WO2017041563A1 - 放射源检测方法和系统 - Google Patents

放射源检测方法和系统 Download PDF

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Publication number
WO2017041563A1
WO2017041563A1 PCT/CN2016/086138 CN2016086138W WO2017041563A1 WO 2017041563 A1 WO2017041563 A1 WO 2017041563A1 CN 2016086138 W CN2016086138 W CN 2016086138W WO 2017041563 A1 WO2017041563 A1 WO 2017041563A1
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Prior art keywords
count rate
rate curve
pattern recognition
detection
detection object
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PCT/CN2016/086138
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English (en)
French (fr)
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赵琨
王强
张阳天
彭华
李元景
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同方威视技术股份有限公司
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Priority to CA2981201A priority Critical patent/CA2981201C/en
Priority to EP16843501.4A priority patent/EP3349046B1/en
Priority to MX2017012584A priority patent/MX2017012584A/es
Publication of WO2017041563A1 publication Critical patent/WO2017041563A1/zh
Priority to US15/720,639 priority patent/US10585050B2/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
    • G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
    • G01T1/16—Measuring radiation intensity
    • G01T1/167—Measuring radioactive content of objects, e.g. contamination
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V5/00—Prospecting or detecting by the use of ionising radiation, e.g. of natural or induced radioactivity
    • G01V5/20—Detecting prohibited goods, e.g. weapons, explosives, hazardous substances, contraband or smuggled objects
    • G01V5/26—Passive interrogation, i.e. by measuring radiation emitted by objects or goods

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  • the present disclosure relates to the field of radioactive source detection, and in particular to a radioactive source detection method and system.
  • the radioactive source detection system (for example, the portal mobile radioactive source detection system) is a device for preventing the smuggling and illegal carrying of radioactive materials, and plays an increasingly important role in customs, quality inspection and other fields.
  • people have also put forward higher requirements.
  • an urgent problem to be solved in such equipment is that during the use of the equipment, innocent alarms caused by natural radioactive materials (such as fertilizers, bananas, ceramics, marble, etc.) often occur, and such alarms are all alarmed.
  • the proportion of events is quite large. In the absence of any measures, this will increase the workload for the staff (especially in the ports with higher throughput), and the efficiency of the passage will be greatly reduced.
  • the present disclosure proposes a radiation source detecting method and system.
  • a radiation source detecting method comprising: measuring, by a detector, a count rate curve of a detected object when the detecting object moves through the detector; pattern recognition of the count rate curve; As a result of the pattern recognition, determining whether the detection object contains a radioactive source, And if the source is included, determine the type of source.
  • the method further comprises: determining whether the movement of the detection object satisfies a predetermined condition, and if the movement of the detection object does not satisfy the predetermined condition, moving the detection object back through the detector and re-executing The measurement, pattern recognition, and determined operations.
  • the predetermined condition is that the detection object does not stay during the movement or the minimum movement speed is higher than the threshold speed.
  • the pattern recognition of the count rate curve comprises: calculating a mathematical characteristic of the count rate curve; and performing pattern recognition according to the calculated result.
  • the pattern recognition comprises: pattern matching with a plurality of patterns determined in advance.
  • the mathematical characteristic is the kurtosis of the curve or the magnitude of the decrease across the maximum of the curve.
  • the count rate curve is a count rate curve from which the background mean has been removed.
  • the method further comprises the step of performing pattern recognition on the count rate curve only if the maximum count rate value in the count rate curve of the detection object is higher than an alarm threshold.
  • a radioactive source detecting system comprising: a detector for detecting a detected object passing therethrough; a processor coupled to the detector, and configured to perform The following operations:
  • the processor is further configured to: determine whether the movement of the detection object satisfies a predetermined condition, and if the movement of the detection object does not satisfy the predetermined condition, move the detection object back through the detection And perform the operations of detection, pattern recognition and determination.
  • the predetermined condition is that the detection object does not stay during the movement or the minimum movement speed is higher than the threshold speed.
  • the operation of pattern recognition of the count rate curve comprises: calculating a mathematical characteristic of the count rate curve; and performing pattern recognition according to the result of the calculation.
  • the pattern recognition comprises: pattern matching with a plurality of patterns determined in advance.
  • the mathematical characteristic is the kurtosis of the curve or the magnitude of the decrease across the maximum of the curve.
  • the count rate curve is a count rate curve from which the background mean has been removed.
  • the processor is further configured to perform the step of pattern recognition of the count rate curve only if the maximum count rate value in the count rate curve of the detected object is higher than an alarm threshold.
  • the present disclosure proposes a radioactive source detection system and a square for the law of the change of the counting rate during the detection process.
  • the method can effectively judge the type of radioactive source (point-like radioactive source or bulk radioactive source), reduce the number of false alarms caused by natural radioactive materials, and improve work efficiency.
  • This technology is applicable to locations where gantry vehicle radioactive material detection systems are installed, such as customs ports.
  • Figure 1 is a schematic illustration of a typical gantry mobile radioactive source detection system.
  • Fig. 2 is a view showing the shape of a count rate curve of a natural radioactive substance during the detection.
  • Fig. 3 is a view showing the shape of the count rate curve of the artificial radiation source (point source) during the detection.
  • Figure 4 shows an example plot of the shape of the count rate curve in various cases in which an alarm is raised.
  • FIG. 5 is a view showing an example of a shape of a count rate curve after removing a background mean value corresponding to each example in FIG. 4.
  • FIG. 5 is a view showing an example of a shape of a count rate curve after removing a background mean value corresponding to each example in FIG. 4.
  • FIG. 6 is a flowchart of a radiation source detecting method according to an embodiment of the present disclosure.
  • FIG. 7 is a structural block diagram of a radiation source detecting system according to an embodiment of the present disclosure.
  • FIG. 8 shows an example of an actual radiation detection flow using an embodiment of the present disclosure.
  • FIG. 1 is a schematic illustration of a typical gantry mobile radioactive source detection system.
  • the detection system has detectors (ie, two detection columns standing on each side of the channel), and the detection object passes through the channel between the two columns to realize detection of the radioactive substance.
  • the movement of the detection object can be realized in various ways.
  • the detection system may be a system for detecting a vehicle such that the detection object passes through it in an on-board manner, for example, the detection object is preferably a container.
  • the description of the detection of the in-vehicle detection object is taken as an example in FIG. It should be understood by those skilled in the art that, for different usage scenarios, the detection object may also be passed through a channel between two detection columns, such as a conveyor belt, a slide, a ship, or the like.
  • the count rate is the number of pulses that the detector receives during unit time due to the radiation of the radioactive material.
  • the count rate reflects the radiation intensity.
  • Fig. 2 is a view showing the shape of a count rate curve of a natural radioactive substance during the detection.
  • Figure 3 shows A schematic diagram of the shape of the count rate curve of the artificial radiation source (point source) during the detection process.
  • the count rate curve has the following rules:
  • the curve reflects the background mean level before the front of the vehicle enters the passage
  • the counting rate drops because the front end forms an occlusion on the detector
  • the count rate will rise when the gap passes over the front of the detector (if there is no significant gap between the front and the body, it will not rise);
  • the counting rate drops again (if it has risen before), the extent of the drop is determined by the type and amount of goods loaded on the car, usually between 10% and 30%, and the fluctuation is relatively flat;
  • the count rate After the vehicle leaves the channel, the count rate returns to the background level.
  • FIG. 4 shows an example plot of the shape of the count rate curve for various situations in which an alarm is raised.
  • FIG. 5 is a view showing an example of a shape of a count rate curve after removing a background mean value corresponding to each example in FIG. 4.
  • FIG. The shape of the count rate curve is typically a combination of one or several of the several examples shown in Figures 4 and 5.
  • FIG. 6 is a flow chart of a radiation source detection method 600 in accordance with an embodiment of the present disclosure.
  • the method 600 begins in step S610, when the detection object moves through the detector, the count rate curve of the detection object is measured by the detector; then, in step S620, the count rate curve is pattern-recognized; finally, in step S630 And determining, according to the result of the pattern recognition, whether the detection object contains a radiation source, and if the radiation source is included, determining the type of the radiation source.
  • step S610 when the detection object moves through the detector, the count rate curve of the detection object is measured by the detector.
  • the "counting rate curve of the detection object” refers to a curve formed by the count rate detected on the detector during the detection of the detection object. Generally, the detection starts from the detection range in which the detection object is about to enter the detector, until the detection object just leaves the detection range of the detector. It will be understood by those skilled in the art that other time points can be set as long as the detection can reflect the complete radiation characteristics of the detected object. Just fine.
  • step S620 pattern recognition is performed on the count rate curve.
  • the count rate curves of the point source and the body source have obvious shape differences.
  • the pattern recognition method it can be determined whether or not the obtained count rate curve has a partial line shape corresponding to a typical spike-like curve of the point source.
  • the pattern recognition comprises: pattern matching with a plurality of patterns determined in advance.
  • the predetermined plurality of modes may be as shown in FIG.
  • performing the pattern recognition step on the count rate curve includes calculating a mathematical characteristic of the count rate curve; and performing pattern recognition based on the calculated result. For example, it is possible to determine whether there is a spike according to the magnitude of the decrease in the count on both sides of the maximum count rate value. Alternatively, whether or not there is a spike can be determined by calculating whether the kurtosis of the statistic exceeds a certain threshold. Among them, kurtosis refers to the ratio of the fourth-order central moment of the random variable to the square of the variance.
  • the count rate curve may be a count rate curve from which the background mean has been removed.
  • the level of background mean is shown in Figure 4.
  • the portion of the count rate curve that exceeds the background mean can be intercepted for analysis (as shown in Figure 5).
  • step S630 based on the result of the pattern recognition, it is determined whether the detection target contains a radiation source, and if the radiation source is included, the type of the radiation source is determined.
  • this step it may be determined based on the pattern recognition that the measured count rate curve matches the count rate curve of the type of the radioactive source, and thereby determines whether the detected object contains the radioactive source and may be in the case of containing the radioactive source. Determine the type of radioactive source.
  • the method further comprises the step of performing pattern recognition on the count rate curve only if the maximum count rate value in the count rate curve of the detection object is higher than an alarm threshold. In this case, if the maximum count rate value in the detected count rate curve does not exceed the alarm threshold, it is considered that the detected object does not contain enough suspicious point source, which may not be taken into account.
  • FIG. 7 shows a block diagram of a structure of a radiation source detection system 700 in accordance with an embodiment of the present disclosure.
  • System 700 includes a detector 710 and a processor 720.
  • the detector 710 is configured to detect a detection object passing therethrough.
  • the processor 720 is connected to the detector 710, and is configured to perform an operation of: obtaining a count rate curve of the detection object according to a detection result of the detector; performing pattern recognition on the count rate curve; As a result of the pattern recognition, it is determined whether the detection object contains a radiation source, and if the radiation source is included, the type of the radiation source is determined.
  • the operations performed by the processor 720 of the source detection system 700 correspond to the source detection method 600 described above.
  • the specific description and explanation of the method 600 is also applicable to the processor 720, and details are not described herein again.
  • FIG. 8 illustrates an example of an actual customs emissions detection process employing an embodiment of the present disclosure.
  • S820 Determine whether the vehicle has paused in the passage. If there is a pause, go to S860 for further inspection (or re-synchronize through the detection channel); if there is no pause, go to S830.
  • a threshold value needs to be set in advance, and once the counting rate caused by natural radioactive substances exceeds this threshold, Then go to S860 for further inspection; if it does not exceed this threshold, go to S850.
  • each vehicle has a corresponding customs declaration, and the customs customs officer can make a decision on whether to release the goods according to the cargo information of the customs declaration and the type information of the radioactive source.

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Abstract

一种放射源检测方法（600）和系统（700），包括检测器（710）和处理器（720），在检测对象移动通过检测器（710）时，由检测器（710）测量检测对象的计数率曲线（S610），对计数率曲线进行模式识别（S620），根据模式识别（S620）的结果，确定检测对象中是否含有放射源，以及如果含有放射源的话，确定放射源的种类（S630）。通过对计数率曲线进行模式识别（S620），降低因天然放射线物质引起的误报警次数，提高工作效率。

Description

放射源检测方法和系统 技术领域
本公开涉及放射源检测领域，具体涉及一种放射源检测方法和系统。
背景技术
放射源检测系统(比如，门式移动放射源检测系统)是一种用于防范放射性物质走私和非法携带的设备，在海关、质检等领域发挥着越来越重要的作用。随着这种设备的普及和大量使用，人们对其也提出了更高的要求。比如，这种设备的一个亟待解决的问题是，在设备使用过程中，经常会出现因天然放射性物质(如化肥、香蕉、陶瓷、大理石等)引起的无害报警，并且这种报警在全部报警事件中所占的比例相当大。在不采取任何措施的情况下，这会给工作人员(尤其是在吞吐量较高的港口)增加许多工作量，通行的效率也会因此大大下降。
为了降低这种报警对港口运营带来的负面影响，有人提出了通过人工观察计数率曲线形状来判断放射源类型(有害源或无害源)的方案，并应用于设备数量众多的大型港口，从一定程度上改善了通关效率。
然而，尽管通过人工看图的方法可以在一定程度上解决上述问题，但是要实施这种方案，不仅需要对看图员进行深入细致的培训，而且还要求看图员在工作过程中时时刻刻精力集中，这些对于用户来说都是不小的负担。以中国海关为例，海关关员每隔一段时间都要进行轮岗，这就意味着进行新一轮的培训，而且轮岗前的看图员积累的经验也将付之东流。另外，看图员的工作时间较长，很难保证在全部工作时间内全神贯注，如果增加岗位轮换看图，那么这也会变相给海关增加负担。
发明内容
为了解决传统方法中存在的至少一个上述问题，本公开提出了一种放射源检测方法和系统。
根据本公开的一个方面，提出了一种放射源检测方法，包括：在检测对象移动通过检测器时，由检测器测量检测对象的计数率曲线；对所述计数率曲线进行模式识别；以及根据所述模式识别的结果，确定所述检测对象中是否含有放射源， 以及如果含有放射源的话，确定放射源的种类。
优选地，所述方法还包括：判断所述检测对象的移动是否满足预定条件，以及如果所述检测对象的移动不满足所述预定条件，则使检测对象重新移动通过检测器，并重新进行所述测量、模式识别和确定的操作。
优选地，所述预定条件是：所述检测对象在移动过程中没有停留过或最低移动速度高于阈值速度。
优选地，所述对所述计数率曲线进行模式识别包括：计算所述计数率曲线的数学特性；以及根据所述计算的结果进行模式识别。
优选地，所述模式识别包括：与预先确定的多种模式进行模式匹配。
优选地，所述数学特性是曲线的峰度或曲线最大值两侧的下降幅度。
优选地，所述计数率曲线是已经去除了本底均值的计数率曲线。
优选地，所述方法还包括：只有在所述检测对象的计数率曲线中的最大计数率值高于报警阈值的情况下，才执行对所述计数率曲线进行模式识别的步骤。
根据本公开的另一方面，还提出了一种放射源检测系统，包括：检测器，用于对从其间通过的检测对象进行检测；处理器，连接到所述检测器，并且被配置为执行以下操作：
优选地，所述处理器还被配置为执行以下操作：判断所述检测对象的移动是否满足预定条件，以及如果所述检测对象的移动不满足所述预定条件，则使检测对象重新移动通过检测器，并重新进行所述检测、模式识别和确定的操作。
优选地，所述预定条件是：所述检测对象在移动过程中没有停留过或最低移动速度高于阈值速度。
优选地，所述对所述计数率曲线进行模式识别的操作包括：计算所述计数率曲线的数学特性；以及根据所述计算的结果进行模式识别。
优选地，所述模式识别包括：与预先确定的多种模式进行模式匹配。
优选地，所述数学特性是曲线的峰度或曲线最大值两侧的下降幅度。
优选地，所述计数率曲线是已经去除了本底均值的计数率曲线。
优选地，所述处理器还被配置为：只有在所述检测对象的计数率曲线中的最大计数率值高于报警阈值的情况下，才执行对所述计数率曲线进行模式识别的步骤。
本公开针对检测过程中计数率的变化的规律，提出了放射源检测系统和方 法，从而能够有效地判断放射源的类型(点状放射源或体放射源)，降低因天然放射性物质引起的误报警次数，提高工作效率。该技术适用于安装有门式车辆放射性物质检测系统的地点，如海关口岸等。
附图说明
图1是典型的门式移动放射源检测系统的示意图。
图2示出了天然放射性物质在检测过程中的计数率曲线形状示意图。
图3示出了人工放射源(点状放射源)在检测过程中的计数率曲线形状示意图。
图4列出了引发了报警的多种情况中计数率曲线形状的示例图。
图5是与图4中的各个示例相对应的去除本底均值之后的计数率曲线形状示例图。
图6是根据本公开的实施例的放射源检测方法的流程图。
图7是根据本公开的实施例的放射源检测系统的结构框图。
图8示出了采用本公开的实施例的实际放射物检测流程示例。
具体实施方式
以下参考附图对本公开进行具体描述。
首先，参照图1-4对典型的门式移动放射物检测过程进行描述。
图1是典型的门式移动放射源检测系统的示意图。检测系统具有检测器(即，分别立于通道两侧的两个探测立柱)，检测对象从两个立柱之间的通道通过，以实现对放射性物质的检测。其中，检测对象的移动可以通过多种方式来实现。比如，所述检测系统可以是对车辆进行检测的系统，从而检测对象以车载的方式从中通过，例如所述检测对象优选为集装箱。图1中采用对车载检测对象进行检测作为示例进行的描述。本领域技术人员应当理解的是，针对不同的使用场景，还可以通过其它方式来使所述检测对象从两个探测立柱之间的通道通过，比如传送带、滑道、船舶等。
计数率是由于放射性物质的辐射导致检测器在单位时间内接收到的脉冲数。计数率反映辐射强度。
图2示出了天然放射性物质在检测过程中的计数率曲线形状示意图。图3示 出了人工放射源(点状放射源)在检测过程中的计数率曲线形状示意图。一般而言，计数率曲线具有如下规律：
-车头进入通道前，曲线反映本底均值水平；
-车头进入通道后，计数率下降，这是由于车头对检测器形成了遮挡；
-如果车头和车身之间的间距较大，形成一个较大的空隙，那么当这个空隙经过检测器正面时，计数率上升(如果车头和车身之间没有明显的间隔，则不会上升)；
-车身进入通道时，计数率再次下降(若之前已上升)，下降的幅度由车上所装货物的种类和多少决定，通常在10％～30％之间，且波动较平缓；
-车辆离开通道后，计数率恢复到本底水平。
此外，通过图2与图3的比较可以看出，由点状放射源和体放射源所产生的计数率曲线的形状差异十分明显，其中点状放射源的计数率曲线呈尖峰状，而体放射源的计数率曲线则平缓的多(平缓程度取决于体放射源的分布均匀程度)。
在车辆通过检测通道的过程中，如果计数率在某一时刻超过了报警阈值，则会引发报警。图4列出了引发报警的多种情况中计数率曲线形状的示例图。图5是与图4中的各个示例相对应的去除本底均值之后的计数率曲线形状示例图。计数率曲线的形状通常是如图4和图5所示的几种示例中的一种或几种的组合。
在此基础上，以下结合图6对根据本公开的实施例的一种放射源检测方法进行描述。
图6是根据本公开的实施例的放射源检测方法600的流程图。所述方法600开始于步骤S610，在检测对象移动通过检测器时，由检测器测量检测对象的计数率曲线；然后，在步骤S620，对所述计数率曲线进行模式识别；最后，在步骤S630，根据所述模式识别的结果，确定所述检测对象中是否含有放射源，以及如果含有放射源的话，确定放射源的种类。
在步骤S610中，在检测对象移动通过检测器时，由检测器测量检测对象的计数率曲线。
“检测对象的计数率曲线”指的是在对检测对象进行检测期间，在检测器上所检测到的计数率形成的曲线。一般地，所述检测从检测对象即将进入检测器的检测范围开始，到检测对象刚好离开检测器的检测范围为止。本领域技术人员理解的是，还可设置其它的时间点，只要检测能够反映出检测对象的完整放射特性 即可。
在步骤S620中，对所述计数率曲线进行模式识别。
通过图2-4可见，点状放射源与体放射源的计数率曲线有着明显的形状差异。通过模式识别方法，可以确定所得到的计数率曲线中是否具有与点状放射源典型尖峰状曲线相符的部分线形。
优选地，所述模式识别包括：与预先确定的多种模式进行模式匹配。举例来讲，所述预先确定的多种模式可如图4所示。
在一种实施例中，对所述计数率曲线进行模式识别步骤包括：计算所述计数率曲线的数学特性；以及根据所述计算的结果进行模式识别。举例来讲，可以根据最大计数率值两侧的计数的下降幅度来判断是否存在尖峰。备选地，可通过计算统计量的峰度是否超过一定阈值来判断是否存在尖峰。其中，峰度(kurtosis)是指随机变量的四阶中心矩与方差平方的比值。
优选地，所述计数率曲线可以是已经去除了本底均值的计数率曲线。在图4中示出了本底均值的水平。为了降低模式识别的复杂度并提高准确率，可以将计数率曲线中超出本底均值的部分截取出来进行分析(如图5所示)。
在步骤S630中，根据所述模式识别的结果，确定所述检测对象中是否含有放射源，以及如果含有放射源的话，确定放射源的种类。
在该步骤中，可基于模式识别确定所测得的计数率曲线与哪种类型的放射源的计数率曲线相符合，并由此确定检测对象中是否含有放射源并可在含有放射源的情况下确定放射源的种类。
在一种实施例中，还可在进行检测时判断所述检测对象在移动过程中是否停留过。备选地，可以判断在此期间检测对象的最低移动速度是否高于预设的阈值速度(当阈值速度为零时，此即判断是否停留过)。如果检测对象在移动过程中停留过，则会影响所测得的计数率曲线的形状，给本公开的技术方案带来破坏。因此，优选地，在本公开的技术方案中，如果所述检测对象在其间停留过，则回到测量检测对象的计数率曲线的步骤重新进行测量。
在例如图1所示的场景中，可通过至少以下方法判断车辆是否在通道内停留过：(1)根据车速(驶入和驶出通道时的速度均值)和车长(应在一定的范围内)计算车辆通过通道所需的时间，如果实际通过时间大于所需时间(车身长度除以平均车速)，那么可以判定为在通道内停过；(2)根据通道内的视频情况 判断是否停过；(3)加装测速仪，判断是否停过。
优选地，所述方法还包括：只有在所述检测对象的计数率曲线中的最大计数率值高于报警阈值的情况下，才执行对所述计数率曲线进行模式识别的步骤。在这种情况中，如果检测到的计数率曲线中的最大计数率值没有超过报警阈值，则认为所述检测对象中不包含足够可疑的点放射源，可不对其加以顾及。
图7示出了根据本公开的实施例的放射源检测系统700的结构框图。系统700包括检测器710和处理器720。所述检测器710用于对从其间通过的检测对象进行检测。所述处理器720连接到所述检测器710，并且被配置为执行以下操作：根据检测器的检测结果，获得所述检测对象的计数率曲线；对所述计数率曲线进行模式识别；以及根据所述模式识别的结果，确定所述检测对象中是否含有放射源，以及如果含有放射源的话，确定放射源的种类。
该放射源检测系统700的处理器720执行的操作与上述放射源检测方法600相对应。以上对方法600的具体描述和解释同样适用于处理器720，在此不再赘述。
图8示出了采用本公开的实施例的实际海关放射物检测流程示例。
S810.开始检测后，可以首先判断是否引起了报警。如果无报警，则可将检测对象放行；如果有报警，则进入S820。
S820.判断车辆在通道内是否有过停顿。如果有过停顿，则进入S860，做进一步检查(或重新匀速通过检测通道)；如果没有停顿过，则进入S830。
S830.使用适当的模式识别方法对计数率曲线的形状进行分析，判断引起报警的放射源是何种类型(点状放射源或体放射源)。如果是点状放射源，则进入S860，做进一步检查；如果是体放射源，则进入S840。
S840.对于有些用户来说，即使是天然放射性物质引起的报警，也需要在强度上加以区分，在这种情况下，需要预先设置一个阈值，一旦由天然放射性物质引起的计数率超出这个阈值，则也要进入S860，做进一步检查；如果没有超过这个阈值，则进入S850。
S850.对于海关监管来说，每辆车都有对应的报关单，海关关员可以结合报关单的货物信息和放射源的类型信息做出是否放行的决定。
S860.对于点状放射源或超过预设阈值的体放射源或与报关单内容不符的体放射源引起的报警，需要使用手持式仪器对货物做进一步的检查。
S870.对于与报关单相符且没有超过预设阈值的体放射源引起的报警，可予以放行。
以上结合图8描述的是一个实施例。本领域的技术人员清楚，上述步骤中的一个或者多个并不是必须的，本领域技术人员会根据不同的应用场景对上述步骤进行删减或者调整顺序。
尽管以上已经结合本公开的优选实施例示出了本公开，但是本领域的技术人员将会理解，在不脱离本公开的精神和范围的情况下，可以对本公开进行各种修改、替换和改变。因此，本公开不应由上述实施例来限定，而应由所附权利要求及其等价物来限定。

Claims (16)

  1. 一种放射源检测方法，包括：
    在检测对象移动通过检测器时，由检测器测量检测对象的计数率曲线；
    对所述计数率曲线进行模式识别；以及
    根据所述模式识别的结果，确定所述检测对象中是否含有放射源，以及如果含有放射源的话，确定放射源的种类。
  2. 根据权利要求1所述的方法，还包括：
    判断所述检测对象的移动是否满足预定条件，以及
    如果所述检测对象的移动不满足所述预定条件，则使检测对象重新移动通过检测器，并重新进行所述测量、模式识别和确定的操作。
  3. 根据权利要求2所述的方法，其中所述预定条件是：
    所述检测对象在移动过程中没有停留过或最低移动速度高于阈值速度。
  4. 根据权利要求1所述的方法，所述对所述计数率曲线进行模式识别包括：
    计算所述计数率曲线的数学特性；以及
    根据所述计算的结果进行模式识别。
  5. 根据权利要求4所述的方法，其中所述模式识别包括：与预先确定的多种模式进行模式匹配。
  6. 根据权利要求4所述的方法，其中所述数学特性是曲线的峰度或曲线最大值两侧的下降幅度。
  7. 根据权利要求1所述的方法，其中所述计数率曲线是已经去除了本底均值的计数率曲线。
  8. 根据权利要求1所述的方法，所述方法还包括：
    只有在所述检测对象的计数率曲线中的最大计数率值高于报警阈值的情况下，才执行对所述计数率曲线进行模式识别的步骤。
  9. 一种放射源检测系统，包括：
    检测器，用于对从其间通过的检测对象进行检测；
    处理器，连接到所述检测器，并且被配置为执行以下操作：
    根据检测器的检测结果，获得所述检测对象的计数率曲线；
    对所述计数率曲线进行模式识别；以及
    根据所述模式识别的结果，确定所述检测对象中是否含有放射源，以及如果含有放射源的话，确定放射源的种类。
  10. 根据权利要求9所述的系统，所述处理器还被配置为执行以下操作：
    判断所述检测对象的移动是否满足预定条件，以及
    如果所述检测对象的移动不满足所述预定条件，则使检测对象重新移动通过检测器，并重新进行所述检测、模式识别和确定的操作。
  11. 根据权利要求10所述的系统，其中所述预定条件是：
    所述检测对象在移动过程中没有停留过或最低移动速度高于阈值速度。
  12. 根据权利要求9所述的系统，所述对所述计数率曲线进行模式识别的操作包括：
    计算所述计数率曲线的数学特性；以及
    根据所述计算的结果进行模式识别。
  13. 根据权利要求12所述的系统，其中所述模式识别包括：与预先确定的多种模式进行模式匹配。
  14. 根据权利要求12所述的系统，其中所述数学特性是曲线的峰度或曲线最大值两侧的下降幅度。
  15. 根据权利要求9所述的系统，其中所述计数率曲线是已经去除了本底均值的计数率曲线。
  16. 根据权利要求9所述的系统，所述处理器还被配置为：
    只有在所述检测对象的计数率曲线中的最大计数率值高于报警阈值的情况下，才执行对所述计数率曲线进行模式识别的步骤。
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