WO2019222964A1 - Method for determining detection equipment, detection device and readable storage medium - Google Patents

Abstract

A method for determining detection equipment, a detection device and a readable storage medium. The method for determining detection equipment comprises: acquiring particle composition information of detected matter (101), the particle composition information being used to indicate any one of the following: the detected matter being composed of atoms, the detected matter being composed of molecules, or there being no way to determine the properties of the particles of which the detected matter is composed; and determining detection equipment used for detecting the detected matter according to the particle composition information of the detected matter.

Description

Method for determining detection equipment, detection device and readable storage medium Technical field

The present application relates to the field of detection, and in particular, to a method, a detection device, and a readable storage medium for determining a detection device.

Background technique

At present, there are existing substance detection equipment on the market, including Raman detection equipment and Laser-Induced Breakdown Spectroscopy (Libs) detection equipment. Among them, Raman detection equipment detects molecular information of substances, and Libs detection equipment detects atomic information of substances. If the two are combined to form a two-in-one product, the product can basically detect all substances existing in the world.

technical problem

The inventor has discovered in the process of studying the prior art that the current two-in-one products are simply a combination of the two, that is, two types of detection equipment are put in one structure. The two detection devices are completely independent, with their own detection light paths and different laser focus positions, and there is not much difference between holding a Raman detection device and a Libs detection device. If the user does not know which kind of detection equipment should be used for the detection of a substance, two kinds of detection equipment should be used to detect the substance separately, resulting in a lower detection efficiency of the user.

It can be seen that how to determine which detection equipment is used to detect the detected substance is a problem that needs to be solved.

Technical solutions

A technical problem to be solved in some embodiments of the present application is how to determine which kind of detection equipment is used to detect a substance to be detected.

An embodiment of the present application provides a method for determining a detection device, including: obtaining particle composition information of a detected substance; wherein the particle composition information is used to indicate that the detected substance is composed of atoms, the detected substance is composed of molecules, and Determining any one of the attributes of particles constituting the detected substance; and determining a detection device for detecting the detected substance based on the particle composition information of the detected substance.

An embodiment of the present application further provides a detection device, including an acquisition module and a determination module; the acquisition module is used to acquire particle composition information of a detected substance; wherein the particle composition information is used to indicate that the detected substance is composed of atoms, The detection substance is composed of molecules and the attributes of the particles constituting the detection substance cannot be determined; the determination module is used to determine a detection device for detecting the detection substance based on the particle composition information of the detection substance.

An embodiment of the present application further provides a detection device, including at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are at least A processor executes to enable at least one processor to execute the method for determining a detection device mentioned in the foregoing embodiment.

An embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method for determining a detection device mentioned in the foregoing embodiment is implemented.

Beneficial effect

Compared with the prior art, the embodiments of the present application allow the detection device to determine the detection for detecting the detected substance by acquiring the particle composition information of the detected substance when the user is not sure which detection equipment is used to detect the detected substance. The device improves the detection efficiency of the user and the intelligence of the detection device.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more embodiments are exemplified by the pictures in the accompanying drawings. These exemplary descriptions do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the drawings in the drawings do not constitute a limitation on scale.

1 is a flowchart of a method for determining a detection device according to a first embodiment of the present application;

2 is a flowchart of a method for determining a detection device according to a second embodiment of the present application;

3 is a schematic structural diagram of a detection device according to a third embodiment of the present application;

4 is a schematic structural diagram of a detection device according to a fourth embodiment of the present application;

5 is a schematic structural diagram of a detection device using an independent laser light path structure according to a fourth embodiment of the present application;

6 is a schematic structural diagram of a detection device using a common laser light path structure according to a fourth embodiment of the present application;

FIG. 7 is a schematic structural diagram of a detection device according to a fifth embodiment of the present application.

Embodiments of the invention

In order to make the purpose, technical solution, and advantages of the present application clearer, some embodiments of the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the application, and are not used to limit the application.

It should be noted that the detection devices in the embodiments of the present application are all combined detection devices, and at least two types of detection devices are provided. In the embodiments of the present application, a combination of a Raman detection device and a Libs detection device is taken as an example. For a method of determining the detection device by other combined detection devices, refer to the embodiments of the present application.

The first embodiment of the present application relates to a method for determining a detection device, which is applied to a detection device. As shown in FIG. 1, a method for determining a detection device includes:

Step 101: Obtain particle composition information of the detected substance.

Specifically, the particle composition information is used to indicate any one of an atomic substance to be detected, a molecular substance to be detected, and an attribute whose particles constitute the substance to be detected cannot be determined.

In specific implementation, before acquiring the particle composition information of the detected substance, the detection device determines whether a specified instruction specifying a detection device is received. If a specified instruction is received, the specified detection equipment is directly called to detect the detected substance. For example, if the user knows the properties of the particles constituting the detected substance and manually selects the Libs detection device, the Libs detection device is directly activated. If the designated instruction is not received, the method for determining the detection device is executed to determine the detection device for detecting the detected substance.

Step 102: Determine a detection device for detecting the detected substance according to the particle composition information of the detected substance.

Specifically, if the detection device determines that the particle composition information indicates that the detected substance is composed of atoms, it determines that the detection device for detecting the detected substance is a first detection device, such as a Libs detection device. The first detection device is configured to obtain a first spectrum of the detected substance, and the first spectrum is used to characterize an atomic composition of the detected substance. If the detection device determines that the particle composition information indicates that the detected substance is composed of molecules, it determines that the detection device for detecting the detected substance is a second detection device, such as a Raman detection device. The second detection device is used to obtain a second spectrum of the detected substance, and the second spectrum is used to characterize the molecular composition of the detected substance. If it is determined that the particle composition information indicates that the attributes constituting the detected substance cannot be determined, the detection equipment used to detect the detected substance is determined to be the first detection equipment and the second detection equipment.

In specific implementation, the particle composition information is determined according to the probability that the detected substance is composed of atoms. When the probability that the detected substance is composed of atoms is greater than a preset value, the particle composition information indicates that the detected substance is composed of atoms. When the probability that the detected substance is composed of atoms is not greater than a preset value, the particle composition information indicates that the detected substance is composed of molecules. The preset value can be 50% or 60%.

In another specific implementation, the particle composition information is determined according to the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules.

Compared with the prior art, in the method for determining a detection device provided in this embodiment, when a user is not sure which detection device is used to detect a detected substance, the detection device can determine the The detection equipment for detecting the detected substance improves the detection efficiency of the user and the intelligence of the detection device.

The second embodiment of the present application relates to a method for determining a detection device. This embodiment is a further refinement of the first embodiment, and specifically describes step 101 and other related steps.

As shown in FIG. 2, this embodiment includes steps 201 to 207. Among them, step 203 is substantially the same as step 102 in the first embodiment, which will not be described in detail here. The following mainly describes the differences:

Step 201: Obtain test data of the detected substance.

Specifically, the user places the sample at a specified location and clicks to start the test. When the detection device receives a detection instruction, it obtains test data of the detected substance. The test data of the detected substance includes an image of the detected substance.

Step 202: Input the test data of the detected substance into a classification model trained in advance, and determine the particle composition information of the detected substance according to the output of the classification model.

Specifically, the classification model is used to define the correspondence between the test data of the detected substance and the particle composition information of the detected substance.

The process of training a classification model is described below as an example.

Because atomic substances only include very few substances such as metals, diamonds, graphite, and rare gases, when training classification models, the above substances are used as atomic substances, and substances other than the above substances are used as molecular substances. An image of atomic matter is stored in a training module for training a classification model, and features in the image of atomic matter are extracted through a Convolutional Neural Network (CNN). The training module establishes the correspondence between the features extracted by the CNN and the particle composition information of the detected substance through a classifier.

It is worth mentioning that, because there are fewer types of atomic materials, the amount of training is small, and the difficulty of recognition is lower. Training the classification model for atomic materials reduces the training difficulty.

It should be noted that the process of training the classification model may be performed in a detection device, or may be performed in another device that communicates with the detection device. For example, the training data is transmitted to the cloud, and the classification model is trained by the cloud.

It should be noted that, in practical applications, those skilled in the art can also determine the test data of the detected substance, the method of training the classification model, and the particle composition information according to the use range of the detection equipment provided in the detection device, so that the detection device can When more than two detection devices are provided, a detection device for detecting a substance to be detected is determined. For example, detection devices for detecting molecular substances in the detection device include Raman detection equipment and infrared detection equipment, and the classification model can be trained according to which substances the Raman detection equipment and the infrared detection equipment are suitable for detecting, respectively.

For another example, in addition to the Raman detection device and the Libs detection device, the detection device is also provided with a microwave detection device. Since Raman detection equipment and Libs detection equipment cannot detect the detected substance in the metal bottle, the test data of the detected substance also includes information on the container containing the detected substance. The classification model determines that the detection device for detecting the detection substance is a microwave detection device when it is determined that the detection substance is placed in the metal bottle according to the container information containing the detection substance. When the classification model determines that the test substance is not placed in the metal bottle based on the information of the container containing the test substance, it determines the attributes of the particles constituting the test substance based on the test substance's test data and other data. Further, the classification model determines that the detection device used to detect the detected substance is a Libs detection device or a Raman detection device according to the attributes of the particles constituting the detected substance.

It should be noted that the test data of the detected substance may also include data obtained by detecting the detected substance such as an odor sensor, an infrared sensor, and the like.

In specific implementation, the output of the classification model may be the particle composition information of the detected substance; it may also be the probability that the detected substance is composed of atoms, and the probability that the detected substance is composed of molecules.

In case 1, the output of the classification model is the particle composition information of the detected substance. The classification model determines the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules based on the test data of the detected substance. The output of the classification model is determined based on the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules.

The method of determining the output of the classification model based on the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules is determined below.

Method 1: The classification model determines whether the probability that the detected substance is composed of atoms is greater than the probability that the detected substance is composed of molecules. If so, the output of the classification model is determined to be that the detected substance is composed of atoms; otherwise, the output of the classification model is determined to be detected. Matter is made up of molecules.

Method 2: The classification model determines whether the difference between the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules is greater than a threshold. For example, the threshold is 10%. If the determination is greater than the threshold, the classification model further determines the attributes of the particles constituting the detected substance according to the method described in Mode 1. Otherwise, it is determined that the output of the classification model cannot determine the attributes of the particles constituting the detected substance.

In Case 2, the output of the classification model is the probability that the detected substance is composed of atoms, and the probability that the detected substance is composed of molecules. The detection device determines particle composition information of the detected substance based on the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules.

It should be noted that the detection device determines the particle composition information of the detected substance based on the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules, and the classification model is based on the probability that the detected substance is composed of atoms. , And the probability that the detected substance is composed of molecules, the method of determining the output of the classification model is roughly the same, and is not repeated here.

Go to step 203.

Step 204: Calling a detection device for detecting the detected substance to detect the detected substance.

Step 205: Determine whether the spectrum detected by the detection device for detecting the detected substance meets a preset requirement.

Specifically, the preset requirement may be that the signal-to-noise ratio of the spectrum is in a preset range, and / or there are peaks in the waveform of the spectrum. If the detection device determines that the spectrum meets the preset requirements, step 206 is performed, and if it is determined that the spectrum does not meet the preset requirements, the detection device performs step 207.

Step 206: Determine the detection result of the detected substance according to the spectrum. End the process of determining the detection equipment.

Specifically, the detection device calls a matching algorithm, matches the spectrum of the detected substance with the spectrum of a known sample stored in advance, determines the detection result according to the matching result, and presents the detection result to the user.

In specific implementation, after determining that the spectrum meets the preset requirements, the detection device may use the test data of the detected substance and the particle composition information of the detected substance as training data of the classification model to train the classification model; wherein the classification model is used to define Correspondence between the test data of the test substance and the particle composition information of the test substance.

It is worth mentioning that when training the classification model in the cloud, the data of all detection devices can be used as training data in the cloud, which improves the training speed. The increase in training data makes the training results more accurate.

Step 207: Calling a detection device other than the detection device for detecting the detected substance to detect the detected substance.

Specifically, if the spectrum does not meet the preset requirements, for example, the signal-to-noise ratio of the spectrum does not meet the standard, or the spectrum does not have peaks, it means that the classification model may be incorrectly classified, or the test data of the detected substance is incorrect, resulting in a detection device. Misidentification issues occur, such as misidentifying atomic matter as molecular matter, or the substance being detected as molecular matter without a Raman signal. In this case, another detection device is called to detect the detected substance.

It should be noted that if the detection device used to detect the detected substance is a user-specified detection device, a detection abnormality is prompted, and another detection device may be used for detection.

It should be noted that if the spectra obtained by each detection device of the detection device do not meet the requirements, all the spectra can be displayed, and / or the user is prompted to detect an abnormality.

Compared with the prior art, in the method for determining a detection device provided in this embodiment, when a user is not sure which detection device is used to detect a detected substance, the detection device can determine the The detection equipment for detecting the detected substance improves the detection efficiency of the user and the intelligence of the detection device. In addition, when training a classification model in the cloud, the data of all detection devices can be used as training data in the cloud, which improves the training speed. The increase in training data makes the training results more accurate.

A third embodiment of the present application relates to a detection device. As shown in FIG. 3, the detection device includes an obtaining module 301 and a determining module 302. The obtaining module 301 is configured to obtain particle composition information of a detected substance. Among them, the particle composition information is used to indicate any one of an atomic substance to be detected, a molecular substance to be detected, and an attribute whose particles constitute the substance to be detected cannot be determined. The determining module 302 is configured to determine a detection device for detecting the detected substance according to the particle composition information of the detected substance.

It is not difficult to find that this embodiment is a system embodiment corresponding to the first embodiment, and this embodiment can be implemented in cooperation with the first embodiment. The related technical details mentioned in the first embodiment are still valid in this embodiment. To reduce repetition, details are not described here. Accordingly, the related technical details mentioned in this embodiment can also be applied in the first embodiment.

The fourth embodiment of the present application relates to a detection device. This embodiment is a refinement of the third embodiment, and specifically describes the function of the acquisition module and other modules of the detection device.

As shown in FIG. 4, the detection device includes: an obtaining module 401, a determining module 402, and a calling module 403.

The obtaining module 401 is specifically configured to obtain test data of a detected substance, input the test data of the detected substance into a classification model trained in advance, and determine particle composition information of the detected substance according to an output of the classification model.

The calling module 403 is used to call the detection device for detecting the detected substance to detect the detected substance; determine whether the spectrum detected by the detection device for detecting the detected substance meets the preset requirements, and if so, determine the detection result of the detected substance according to the spectrum ; Otherwise, call a detection device other than the detection device for detecting the detected substance to detect the detected substance.

It should be noted that in FIG. 4, the detection device uses the first detection device 404 and the second detection device 405 as examples to describe the structure of the detection device. In practical applications, the number of detection devices can be set as required.

It should be noted that, in practical applications, the first detection device 404 and the second detection device 405 may be set so that the focal points do not coincide, and the two may be set as a common focus. The first detection device 404 and the second detection device 405 may be two independent laser light paths, or they may share the last part of the laser light path. Among them, a detection device using an independent laser light path structure is shown in FIG. 5, and a detection device using a common laser light path structure is shown in FIG. 6.

It is not difficult to find that this embodiment is a system embodiment corresponding to the second embodiment, and this embodiment can be implemented in cooperation with the second embodiment. The related technical details mentioned in the second embodiment are still valid in this embodiment. To reduce repetition, details are not described here. Accordingly, the related technical details mentioned in this embodiment can also be applied in the second embodiment.

A fifth embodiment of the present application relates to a detection device, as shown in FIG. 7, including at least one processor 501; and a memory 502 communicatively connected to the at least one processor 501. The memory 502 stores instructions that can be executed by the at least one processor 501, and the instructions are executed by the at least one processor 501, so that the at least one processor 501 can execute the method for determining a detection device.

In this embodiment, the processor 501 is a central processing unit (Central Processing Unit, CPU) as an example, and the memory 502 is a readable and writable memory (Random Access Memory (RAM) as an example. The processor 501 and the memory 502 may be connected through a bus or in other manners. In FIG. 7, the connection through the bus is taken as an example. The memory 502 is a non-volatile computer-readable storage medium and can be used to store non-volatile software programs, non-volatile computer executable programs, and modules. For example, the classification model in the embodiment of the present application can be stored in the memory. 502. The processor 501 executes various functional applications and data processing of the device by running non-volatile software programs, instructions, and modules stored in the memory 502, that is, the above method for determining a detection device is implemented.

The memory 502 may include a storage program area and a storage data area, where the storage program area may store an operating system and an application program required for at least one function; the storage data area may store a list of options and the like. In addition, the memory 502 may include a high-speed random access memory, and may further include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 502 may optionally include a memory remotely set relative to the processor, and these remote memories may be connected to an external device through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

One or more modules are stored in the memory, and when executed by one or more processors, execute the method for determining a detection device in any of the foregoing method embodiments.

The above product can execute the method provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not described in this embodiment, refer to the method provided in the embodiment of the present application.

A sixth embodiment of the present application relates to a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method for determining a detection device described in any of the above method embodiments is implemented.

That is, those skilled in the art can understand that all or part of the steps in the method of the above embodiments can be implemented by a program instructing related hardware. The program is stored in a storage medium and includes several instructions to make a device ( It may be a single-chip microcomputer, a chip, or the like) or a processor that executes all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks or optical disks and other media that can store program code .

Those of ordinary skill in the art can understand that the foregoing embodiments are specific embodiments for implementing the present application, and in practical applications, various changes can be made in form and details without departing from the spirit and range.

Claims (16)

 A method for determining a detection device, including: Obtain particle composition information of a detected substance; wherein the particle composition information is used to indicate that the substance to be detected is composed of atoms, the substance to be detected is composed of molecules, and attributes of particles that constitute the substance to be detected cannot be determined Any one of A detection device for detecting the detected substance is determined according to the particle composition information of the detected substance.  The method for determining a detection device according to claim 1, wherein the determining a detection device for detecting the detected substance based on particle composition information of the detected substance specifically includes: If it is determined that the particle composition information indicates that the detected substance is composed of atoms, determining that the detection device for detecting the detected substance is a first detection device; wherein the first detection device is configured to acquire the A first spectrum of a detected substance, the first spectrum being used to characterize an atomic composition of the detected substance; If it is determined that the particle composition information indicates that the detected substance is composed of molecules, it is determined that the detection device for detecting the detected substance is a second detection device; wherein the second detection device is used for obtaining the A second spectrum of the detected substance, the second spectrum being used to characterize the molecular composition of the detected substance; If it is determined that the particle composition information indicates that the attributes constituting the detected substance cannot be determined, it is determined that the detection device for detecting the detected substance is the first detection device and the second detection device.  The method for determining a detection device according to claim 1 or 2, wherein the acquiring particle composition information of a detected substance specifically comprises: Acquiring test data of the detected substance; wherein the test data of the detected substance includes an image of the detected substance; Input test data of the detected substance into a classification model trained in advance, and determine particle composition information of the detected substance according to the output of the classification model; wherein the classification model is used to define the detected substance Corresponding relationship between the test data and the particle composition information of the detected substance.  The method for determining a detection device according to claim 3, wherein the test data of the detected substance further comprises data obtained by detecting the detected substance by an odor sensor and / or an infrared sensor.  The method for determining a detection device according to claim 3 or 4, wherein the output of the classification model is particle composition information of the detected substance; the specific process of determining the output of the classification model is: Determining, according to test data of the detected substance, a probability that the detected substance is composed of atoms, and a probability that the detected substance is composed of molecules; An output of the classification model is determined according to a probability that the detected substance is composed of atoms and a probability that the detected substance is composed of molecules.  The method for determining a detection device according to claim 5, wherein the output of the classification model is determined based on a probability that the detected substance is composed of atoms and a probability that the detected substance is composed of molecules, specifically include: Determining whether the probability that the detected substance is composed of atoms is greater than the probability that the detected substance is composed of molecules; If yes, determine that the output of the classification model is that the detected substance consists of atoms; Otherwise, it is determined that the output of the classification model is that the detected substance is composed of molecules.  The method for determining a detection device according to claim 5, wherein determining the output of the classification model according to a probability that the detected substance is composed of atoms and a probability that the detected substance is composed of molecules specifically includes: If it is determined that the difference between the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules is not greater than a threshold, determining that the output of the classification model is that the attributes of the particles constituting the detected substance cannot be determined; .  The method for determining a detection device according to claim 3 or 4, wherein the output of the classification model is a probability that the detected substance is composed of atoms, and a probability that the detected substance is composed of molecules; The determining particle composition information of the detected substance based on the output of the classification model specifically includes: Determining whether the probability that the detected substance is composed of atoms is greater than the probability that the detected substance is composed of molecules; If yes, determining that the particle composition information indicates that the detected substance consists of atoms; Otherwise, it is determined that the particle composition information indicates that the detected substance is composed of molecules.  The method for determining a detection device according to claim 6 or 8, wherein before determining whether the probability that the detected substance is composed of atoms is greater than the probability that the detected substance is composed of molecules, the determination detection device The method also includes: It is determined that a difference between a probability that the detected substance is composed of atoms and a probability that the detected substance is composed of molecules is greater than a threshold.  The method for determining a detection device according to claim 3 or 4, wherein the output of the classification model is a probability that the detected substance is composed of atoms, and a probability that the detected substance is composed of molecules; The determining particle composition information of the detected substance based on the output of the classification model specifically includes: If it is determined that the difference between the probability that the detected substance is composed of atoms and the probability that the detected substance is composed of molecules is not greater than a threshold, determining the particle composition information of the detected substance indicates that the composition of the detected substance cannot be determined Particle properties.  The method for determining a detection device according to any one of claims 1 to 10, wherein after the determining a detection device for detecting the detected substance, the method for determining a detection device further comprises: Calling the detection device for detecting the detected substance to detect the detected substance; Determining whether the spectrum detected by the detection device for detecting the detected substance meets a preset requirement; If yes, determine a detection result of the detected substance according to the spectrum; Otherwise, a detection device other than the detection device for detecting the detection substance is called to detect the detection substance.  The method for determining a detection device according to claim 11, wherein the preset requirement is that a signal-to-noise ratio of the spectrum is in a preset range, and / or a waveform of the spectrum has a peak.  The method for determining a detection device according to claim 11 or 12, wherein after determining that the spectrum meets the preset requirement, the method for determining a detection device further comprises: Use the test data of the test substance and the particle composition information of the test substance as training data for the classification model to train the classification model; wherein the classification model is used to define the test data and the test substance of the test substance. The correspondence relationship of the particle composition information of the detected substance is described.  A detection device, including: an acquisition module and a determination module; The acquisition module is used to acquire particle composition information of the detected substance; wherein the particle composition information is used to indicate that the detected substance is composed of atoms, the detected substance is composed of molecules, and the detected substance cannot be determined to constitute the detected substance Any of the properties of the particles of matter; The determination module is configured to determine a detection device for detecting the detected substance according to the particle composition information of the detected substance. A detection device comprising at least one processor; and A memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processing The device is capable of performing the method for determining a detection device according to any one of claims 1 to 13.  A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the method for determining a detection device according to any one of claims 1 to 13 is implemented.