes the following steps: The logic for obtaining the air pressure warning period is as follows: multiply the deviation threshold by 0.9 to obtain the warning deviation threshold, compare the real-time air pressure with the warning deviation threshold, and record the period when the air pressure is greater than the warning deviation threshold as the air pressure warning period; The logic for obtaining the radiation dose warning period is as follows: multiply the dose threshold by 0.9 to obtain the warning dose threshold, compare the radiation dose obtained in real time with the warning dose threshold, and record the period when the radiation dose is greater than the warning dose threshold as the radiation dose warning period; The radiation fluctuation coefficient is obtained by integrating the air pressure warning period and the radiation dose warning period. The expression is: FBZ is the radiation fluctuation coefficient, S(t) is the real-time change of the container radiation level, [t x , t y ] is the air pressure warning period, [t i , t j ] is the radiation dose warning period; The remote management platform classifies containers based on the comparison results between the evaluation coefficient and the evaluation threshold, and generates corresponding management strategies based on the classification results, including the following steps: The evaluation threshold includes a first gradient threshold and a second gradient threshold, and the first gradient threshold is less than the second gradient threshold. The obtained evaluation coefficient is compared with the first gradient threshold and the second gradient threshold. The first gradient threshold is used to determine whether there is an abnormality in the container, and the second gradient threshold is used to determine the severity of the abnormality in the container. If the evaluation coefficient is less than or equal to the first gradient threshold, it is determined that the container is not abnormal and the container is classified into the normal set; If the evaluation coefficient is greater than the first gradient threshold and the evaluation coefficient is less than or equal to the second gradient threshold, it is determined that the container is slightly abnormal and the container is classified into the slightly abnormal set; If the evaluation coefficient is greater than the second gradient threshold, it is determined that the container is severely abnormal and the container is classified into a severely abnormal set; If at least one container in the same batch of transport containers is included in the severe abnormality set, the remote management platform issues a timely management strategy, which requires transshipment inspection of the containers in the severe abnormality set; If all the transport containers of the same batch are classified into normal collection, no management will be carried out; If there are more than two containers in the same batch of transport containers that are classified into the mild anomaly set, the average evaluation coefficient and standard deviation of the evaluation coefficient of all containers in the mild anomaly set are calculated; If the average evaluation coefficient is less than or equal to the benchmark threshold, and the standard deviation of the evaluation coefficient is less than or equal to the standard deviation threshold, it is analyzed that there is no obvious abnormality in the overall container in the mild abnormality set, and no management is performed; If the average evaluation coefficient is less than or equal to the benchmark threshold, and the standard deviation of the evaluation coefficient is greater than the standard deviation threshold, it is analyzed that there is no obvious abnormality in the containers in the mild abnormality set, but some containers are abnormal, and a management prompt is sent to the management personnel, who decide whether to manage it; If the average evaluation coefficient is greater than the benchmark threshold, and the standard deviation of the evaluation coefficient is greater than the standard deviation threshold, the containers in the slightly abnormal set are analyzed to be obviously abnormal, but some containers are not abnormal, and a mitigation management strategy is issued; If the average evaluation coefficient is greater than the benchmark threshold, and the standard deviation of the evaluation coefficient is less than or equal to the standard deviation threshold, the overall container in the mild anomaly set is analyzed for obvious anomalies, and an emergency management strategy is issued.

2. The container rapid assessment method based on intelligent gas analysis and sniffing according to claim 1 is characterized by: The evaluation system monitors the real-time oxygen concentration and the rate of change of the oxygen concentration through an oxygen sensor, monitors the real-time carbon monoxide concentration and the rate of change of the carbon monoxide concentration through a carbon monoxide sensor, monitors the real-time carbon dioxide concentration and the rate of change of the carbon dioxide concentration through a carbon dioxide sensor, and monitors the volatile organic compound concentration and the rate of change of the volatile organic compound concentration through a volatile organic compound sensor.

3. The container rapid assessment method based on intelligent gas analysis and sniffing according to claim 2 is characterized by: The logic for obtaining the gas concentration change rate is as follows: the initial gas concentration and the final gas concentration are obtained through the gas sensor at the start time point and the end time point of the monitoring time period, and the absolute value of the concentration difference is obtained by subtracting the initial gas concentration from the final gas concentration, and the gas concentration change rate is obtained by dividing the absolute value of the concentration difference by the monitoring time.

4. A container rapid assessment system based on intelligent gas analysis and sniffing, used to implement the assessment method according to any one of claims 1 to 3, characterized in that: It includes container marking module, gas analysis module, radiation analysis module, calculation module and remote management module; Container marking module: obtains container information of the same batch of transportation and marks each container; Gas analysis module: The real-time concentration of various gases in the container and the corresponding gas concentration change rate are monitored in real time through several gas sensors installed inside the container. The gas sensors include oxygen sensors, carbon monoxide sensors, carbon dioxide sensors, and volatile organic compound sensors. The edge computing device performs a comprehensive calculation on the obtained gas concentrations and gas concentration change rates to obtain a gas hazard score; Radiation analysis module: monitors the air pressure and radiation dose inside the container through air pressure sensors and radiation detectors respectively, records the air pressure warning period and radiation dose warning period, and performs integral calculations on the air pressure warning period and radiation dose warning period to obtain the radiation fluctuation coefficient; Calculation module: weighted calculation of radiation fluctuation coefficient and gas hazard score to obtain container assessment coefficient; Remote management module: classifies containers based on the comparison results between the evaluation coefficient and the evaluation threshold, and generates corresponding management strategies based on the classification results.

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