CN118624820B - Container rapid assessment method and system based on intelligent gas analysis and sniffing - Google Patents
Container rapid assessment method and system based on intelligent gas analysis and sniffing Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000004868 gas analysis Methods 0.000 title claims abstract description 19
- 239000007789 gas Substances 0.000 claims abstract description 167
- 230000005855 radiation Effects 0.000 claims abstract description 136
- 238000011156 evaluation Methods 0.000 claims abstract description 107
- 230000008859 change Effects 0.000 claims abstract description 53
- 238000012544 monitoring process Methods 0.000 claims abstract description 14
- 238000001514 detection method Methods 0.000 claims abstract description 7
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims description 28
- 238000004364 calculation method Methods 0.000 claims description 23
- 230000002159 abnormal effect Effects 0.000 claims description 20
- 239000012855 volatile organic compound Substances 0.000 claims description 17
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 15
- 229910002091 carbon monoxide Inorganic materials 0.000 claims description 15
- 238000010606 normalization Methods 0.000 claims description 15
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 14
- 229910002092 carbon dioxide Inorganic materials 0.000 claims description 14
- 239000001569 carbon dioxide Substances 0.000 claims description 14
- 229910052760 oxygen Inorganic materials 0.000 claims description 14
- 239000001301 oxygen Substances 0.000 claims description 14
- 230000005856 abnormality Effects 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 6
- 230000002547 anomalous effect Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 5
- 230000007423 decrease Effects 0.000 description 7
- 238000009792 diffusion process Methods 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000013450 outlier detection Methods 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 229910021529 ammonia Inorganic materials 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
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- G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
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Abstract
The invention discloses a rapid container assessment method and system based on intelligent gas analysis sniffing, which relates to the technical field of container security assessment, and is characterized in that the gas hazard score is obtained by comprehensively calculating the obtained gas concentration and the gas concentration change rate by monitoring the real-time concentration of various gases in the container and the corresponding gas concentration change rate, the gas pressure and the radiation dose in the container are monitored, and recording an air pressure warning period and a radiation dose warning period, carrying out integral operation on the air pressure warning period and the radiation dose warning period to obtain a radiation fluctuation coefficient, weighting and calculating the radiation fluctuation coefficient and the gas hazard score to obtain an evaluation coefficient of the container, classifying the container according to a comparison result of the evaluation coefficient and an evaluation threshold value, and generating a corresponding management strategy according to the classification result. The evaluation system combines the multi-source data to comprehensively analyze the container and manage the container accordingly, so that the detection effect is improved and the comprehensiveness is evaluated.
Description
Technical Field
The invention relates to the technical field of container safety evaluation, in particular to a container rapid evaluation method and system based on intelligent gas analysis sniffing.
Background
Containers play an important role in global logistics and trade and are widely used for transporting various commodities, including foods, chemicals, electronic products, pharmaceuticals, etc., however, the environment within the container may be affected by various factors, such as changes in temperature and humidity, which may cause deterioration, contamination or other security problems of goods, and thus, real-time monitoring and assessment of the environment within the container becomes particularly important.
The prior art has the following defects:
The existing method for detecting the safety of the container generally uses an X-ray scanner or an infrared thermal imager to detect, firstly, the container needs to be opened for detection, which can cause delay and extra cost of goods, and secondly, if the container is not opened, only the surface or local area of the container can be detected, and the condition inside the container cannot be comprehensively evaluated.
Disclosure of Invention
The invention aims to provide a container rapid assessment method and system based on intelligent gas analysis sniffing so as to solve the defects in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme that the method for rapidly evaluating the container based on intelligent gas analysis sniffing comprises the following steps:
The assessment system acquires container information of the same batch of transportation, marks each container, monitors various gas real-time concentrations and corresponding gas concentration change rates in the container in real time at regular time through a plurality of gas sensors arranged in the container, and comprehensively calculates the acquired various gas concentrations and gas concentration change rates through the edge computing equipment to acquire gas hazard scores;
The evaluation system monitors the air pressure and the radiation dose in the container through the air pressure sensor and the radiation detector respectively, records the air pressure warning period and the radiation dose warning period, and performs integral operation on the air pressure warning period and the radiation dose warning period to obtain a radiation fluctuation coefficient;
And carrying out weighted calculation on the radiation fluctuation coefficient and the gas hazard score to obtain an evaluation coefficient of the container, transmitting the evaluation coefficient to a remote management platform based on a 4G/5G signal, classifying the container by the remote management platform according to a comparison result of the evaluation coefficient and an evaluation threshold value, and generating a corresponding management strategy according to the classification result.
In a preferred embodiment, the evaluation system monitors the real-time concentration of oxygen and the rate of change of concentration of oxygen by an oxygen sensor, the real-time concentration of carbon monoxide and the rate of change of concentration of carbon monoxide by a carbon monoxide sensor, the real-time concentration of carbon dioxide and the rate of change of concentration of carbon dioxide by a carbon dioxide sensor, and the concentration of volatile organic compounds and the rate of change of concentration of volatile organic compounds by a volatile organic compound sensor.
In a preferred embodiment, the gas hazard score is obtained by comprehensively calculating the obtained gas concentrations and the gas concentration change rate by the edge calculating equipment, and the method comprises the following steps of:
The edge computing equipment carries out normalization processing on various gas concentrations and gas concentration change rates, maps various gas concentrations and gas concentration change rate values to be between [0,1] to obtain various gas concentration normalization values and gas concentration change rate normalization values, and adds the various gas concentration normalization values to the gas concentration change rate normalization values to obtain various gas indexes;
Summing the indexes of various gases to obtain a gas hazard score, wherein the function expression is as follows: Where G_index j is the j-th gas index, G_ hazards is the gas hazard score, and m is the number of gas species.
In a preferred embodiment, the recording of the air pressure warning period and the radiation dose warning period comprises the steps of:
comparing the monitored air pressure deviation with a deviation threshold value, comparing the radiation dose with a dose threshold value, judging that the container has leakage or high-pressure risk, and judging that the container has radiation hazard, wherein the radiation dose is larger than the dose threshold value;
The acquisition logic of the air pressure warning period is that the deviation threshold value is multiplied by 0.9 to acquire a warning deviation threshold value, the air pressure acquired in real time is compared with the warning deviation threshold value, and the period of the air pressure larger than the warning deviation threshold value is recorded as the air pressure warning period;
the acquisition logic of the radiation dose warning period is that the dose threshold value is multiplied by 0.9 to acquire the warning dose threshold value, the radiation dose acquired in real time is compared with the warning dose threshold value, and the period of the radiation dose larger than the warning dose threshold value is recorded as the radiation dose warning period.
In a preferred embodiment, the radiation fluctuation coefficient is obtained by integrating the air pressure warning period and the radiation dose warning period, and the method comprises the following steps:
The acquisition logic of the air pressure warning period is that the deviation threshold value is multiplied by 0.9 to acquire a warning deviation threshold value, the air pressure acquired in real time is compared with the warning deviation threshold value, and the period of the air pressure larger than the warning deviation threshold value is recorded as the air pressure warning period;
The acquisition logic of the radiation dose warning period is that the dose threshold value is multiplied by 0.9 to acquire the warning dose threshold value, the radiation dose acquired in real time is compared with the warning dose threshold value, and the period of the radiation dose larger than the warning dose threshold value is recorded as the radiation dose warning period;
and carrying out integral operation on the air pressure warning period and the radiation dose warning period to obtain a radiation fluctuation coefficient, wherein the expression is as follows: FBZ is the radiation fluctuation coefficient, S (t) is the real-time variation of the container radiation level, [ t x,ty ] is the air pressure warning period, [ t i,tj ] is the radiation dose warning period.
In a preferred embodiment, the remote management platform classifies containers according to the comparison result of the evaluation coefficient and the evaluation threshold value, and generates a corresponding management policy according to the classification result, including the following steps:
The evaluation threshold comprises a first gradient threshold and a second gradient threshold, the first gradient threshold is smaller than the second gradient threshold, the acquired evaluation coefficient is compared with the first gradient threshold and the second gradient threshold, the first gradient threshold is used for judging whether the container is abnormal or not, and the second gradient threshold is used for judging the severity of the container abnormality;
If the evaluation coefficient is smaller than or equal to the first gradient threshold value, judging that the container is not abnormal, and dividing the container into a normal set;
if the evaluation coefficient is larger than the first gradient threshold value and smaller than or equal to the second gradient threshold value, judging that the container is slightly abnormal, and dividing the container into a slightly abnormal set;
If the evaluation coefficient is larger than the second gradient threshold value, judging that the container has serious abnormality, and dividing the container into a serious abnormality set;
If at least one container in the same batch of transportation containers is marked into a serious abnormal set, the remote management platform sends out a timely management strategy, and the timely management strategy is that the transportation detection is required to be carried out on the containers in the serious abnormal set;
If all the transport containers in the same batch are marked into a normal set, not managing;
if more than two containers in the same batch of transportation containers are marked into a mild anomaly set, calculating the average evaluation coefficient and the standard deviation of the evaluation coefficient of all the containers in the mild anomaly set;
if the average evaluation coefficient is smaller than or equal to a reference threshold value and the standard deviation of the evaluation coefficient is smaller than or equal to a standard deviation threshold value, analyzing that the whole container in the mild anomaly set has no obvious anomaly, and not managing;
If the average evaluation coefficient is smaller than or equal to the reference threshold value and the standard deviation of the evaluation coefficient is larger than the standard deviation threshold value, analyzing that the container in the mild anomaly set has no obvious anomaly, but has partial container anomaly, sending a management prompt to a manager, and judging whether to manage by the manager;
if the average evaluation coefficient is larger than the reference threshold value and the standard deviation of the evaluation coefficient is larger than the standard deviation threshold value, analyzing that the container in the mild anomaly set is obviously anomaly, but partial containers are not anomaly, and sending out a moderation management strategy;
if the average evaluation coefficient is larger than the reference threshold and the standard deviation of the evaluation coefficient is smaller than or equal to the standard deviation threshold, analyzing that the whole container in the mild anomaly set is obviously anomalous, and sending out an emergency management strategy.
In a preferred embodiment, the logic for obtaining the gas concentration change rate is configured to obtain the initial gas concentration and the final gas concentration at a start time point and an end time point of the monitoring time period through the gas sensor, obtain a concentration difference absolute value by subtracting the initial gas concentration from the final gas concentration, and obtain the gas concentration change rate by comparing the concentration difference absolute value with the monitoring time period.
The intelligent gas analysis sniffing-based container rapid assessment system comprises a container marking module, a gas analysis module, a radiation analysis module, a calculation module and a remote management module;
The container marking module is used for obtaining container information of the same batch of transportation and marking each container;
The gas analysis module is used for monitoring the real-time concentration of various gases in the container and the corresponding gas concentration change rate in real time at regular time through a plurality of gas sensors arranged in the container, wherein the gas sensors comprise an oxygen sensor, a carbon monoxide sensor, a carbon dioxide sensor and a volatile organic compound sensor, and the obtained various gas concentrations and the obtained gas concentration change rate are comprehensively calculated through edge calculation equipment to obtain a gas hazard score;
the radiation analysis module is used for respectively monitoring the air pressure and the radiation dose in the container through the air pressure sensor and the radiation detector, recording an air pressure warning period and a radiation dose warning period, and carrying out integral operation on the air pressure warning period and the radiation dose warning period to obtain a radiation fluctuation coefficient;
the calculation module is used for carrying out weighted calculation on the radiation fluctuation coefficient and the gas hazard score to obtain an evaluation coefficient of the container;
And the remote management module classifies the containers according to the comparison result of the evaluation coefficient and the evaluation threshold value, and generates a corresponding management strategy according to the classification result.
In the technical scheme, the invention has the technical effects and advantages that:
According to the invention, various gas concentrations and corresponding gas concentration change rates in the container are monitored in real time through a plurality of gas sensors arranged in the container, gas hazard scores are obtained through comprehensive calculation of the acquired various gas concentrations and gas concentration change rates through edge calculation equipment, the gas pressure and radiation doses in the container are respectively monitored through the gas pressure sensors and the radiation detectors, the gas pressure warning period and the radiation dose warning period are recorded, the gas pressure warning period and the radiation dose warning period are subjected to integral operation to obtain radiation fluctuation coefficients, the radiation fluctuation coefficients and the gas hazard scores are subjected to weighted calculation to obtain evaluation coefficients of the container, the container is classified by a remote management platform according to comparison results of the evaluation coefficients and evaluation thresholds, and corresponding management strategies are generated according to classification results. The evaluation system combines the multi-source data to comprehensively analyze the container and manage the container accordingly, so that the detection effect is improved and the comprehensiveness is evaluated.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment 1 referring to fig. 1, the method for rapidly evaluating a container based on intelligent gas analysis sniffing in this embodiment includes the following steps:
The method comprises the steps that an evaluation system obtains container information of the same batch of transportation, marks each container, monitors the real-time concentration of various gases in the container and the corresponding gas concentration change rate in real time through a plurality of gas sensors arranged in the container, wherein each gas sensor comprises an oxygen sensor, a carbon monoxide sensor, a carbon dioxide sensor, a Volatile Organic Compound (VOCs) sensor and the like, the obtained various gas concentrations and the obtained gas concentration change rate are comprehensively calculated through edge computing equipment to obtain gas hazard scores, the evaluation system monitors the air pressure and the radiation dose in the container through an air pressure sensor and a radiation detector respectively, records the air pressure warning period and the radiation dose warning period, performs integral operation on the air pressure warning period and the radiation dose warning period to obtain a 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 sends the evaluation coefficient to a remote management platform based on a 4G/5G signal, and the remote management platform classifies the container according to the comparison result of the evaluation coefficient and the evaluation threshold value and generates a corresponding management strategy according to the classification result.
According to the application, various gas concentrations and corresponding gas concentration change rates in the container are monitored in real time through a plurality of gas sensors arranged in the container, gas hazard scores are obtained through comprehensive calculation of the acquired various gas concentrations and gas concentration change rates through edge calculation equipment, the gas pressure and radiation doses in the container are respectively monitored through the gas pressure sensors and the radiation detectors, the gas pressure warning period and the radiation dose warning period are recorded, the gas pressure warning period and the radiation dose warning period are subjected to integral operation to obtain radiation fluctuation coefficients, the radiation fluctuation coefficients and the gas hazard scores are subjected to weighted calculation to obtain evaluation coefficients of the container, the container is classified by a remote management platform according to comparison results of the evaluation coefficients and evaluation thresholds, and corresponding management strategies are generated according to classification results. The evaluation system combines the multi-source data to comprehensively analyze the container and manage the container accordingly, so that the detection effect is improved and the comprehensiveness is evaluated.
Embodiment 2 an assessment system obtains container information for the same batch of transportation and marks each container, comprising the steps of:
The assessment system obtains container information from the same batch through a logistics information system or other data sources, wherein the container information comprises information such as container loading product types, container quantity, shipping names, voyages, start-stop ports, shipping companies and the like, and each container is marked initially, and the marking can be marked by English letters or Arabic numerals.
The timing is through setting up a plurality of gas sensor real-time supervision container inside each kind of gas real-time concentration and corresponding gas concentration change rate, and gas sensor includes oxygen sensor, carbon monoxide sensor, carbon dioxide sensor, volatile Organic Compounds (VOCs) sensor etc. including following step:
The evaluation system monitors the real-time concentration of oxygen and the change rate of the concentration of oxygen through an oxygen sensor, monitors the real-time concentration of carbon monoxide and the change rate of the concentration of carbon monoxide through a carbon monoxide sensor, monitors the real-time concentration of carbon dioxide and the change rate of the concentration of carbon dioxide through a carbon dioxide sensor, and monitors the concentration of volatile organic compounds and the change rate of the concentration of volatile organic compounds through a volatile organic compound sensor;
The acquisition logic of the gas concentration change rate is that the initial gas concentration and the final gas concentration are acquired through the gas sensor at the starting time point and the ending time point of the monitoring time period, the absolute value of the concentration difference value is obtained by subtracting the initial gas concentration from the final gas concentration, and the gas concentration change rate is acquired by comparing the absolute value of the concentration difference value with the monitoring time length.
The edge computing equipment is used for comprehensively computing the obtained gas concentration and the change rate of the gas concentration to obtain the gas hazard score, and the method comprises the following steps:
The edge computing equipment firstly carries out normalization processing on various gas concentrations and gas concentration change rates, maps various gas concentrations and gas concentration change rate values to between [0,1], obtains various gas concentration normalization values and gas concentration change rate normalization values, adds various gas concentration normalization values to gas concentration change rate normalization values to obtain various gas indexes, sums various gas indexes to obtain gas hazard scores, and has the following function expression: Where G_index j is the j-th gas index, G_ hazards is the gas hazard score, and m is the number of gas species.
The greater the gas hazard score, the greater the concentration of one or more gases inside the container and the faster the concentration increase or concentration decrease, indicating that the container may have the following anomalies:
1) Leakage or spillage:
the greater the concentration, the greater the concentration of one or more gases, which may indicate that some material within the container has leaked or overflowed, resulting in a gas concentration that exceeds normal levels;
the faster the increase or decrease, the more the rate of concentration increase or decrease may mean that the severity of the leak or spill is exacerbated, the faster the gas release rate, or the location of the source of the leak has changed;
2) Abnormal goods:
The greater the concentration, the more concentrated the gas may be in the form of volatile matter of some cargo, the more concentrated it may be, which may indicate that the cargo is abnormal or that the storage condition of the cargo is improper;
The faster the concentration increases or decreases, the more likely the cargo changes in state, possibly due to problems such as spoilage, leakage or chemical reactions;
3) Safety risk:
the greater the concentration, the greater the concentration of harmful gases may pose a threat to personnel health, such as carbon monoxide, ammonia, etc., and therefore the presence of high concentrations may lead to increased safety risks;
The faster the increase or decrease, the faster the concentration increase or decrease may result in the gas concentration exceeding safety limits, increasing the risk of personnel poisoning or choking.
The evaluation system monitors the air pressure and the radiation dosage in the container through the air pressure sensor and the radiation detector respectively, and comprises the following steps:
The method comprises the steps that an air pressure sensor periodically collects air pressure data in a container, a radiation detector periodically collects radiation dose data in the container, an evaluation system processes and analyzes the received air pressure data, including data cleaning, outlier detection, data calibration and the like, so as to ensure accuracy and reliability of the data, and similarly processes and analyzes the received radiation dose data, including outlier detection, radiation level calculation, data calibration and the like, so as to obtain accurate radiation dose information, compare the monitored air pressure deviation with a preset deviation threshold value, compare the radiation dose with the preset dose threshold value, judge that the container has leakage or high-pressure risk, judge that the container has radiation damage, and judge that the container has radiation damage;
The difference of the actual air pressure minus the standard air pressure is the air pressure deviation.
Recording an air pressure warning period and a radiation dose warning period, and carrying out integral operation on the air pressure warning period and the radiation dose warning period to obtain a radiation fluctuation coefficient, wherein the method comprises the following steps of:
The acquisition logic of the air pressure warning period is that the deviation threshold value is multiplied by 0.9 to acquire a warning deviation threshold value, the air pressure acquired in real time is compared with the warning deviation threshold value, and the period of the air pressure larger than the warning deviation threshold value is recorded as the air pressure warning period;
the acquisition logic of the radiation dose warning period is that the dose threshold value is multiplied by 0.9 to acquire the warning dose threshold value, the radiation dose acquired in real time is compared with the warning dose threshold value, and the period of the radiation dose larger than the warning dose threshold value is recorded as the radiation dose warning period.
And carrying out integral operation on the air pressure warning period and the radiation dose warning period to obtain a radiation fluctuation coefficient, wherein the expression is as follows: FBZ is a radiation fluctuation coefficient, S (t) is a real-time variation of the radiation level of the container, [ t x,ty ] is a barometric warning period, [ t i,tj ] is a radiation dose warning period;
When there is a radiation source or radiation leak inside the container, this can lead to an elevated radiation level, increasing the radiation dose inside the container. This may be due to increased activity of the radiation source itself, damage or leakage of the radiation source, interaction of the radiation source with other substances, etc.;
Pressure anomalies may cause the rate of gas diffusion inside the container to increase or decrease. When the air pressure is increased, the gas diffusion rate may be increased, accelerating the propagation speed of radiation;
it is assumed that a batch of containers contains radioactive material therein, wherein some of the containers experience radiation source damage, resulting in abnormally elevated radiation levels. At the same time, the pressure inside the container is increased due to the occurrence of pressure abnormality in the transport ship. In this case, the pressure anomaly increases the diffusion rate of the gas inside the container and may cause the gas flow to be blocked, so that the radiation is more easily collected and diffused inside the container, thereby exacerbating the anomaly of the radiation level.
The radiation fluctuation coefficient and the gas hazard score are weighted to obtain an evaluation coefficient of the container, and the evaluation coefficient is sent to a remote management platform based on a 4G/5G signal, and the method comprises the following steps:
E_coeffient=ω 1·G_hazards+ω2.FBZ, wherein E_coeffient is the evaluation coefficient, G_ hazards is the gas hazard score, FBZ is the radiation fluctuation coefficient, ω 1、ω2 is the gas hazard score and the weight of the radiation fluctuation coefficient respectively, ω 1+ω2 =1, and the evaluation coefficient calculated by the edge calculation device is sent to a remote management platform based on 4G/5G signals;
It should be noted that, the evaluation coefficient in the present application is obtained by combining the radiation, the air pressure, the air concentration and the air concentration change rate inside the container, and the larger the evaluation coefficient is, the more serious the overall abnormality of the container is, the more the management should be performed.
The remote management platform classifies containers according to the comparison result of the evaluation coefficient and the evaluation threshold value, and generates a corresponding management strategy according to the classification result, and the method comprises the following steps:
The evaluation threshold comprises a first gradient threshold and a second gradient threshold, the first gradient threshold is smaller than the second gradient threshold, the acquired evaluation coefficient is compared with the first gradient threshold and the second gradient threshold, the first gradient threshold is used for judging whether the container is abnormal or not, and the second gradient threshold is used for judging the severity of the container abnormality;
If the evaluation coefficient is smaller than or equal to the first gradient threshold value, judging that the container is not abnormal, and dividing the container into a normal set;
if the evaluation coefficient is larger than the first gradient threshold value and smaller than or equal to the second gradient threshold value, judging that the container is slightly abnormal, and dividing the container into a slightly abnormal set;
If the evaluation coefficient is larger than the second gradient threshold value, judging that the container has serious abnormality, and dividing the container into a serious abnormality set;
If at least one container in the same batch of transportation containers is marked into a serious abnormal set, the remote management platform sends out a timely management strategy, and the timely management strategy is that the transportation detection is required to be carried out on the containers in the serious abnormal set;
If all the transport containers in the same batch are marked into a normal set, not managing;
if more than two containers in the same batch of transportation containers are marked into a mild anomaly set, calculating the average evaluation coefficient and the standard deviation of the evaluation coefficient of all the containers in the mild anomaly set;
if the average evaluation coefficient is smaller than or equal to a reference threshold value and the standard deviation of the evaluation coefficient is smaller than or equal to a standard deviation threshold value, analyzing that the whole container in the mild anomaly set has no obvious anomaly, and not managing;
if the average evaluation coefficient is smaller than or equal to the reference threshold value and the standard deviation of the evaluation coefficient is larger than the standard deviation threshold value, analyzing that the container in the mild anomaly set has no obvious anomaly, but partial container anomalies exist (namely, the average evaluation coefficient of partial containers is larger than the reference threshold value), sending a management prompt to a manager, and judging whether to manage by the manager;
if the average evaluation coefficient is larger than the reference threshold value and the standard deviation of the evaluation coefficient is larger than the standard deviation threshold value, analyzing that the container in the mild anomaly set is obviously anomaly, but partial containers are not anomaly (namely the average evaluation coefficient of the partial containers is smaller than or equal to the reference threshold value), and sending out a moderation management strategy;
if the average evaluation coefficient is larger than the reference threshold and the standard deviation of the evaluation coefficient is smaller than or equal to the standard deviation threshold, analyzing that the whole container in the mild anomaly set is obviously anomalous, and sending out an emergency management strategy.
Wherein 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.
The calculation expression of the average evaluation coefficient and the standard deviation of the evaluation coefficient is as follows:
wherein n represents the number of containers in the mild anomaly set, n is a positive integer, E_coefficient i represents the evaluation coefficient of the ith container in the mild anomaly set, Representing the average evaluation coefficient.
The embodiment 3 is that the intelligent gas analysis sniffing-based container rapid assessment system comprises a container marking module, a gas analysis module, a radiation analysis module, a calculation module and a remote management module;
The container marking module is used for obtaining container information of the same batch of transportation, marking each container and sending the marking information to the remote management module based on 4G/5G signals;
The gas analysis module is used for monitoring the real-time concentration of various gases in the container and the corresponding gas concentration change rate in real time at regular time through a plurality of gas sensors arranged in the container, wherein the gas sensors comprise an oxygen sensor, a carbon monoxide sensor, a carbon dioxide sensor, a Volatile Organic Compounds (VOCs) sensor and the like, comprehensively calculating the acquired various gas concentrations and the gas concentration change rate through edge computing equipment to acquire gas hazard scores, and transmitting the gas hazard scores to the computing module;
The radiation analysis module is used for respectively monitoring the air pressure and the radiation dose in the container through the air pressure sensor and the radiation detector, recording an air pressure warning period and a radiation dose warning period, carrying out integral operation on the air pressure warning period and the radiation dose warning period to obtain a radiation fluctuation coefficient, and sending the radiation fluctuation coefficient to the calculation module;
the calculation module is used for carrying out weighted calculation on the radiation fluctuation coefficient and the gas hazard score to obtain an evaluation coefficient of the container, and the evaluation coefficient is sent to the remote management module based on the 4G/5G signal;
And the remote management module classifies the containers according to the comparison result of the evaluation coefficient and the evaluation threshold value, and generates a corresponding management strategy according to the classification result.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (4)
1. The intelligent gas analysis sniffing-based container rapid assessment method is characterized by comprising the following steps of:
The assessment system acquires container information of the same batch of transportation, marks each container, monitors various gas real-time concentrations and corresponding gas concentration change rates in the container in real time at regular time through a plurality of gas sensors arranged in the container, and comprehensively calculates the acquired various gas concentrations and gas concentration change rates through the edge computing equipment to acquire gas hazard scores;
The evaluation system monitors the air pressure and the radiation dose in the container through the air pressure sensor and the radiation detector respectively, records the air pressure warning period and the radiation dose warning period, and performs integral operation on the air pressure warning period and the radiation dose warning period to obtain a radiation fluctuation coefficient;
The method comprises the steps that the radiation fluctuation coefficient and the gas hazard score are weighted and calculated to obtain an evaluation coefficient of the container, the evaluation coefficient is sent to a remote management platform based on a 4G/5G signal, the remote management platform classifies the container according to a comparison result of the evaluation coefficient and an evaluation threshold value, and a corresponding management strategy is generated according to the classification result;
the edge computing equipment is used for comprehensively computing the obtained gas concentration and the change rate of the gas concentration to obtain the gas hazard score, and the method comprises the following steps:
The edge computing equipment carries out normalization processing on various gas concentrations and gas concentration change rates, maps various gas concentrations and gas concentration change rate values to be between [0,1] to obtain various gas concentration normalization values and gas concentration change rate normalization values, and adds the various gas concentration normalization values to the gas concentration change rate normalization values to obtain various gas indexes;
Summing the indexes of various gases to obtain a gas hazard score, wherein the function expression is as follows: Wherein G_index j is the j-th class gas index, G_ hazards is the gas hazard score, and m is the number of gas classes;
recording an air pressure warning period and a radiation dose warning period, comprising the following steps:
comparing the monitored air pressure deviation with a deviation threshold value, comparing the radiation dose with a dose threshold value, judging that the container has leakage or high-pressure risk, and judging that the container has radiation hazard, wherein the radiation dose is larger than the dose threshold value;
The acquisition logic of the air pressure warning period is that the deviation threshold value is multiplied by 0.9 to acquire a warning deviation threshold value, the air pressure acquired in real time is compared with the warning deviation threshold value, and the period of the air pressure larger than the warning deviation threshold value is recorded as the air pressure warning period;
The acquisition logic of the radiation dose warning period is that the dose threshold value is multiplied by 0.9 to acquire the warning dose threshold value, the radiation dose acquired in real time is compared with the warning dose threshold value, and the period of the radiation dose larger than the warning dose threshold value is recorded as the radiation dose warning period;
the method for obtaining the radiation fluctuation coefficient by carrying out integral operation on the air pressure warning period and the radiation dose warning period comprises the following steps:
The acquisition logic of the air pressure warning period is that the deviation threshold value is multiplied by 0.9 to acquire a warning deviation threshold value, the air pressure acquired in real time is compared with the warning deviation threshold value, and the period of the air pressure larger than the warning deviation threshold value is recorded as the air pressure warning period;
The acquisition logic of the radiation dose warning period is that the dose threshold value is multiplied by 0.9 to acquire the warning dose threshold value, the radiation dose acquired in real time is compared with the warning dose threshold value, and the period of the radiation dose larger than the warning dose threshold value is recorded as the radiation dose warning period;
and carrying out integral operation on the air pressure warning period and the radiation dose warning period to obtain a radiation fluctuation coefficient, wherein the expression is as follows: FBZ is a radiation fluctuation coefficient, S (t) is a real-time variation of the radiation level of the container, [ t x,ty ] is a barometric warning period, [ t i,tj ] is a radiation dose warning period;
The remote management platform classifies containers according to the comparison result of the evaluation coefficient and the evaluation threshold value, and generates a corresponding management strategy according to the classification result, and the method comprises the following steps:
The evaluation threshold comprises a first gradient threshold and a second gradient threshold, the first gradient threshold is smaller than the second gradient threshold, the acquired evaluation coefficient is compared with the first gradient threshold and the second gradient threshold, the first gradient threshold is used for judging whether the container is abnormal or not, and the second gradient threshold is used for judging the severity of the container abnormality;
If the evaluation coefficient is smaller than or equal to the first gradient threshold value, judging that the container is not abnormal, and dividing the container into a normal set;
if the evaluation coefficient is larger than the first gradient threshold value and smaller than or equal to the second gradient threshold value, judging that the container is slightly abnormal, and dividing the container into a slightly abnormal set;
If the evaluation coefficient is larger than the second gradient threshold value, judging that the container has serious abnormality, and dividing the container into a serious abnormality set;
If at least one container in the same batch of transportation containers is marked into a serious abnormal set, the remote management platform sends out a timely management strategy, and the timely management strategy is that the transportation detection is required to be carried out on the containers in the serious abnormal set;
If all the transport containers in the same batch are marked into a normal set, not managing;
if more than two containers in the same batch of transportation containers are marked into a mild anomaly set, calculating the average evaluation coefficient and the standard deviation of the evaluation coefficient of all the containers in the mild anomaly set;
if the average evaluation coefficient is smaller than or equal to a reference threshold value and the standard deviation of the evaluation coefficient is smaller than or equal to a standard deviation threshold value, analyzing that the whole container in the mild anomaly set has no obvious anomaly, and not managing;
If the average evaluation coefficient is smaller than or equal to the reference threshold value and the standard deviation of the evaluation coefficient is larger than the standard deviation threshold value, analyzing that the container in the mild anomaly set has no obvious anomaly, but has partial container anomaly, sending a management prompt to a manager, and judging whether to manage by the manager;
if the average evaluation coefficient is larger than the reference threshold value and the standard deviation of the evaluation coefficient is larger than the standard deviation threshold value, analyzing that the container in the mild anomaly set is obviously anomaly, but partial containers are not anomaly, and sending out a moderation management strategy;
if the average evaluation coefficient is larger than the reference threshold and the standard deviation of the evaluation coefficient is smaller than or equal to the standard deviation threshold, analyzing that the whole container in the mild anomaly set is obviously anomalous, and sending out an emergency management strategy.
2. The rapid container assessment method based on intelligent gas analysis sniffing according to claim 1, wherein the assessment system monitors the real-time concentration of oxygen and the change rate of the concentration of oxygen through an oxygen sensor, the real-time concentration of carbon monoxide and the change rate of the concentration of carbon monoxide through a carbon monoxide sensor, the real-time concentration of carbon dioxide and the change rate of the concentration of carbon dioxide through a carbon dioxide sensor, and the concentration of volatile organic compounds and the change rate of the concentration of volatile organic compounds through a volatile organic compounds sensor.
3. The method for rapidly evaluating the container based on intelligent gas analysis sniffing according to claim 2, wherein the logic for acquiring the gas concentration change rate is that the initial gas concentration and the final gas concentration are acquired through the gas sensor at the beginning time point and the ending time point of the monitoring time period, the absolute value of the concentration difference value is obtained by subtracting the initial gas concentration from the final gas concentration, and the gas concentration change rate is acquired by comparing the absolute value of the concentration difference value with the monitoring time length.
4. The rapid container assessment system based on intelligent gas analysis sniffing is used for realizing the assessment method according to any one of claims 1-3, and is characterized by comprising a container marking module, a gas analysis module, a radiation analysis module, a calculation module and a remote management module;
The container marking module is used for obtaining container information of the same batch of transportation and marking each container;
The gas analysis module is used for monitoring the real-time concentration of various gases in the container and the corresponding gas concentration change rate in real time at regular time through a plurality of gas sensors arranged in the container, wherein the gas sensors comprise an oxygen sensor, a carbon monoxide sensor, a carbon dioxide sensor and a volatile organic compound sensor, and the obtained various gas concentrations and the obtained gas concentration change rate are comprehensively calculated through edge calculation equipment to obtain a gas hazard score;
the radiation analysis module is used for respectively monitoring the air pressure and the radiation dose in the container through the air pressure sensor and the radiation detector, recording an air pressure warning period and a radiation dose warning period, and carrying out integral operation on the air pressure warning period and the radiation dose warning period to obtain a radiation fluctuation coefficient;
the calculation module is used for carrying out weighted calculation on the radiation fluctuation coefficient and the gas hazard score to obtain an evaluation coefficient of the container;
And the remote management module classifies the containers according to the comparison result of the evaluation coefficient and the evaluation threshold value, and generates a corresponding management strategy according to the classification result.
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| CN117909703B (en) * | 2024-03-18 | 2024-05-31 | 山东省国土空间数据和遥感技术研究院(山东省海域动态监视监测中心) | Data quality evaluation method and system based on alarm threshold trigger |
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| CN1934595A (en) * | 2004-03-24 | 2007-03-21 | 全套海运安全公司 | Method and system for monitoring containers to maintain the security thereof |
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