Soil heavy metal detection method and system based on pXRF technology

Abstract

The present invention relates to the technical field of soil heavy metal detection, and in particular to a soil heavy metal detection method and system based on pXRF technology. The present invention first obtains the spectral detection results of soil heavy metals in each partition of the area to be tested, further determines the suspected undetected elements in each partition, and obtains the existence possibility coefficient of each suspected undetected element; then obtains the precipitation retention probability coefficient of the heavy metal elements in each non-single element set in all element sets, further determines the corrected existence possibility coefficient of each suspected undetected element in each partition, and finally determines the heavy metal detection results of each partition in combination with the spectral detection results. The present invention combines the migration characteristics of particles corresponding to heavy metal elements and the composite precipitation characteristics between particles corresponding to different heavy metal elements to accurately analyze the possibility of the existence of undetected heavy metal elements in each partition due to the detection limit, thereby improving the detection effect of soil heavy metals.

Description

Technical Field

[0001] The present invention relates to the technical field of soil heavy metal detection, and in particular to a soil heavy metal detection method and system based on pXRF technology. Background Art

[0002] With the discharge of industrial waste, some heavy metal elements such as Cu, Pb, Zn, Ni, Hg, As, etc. will appear in the soil, causing heavy metal pollution. These heavy metals cannot be decomposed by soil microorganisms and remain in the soil for a long time, destroying the soil structure and reducing soil fertility. They may also enter the human body through the food chain, causing chronic poisoning and various diseases, posing a serious threat to ecological balance and human health. Therefore, it is crucial to conduct soil heavy metal testing to assess pollution risks in order to carry out soil remediation.

[0003] Currently, soil testing is typically performed based on pXRF technology. Spectral images are acquired and the positions and intensities of their peaks are analyzed. These images are then compared with preset spectral thresholds to determine the types and concentrations of heavy metals in the soil. However, pXRF technology has detection limits for each heavy metal element. When the heavy metal content is low, its spectral performance is not obvious, which may lead to omissions. Furthermore, heavy metals may migrate in the soil due to factors such as moisture and soil texture, making the assessment of soil heavy metal contamination risk based solely on spectral analysis inaccurate, ultimately resulting in poor detection of heavy metals in the soil. Summary of the Invention

[0004] In order to solve the technical problem of poor detection effect of heavy metal detection in soil, the purpose of the present invention is to provide a soil heavy metal detection method and system based on pXRF technology. The technical solution adopted is as follows:

[0005] A soil heavy metal detection method based on pXRF technology, the method comprising:

[0006] Obtaining spectral detection results of heavy metals in the soil of each subarea of ​​the tested area, wherein the spectral detection results include the elemental set of heavy metals and the elemental content of each heavy metal;

[0007] For each partition, the heavy metal elements that do not exist in the corresponding element set are regarded as suspected undetected elements. The presence probability coefficient of each suspected undetected element is obtained by combining the spectral detection results of all neighboring partitions within its preset neighborhood and the detection limit of each suspected undetected element.

[0008] For each non-single element set, the precipitation and retention probability coefficient of the heavy metal elements in each non-single element set is obtained based on the total number of its corresponding superset in all element sets, combined with the total number of heavy metal elements in it and the element content of each heavy metal element in the corresponding partition of each superset;

[0009] For each suspected undetected element in each partition, the corrected existence possibility coefficient of each suspected undetected element is obtained based on the existence possibility coefficient and its detection status in all adjacent partitions of the corresponding partition, combined with the precipitation retention probability coefficient of the heavy metal elements in all non-single element subsets of the non-single element set corresponding to each adjacent partition; based on the corrected existence possibility coefficient and the spectral detection results, the heavy metal detection results in each partition are obtained.

[0010] Furthermore, the method for obtaining the possible existence coefficient includes:

[0011] Take any partition as the target partition, and any suspected undetected element in the target partition as the target element; within the preset neighborhood of the target partition, select all neighboring partitions where the target element exists as suspected interference partitions of the target partition;

[0012] According to the element content of the target element in each of the suspected interference partitions, combined with the detection limit of the target element and the total number of the suspected interference partitions, the existence possibility coefficient of the target element in the target partition is obtained.

[0013] Furthermore, the method for obtaining the existence possibility coefficient of the target element in the target partition includes:

[0014] In the preset neighborhood of the target partition, the negative correlation mapping result of the total number of non-suspected interference partitions is used as the comparison weight, and the total number of the suspected interference partitions is weighted using the comparison weight to obtain the first interference parameter; the cumulative sum of the element content of the target element in all the suspected interference partitions is used as the second interference parameter; the first interference parameter, the second interference parameter and the detection limit of the target element are integrated to obtain the existence possibility coefficient of the target element in the target partition.

[0015] Furthermore, the method for obtaining the sedimentation retention probability coefficient includes:

[0016] Among the element sets corresponding to all partitions of the area to be tested, any non-single element set containing at least two heavy metal elements is used as the target set;

[0017] According to the element content of each heavy metal element in the target set in the corresponding partitions of all its supersets, the retention parameters of the heavy metal elements in the target set are obtained; the proportion of the number of all supersets of the target set in all non-single element sets is used as the retention reference weight; the retention parameters are weighted using the retention reference weight to obtain the retention probability index; the types and numbers of heavy metal elements in the target set are negatively correlated to obtain the composite precipitation influence parameters of the heavy metal elements; the retention probability index and the composite precipitation influence parameters are integrated to obtain the precipitation retention probability coefficient of the heavy metal elements in the target set.

[0018] Furthermore, the method for obtaining the retention parameter includes:

[0019] The mean value of the element content of each heavy metal element in the target set in the corresponding partitions of the target set and all its supersets is used as the retention sub-parameter of each heavy metal element. The retention sub-parameters of all heavy metal elements are combined to obtain the retention parameter.

[0020] Furthermore, the method for obtaining the modified existence possibility coefficient includes:

[0021] Take any partition as the target partition, and any suspected undetected element in the target partition as the target element; among all the adjacent partitions of the target partition, select all the adjacent partitions that contain the target element and are not corresponding to a single element set as reference partitions;

[0022] The non-singleton set corresponding to each reference partition is split into non-singleton subsets containing the target element, and the precipitation retention index of the target element in each reference partition is obtained based on the precipitation retention probability coefficients of heavy metal elements in all non-singleton subsets;

[0023] The precipitation retention index of the target element in all reference partitions is integrated to obtain the migration interference weight of the target element to the target partition; the existence possibility coefficient of the target element is weighted using the migration interference weight, and the weighted result is normalized to obtain the corrected existence possibility coefficient of the target element.

[0024] Furthermore, the method for obtaining the sedimentation retention index includes:

[0025] The maximum value of the precipitation retention probability coefficients of all heavy metal elements in the non-single element subsets containing the target element is used as the precipitation retention index of the target element in the reference partition.

[0026] Furthermore, the method for obtaining the migration interference weight includes:

[0027] The negative correlation normalized result of the sum of the precipitation retention indexes of the target elements in all reference partitions is used as the migration interference weight of the target element to the target partition.

[0028] Furthermore, the method for obtaining the heavy metal detection results in each partition includes:

[0029] For each partition, when the corrected existence possibility coefficient of each suspected undetected element is greater than a preset threshold, the suspected undetected element is treated as an undetected element, and the heavy metal detection result is determined in combination with the heavy metal elements in the element set.

[0030] A soil heavy metal detection system based on pXRF technology, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the soil heavy metal detection method based on pXRF technology when executing the computer program.

[0031] The present invention has the following beneficial effects:

[0032] The present invention first obtains the spectral detection results of soil heavy metals in each partition and determines the suspected undetected elements therein; then analyzes and evaluates the migration possibility of the suspected undetected elements in the neighboring partitions, and at the same time, combined with the detection limit of each suspected undetected element, roughly evaluates the possible existence amount of the suspected undetected elements in the partition, and determines the existence possibility coefficient of each suspected undetected element; then, with the idea of ​​element combination for composite precipitation, analyzes the total number of corresponding supersets of each non-single element set in all element sets, that is, the combination frequency of elements in each non-single element set, further combines the number of heavy metal elements to evaluate the composite complexity between elements, and the element content to evaluate the precipitation retention possibility, thereby obtaining the precipitation retention probability coefficient of the heavy metal elements in each non-single element set; then, based on the existence possibility coefficient of each suspected undetected element in each partition and its detection status in the adjacent partitions, and splitting the element combination, analyzes the precipitation retention probability coefficients of the heavy metal elements in all non-single element subsets of the non-single element set corresponding to each adjacent partition, so as to provide an accurate composite precipitation reference, thereby correcting the existence possibility coefficient of each suspected undetected element, and finally combining the spectral detection results to accurately obtain the heavy metal detection results in each partition. The present invention combines the migration characteristics of particles corresponding to heavy metal elements and the composite precipitation characteristics between particles corresponding to different heavy metal elements to accurately analyze the possibility of the existence of undetected heavy metal elements due to the detection limit in each partition, thereby improving the detection effect of soil heavy metals based on pXRF technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0034] Figure 1 A flow chart of a method for detecting heavy metals in soil based on pXRF technology provided by one embodiment of the present invention;

[0035] Figure 2 A flowchart of a method for obtaining a modified existence possibility coefficient provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0036] To further illustrate the technical means and effectiveness of the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a soil heavy metal detection method and system based on pXRF technology proposed by the present invention. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0037] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0038] The following describes in detail a method and system for detecting heavy metals in soil based on pXRF technology provided by the present invention with reference to the accompanying drawings.

[0039] See also Figure 1 , which shows a flow chart of a soil heavy metal detection method based on pXRF technology provided by one embodiment of the present invention, specifically including:

[0040] Step S1, obtaining the spectrum detection results of heavy metals in the soil in each partition of the area to be tested, the spectrum detection results including the element set of heavy metals and the element content of each heavy metal.

[0041] In one embodiment of the present invention, the area to be tested for heavy metals is first determined as the test area, and then the test area is evenly divided into several partitions. A portable X-ray fluorescence spectrometer, i.e., pXRF, is used to detect and analyze each partition, obtaining a spectrum of heavy metals in the soil in each partition. The spectrum is then analyzed and processed to determine the spectral detection results.

[0042] Specifically, taking any partition as an example, the spectrum is subjected to sliding averaging to denoise, and the denoised spectrum is further analyzed to determine all fluorescence peaks. The heavy metal elements corresponding to each peak are determined by comparing with standard spectral libraries such as NIST, thereby obtaining the elemental set of heavy metals in each partition, and estimating the elemental content of each heavy metal element based on the peak area method.

[0043] It should be noted that the partitions should be square areas as much as possible for analysis. At the same time, the partitions need to be determined in combination with the detection window of the portable X-ray fluorescence spectrometer, that is, the area range of each partition shall not be larger than the detection window of the spectrometer; if the area to be tested is large, the implementer can also directly divide the area to be tested into square areas of a preset size, such as one square meter, and then conduct sampling analysis to determine the spectral detection results.

[0044] It should be noted that obtaining a spectrum, performing noise reduction preprocessing on the spectrum, analyzing and determining the heavy metal elements contained therein and then constructing an element set, and determining the element content of each heavy metal element are all existing technologies well known to those skilled in the art and will not be repeated here.

[0045] Step S2: For each partition, the heavy metal elements that do not exist in the corresponding element set are regarded as suspected undetected elements, and the possible existence coefficient of each suspected undetected element is obtained by combining the spectral detection results of all neighboring partitions within its preset neighborhood and the detection limit of each suspected undetected element.

[0046] Due to the existence of the detection limit, each partition may contain a small amount of heavy metal elements that have not been detected, resulting in poor detection results. Therefore, the embodiment of the present invention first determines the suspected undetected elements in each partition.

[0047] In one embodiment of the present invention, the element sets of all partitions are combined to obtain all heavy metal elements contained in the area to be tested, and the non-existent heavy metal elements in the element set of each partition are regarded as suspected undetected elements.

[0048] In another embodiment of the present invention, the implementer may also customize the full set of heavy metal element types to further determine the suspected undetected elements in each partition.

[0049] Considering that heavy metal ions will spontaneously migrate from high-concentration areas to low-concentration areas with the movement of water or the diffusion of their own molecules in the soil, if there are suspected undetected elements in a certain partition in the adjacent partitions, the suspected undetected elements may migrate from the surrounding adjacent partitions to the partition, thereby causing inaccurate heavy metal detection results in the partition; and considering that the detection limit of the suspected undetected elements is the minimum detection amount, it indirectly reflects the maximum content or maximum migration amount of the suspected undetected elements in the partition, which has not yet been detected;

[0050] Therefore, the embodiment of the present invention will further obtain the existence possibility coefficient of each suspected undetected element based on the spectral detection results of all neighboring partitions within the preset neighborhood of each partition and the detection limit of each suspected undetected element. The existence possibility coefficient is preliminarily combined with the element distribution in the neighboring partition to evaluate the possibility that heavy metal elements exist in the partition but are not detected, in preparation for the subsequent accurate determination of heavy metal detection results.

[0051] Preferably, in one embodiment of the present invention, first, any partition is taken as the target partition, and any suspected undetected element in the target partition is taken as the target element. Then, the suspected interference area containing the target element is screened out in the neighboring partitions around the target partition, that is, the neighboring area that has migration interference with the target area, so as to facilitate subsequent analysis and expression. Then, by changing the target partition and the target element, the existence probability coefficient of each suspected undetected element in each partition can be determined.

[0052] Considering that the more suspected interference partitions there are and the higher the content of the target element in each suspected interference partition, the greater the possibility of the target element migrating to the target partition, and the greater its existence possibility coefficient; at the same time, if the detection limit of the target element is larger, it means that the content of the target element that has not been detected in the target partition is likely to be greater, and the greater its existence possibility coefficient;

[0053] Therefore, there are possible methods to obtain the coefficient:

[0054] Take any partition as the target partition, and any suspected undetected element in the target partition as the target element; within the preset neighborhood of the target partition, select all neighboring partitions where the target element exists as suspected interference partitions of the target partition;

[0055] According to the element content of the target element in each suspected interference partition, combined with the detection limit of the target element and the total number of suspected interference partitions, the existence possibility coefficient of the target element in the target partition is obtained.

[0056] Among them, in a preferred embodiment of the present invention, considering that the number of non-suspected interference partitions can provide a certain reference for the number of suspected interference partitions, the comparison weight is obtained by adjusting the logic through negative correlation mapping to weight the total number of suspected interference partitions; then, the element content of the target element in all suspected interference partitions and the detection limit of the target element are integrated to evaluate the possibility of existence; therefore, the method for obtaining the existence possibility coefficient of the target element in the target partition includes:

[0057] In the preset neighborhood of the target partition, the negative correlation mapping result of the total number of non-suspected interference partitions is used as the comparison weight, and the total number of suspected interference partitions is weighted using the comparison weight to obtain the first interference parameter; the cumulative sum of the element contents of the target element in all suspected interference partitions is used as the second interference parameter; the first interference parameter, the second interference parameter and the detection limit of the target element are integrated to obtain the existence possibility coefficient of the target element in the target partition.

[0058] As an example, first determine the target partition and target element, and then set the preset neighborhood to 8 neighborhoods, so that all suspected interference partitions of the target partition can be screened out, and the remaining neighborhood partitions within the preset neighborhood are used as non-suspected interference partitions; further, the total number of non-suspected interference partitions is added to a very small positive parameter such as 0.1 and then an inverse operation is performed to obtain the comparison weight, and then the comparison weight is multiplied by the total number of suspected interference partitions to obtain the first interference parameter; then the first interference parameter, the second interference parameter and the detection limit of the target element are multiplied and fused to obtain the possible existence coefficient of the target element in the target partition.

[0059] It should be noted that obtaining the detection limit is a well-known technical means and the obtaining process will not be described in detail. In other examples, the implementer can also customize the preset neighborhood, or adopt other negative correlation mapping means such as mapping to the exponential function exp(-x) with the natural constant e as the base, or adopt other fusion means such as addition or weighted summation. Before the fusion operation, all fusion parameters need to be dedimensionalized, and subsequent operations in the embodiment of the present invention also need to be dedimensionalized.

[0060] Step S3, for each non-single element set, according to the total number of its corresponding superset in all element sets, combined with the total number of heavy metal elements therein and the element content of each heavy metal element in the corresponding partition of each superset, obtain the precipitation retention probability coefficient of the heavy metal elements in each non-single element set.

[0061] Considering that heavy metal ions not only have the behavioral characteristic of migrating from high concentration to low concentration in the soil environment, but also when multiple heavy metal ions coexist, different heavy metal ions often form complexes and precipitate together, causing them to be retained in a specific partition, making it difficult to diffuse to the surrounding areas; and when complex precipitation is formed, the content of heavy metal elements in the specific partition will be higher. At the same time, the fewer the types of heavy metal elements, the smaller the complex interference, and the greater the possibility of precipitation formation;

[0062] Taking into account that the partition with composite precipitation contains at least two heavy metal elements, the embodiment of the present invention will analyze the non-single element set; since there are multiple partitions in the area to be tested, there are multiple non-single element sets, and for each non-single element set, the higher the frequency of occurrence and the more it meets the above-mentioned retention characteristics and composite interference characteristics, the greater the possibility of precipitation and retention of heavy metal elements in the non-single element set; and similar composite precipitation may also exist in the superset of each non-single element set, so in order to avoid omissions, the embodiment of the present invention will combine the total number of supersets to comprehensively evaluate the precipitation and retention probability coefficient of heavy metal elements in each non-single element set.

[0063] It should be noted that a non-single element set refers to an element set containing at least two heavy metal elements, and a superset is a well-known technology. If set L2 contains set L1, and set L2 may contain elements that are not in set L1, then set L2 is a superset of set L1.

[0064] Preferably, in one embodiment of the present invention, first, a non-single element set is determined as a target set in the element sets corresponding to all partitions of the test area, and all its supersets are determined in the element set; considering that for heavy metal elements in the target set, the higher its content in all partitions corresponding to the target set and its supersets, the greater its retention possibility, so a retention parameter can be obtained, and the more target sets and their supersets there are, it means that retention is prevalent in most partitions, and the retention reference weight is also greater; considering that when the number of heavy metal elements in the target set is less, the impact of the composite reaction is smaller and the possibility of precipitation is greater, a negative correlation mapping adjustment logic is performed to provide a certain reference for evaluating precipitation retention; based on this, the method for obtaining the precipitation retention probability coefficient includes:

[0065] Among all element sets, any non-single element set containing at least two heavy metal elements is taken as the target set; the retention parameters of the heavy metal elements in the target set are obtained according to the element content of each heavy metal element in the corresponding partitions of all its supersets; the proportion of the number of all supersets of the target set in all non-single element sets is used as the retention reference weight; the retention parameter is weighted using the retention reference weight to obtain the retention probability index; the number of types of heavy metal elements in the target set is negatively correlated to obtain the composite precipitation influence parameter of the heavy metal elements; the retention probability index and the composite precipitation influence parameter are integrated to obtain the precipitation retention probability coefficient of the heavy metal elements in the target set.

[0066] In a preferred embodiment of the present invention, the method for obtaining the retention parameter includes:

[0067] The mean value of the element content of each heavy metal element in the target set in the corresponding partitions of all its supersets is used as the retention sub-parameter of each heavy metal element. The retention sub-parameters of all heavy metal elements are combined to obtain the retention parameter.

[0068] As an example, first obtain the retention sub-parameter of each heavy metal element in the target set, then multiply and combine the retention sub-parameters of all heavy metal elements in the target set to obtain the retention parameter; then use the total number of the target set and all its supersets as the numerator, the total number of all non-single element sets as the denominator, and the fraction ratio as the quantity ratio to obtain the retention reference weight, and further multiply and combine the retention reference weight with the retention parameter to obtain the retention probability index;

[0069] Then, the inverse of the number of types of heavy metal elements in the target set is taken for negative correlation mapping to obtain the composite precipitation influence parameter. The retention probability index and the composite precipitation influence parameter are further combined to obtain the precipitation retention probability coefficient of the heavy metal elements in the target set. By changing the target set, the precipitation retention probability coefficient of the heavy metal elements in each non-single element set can be obtained.

[0070] It should be noted that the superset of the target set also includes the target set itself.

[0071] Step S4: For each suspected undetected element in each partition, the corrected existence possibility coefficient of each suspected undetected element is obtained based on the existence possibility coefficient and its detection status in all adjacent partitions of the corresponding partition, combined with the precipitation retention probability coefficient of the heavy metal elements in all non-single element subsets of the non-single element set corresponding to each adjacent partition; based on the corrected existence possibility coefficient and the spectral detection result, the heavy metal detection result in each partition is obtained.

[0072] Considering that for each partition, if there are suspected undetected elements in the surrounding adjacent partitions, the possibility of the suspected undetected elements in the surrounding adjacent partitions migrating to the partition is greater, and the suspected undetected elements may undergo complex precipitation in the surrounding adjacent partitions, making it difficult to migrate, so the possibility of the suspected undetected elements existing in the partition is relatively reduced;

[0073] Considering that the composite precipitation of heavy metal elements in each non-single element set may not involve all heavy metal elements, but only some heavy metal elements; therefore, it is necessary to evaluate the precipitation retention probability coefficient in the composite precipitation combination of some heavy metal elements corresponding to all subsets of each non-single element set to increase the consideration of the interference of composite precipitation on the assessment of the possibility of existence, thereby improving the assessment accuracy of the suspected undetected elements in the partition;

[0074] Therefore, in the embodiment of the present invention, for each suspected undetected element in each partition, the corrected existence possibility coefficient of each suspected undetected element is obtained based on the existence possibility coefficient and its detection status in all adjacent partitions of the corresponding partition, combined with the precipitation retention probability coefficients of heavy metal elements in all non-single element subsets of the non-single element set corresponding to each adjacent partition; the precipitation retention probability coefficient is used to adjust the interference effect of heavy metal element precipitation on the existence possibility coefficient to improve the evaluation accuracy.

[0075] Preferably, in one embodiment of the present invention, the method for obtaining the modified existence possible coefficient includes:

[0076] See also Figure 2 , which shows a flow chart of a method for obtaining a modified existence possibility coefficient provided by an embodiment of the present invention, specifically comprising:

[0077] Step S401 , taking any partition as a target partition and any suspected undetected element of the target partition as a target element; and selecting all adjacent partitions of the target partition that contain the target element and correspond to non-singleton sets as reference partitions.

[0078] To facilitate analysis and expression, an embodiment of the present invention first determines a target partition among all partitions, determines a target element of the target partition, and simultaneously determines all reference partitions of the target partition; then, after obtaining the corrected existence possibility coefficient of the target element of the target partition in steps S402-S403, the target partition and the target element are changed to obtain the corrected existence possibility coefficient of each suspected undetected element in each partition.

[0079] It should be noted that the bordering partition is also the neighborhood partition within the 8-neighborhood of the target partition.

[0080] Step S402: Split the non-singleton set corresponding to each reference partition into non-singleton subsets containing the target element, and obtain the precipitation retention index of the target element in each reference partition based on the precipitation retention probability coefficients of the heavy metal elements in all non-singleton subsets.

[0081] Considering that if the target element in the reference area is precipitated and retained, it will interfere with the assessment of the possibility of the target element in the target partition; considering that in each reference partition, the target element may only be precipitated with some heavy metal elements, and the existence of some heavy metal elements that are not precipitated with the target element will have a certain impact on the assessment accuracy of the precipitation retention probability coefficient;

[0082] Therefore, in one embodiment of the present invention, the non-singleton set corresponding to each reference partition is first split into non-singleton subsets containing the target element. For example, the non-singleton set corresponding to a reference partition is {A, B, C}, ABC are all heavy metal element codes, and B is the target element. Then, its non-singleton subsets containing the target element include {A, B}{B, C}{A, B, C};

[0083] Considering that if the precipitation retention probability coefficient of a heavy metal element in a non-single element subset containing a target element is larger, it means that the probability of precipitation retention under this heavy metal element combination is greater, and it can be used as a reference representative to improve the analytical accuracy of the precipitation retention index of the target element in the reference partition;

[0084] Based on this, in a preferred embodiment of the present invention, the method for obtaining the sedimentation retention index includes:

[0085] The maximum value of the precipitation retention probability coefficients of all heavy metal elements in the non-single element subsets containing the target element is used as the precipitation retention index of the target element in the reference partition.

[0086] It should be noted that by traversing all element sets, a non-single element subset containing the target element can be obtained, and then its retention and precipitation probability coefficient can be determined to determine the maximum value; if in the above-mentioned non-single element subset {A, B}{B, C}{A, B, C}, only {B, C}{A, B, C} can be traversed and obtained in all element sets, then it is only necessary to obtain the maximum value of the corresponding precipitation retention probability coefficients of {B, C}{A, B, C} to obtain the precipitation retention index.

[0087] Step S403: The precipitation retention index of the target element in all reference partitions is integrated to obtain the migration interference weight of the target element to the target partition; the existence possibility coefficient of the target element is weighted using the migration interference weight, and the weighted result is normalized to obtain the modified existence possibility coefficient of the target element.

[0088] After obtaining the precipitation retention index of the target elements in all reference partitions, we can further evaluate the impact of the complex precipitation of the target elements on their migration to the target partition and determine the migration interference weight; further use the migration interference weight to correct the possible existence coefficient of the target elements in the target partition, in preparation for the subsequent accurate evaluation of the heavy metal detection results.

[0089] Among them, in a preferred embodiment of the present invention, considering that the larger the sedimentation retention index is, the greater the impact on its migration to the target partition, the logical relationship can be adjusted through negative correlation mapping; therefore, the method for obtaining the migration interference weight includes: taking the negative correlation normalization result of the sum of the sedimentation retention indexes of the target elements in all reference partitions as the migration interference weight of the target element to the target partition.

[0090] As an example, the precipitation retention index of the target element in all reference partitions of the target area is first accumulated and summed, and the sum is further used as the x in the exponential function exp(-x) with the natural constant e as the base. The logic is adjusted and normalized using negative correlation mapping to obtain the migration interference weight. In other examples, implementers may also use other negative correlation mapping methods.

[0091] The migration interference weight is then multiplied and combined with the possible existence coefficient of the target element. Since the migration interference weight is less than or equal to 1, the possible existence coefficient will be appropriately reduced, thereby taking the sedimentation effect into account and achieving the correction purpose; the obtained product is then mapped to the sigmoid function for normalization to obtain the migration interference weight of the target element to the target partition.

[0092] After obtaining the corrected possible existence coefficient of each suspected undetected element in each partition, the spectral detection results of each partition can be further combined to accurately obtain the heavy metal detection results in each partition.

[0093] Preferably, in one embodiment of the present invention, considering that for each partition, the larger the corrected existence probability coefficient of the suspected undetected element, the more likely it is that it has migrated from other neighboring partitions, but has not been detected due to the detection limit. At the same time, the greater the possibility of its migration within a certain period of time in the future, the greater the contamination impact of the suspected undetected element on the partition; therefore, a threshold is set to assess the contamination risk, and the final result is further determined in combination with the detected results; therefore, the method for obtaining the heavy metal detection results in each partition includes:

[0094] For each partition, when the corrected existence possibility coefficient of each suspected undetected element is greater than a preset threshold, the suspected undetected element is treated as an undetected element, and the heavy metal detection result is determined in combination with the heavy metal elements in the element set.

[0095] As an example, since the value range of the correction possibility coefficient is 0-1, the preset threshold is set to 0.75, and the implementer can also customize it, so that undetected elements can be obtained, and the undetected elements and heavy metal elements that have been detected by the spectrum graph can be used together as the detection results of heavy metal elements present in the partition.

[0096] After determining the heavy metal elements present in each partition, it can provide certain information reference for subsequent soil improvement.

[0097] The present invention also proposes a soil heavy metal detection system based on pXRF technology. The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the soil heavy metal detection method based on pXRF technology described in the above steps S1-S4 is implemented.

[0098] In summary, the present invention first obtains the spectral detection results of soil heavy metals in each partition of the test area, further determines the suspected undetected elements in each partition, and obtains the existence possibility coefficient of each suspected undetected element; then obtains the precipitation retention probability coefficient of the heavy metal elements in each non-single element set in all element sets, further determines the corrected existence possibility coefficient of each suspected undetected element in each partition, and finally determines the heavy metal detection results of each partition in combination with the spectral detection results. The present invention combines the migration characteristics of particles corresponding to heavy metal elements and the composite precipitation characteristics between particles corresponding to different heavy metal elements to accurately analyze the possibility of the existence of undetected heavy metal elements in each partition due to the detection limit, thereby improving the detection effect of soil heavy metals based on pXRF technology.

[0099] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0100] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A soil heavy metal detection method based on pXRF technology, characterized in that: The method comprises: Obtaining spectral detection results of heavy metals in the soil of each subarea of ​​the tested area, wherein the spectral detection results include the elemental set of heavy metals and the elemental content of each heavy metal; For each partition, the heavy metal elements that do not exist in the corresponding element set are regarded as suspected undetected elements. The presence probability coefficient of each suspected undetected element is obtained by combining the spectral detection results of all neighboring partitions within its preset neighborhood and the detection limit of each suspected undetected element. For each non-single element set, the precipitation and retention probability coefficient of the heavy metal elements in each non-single element set is obtained based on the total number of its corresponding superset in all element sets, combined with the total number of heavy metal elements in it and the element content of each heavy metal element in the corresponding partition of each superset; For each suspected undetected element in each partition, the corrected existence possibility coefficient of each suspected undetected element is obtained based on the existence possibility coefficient and its detection status in all adjacent partitions of the corresponding partition, combined with the precipitation retention probability coefficient of the heavy metal elements in all non-single element subsets of the non-single element set corresponding to each adjacent partition; based on the corrected existence possibility coefficient and the spectral detection results, the heavy metal detection results in each partition are obtained.

2. The soil heavy metal detection method based on pXRF technology according to claim 1, characterized in that: The method for obtaining the possible existence coefficient includes: Take any partition as the target partition, and any suspected undetected element in the target partition as the target element; within the preset neighborhood of the target partition, select all neighboring partitions where the target element exists as suspected interference partitions of the target partition; According to the element content of the target element in each of the suspected interference partitions, combined with the detection limit of the target element and the total number of the suspected interference partitions, the existence possibility coefficient of the target element in the target partition is obtained.

3. The soil heavy metal detection method based on pXRF technology according to claim 2, characterized in that: The method for obtaining the existence possibility coefficient of the target element in the target partition includes: In the preset neighborhood of the target partition, the negative correlation mapping result of the total number of non-suspected interference partitions is used as the comparison weight, and the total number of the suspected interference partitions is weighted using the comparison weight to obtain the first interference parameter; the cumulative sum of the element content of the target element in all the suspected interference partitions is used as the second interference parameter; the first interference parameter, the second interference parameter and the detection limit of the target element are integrated to obtain the existence possibility coefficient of the target element in the target partition.

4. The soil heavy metal detection method based on pXRF technology according to claim 1, characterized in that: The method for obtaining the sedimentation retention probability coefficient includes: Among the element sets corresponding to all partitions of the area to be tested, any non-single element set containing at least two heavy metal elements is used as the target set; According to the element content of each heavy metal element in the target set in the corresponding partitions of all its supersets, the retention parameters of the heavy metal elements in the target set are obtained; the proportion of the number of all supersets of the target set in all non-single element sets is used as the retention reference weight; the retention parameters are weighted using the retention reference weight to obtain the retention probability index; the types and numbers of heavy metal elements in the target set are negatively correlated to obtain the composite precipitation influence parameters of the heavy metal elements; the retention probability index and the composite precipitation influence parameters are integrated to obtain the precipitation retention probability coefficient of the heavy metal elements in the target set.

5. The soil heavy metal detection method based on pXRF technology according to claim 4 is characterized in that: The method for obtaining the retention parameter includes: The mean value of the element content of each heavy metal element in the target set in the corresponding partitions of the target set and all its supersets is used as the retention sub-parameter of each heavy metal element. The retention sub-parameters of all heavy metal elements are combined to obtain the retention parameter.

6. The soil heavy metal detection method based on pXRF technology according to claim 1, characterized in that: The method for obtaining the modified existence possibility coefficient includes: Take any partition as the target partition, and any suspected undetected element in the target partition as the target element; among all the adjacent partitions of the target partition, select all the adjacent partitions that contain the target element and are not corresponding to a single element set as reference partitions; The non-singleton set corresponding to each reference partition is split into non-singleton subsets containing the target element, and the precipitation retention index of the target element in each reference partition is obtained based on the precipitation retention probability coefficients of heavy metal elements in all non-singleton subsets; The precipitation retention index of the target element in all reference partitions is integrated to obtain the migration interference weight of the target element to the target partition; the existence possibility coefficient of the target element is weighted using the migration interference weight, and the weighted result is normalized to obtain the corrected existence possibility coefficient of the target element.

7. The soil heavy metal detection method based on pXRF technology according to claim 6, characterized in that: The method for obtaining the sedimentation retention index includes: The maximum value of the precipitation retention probability coefficients of all heavy metal elements in the non-single element subsets containing the target element is used as the precipitation retention index of the target element in the reference partition.

8. The method for detecting heavy metals in soil based on pXRF technology according to claim 6, characterized in that: The method for obtaining the migration interference weight includes: The negative correlation normalized result of the sum of the precipitation retention indexes of the target elements in all reference partitions is used as the migration interference weight of the target element to the target partition.

9. The soil heavy metal detection method based on pXRF technology according to claim 1, characterized in that: The methods for obtaining heavy metal detection results in each partition include: For each partition, when the corrected existence possibility coefficient of each suspected undetected element is greater than a preset threshold, the suspected undetected element is treated as an undetected element, and the heavy metal detection result is determined in combination with the heavy metal elements in the element set.

10. A soil heavy metal detection system based on pXRF technology, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the soil heavy metal detection method based on pXRF technology are implemented as described in any one of claims 1 to 9.

Images