Method and system for identifying heavy metal cadmium in ligusticum wallichii extracting solution
By executing the target heavy metal identification instructions in the Chuanxiong extract and generating detection instructions to identify and remove cadmium pollution, the problem of difficult cadmium pollution in the Chuanxiong extract is solved, the accuracy and efficiency of cadmium identification and removal are improved, and heavy metals for traditional Chinese medicine are used as a heavy metal for Chinese medicine. Governance provides new approaches.
Patent Information
- Application Number
- CN202411140321.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-20
- Publication Date
- 2024-12-10
AI Technical Summary
The prior art is difficult to effectively identify and remove heavy metal cadmium from Chuanxiong extract, which leads to difficulties in controlling cadmium pollution.
By executing the target heavy metal identification instructions in the Chuanxiong extract and generating corresponding detection instructions based on the identification instructions, the cadmium content is identified and determined by data detection, so as to improve the accuracy of cadmium identification and removal efficiency.
The accurate identification and efficient removal of heavy metal cadmium in Chuanxiong extract was achieved, the effect of cadmium pollution control was improved, and new ideas were provided for the treatment of heavy metals in other traditional Chinese medicines.
Smart Images
Figure CN119108040A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data identification technology, and in particular, to a method and system for identifying heavy metal cadmium in a chuanxiong extract. Background Art
[0002] As a heavy metal cadmium-accumulating plant, the cadmium pollution problem of Chuanxiong has become a recognized pain point in the industry, and there is currently no effective solution. Previous explorations have found that "terminal" governance from the perspective of extracts may be a potential effective approach. In view of this, this project intends to study the governance of cadmium pollution in Chuanxiong from the perspective of Chuanxiong extracts, and is committed to establishing a new technology and method for cadmium reduction in Chuanxiong, and using Chuanxiong as an example to provide new ideas for heavy metal governance in other traditional Chinese medicines. At present, how to identify heavy metal cadmium is a technical problem that is difficult to solve. Summary of the invention
[0003] In order to improve the technical problems existing in the related technologies, the present application provides a method and system for identifying heavy metal cadmium in Chuanxiong extract.
[0004] In a first aspect, a method for identifying heavy metal cadmium in a chuanxiong extract is provided, comprising: Obtaining the target heavy metal identification instruction of the Chuanxiong extract data, and executing the target heavy metal identification instruction on the Chuanxiong extract data; After the target heavy metal identification instruction is executed, determining that at least one detection instruction corresponds to the target heavy metal identification instruction; the detection instruction is used to perform data detection in a data detection manner; The at least one detection instruction is executed on the transition data generated by the target heavy metal identification instruction to obtain the heavy metal cadmium content data in the Chuanxiong extract.
[0005] In the present application, the target heavy metal identification instruction is used to execute the target Chuanxiong extract, and the data detection method is related to the data requirements of the target Chuanxiong extract.
[0006] In the present application, the data requirements of the target Chuanxiong extract include several different data description features, and the data detection method includes a separate detection method of the data description features and a joint detection method between different data description features.
[0007] In the present application, the separate detection method includes at least one of the first detection method and the second detection method; Among them, the first detection method is used to detect whether the data description feature is empty; the second detection method is used to detect whether the data volume of the data description feature meets the preset data volume.
[0008] In the present application, the joint detection method includes at least one of the first sub-method and the second sub-method; The first sub-method is used to detect whether the data description feature meets the requirements specified under the premise that other data description features are effective; the second sub-method is used to detect whether the value of the data description feature is unique.
[0009] In the present application, the transition data generated by the target heavy metal identification instruction is subjected to at least one detection instruction to obtain the heavy metal cadmium content data in the Chuanxiong extract, including: Obtaining a first data description feature corresponding to the first detection method in the transition data; Execute a detection instruction corresponding to the first detection method to determine whether the first data description feature is empty; According to whether the first data description feature is empty, the heavy metal cadmium content data in the Chuanxiong extract is determined.
[0010] In the present application, the transition data generated by the target heavy metal identification instruction is subjected to at least one detection instruction to obtain the heavy metal cadmium content data in the Chuanxiong extract, including: Obtaining a second data description feature corresponding to the second detection mode in the transition data; Executing a detection instruction corresponding to the second detection method to determine whether the amount of data describing the second data characteristic meets a preset amount of data; The heavy metal cadmium content data in the Chuanxiong extract is determined based on whether the data volume of the second data description feature meets the preset data volume.
[0011] In the present application, the transition data generated by the target heavy metal identification instruction is subjected to at least one detection instruction to obtain the heavy metal cadmium content data in the Chuanxiong extract, including: Obtaining a third data description feature corresponding to the first sub-mode and other data description features related to the third data description feature in the transition data; Execute the detection instruction corresponding to the first sub-mode to determine whether the third data description feature meets the requirements defined under the premise that the other data description features are effective; The heavy metal cadmium content data in the Chuanxiong extract is determined based on whether the third data field meets the requirements specified under the premise that the other data description features are effective.
[0012] In the present application, the transition data generated by the target heavy metal identification instruction is subjected to at least one detection instruction to obtain the heavy metal cadmium content data in the Chuanxiong extract, including: Obtaining a fourth data description feature corresponding to the second sub-mode in the transition data; Execute a detection instruction corresponding to the second sub-characteristic to determine whether the value of the fourth data description feature meets the value uniqueness requirement; The heavy metal cadmium content data in the Chuanxiong extract is determined based on whether the value of the fourth data description feature meets the value uniqueness requirement.
[0013] In the present application, the method further comprises: Obtaining data requirements of the target Chuanxiong extract through a training port; At least one data detection method is generated based on the data requirement, and at least one detection instruction corresponding to the at least one data detection method is determined.
[0014] In this application, determining that the target heavy metal identification instruction corresponds to at least one detection instruction specifically includes: According to the label of the target heavy metal identification instruction and the detection method training information, determine at least one detection instruction corresponding to the target heavy metal identification instruction; the detection method training information is used to indicate at least one heavy metal identification instruction label and the detection instruction corresponding to each heavy metal identification instruction label.
[0015] In a second aspect, a system for identifying heavy metal cadmium in a chuanxiong extract is provided, comprising a processor and a memory communicating with each other, wherein the processor is used to read a computer program from the memory and execute it to implement the above method.
[0016] The embodiment of the present application provides a method and system for identifying heavy metal cadmium in a Chuanxiong extract. First, by obtaining the Chuanxiong extract data of the target heavy metal identification instruction, the target heavy metal identification instruction is executed based on the Chuanxiong extract data. In addition, after the execution of the target heavy metal identification instruction is completed, it is determined that at least one detection instruction corresponds to the target heavy metal identification instruction, and the detection instruction is used to perform data detection using a data detection method, and then at least one detection instruction is executed based on the business data generated by the target heavy metal identification instruction to obtain the detection result of the business data. Compared with the prior art, the technical solution in the present application can improve the accuracy of heavy metal cadmium identification, and can accurately remove it when it is removed later. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.
[0018] Figure 1This is a flow chart of a method for identifying heavy metal cadmium in a chuanxiong extract provided in an embodiment of the present application. DETAILED DESCRIPTION
[0019] In order to better understand the above technical scheme, the technical scheme of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical scheme of the present application, rather than limitations on the technical scheme of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.
[0020] See also Figure 1 , shows a method for identifying heavy metal cadmium in Chuanxiong extract, which may include the technical solutions described in the following steps S101-S103.
[0021] S101, obtaining the target heavy metal identification instruction of the Chuanxiong extract data, and executing the target heavy metal identification instruction on the Chuanxiong extract data.
[0022] Exemplarily, the data of Chuanxiong extract can be obtained by ultrasonic or electromagnetic identification of Chuanxiong extract, for example, ultrasound can determine different material components through the reflected wave band. This application has made substantial improvements to traditional technologies. Traditional heavy metal detection is a very cumbersome process. It is necessary to detect the type of heavy metals through different chemical methods, but it cannot detect the content of heavy metals. When extracting heavy metals, it may not be possible to ensure that the heavy metals are completely removed. This application can not only quickly detect the type of heavy metals but also know the content of heavy metals, so as to ensure that the heavy metals can be completely removed later.
[0023] It is understandable that the above target heavy metal identification instruction refers to the heavy metal identification instruction that needs to be executed currently. The target heavy metal identification instruction may include a target heavy metal identification instruction event and a corresponding target heavy metal identification instruction processing time.
[0024] The Chuanxiong extract data of the above-mentioned target heavy metal identification instruction refers to the data referenced when the target heavy metal identification instruction needs to be executed, and refers to the data generated by the previous heavy metal identification instruction corresponding to the target heavy metal identification instruction in the target Chuanxiong extract. Among them, the Chuanxiong extract data can be the original business Chuanxiong extract data corresponding to the execution of the target Chuanxiong extract, or it can be the calculated data after the execution of the transition heavy metal identification instruction in the target Chuanxiong extract. The Chuanxiong extract data of the target heavy metal identification instruction can be the data of the previous heavy metal identification instruction obtained by collecting at several collection frequencies or several collection cycles, and the data is the data generated by executing the previous heavy metal identification instruction.
[0025] It can be understood that when the target Chuanxiong extract includes several heavy metal identification instructions, the heavy metal identification instructions are the initial heavy metal identification instruction, the transition heavy metal identification instruction and the last heavy metal identification instruction in the order of task execution time. When the target heavy metal identification instruction is the initial heavy metal identification instruction, the Chuanxiong extract data of the target heavy metal identification instruction can be the original business Chuanxiong extract data; when the target heavy metal identification instruction is the transition heavy metal identification instruction, the Chuanxiong extract data of the target heavy metal identification instruction can be the calculated data obtained by executing the initial heavy metal identification instruction, or the calculated data obtained by executing the last transition heavy metal identification instruction; when the target heavy metal identification instruction is the last heavy metal identification instruction, the Chuanxiong extract data of the target heavy metal identification instruction is the calculated data obtained by executing the last transition heavy metal identification instruction.
[0026] As an implementable method, the above-mentioned target Chuanxiong extract may include several heavy metal identification instructions, namely, an initial heavy metal identification instruction, a transitional heavy metal identification instruction and a final heavy metal identification instruction. When the target heavy metal identification instruction is the initial heavy metal identification instruction, the business Chuanxiong extract data corresponding to the target Chuanxiong extract can be obtained, and the business Chuanxiong extract data can be used as the Chuanxiong extract data of the target heavy metal identification instruction.
[0027] As another feasible method, when the target heavy metal identification instruction is any transition heavy metal identification instruction, the business Chuanxiong extract data corresponding to the target Chuanxiong extract can be obtained, and the transition heavy metal identification instruction is executed on the business Chuanxiong extract data to obtain calculated data, and the calculated data is used as the Chuanxiong extract data of the target heavy metal identification instruction.
[0028] It can be understood that the above-mentioned target heavy metal identification instruction and the transition heavy metal identification instruction have a dependency relationship, which means that there is a data association relationship between the target heavy metal identification instruction and the transition heavy metal identification instruction, that is, the calculation data generated by executing the transition heavy metal identification instruction is used as the Chuanxiong extract data of the target heavy metal identification instruction.
[0029] As another feasible method, when the target heavy metal identification instruction is the last heavy metal identification instruction, the business Chuanxiong extract data corresponding to the target Chuanxiong extract can be obtained, and then the transition heavy metal identification instruction is executed on the business Chuanxiong extract data to obtain calculation data, and the next transition heavy metal identification instruction is executed based on the calculation data until the last transition heavy metal identification instruction is executed to obtain calculation data, and then the calculation data generated by the last transition heavy metal identification instruction is used as the Chuanxiong extract data of the target heavy metal identification instruction.
[0030] In one possible implementation, the business processing component may send a request for obtaining Chuanxiong extract data to the data storage component, and the request for obtaining Chuanxiong extract data may include a target heavy metal identification instruction tag, and then the data storage component responds to the request for obtaining Chuanxiong extract data, and based on the target heavy metal identification instruction tag, sends the calculated data generated by the previous heavy metal identification instruction of the target heavy metal identification instruction as Chuanxiong extract data to the business processing component, so that the business processing component obtains the Chuanxiong extract data of the target heavy metal identification instruction, and then executes the target heavy metal identification instruction based on the Chuanxiong extract data.
[0031] S102. After the target heavy metal identification instruction is executed, determine that there is at least one detection instruction corresponding to the target heavy metal identification instruction; the detection instruction is used to perform data detection in a data detection manner.
[0032] It is understandable that transition data will be generated after the execution of the target heavy metal identification instruction. In order to avoid quality problems in the subsequent application of data, it is necessary to adopt the idea of continuous integration. After the execution of the target heavy metal identification instruction, the generated transition data is tested. The detection instruction corresponding to the target heavy metal identification instruction can be determined first, and the detection instruction is executed to detect the transition data generated by the target heavy metal identification instruction. The detection instruction is pre-trained according to the data requirements of the target heavy metal identification instruction, and the number of detection instructions can be one, two or several.
[0033] In this embodiment, after executing the target heavy metal identification instruction on the obtained Chuanxiong extract data, at least one detection instruction corresponding to the target heavy metal identification instruction is automatically determined, so that after the execution of the target heavy metal identification instruction is completed, the transition data detection response generated by the target heavy metal identification instruction can be quickly performed, and the data can be detected and processed in a timely manner, so that the detection instruction can be executed on the transition data generated by the target heavy metal identification instruction in a targeted manner later.
[0034] S103, executing at least one detection instruction on the transition data generated by the target heavy metal identification instruction to obtain a detection result of the transition data.
[0035] As an implementable method, after determining at least one detection instruction, several detection instructions can be sorted from few to many according to the number of data description features corresponding to the detection method, so as to obtain detection instructions including a single detection method and detection instructions including a joint detection method, and then execute the detection instructions including the single detection method and execute the detection instructions including the joint detection method, so as to obtain the detection results of the transition data.
[0036] As another achievable method, at least one detection instruction may be summarized to obtain a detection instruction table, and each detection instruction in the detection instruction table may be executed in sequence from top to bottom in the detection instruction table to obtain a detection result of the transition data.
[0037] Among them, in the process of executing each detection instruction, the data description feature corresponding to the detection instruction can be obtained from the transition data, and then the detection instruction is executed, and the data description feature is detected and processed using the detection method corresponding to the detection instruction. For example, it can be checked whether the data description feature is empty, or it can be checked whether the data volume of the data description feature meets the preset data volume, so as to obtain the detection result corresponding to the detection instruction.
[0038] Exemplarily, taking the WeChat payment entrusted deduction business scenario as an example, the target heavy metal identification instruction is an automatic deduction task, and the Chuanxiong extract data of the target heavy metal identification instruction can be obtained. The Chuanxiong extract data can include merchant tags, merchant order numbers, WeChat payment order numbers, order amounts, etc., and the automatic deduction task is executed. When the automatic deduction task is executed, transition data is generated, and then it is determined that there is at least one detection instruction corresponding to the automatic deduction task. For example, for one of the detection instructions, the detection instruction is executed, and the data detection field in the transition data is checked to see whether it is empty, and then the data description feature of the empty data detection field is determined as the detection result of the transition data.
[0039] The method for identifying heavy metal cadmium in Chuanxiong extract provided in the embodiment of the present application, compared with the prior art, on the one hand, automatically determines at least one detection instruction corresponding to the target heavy metal identification instruction after executing the target heavy metal identification instruction on the obtained Chuanxiong extract data, so that after the execution of the target heavy metal identification instruction is completed, it can quickly perform a detection response on the transition data generated by the target heavy metal identification instruction, and then perform detection and processing on the data in a timely manner, and provide accurate task guidance information for subsequent data detection by determining the detection instruction, so that the detection instruction can be executed in a targeted manner on the transition data generated by the target heavy metal identification instruction.
[0040] In another embodiment of the present application, a specific implementation method of a target heavy metal identification instruction and a data detection method is also provided. The above-mentioned target heavy metal identification instruction is used to execute the target Chuanxiong extract, and the data detection method is related to the data requirements of the target Chuanxiong extract.
[0041] It is understandable that the target Chuanxiong extract may include several heavy metal identification instructions, and there is a data association relationship between every two connected heavy metal identification instructions, that is, the transition data generated by executing the previous heavy metal identification instruction is the Chuanxiong extract data for executing the next heavy metal identification instruction. Each heavy metal identification instruction is used to execute the target Chuanxiong extract, that is, the target heavy metal identification instruction is used to execute the target Chuanxiong extract. The target Chuanxiong extract may, for example, refer to a WeChat payment entrusted deduction service, and the target heavy metal identification instruction may, for example, be a deduplication task, a scheduled deduction task, etc.
[0042] During the execution of the target Chuanxiong extract, it is necessary to implement business processing by executing several heavy metal identification instructions respectively. Among them, each heavy metal identification instruction such as the target heavy metal identification instruction needs to meet some data requirements after execution. Therefore, the data detection method can be set according to the data requirements of the target Chuanxiong extract to detect the transition data generated after the heavy metal identification instruction is executed. Different target heavy metal identification instructions need to meet different data requirements, and the corresponding data detection methods are also different.
[0043] The data requirements of the target Chuanxiong extract include several different data description features, and the data detection method includes a separate detection method of the data description features and a joint detection method between different data description features.
[0044] It can be understood that the above-mentioned single detection method refers to the detection method corresponding to a data description feature, which can be understood as the constraint requirements that a single data description feature needs to meet during the processing. The above-mentioned joint detection method refers to the collaborative detection method between two or more different data description features with an associated relationship, which can be understood as the constraint requirements that need to be coordinated and met between two or more different data description features with an associated relationship. For example, it can mean that under the premise that a certain data description feature takes effect, other data description features need to meet the specified requirements. Among them, two or more different data description features with an associated relationship can refer to two or more different data description features with a corresponding relationship that has a logical correlation or a numerical correlation. Logical correlation refers to the existence of a connection relationship or a causal relationship between two or more different data description features. Numerical correlation means that there is a dependency relationship between the numerical values of two or more different data description features, which can be understood as the numerical value of a data description feature among several different data description features being the sum or difference of other data description features.
[0045] As another feasible method, the above-mentioned joint detection method may be the data requirements that need to be met by two or several different data description features with a correlation in the transition data generated after executing the target heavy metal identification instruction. For example, it may be to detect whether a data description feature meets the requirements specified under the premise that other data description features are effective, or it may be to detect whether the values of several data description features are unique.
[0046] Exemplarily, the above-mentioned joint detection method can be that a data description feature among several data description features detects the data attributes of other data description features under the premise that the data attributes are effective. Among them, the effectiveness of the data attributes of the data description feature means that the field format, data volume, data value range, etc. of the data description feature meet the requirements.
[0047] In another embodiment of the present application, the above-mentioned separate detection method includes at least one of the first detection method and the second detection method. The first detection method is used to detect whether the data description feature is empty; the second detection method is used to detect whether the data volume of the data description feature meets the preset data volume.
[0048] The above-mentioned joint detection method includes at least one of the first sub-method and the second sub-method. The first sub-method is used to detect whether the data description feature meets the requirements specified under the premise that other data description features are effective; the second sub-method is used to detect whether the value of the data description feature is unique.
[0049] It can be understood that the above-mentioned data description features and other data description features can be determined from the transition data generated after executing a certain heavy metal identification instruction, or can be determined from several transition data generated after executing different heavy metal identification instructions respectively, and there is a data association relationship between the different heavy metal identification instructions.
[0050] In another embodiment of the present application, after determining at least one detection instruction of the target heavy metal identification instruction, a specific implementation method is provided for executing at least one detection instruction on the transition data generated by the target heavy metal identification instruction to obtain the detection result of the transition data.
[0051] Each detection instruction has a corresponding detection instruction label. Before executing each detection instruction, it is necessary to obtain the data description features corresponding to the detection instruction from the transition data according to the detection instruction label, and then execute the detection instruction. The data description features are detected using a data detection method to obtain the detection results corresponding to each detection instruction.
[0052] In one possible implementation, when the detection method is the first detection method in a separate detection method, a first data description feature corresponding to the first detection method can be obtained in the transition data, and a detection instruction corresponding to the first inspection method can be executed to determine whether the first data description feature is empty, and based on whether the first data description feature is empty, the detection result of the transition data is determined.
[0053] It can be understood that the above-mentioned first data description feature refers to a field that needs to be detected by the first detection method. In this embodiment, the detection instruction label of the first detection method can be obtained, and the first data description feature corresponding to the first detection method can be found from the transition data according to the detection instruction label of the first detection method, and then the detection instruction corresponding to the first detection method is executed to determine whether the first data description feature is empty. When the first data description feature is not empty, it indicates that the first data description feature is normal; when the first data description feature is empty, it indicates that the first data description feature is abnormal, and the first data description feature information of the empty field is counted.
[0054] In another possible implementation method, when the detection method is the second detection method in the separate detection method, a second data description feature corresponding to the second detection method can be obtained in the transition data, and a detection instruction corresponding to the second detection method can be executed to determine whether the data volume of the second data description feature meets the preset data volume, and the detection result of the transition data is determined based on whether the second data description feature meets the preset data volume.
[0055] It can be understood that the above-mentioned second data description feature refers to a field that needs to be detected by the second detection method. In this embodiment, the detection instruction label of the second detection method can be obtained, and the second data description feature corresponding to the second detection method can be found from the transition data according to the detection instruction label of the second detection method, and then the detection instruction corresponding to the second detection method is executed to determine whether the data volume of the second data description feature meets the preset data volume. When the data volume of the second data description feature meets the preset data volume, the second data description feature is characterized as normal; when the data volume of the second data description feature does not meet the preset data volume, the second data description feature is characterized as abnormal, and the second data description feature information whose statistical data volume does not meet the preset data volume is counted, such as the number of fields and field names whose statistical data volume does not meet the preset data volume, to obtain the detection result corresponding to the detection instruction.
[0056] In another possible implementation method, when the detection method is the first sub-method in the joint detection method, the third data description feature corresponding to the first sub-method and other data description features related to the third data description feature can be obtained in the transition data, and then the detection instruction corresponding to the first sub-method is executed to determine whether the third data description feature meets the requirements specified under the premise that other data description features are effective, and the detection result of the transition data is determined based on whether the third data description feature meets the requirements specified under the premise that other data description features are effective.
[0057] It is understandable that the third data description feature refers to a field that needs to be detected by the first sub-method. Other data description features related to the third data description feature refer to fields that have a logical relationship or a numerical relationship with the third data description feature. The first sub-method may include a single-table logical consistency method and a single-table equivalent consistency method.
[0058] In this embodiment, when the first sub-mode is a single-table logical consistency mode, a detection instruction label of the single-table logical consistency mode can be obtained, and according to the detection instruction label of the single-table logical consistency mode, a third data description feature corresponding to the single-table logical consistency mode and other related data description features are searched from the transition data, and then the detection instruction corresponding to the single-table logical consistency mode is executed to determine whether the third data description feature is consistent with the logical relationship with other data description features under the premise that other data description features are effective. When the logical relationship is consistent, the third data description feature is characterized as normal; when the logical relationship is inconsistent, the third data description feature is characterized as abnormal.
[0059] When the first sub-method is the single-table equivalent consistency method, a detection instruction label of the single-table equivalent consistency method can be obtained, and according to the detection instruction label of the single-table equivalent consistency method, a third data description feature and other data description features corresponding to the single-table equivalent consistency method are searched from the transition data, and the third data description feature has a data correlation relationship with the other data description features. Then, the detection instruction corresponding to the single-table equivalent consistency method is executed to determine whether the third data description feature is consistent with the numerical relationship with other data description features under the premise that other data description features are effective. When the numerical relationship is consistent, the third data description feature is characterized as normal; when the logical relationship is inconsistent, the third data description feature is characterized as abnormal.
[0060] In another possible implementation method, when the detection method is the second sub-method in the joint detection method, the fourth data description feature corresponding to the second sub-method can be obtained in the transition data, and the detection instruction corresponding to the second sub-method can be executed to determine whether the value of the fourth data description feature meets the value uniqueness requirement, and the detection result of the transition data is determined based on whether the value of the fourth data description feature meets the value uniqueness requirement.
[0061] It can be understood that the fourth data description feature refers to a field that needs to be detected by the second sub-mode. In this embodiment, the second sub-mode can include detecting the uniqueness of the data value, and the fourth data description feature corresponding to the second sub-mode of the value range can be found from the transition data according to the detection instruction tag of the second sub-mode, and then the detection instruction corresponding to the second sub-mode is executed to determine whether the value of the fourth data description feature meets the value uniqueness requirement, for example, it can be detected whether a data description feature is unique or whether a combination of several data description features is unique. When the value of the fourth data description feature meets the value uniqueness requirement, the fourth data description feature is characterized as normal; when the value of the fourth data description feature does not meet the value uniqueness requirement, the fourth data description feature is characterized as abnormal, and the fourth data description feature information that does not meet the value uniqueness requirement is counted, for example, the number of fields and field names that do not meet the value uniqueness requirement are counted to obtain the detection result corresponding to the detection instruction.
[0062] In this embodiment, by executing no less than one detection instruction on the transition data generated by the target heavy metal identification instruction, the transition data can be detected and processed in a finer granularity, thereby accurately obtaining the detection results of the transition data, thereby ensuring the quality and reliability of the data.
[0063] In another embodiment of the present application, before determining that the target heavy metal identification instruction corresponds to at least one detection instruction, a specific implementation method for training the detection instruction is also provided. The method includes: S201. Obtain data requirements of target Chuanxiong extract through a training port.
[0064] S202: Generate at least one data detection method based on the data requirement, and determine at least one detection instruction corresponding to at least one data detection method.
[0065] It can be understood that the above-mentioned training port refers to the entry for obtaining the data requirements of the target Chuanxiong extract, including training items of the detection method, which detection method may include a separate detection method and a combined detection method. The separate detection method may include a first detection method and a second detection method. The combined detection method may include a first sub-method and a second sub-method. The first sub-method may include a single-table logical consistency method and a single-table equivalent consistency method. The second sub-method may include a data value consistency method.
[0066] Optionally, the constraints that the data must comply with when executing the target Chuanxiong extract can be obtained in advance, and then an interface input file can be generated based on the constraints. Then, in response to a training input operation, the data requirements of the target Chuanxiong extract can be obtained through a training port based on the interface input file. In response to a task creation instruction, at least one data detection method can be generated based on the data requirements of the target Chuanxiong extract, and at least one corresponding detection instruction can be created based on at least one data detection method.
[0067] In this embodiment, the detection personnel can train the relevant parameters of the data detection method according to the detection requirements, and when the corresponding training input operation is detected, the training input operation is responded to, and the input content is obtained to obtain the data requirements of the target Chuanxiong extract. After the data requirements of the target Chuanxiong extract are prepared, if a task creation instruction is received, the task creation instruction is responded to, and at least one data detection method is generated according to the data requirements of the target Chuanxiong extract, and then at least one corresponding detection instruction is created based on at least one data detection method.
[0068] After obtaining the data requirements of the target Chuanxiong extract through the training port, at least one data detection method is generated based on the data requirements, and then a corresponding detection instruction is generated according to each data detection method.
[0069] In another embodiment of the present application, after the target heavy metal identification instruction is executed, a specific implementation method for determining at least one detection instruction corresponding to the target heavy metal identification instruction is provided. On the basis of the above embodiment, the present application determines at least one detection instruction corresponding to the target heavy metal identification instruction. The method includes: S301, obtaining a label of a target heavy metal identification instruction.
[0070] S302, determining at least one detection instruction corresponding to the target heavy metal identification instruction according to the label of the target heavy metal identification instruction and the detection method training information; the detection method training information is used to indicate at least one heavy metal identification instruction label and the detection instruction corresponding to each heavy metal identification instruction label.
[0071] In order to explain the present application more clearly, the following further describes the method for identifying heavy metal cadmium in the extract of Chuanxiong proposed in the present application. The method for identifying heavy metal cadmium in the extract of Chuanxiong provided in the embodiment of the present application comprises: S401, obtaining the target heavy metal identification instruction of the Chuanxiong extract data, and executing the target heavy metal identification instruction on the Chuanxiong extract data.
[0072] S402: After the target heavy metal identification instruction is executed, determine at least one detection instruction corresponding to the target heavy metal identification instruction according to the label of the target heavy metal identification instruction and the detection method training information.
[0073] S403: Obtain data description features corresponding to the detection method in the transition data.
[0074] S404: Execute a detection instruction corresponding to the detection method based on the data description feature to obtain a detection result of the transition data.
[0075] The embodiment of the present application automatically determines at least one detection instruction corresponding to the target heavy metal identification instruction after executing the target heavy metal identification instruction on the obtained Chuanxiong extract data, so that after executing the target heavy metal identification instruction, it can quickly detect and respond to the transition data generated by the target heavy metal identification instruction, and then detect and process the data in a timely manner, and provide accurate task guidance information for subsequent data detection by determining the detection instruction, so that the detection instruction can be executed in a targeted manner on the transition data generated by the target heavy metal identification instruction. And by executing at least one detection instruction on the transition data generated by the target heavy metal identification instruction, it is possible to detect and process the transition data comprehensively and in a more fine-grained manner by executing several detection instructions, so as to accurately obtain the detection results of the transition data, and then timely discover data quality problems, avoid realizing the errors of the data when using the data later, ensure the quality and reliability of the data, and improve the efficiency of data detection.
[0076] On the basis of the above, a system for identifying heavy metal cadmium in Chuanxiong extract is shown, including a processor and a memory that communicate with each other, and the processor is used to read and execute a computer program from the memory to implement the above method.
[0077] Based on the above, a computer-readable storage medium is also provided, on which a computer program stored implements the above method when running.
[0078] In summary, based on the above scheme, first, by obtaining the Chuanxiong extract data of the target heavy metal identification instruction, the target heavy metal identification instruction is executed based on the Chuanxiong extract data. In addition, after the execution of the target heavy metal identification instruction is completed, it is determined that at least one detection instruction corresponds to the target heavy metal identification instruction, and the detection instruction is used to perform data detection using a data detection method, and then at least one detection instruction is executed based on the business data generated by the target heavy metal identification instruction to obtain the detection result of the business data. Compared with the prior art, the technical solution in this application can improve the accuracy of heavy metal cadmium identification, and can accurately remove it when it is removed later.
[0079] It can be seen that in the embodiments of the present disclosure, the movement mode of the important movement content of each improvement item in the movement-to-cognitive function description data can be dimensionally simplified, and then, the improvement evaluation results in the movement-to-cognitive function description data can be compared based on the dimensionless simplified movement mode information of each improvement item in the movement-to-cognitive function description data; by dimensionally simplifying the movement mode of the important movement content of each improvement item in the movement-to-cognitive function description data, the accuracy and reliability of the evaluation can be improved.
[0080] It should be understood that the system and its modules shown above can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or a dedicated design hardware. Those skilled in the art will understand that the above methods and systems can be implemented using computer executable instructions and / or included in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application can not only be implemented by hardware circuits such as ultra-large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but can also be implemented by software such as executed by various types of processors, and can also be implemented by a combination of the above hardware circuits and software (e.g., firmware).
[0081] It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects that may be produced may be any one or a combination of the above, or any other possible beneficial effects.
Claims
1. A method for identifying heavy metal cadmium in Chuanxiong extract, It is characterized in that The method comprises: Obtaining the target heavy metal identification instruction of the Chuanxiong extract data, and executing the target heavy metal identification instruction on the Chuanxiong extract data; After the target heavy metal identification instruction is executed, determining that at least one detection instruction corresponds to the target heavy metal identification instruction; the detection instruction is used to perform data detection in a data detection manner; The at least one detection instruction is executed on the transition data generated by the target heavy metal identification instruction to obtain the heavy metal cadmium content data in the Chuanxiong extract.
2. The method according to claim 1, It is characterized in that The target heavy metal identification instruction is used to execute the target Chuanxiong extract, and the data detection method is related to the data requirements of the target Chuanxiong extract.
3. The method according to claim 2, It is characterized in that The data requirements of the target Chuanxiong extract include several different data description features, and the data detection method includes a separate detection method of the data description features and a joint detection method between different data description features.
4. The method according to claim 3, It is characterized in that The separate detection method includes at least one of the first detection method and the second detection method; Among them, the first detection method is used to detect whether the data description feature is empty; the second detection method is used to detect whether the data volume of the data description feature meets the preset data volume.
5. The method according to claim 3 or 4, It is characterized in that The joint detection method includes at least one of the first sub-method and the second sub-method; The first sub-method is used to detect whether the data description feature meets the requirements specified under the premise that other data description features are effective; the second sub-method is used to detect whether the value of the data description feature is unique.
6. The method according to claim 4, It is characterized in that Executing the at least one detection instruction on the transition data generated by the target heavy metal identification instruction to obtain the heavy metal cadmium content data in the Chuanxiong extract, including: Obtaining a first data description feature corresponding to the first detection method in the transition data; Execute a detection instruction corresponding to the first detection method to determine whether the first data description feature is empty; According to whether the first data description feature is empty, the heavy metal cadmium content data in the Chuanxiong extract is determined.
7. The method according to claim 4, It is characterized in that Executing the at least one detection instruction on the transition data generated by the target heavy metal identification instruction to obtain the heavy metal cadmium content data in the Chuanxiong extract, including: Obtaining a second data description feature corresponding to the second detection mode in the transition data; Executing a detection instruction corresponding to the second detection method to determine whether the amount of data describing the second data characteristic meets a preset amount of data; The heavy metal cadmium content data in the Chuanxiong extract is determined based on whether the data volume of the second data description feature meets the preset data volume.
8. The method according to claim 5, It is characterized in that Executing the at least one detection instruction on the transition data generated by the target heavy metal identification instruction to obtain the heavy metal cadmium content data in the Chuanxiong extract, including: Obtaining a third data description feature corresponding to the first sub-mode and other data description features related to the third data description feature in the transition data; Execute the detection instruction corresponding to the first sub-mode to determine whether the third data description feature meets the requirements defined under the premise that the other data description features are effective; Determine the heavy metal cadmium content data in the Chuanxiong extract according to whether the third data field meets the requirements defined under the premise that the other data description features are effective; Wherein, executing the at least one detection instruction on the transition data generated by the target heavy metal identification instruction to obtain the heavy metal cadmium content data in the Chuanxiong extract includes: Obtaining a fourth data description feature corresponding to the second sub-mode in the transition data; Execute a detection instruction corresponding to the second sub-characteristic to determine whether the value of the fourth data description feature meets the value uniqueness requirement; The heavy metal cadmium content data in the Chuanxiong extract is determined based on whether the value of the fourth data description feature meets the value uniqueness requirement.
9. The method according to claim 2, It is characterized in that The method further comprises: Obtaining data requirements of the target Chuanxiong extract through a training port; Generate at least one data detection method based on the data requirement, and determine at least one detection instruction corresponding to the at least one data detection method; Wherein, determining that the target heavy metal identification instruction corresponds to at least one detection instruction specifically includes: According to the label of the target heavy metal identification instruction and the detection method training information, determine at least one detection instruction corresponding to the target heavy metal identification instruction; the detection method training information is used to indicate at least one heavy metal identification instruction label and the detection instruction corresponding to each heavy metal identification instruction label.
10. A system for identifying heavy metal cadmium in Chuanxiong extract. It is characterized in that The invention comprises a processor and a memory communicating with each other, wherein the processor is used to read a computer program from the memory and execute the computer program to implement the method according to any one of claims 1 to 9.