A drug detection method and system based on big data

Abstract

The present invention provides a drug detection method and system based on big data, the method comprising: detecting the target production drug corresponding to the liquid drug production line in real time, and detecting the target drug information corresponding to the target production drug in real time in the preset drug database; when it is detected in real time that the target production drug is transferred to the first preset detection area, judging in real time whether the production dosage of the target production drug meets the first preset requirement according to the first preset rule; if so, adding a first label to the target production drug, and transferring the target production drug to the second preset detection area, and judging in real time whether the production components of the target production drug meet the second preset requirement according to the second preset rule; if so, adding a second label to the target production drug, so as to complete the detection of the target production drug. The present invention can complete the detection of liquid drugs in an all-round way, and correspondingly improve the work efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of drug detection, and in particular to a drug detection method and system based on big data. Background Art

[0002] With the advancement of science and technology and the development of the times, people have developed various types of medicines, including solid medicines, liquid medicines, and gaseous medicines, etc., to treat different patients.

[0003] Among them, existing liquid medicines need to undergo corresponding testing before they are officially shipped out of the factory. Specifically, the existing technology will transfer the liquid medicines produced in real time to the existing drug testing equipment, and further complete the testing of the current liquid medicines through the drug testing equipment to determine in real time whether the liquid medicines meet the factory requirements.

[0004] Furthermore, due to the large number of liquid medicines produced, most of the existing technologies rely on staff to use existing medicine testing equipment to conduct random inspections on the produced liquid medicines, and judge the production status of the medicines in real time based on the inspection results. However, this detection method is prone to missing defective medicines and false detection, thereby correspondingly reducing the yield of the product. Summary of the invention

[0005] Based on this, the purpose of the present invention is to provide a drug detection method and system based on big data to solve the problem of missing bad drugs and misdetection in the prior art.

[0006] The first aspect of the embodiment of the present invention proposes:

[0007] A drug detection method based on big data, wherein the method is used to detect liquid drugs, and the method comprises:

[0008] When it is detected in real time that the liquid drug production line is started, the target production drug corresponding to the liquid drug production line is detected in real time, and the target drug information corresponding to the target production drug is detected in real time in the preset drug database, the target drug information including the production dosage and production ingredients corresponding to the target production drug;

[0009] When it is detected in real time that the target production drug is transferred to the first preset detection area, it is determined in real time according to the first preset rule whether the production dosage of the target production drug meets the first preset requirement;

[0010] If it is determined in real time according to the first preset rule that the production dosage of the target production drug meets the first preset requirement, a first label is added to the target production drug, and the target production drug is transferred to a second preset detection area, and it is determined in real time according to the second preset rule whether the production ingredients of the target production drug meet the second preset requirement;

[0011] If it is determined in real time according to the second preset rule that the production ingredients of the target drug meet the second preset requirement, a second label is added to the target drug to complete the detection of the target drug.

[0012] The beneficial effect of the present invention is that by real-time detection of target production drugs in the production line, the required target drug information can be obtained, based on which subsequent analysis and detection can be carried out. Furthermore, by respectively setting a first preset detection area for detecting dosage and a second preset detection area for detecting ingredients on the production line, it is possible to comprehensively detect whether the drugs produced in real time meet the corresponding requirements, thereby correspondingly improving work efficiency.

[0013] Furthermore, the step of determining in real time according to the first preset rule whether the production dosage of the target production drug meets the first preset requirement includes:

[0014] When it is detected that the target production drug is located in the first preset detection area, a target pressure value corresponding to the target production drug is collected in real time by a preset collection device, and the target pressure value is a specific numerical value;

[0015] Detecting in real time the target drug model corresponding to the target production drug in the preset drug database, and constructing in real time the corresponding drug data chain according to the target drug model, the production dosage and the production ingredients;

[0016] According to the target pressure value and the drug data link, it is determined in real time whether the production dosage of the target drug meets the first preset requirement.

[0017] Furthermore, the step of determining in real time according to the target pressure value and the drug data link whether the production dosage of the target drug meets the first preset requirement includes:

[0018] When the drug data link is acquired in real time, the drug data link is set as a matching object, and the corresponding target conversion coefficient is detected in real time in the preset drug database according to the drug data link;

[0019] When the target pressure value is acquired in real time, a target resistance signal corresponding to the target pressure value is detected in real time, and the target resistance signal is converted into a corresponding target voltage signal in real time according to the target conversion coefficient;

[0020] Whether the production dosage of the target produced drug meets the first preset requirement is determined in real time according to the target resistance signal and the target voltage signal.

[0021] Furthermore, the step of determining in real time whether the production dosage of the target produced drug meets the first preset requirement according to the target resistance signal and the target voltage signal includes:

[0022] Determine in real time in the preset drug database a qualified dosage threshold value corresponding to the target production drug, and calculate in real time the corresponding actual production dosage according to the target resistance signal and the target voltage signal based on a preset algorithm;

[0023] Determine in real time whether the actual production dose is within the range of the dose qualification threshold;

[0024] If it is determined in real time that the actual production dose is within the range of the qualified dose threshold, it is correspondingly determined that the production dose of the target production drug satisfies the first preset requirement.

[0025] Furthermore, the expression of the preset algorithm is:

[0026] D = a ⋅ V + b ⋅1 / R + c

[0027] Among them, a represents the voltage coefficient, b represents the resistance coefficient, V represents the target voltage signal, R represents the target resistance signal, c represents the dose constant, and D represents the actual production dose.

[0028] Furthermore, the step of determining in real time according to the second preset rule whether the production components of the target production drug meet the second preset requirement includes:

[0029] When it is detected in real time that the target production drug is located in the second preset detection area, sampling processing is performed on the target production drug to obtain a corresponding detection sample in real time;

[0030] Performing component analysis on the test sample in real time through a preset detection device to output a corresponding analysis report in real time, wherein the analysis report includes a number of analysis elements;

[0031] In real time, judging based on a number of the analysis elements whether the production ingredients of the target drug meet the second preset requirement.

[0032] Furthermore, the step of determining in real time based on the plurality of analysis elements whether the production components of the target drug meet the second preset requirement includes:

[0033] When a plurality of analysis elements are obtained, respectively extracting the actual detection value corresponding to each analysis element in the analysis report;

[0034] According to the drug data link, the qualified detection threshold corresponding to each of the analytical elements is matched in the preset drug database, and the actual detection value of each of the analytical elements is judged one by one whether it is within the range of the corresponding qualified detection threshold;

[0035] If it is determined in real time that the actual detection value of each of the analyzed elements is within the range of the corresponding detection qualified threshold, then it is determined that the production components of the target production drug meet the second preset requirement, so as to complete the detection of the target production drug.

[0036] The second aspect of the embodiment of the present invention proposes:

[0037] A drug detection system based on big data, which is used to detect liquid drugs, and the system includes:

[0038] A detection module, for detecting in real time when the liquid drug production line is detected to be started, detecting in real time the target production drug corresponding to the liquid drug production line, and detecting in real time the target drug information corresponding to the target production drug in a preset drug database, wherein the target drug information includes the production dosage and production ingredients corresponding to the target production drug;

[0039] A first judgment module is used to judge in real time whether the production dosage of the target production drug meets the first preset requirement according to the first preset rule when it is detected in real time that the target production drug is transferred to the first preset detection area;

[0040] A second judgment module is used for adding a first label to the target production drug, transferring the target production drug to a second preset detection area, and judging in real time according to the second preset rule whether the production component of the target production drug meets the second preset requirement if it is judged in real time according to the first preset rule that the production dosage of the target production drug meets the first preset requirement;

[0041] The output module is used to add a second label to the target production drug if it is determined in real time according to the second preset rule that the production ingredients of the target production drug meet the second preset requirement, so as to complete the detection of the target production drug.

[0042] Furthermore, the first determination module is specifically used for:

[0043] When it is detected that the target production drug is located in the first preset detection area, a target pressure value corresponding to the target production drug is collected in real time by a preset collection device, and the target pressure value is a specific numerical value;

[0044] Detecting in real time the target drug model corresponding to the target production drug in the preset drug database, and constructing in real time the corresponding drug data chain according to the target drug model, the production dosage and the production ingredients;

[0045] According to the target pressure value and the drug data link, it is determined in real time whether the production dosage of the target drug meets the first preset requirement.

[0046] Furthermore, the first determination module is specifically used for:

[0047] When the drug data link is acquired in real time, the drug data link is set as a matching object, and the corresponding target conversion coefficient is detected in real time in the preset drug database according to the drug data link;

[0048] When the target pressure value is acquired in real time, a target resistance signal corresponding to the target pressure value is detected in real time, and the target resistance signal is converted into a corresponding target voltage signal in real time according to the target conversion coefficient;

[0049] Whether the production dosage of the target produced drug meets the first preset requirement is determined in real time according to the target resistance signal and the target voltage signal.

[0050] Furthermore, the first determination module is specifically used for:

[0051] Determine in real time in the preset drug database a qualified dosage threshold value corresponding to the target production drug, and calculate in real time the corresponding actual production dosage according to the target resistance signal and the target voltage signal based on a preset algorithm;

[0052] Determine in real time whether the actual production dose is within the range of the dose qualification threshold;

[0053] If it is determined in real time that the actual production dose is within the range of the qualified dose threshold, it is correspondingly determined that the production dose of the target production drug satisfies the first preset requirement.

[0054] Furthermore, the expression of the preset algorithm is:

[0055] D = a ⋅ V + b ⋅1 / R + c

[0056] Among them, a represents the voltage coefficient, b represents the resistance coefficient, V represents the target voltage signal, R represents the target resistance signal, c represents the dose constant, and D represents the actual production dose.

[0057] Furthermore, the second judgment module is specifically used for:

[0058] When it is detected in real time that the target production drug is located in the second preset detection area, sampling processing is performed on the target production drug to obtain a corresponding detection sample in real time;

[0059] Performing component analysis on the test sample in real time through a preset detection device to output a corresponding analysis report in real time, wherein the analysis report includes a number of analysis elements;

[0060] In real time, judging based on a number of the analysis elements whether the production ingredients of the target drug meet the second preset requirement.

[0061] Furthermore, the second judgment module is specifically used for:

[0062] When a plurality of analysis elements are obtained, respectively extracting the actual detection value corresponding to each analysis element in the analysis report;

[0063] According to the drug data link, the qualified detection threshold corresponding to each of the analytical elements is matched in the preset drug database, and the actual detection value of each of the analytical elements is judged one by one whether it is within the range of the corresponding qualified detection threshold;

[0064] If it is determined in real time that the actual detection value of each of the analyzed elements is within the range of the corresponding detection qualified threshold, then it is determined that the production components of the target production drug meet the second preset requirement, so as to complete the detection of the target production drug.

[0065] The third aspect of the embodiment of the present invention proposes:

[0066] A computer comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the drug detection method based on big data as described above is implemented.

[0067] The fourth aspect of the embodiments of the present invention proposes:

[0068] A readable storage medium stores a computer program, wherein when the program is executed by a processor, the drug detection method based on big data as described above is implemented.

[0069] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 A flowchart of a drug detection method based on big data provided by the first embodiment of the present invention;

[0071] Figure 2 A structural block diagram of a drug detection system based on big data provided in the third embodiment of the present invention.

[0072] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0073] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0074] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0075] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0076] See also Figure 1 , shown is the drug detection method based on big data provided by the first embodiment of the present invention. The drug detection method based on big data provided by this embodiment can complete the detection of production drugs in an all-round way, thereby correspondingly improving the product yield and work efficiency.

[0077] Specifically, this embodiment provides:

[0078] A drug detection method based on big data is used to detect liquid drugs, the method comprising:

[0079] Step S10, when it is detected in real time that the liquid drug production line is started, the target production drug corresponding to the liquid drug production line is detected in real time, and the target drug information corresponding to the target production drug is detected in real time in a preset drug database, the target drug information including the production dosage and production ingredients corresponding to the target production drug;

[0080] Step S20, when it is detected in real time that the target production drug is transferred to the first preset detection area, judging in real time according to the first preset rule whether the production dosage of the target production drug meets the first preset requirement;

[0081] Step S30, if it is determined in real time according to the first preset rule that the production dosage of the target production drug meets the first preset requirement, then a first label is added to the target production drug, and the target production drug is transferred to a second preset detection area, and it is determined in real time according to the second preset rule whether the production ingredients of the target production drug meet the second preset requirement;

[0082] Step S40: If it is determined in real time according to the second preset rule that the production ingredients of the target drug meet the second preset requirement, a second label is added to the target drug to complete the detection of the target drug.

[0083] Specifically, in this embodiment, it should be noted that, in order to be able to comprehensively and accurately complete the detection of produced drugs, it is necessary to accurately obtain the information of the produced drugs and the corresponding detection standards, based on which, targeted detection can be performed on different types of drugs. Specifically, in the actual application process, when the server set in the background detects in real time that the production line of a certain type of liquid drug is started, the server will immediately enable the drug detection method, and further, the current server will first detect the target production drug corresponding to the current production line, and at the same time, further detect the target drug information corresponding to the current target production drug in real time in the drug database pre-set inside it, based on which, the present invention will further extract the production dosage and production ingredients that are compatible with the current target production drug in real time from the current target drug information, that is, the qualified dosage and qualified ingredients that meet the production requirements, and only when both parameters are met, can it be determined that the real-time production drug meets the production requirements.

[0084] Furthermore, the present invention will pre-set the required first preset detection area and second preset detection area in the drug production line, wherein the first preset detection area is used to focus on detecting whether the production dosage of the drug meets the requirements, and correspondingly, the second preset detection area is used to focus on detecting whether the production ingredients of the drug meet the requirements. It should be pointed out that if the same drug meets both of the above requirements, it can be directly determined that the drug currently produced in real time is a qualified product. Correspondingly, if the same drug does not meet one of the requirements, or both requirements are not met, it can be directly determined that the drug currently produced in real time is an unqualified product, so that it can comprehensively and accurately detect whether the drug is qualified, which correspondingly improves the yield of the drug and improves work efficiency.

[0085] Second embodiment

[0086] Furthermore, the step of determining in real time according to the first preset rule whether the production dosage of the target production drug meets the first preset requirement includes:

[0087] When it is detected that the target production drug is located in the first preset detection area, a target pressure value corresponding to the target production drug is collected in real time by a preset collection device, and the target pressure value is a specific numerical value;

[0088] Detecting in real time the target drug model corresponding to the target production drug in the preset drug database, and constructing in real time the corresponding drug data chain according to the target drug model, the production dosage and the production ingredients;

[0089] According to the target pressure value and the drug data link, it is determined in real time whether the production dosage of the target drug meets the first preset requirement.

[0090] Furthermore, the step of determining in real time according to the target pressure value and the drug data link whether the production dosage of the target drug meets the first preset requirement includes:

[0091] When the drug data link is acquired in real time, the drug data link is set as a matching object, and the corresponding target conversion coefficient is detected in real time in the preset drug database according to the drug data link;

[0092] When the target pressure value is acquired in real time, a target resistance signal corresponding to the target pressure value is detected in real time, and the target resistance signal is converted into a corresponding target voltage signal in real time according to the target conversion coefficient;

[0093] Whether the production dosage of the target produced drug meets the first preset requirement is determined in real time according to the target resistance signal and the target voltage signal.

[0094] Furthermore, the step of determining in real time whether the production dosage of the target produced drug meets the first preset requirement according to the target resistance signal and the target voltage signal includes:

[0095] Determine in real time in the preset drug database a qualified dosage threshold value corresponding to the target production drug, and calculate in real time the corresponding actual production dosage according to the target resistance signal and the target voltage signal based on a preset algorithm;

[0096] Determine in real time whether the actual production dose is within the range of the dose qualification threshold;

[0097] If it is determined in real time that the actual production dose is within the range of the qualified dose threshold, it is correspondingly determined that the production dose of the target production drug satisfies the first preset requirement.

[0098] Furthermore, the expression of the preset algorithm is:

[0099] D = a ⋅ V + b ⋅1 / R + c

[0100] Among them, a represents the voltage coefficient, b represents the resistance coefficient, V represents the target voltage signal, R represents the target resistance signal, c represents the dose constant, and D represents the actual production dose.

[0101] Furthermore, the step of determining in real time according to the second preset rule whether the production components of the target production drug meet the second preset requirement includes:

[0102] When it is detected in real time that the target production drug is located in the second preset detection area, sampling processing is performed on the target production drug to obtain a corresponding detection sample in real time;

[0103] Performing component analysis on the test sample in real time through a preset detection device to output a corresponding analysis report in real time, wherein the analysis report includes a number of analysis elements;

[0104] In real time, judging based on a number of the analysis elements whether the production ingredients of the target drug meet the second preset requirement.

[0105] Furthermore, the step of determining in real time based on the plurality of analysis elements whether the production components of the target drug meet the second preset requirement includes:

[0106] When a plurality of analysis elements are obtained, respectively extracting the actual detection value corresponding to each analysis element in the analysis report;

[0107] According to the drug data link, the qualified detection threshold corresponding to each of the analytical elements is matched in the preset drug database, and the actual detection value of each of the analytical elements is judged one by one whether it is within the range of the corresponding qualified detection threshold;

[0108] If it is determined in real time that the actual detection value of each of the analyzed elements is within the range of the corresponding detection qualified threshold, then it is determined that the production components of the target production drug meet the second preset requirement, so as to complete the detection of the target production drug.

[0109] In addition, in this embodiment, it should be noted that after the required target drug information is obtained in real time through the above steps, subsequent analysis and judgment will be immediately performed. Specifically, in the actual application process, the above target production drug will be continuously circulated in the production line, wherein, when the target production drug is transferred to the above first preset detection area, the target pressure value corresponding to the current target production drug will be synchronously collected, that is, a specific value is detected in real time. Based on this, in order to facilitate subsequent judgment, it is necessary to further obtain the judgment basis corresponding to the current target production drug. Preferably, the present invention will first detect the target drug model corresponding to the current target production drug in real time through the above preset drug database, wherein it should be pointed out that each target drug model is unique. Based on this, in order to further improve the accuracy of subsequent retrieval, the present invention will further construct a corresponding drug data chain based on the current production dosage, production ingredients and target drug model in real time, and can further use the current drug data chain as the corresponding matching object, and further detect the target conversion coefficient adapted to the current target production drug in real time in the above preset drug database. Based on this, the subsequent calculation process can be further completed. Preferably, the present invention can detect the target resistance signal corresponding to the current target pressure value in real time based on the existing circuit principle, wherein it should be pointed out that the weight corresponding to the current target production drug can be further calculated according to the voltage and resistance generated in real time, based on which the net content of the current target production drug, that is, the dosage of the current target production drug, can be further obtained, based on which the present invention will further convert the current target resistance signal into the required target voltage signal through the above-mentioned target conversion coefficient, on this basis, the present invention will further input the current target resistance signal and the target voltage signal into the above-mentioned preset algorithm, and can further output the actual production dosage corresponding to the current target production drug, at the same time, the dosage qualification threshold corresponding to the current target production drug is further determined in real time in the above-mentioned preset drug database, based on which it can be directly judged whether the current actual production dosage is within the range of the current dosage qualification threshold, specifically, if so, it can be correspondingly explained that the current target production drug meets the first preset requirement, correspondingly, if not, it can be directly determined that the current target production drug does not meet the current first preset requirement, thereby effectively completing a screening, so as to facilitate subsequent processing.

[0110] Furthermore, when it is determined in real time that the target production drug meets the first preset requirement, the subsequent circulation will be further carried out at this time, and it can be further transferred to the above-mentioned second preset detection area. Specifically, the present invention will perform real-time sampling processing on the target production drug passing through the current second preset detection area to obtain the required test samples. Based on this, in order to further improve the detection efficiency, the present invention will directly transfer the obtained test samples to the inside of the pre-set detection equipment, and can further complete the corresponding detection analysis through the detection equipment, and can further output the corresponding analysis report. Based on this, in order to shorten the subsequent analysis time, the present invention will further detect several analysis elements contained in the current analysis report, and at the same time, synchronously extract the actual detection values ​​corresponding to each analysis element in the current analysis report. Based on this, in order to quickly complete the subsequent judgment, the present invention will further match the detection qualified threshold corresponding to each current analysis element in the above-mentioned preset drug database according to the above-mentioned drug data link, and will judge one by one whether the actual detection value of each current analysis element is within the range of the corresponding detection qualified threshold. Specifically, if so, it can be finally determined that the current target production drug is a qualified product. Correspondingly, if not, it can be directly determined that the current target production drug is an unqualified product, so that the detection of each target production drug can be completed comprehensively and accurately, which correspondingly improves the yield rate and work efficiency of the drug.

[0111] See also Figure 2 , the third embodiment of the present invention provides:

[0112] A drug detection system based on big data, which is used to detect liquid drugs, and the system includes:

[0113] A detection module, for detecting in real time when the liquid drug production line is detected to be started, detecting in real time the target production drug corresponding to the liquid drug production line, and detecting in real time the target drug information corresponding to the target production drug in a preset drug database, wherein the target drug information includes the production dosage and production ingredients corresponding to the target production drug;

[0114] A first judgment module is used to judge in real time whether the production dosage of the target production drug meets the first preset requirement according to the first preset rule when it is detected in real time that the target production drug is transferred to the first preset detection area;

[0115] A second judgment module is used for adding a first label to the target production drug, transferring the target production drug to a second preset detection area, and judging in real time according to the second preset rule whether the production component of the target production drug meets the second preset requirement if it is judged in real time according to the first preset rule that the production dosage of the target production drug meets the first preset requirement;

[0116] The output module is used to add a second label to the target production drug if it is determined in real time according to the second preset rule that the production ingredients of the target production drug meet the second preset requirement, so as to complete the detection of the target production drug.

[0117] Furthermore, the first determination module is specifically used for:

[0118] When it is detected that the target production drug is located in the first preset detection area, a target pressure value corresponding to the target production drug is collected in real time by a preset collection device, and the target pressure value is a specific numerical value;

[0119] Detecting in real time the target drug model corresponding to the target production drug in the preset drug database, and constructing in real time the corresponding drug data chain according to the target drug model, the production dosage and the production ingredients;

[0120] According to the target pressure value and the drug data link, it is determined in real time whether the production dosage of the target drug meets the first preset requirement.

[0121] Furthermore, the first determination module is specifically used for:

[0122] When the drug data link is acquired in real time, the drug data link is set as a matching object, and the corresponding target conversion coefficient is detected in real time in the preset drug database according to the drug data link;

[0123] When the target pressure value is acquired in real time, a target resistance signal corresponding to the target pressure value is detected in real time, and the target resistance signal is converted into a corresponding target voltage signal in real time according to the target conversion coefficient;

[0124] Whether the production dosage of the target produced drug meets the first preset requirement is determined in real time according to the target resistance signal and the target voltage signal.

[0125] Furthermore, the first determination module is specifically used for:

[0126] Determine in real time in the preset drug database a qualified dosage threshold value corresponding to the target production drug, and calculate in real time the corresponding actual production dosage according to the target resistance signal and the target voltage signal based on a preset algorithm;

[0127] Determine in real time whether the actual production dose is within the range of the dose qualification threshold;

[0128] If it is determined in real time that the actual production dose is within the range of the qualified dose threshold, it is correspondingly determined that the production dose of the target production drug satisfies the first preset requirement.

[0129] Furthermore, the expression of the preset algorithm is:

[0130] D = a ⋅ V + b ⋅1 / R + c

[0131] Among them, a represents the voltage coefficient, b represents the resistance coefficient, V represents the target voltage signal, R represents the target resistance signal, c represents the dose constant, and D represents the actual production dose.

[0132] Furthermore, the second judgment module is specifically used for:

[0133] When it is detected in real time that the target production drug is located in the second preset detection area, sampling processing is performed on the target production drug to obtain a corresponding detection sample in real time;

[0134] Performing component analysis on the test sample in real time through a preset detection device to output a corresponding analysis report in real time, wherein the analysis report includes a number of analysis elements;

[0135] In real time, judging based on a number of the analysis elements whether the production ingredients of the target drug meet the second preset requirement.

[0136] Furthermore, the second judgment module is specifically used for:

[0137] When a plurality of analysis elements are obtained, respectively extracting the actual detection value corresponding to each analysis element in the analysis report;

[0138] According to the drug data link, the qualified detection threshold corresponding to each of the analytical elements is matched in the preset drug database, and the actual detection value of each of the analytical elements is judged one by one whether it is within the range of the corresponding qualified detection threshold;

[0139] If it is determined in real time that the actual detection value of each of the analyzed elements is within the range of the corresponding detection qualified threshold, then it is determined that the production components of the target production drug meet the second preset requirement, so as to complete the detection of the target production drug.

[0140] A fourth embodiment of the present invention provides a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the drug detection method based on big data as described above when executing the computer program.

[0141] The fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the drug detection method based on big data as described above.

[0142] In summary, the big data-based drug detection method and system provided in the above embodiments of the present invention can comprehensively complete the detection of produced drugs, thereby correspondingly improving the drug yield and work efficiency.

[0143] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0144] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0145] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0146] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0147] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0148] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A drug detection method based on big data, characterized in that: Used for testing liquid medicine, the method comprises: When it is detected in real time that the liquid drug production line is started, the target production drug corresponding to the liquid drug production line is detected in real time, and the target drug information corresponding to the target production drug is detected in real time in the preset drug database, the target drug information including the production dosage and production ingredients corresponding to the target production drug; When it is detected in real time that the target production drug is transferred to the first preset detection area, it is determined in real time according to the first preset rule whether the production dosage of the target production drug meets the first preset requirement; If it is determined in real time according to the first preset rule that the production dosage of the target production drug meets the first preset requirement, a first label is added to the target production drug, the target production drug is transferred to a second preset detection area, and it is determined in real time according to the second preset rule whether the production ingredients of the target production drug meet the second preset requirement; If it is determined in real time according to the second preset rule that the production component of the target production drug meets the second preset requirement, a second label is added to the target production drug to complete the detection of the target production drug; The step of determining in real time according to the first preset rule whether the production dosage of the target production drug meets the first preset requirement comprises: When it is detected that the target production drug is located in the first preset detection area, a target pressure value corresponding to the target production drug is collected in real time by a preset collection device, and the target pressure value is a specific numerical value; Detecting in real time the target drug model corresponding to the target production drug in the preset drug database, and constructing in real time the corresponding drug data chain according to the target drug model, the production dosage and the production ingredients; Determine in real time whether the production dosage of the target produced drug meets the first preset requirement according to the target pressure value and the drug data link; The step of determining in real time whether the production dosage of the target produced drug meets the first preset requirement according to the target pressure value and the drug data link includes: When the drug data link is acquired in real time, the drug data link is set as a matching object, and the corresponding target conversion coefficient is detected in real time in the preset drug database according to the drug data link; When the target pressure value is acquired in real time, a target resistance signal corresponding to the target pressure value is detected in real time, and the target resistance signal is converted into a corresponding target voltage signal in real time according to the target conversion coefficient; Determine in real time whether the production dosage of the target produced drug meets the first preset requirement according to the target resistance signal and the target voltage signal; The step of determining in real time whether the production dosage of the target produced drug meets the first preset requirement according to the target resistance signal and the target voltage signal comprises: Determine in real time in the preset drug database the qualified dose threshold value corresponding to the target production drug, and calculate in real time the corresponding actual production dose according to the target resistance signal and the target voltage signal based on a preset algorithm; Determine in real time whether the actual production dose is within the dose qualification threshold; If it is determined in real time that the actual production dose is within the range of the qualified dose threshold, then it is determined that the production dose of the target drug meets the first preset requirement; The expression of the preset algorithm is: D = a ⋅ V + b ⋅1 / R + c Among them, a represents the voltage coefficient, b represents the resistance coefficient, V represents the target voltage signal, R represents the target resistance signal, c represents the dose constant, and D represents the actual production dose.

2. The drug detection method based on big data according to claim 1, characterized in that: The step of determining in real time according to the second preset rule whether the production components of the target production drug meet the second preset requirement comprises: When it is detected in real time that the target production drug is located in the second preset detection area, sampling processing is performed on the target production drug to obtain a corresponding detection sample in real time; Performing component analysis on the test sample in real time through a preset detection device to output a corresponding analysis report in real time, wherein the analysis report includes a number of analysis elements; In real time, judging based on a number of the analysis elements whether the production ingredients of the target drug meet the second preset requirement.

3. The drug detection method based on big data according to claim 2, characterized in that: The step of determining in real time based on the plurality of analysis elements whether the production components of the target drug meet the second preset requirement comprises: When a plurality of analysis elements are obtained, respectively extracting the actual detection value corresponding to each analysis element in the analysis report; According to the drug data link, the qualified detection threshold corresponding to each of the analytical elements is matched in the preset drug database, and the actual detection value of each of the analytical elements is judged one by one whether it is within the range of the corresponding qualified detection threshold; If it is determined in real time that the actual detection value of each of the analyzed elements is within the range of the corresponding detection qualified threshold, then it is determined that the production components of the target production drug meet the second preset requirement, so as to complete the detection of the target production drug.

4. A drug detection system based on big data, characterized in that: The method for detecting liquid medicines is used to implement the method for detecting liquid medicines based on big data as claimed in any one of claims 1 to 3, and the system comprises: A detection module, for detecting in real time when the liquid drug production line is detected to be started, detecting in real time the target production drug corresponding to the liquid drug production line, and detecting in real time the target drug information corresponding to the target production drug in a preset drug database, wherein the target drug information includes the production dosage and production ingredients corresponding to the target production drug; A first judgment module is used to judge in real time whether the production dosage of the target production drug meets the first preset requirement according to the first preset rule when it is detected in real time that the target production drug is transferred to the first preset detection area; A second judgment module is used for adding a first label to the target production drug, transferring the target production drug to a second preset detection area, and judging in real time according to the second preset rule whether the production component of the target production drug meets the second preset requirement if it is judged in real time according to the first preset rule that the production dosage of the target production drug meets the first preset requirement; The output module is used to add a second label to the target production drug if it is determined in real time according to the second preset rule that the production ingredients of the target production drug meet the second preset requirement, so as to complete the detection of the target production drug.

5. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the big data-based drug detection method as described in any one of claims 1 to 3 is implemented.

6. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, it implements the big data-based drug detection method as described in any one of claims 1 to 3.

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