阅读说明：本技术 实验室化学物质检测系统 (laboratory chemical substance detecting system ) 是由 邢希学 于 2019-08-20 设计创作，主要内容包括：本发明涉及化学检测技术领域,具体涉及一种实验室化学物质检测系统,包括终端检测系统和数据处理系统,终端检测系统包括化学物质检测设备和数据上传处理终端,化学物质检测设备将检测后的数据通过数据上传处理终端上传至数据处理系统,数据处理系统利用数据分类算法、数据加密算法和相似数据处理算法处理后通过通信系统将处理后的数据传送至实验室控制终端；本发明通过化学物质检测设备检测待检测物质,并将检测的结果通过数据处理系统,利用数据分类算法、数据加密算法和相似数据处理算法处理后得到安全性更高、准确度更好,数据冗余更低的检测结果,并通过通信系统实现远程智能连接,具有很强的创造性。(the invention relates to the technical field of chemical detection, in particular to a laboratory chemical substance detection system which comprises a terminal detection system and a data processing system, wherein the terminal detection system comprises chemical substance detection equipment and a data uploading processing terminal, the chemical substance detection equipment uploads detected data to the data processing system through the data uploading processing terminal, and the data processing system processes the data by using a data classification algorithm, a data encryption algorithm and a similar data processing algorithm and then transmits the processed data to a laboratory control terminal through a communication system; the invention detects the substance to be detected through the chemical substance detection equipment, obtains the detection result with higher safety, better accuracy and lower data redundancy after the detection result is processed through the data processing system and the data classification algorithm, the data encryption algorithm and the similar data processing algorithm, realizes remote intelligent connection through the communication system, and has strong creativity.)

1. The laboratory chemical substance detection system is characterized by comprising a terminal detection system and a data processing system, wherein the terminal detection system comprises chemical substance detection equipment and a data uploading processing terminal, the chemical substance detection equipment uploads detected data to the data processing system through the data uploading processing terminal, and the data processing system utilizes a data classification algorithm, a data encryption algorithm and a similar data processing algorithm to process the processed data and then transmits the processed data to a laboratory control terminal through a communication system.

2. the laboratory chemical detection system according to claim 1, wherein the chemical detection apparatus detects using a sensing system sensitive to various chemicals and converts the concentration thereof into an electric signal; the data uploading processing terminal collects, stores, retrieves, processes, transforms and transmits data, and can be processed by manual or automatic devices.

3. The laboratory chemical detection system according to claim 1, wherein in the data classification algorithm, data uploaded to a processing terminal are optimally planned to obtain a weight coefficient of each data belonging to each category;

wherein the content of the first and second substances,to construct an objective functionOptimal planning with minimum value, s.t. as limiting condition, w_i,jProbability that the ith piece of data of the uploading processing terminal belongs to the jth category, d_i,jthe central distance between the ith data of the uploading processing terminal and the jth category is determined, p is the total number of data uploaded by the data uploading processing terminal, K is preset to divide the data of the uploading processing terminal into K categories, and N is the central distance between the ith data of the uploading processing terminal and the jth category^*is a set of positive integers.

4. The laboratory chemical detection system of claim 3, wherein, during the optimal planning process,

Wherein, C_i,lprocessing the ith value of the terminal's ith data for upload, F_j,lThe first value is the center of the preset jth category, and l is the number of values contained in each piece of data.

5. The laboratory chemical detection system of claim 3, wherein said data classification algorithm determines the preset number of classes k by:

T1, initializing, and enabling K to be 2, and selecting a first piece of data and a second piece of data uploaded by a data uploading processing terminal as an initial classification center;

t2, respectively calculating the distance d between each piece of data of the uploading processing terminal and the classification center_i,jacquiring the distance d between each piece of data uploaded by the uploading processing terminal and all the classification centers_i,jdistance d of each piece of data from all classification centers_i,jthe classification corresponding to the minimum value in the data is used as the classification of the data;

T3, calculating the overall stability of the category;

Wherein D is_KFor a stability classified as K, i ∈ F_jThe value of i is the data of all the uploading processing terminals belonging to the j-th class, S_jThe total number of data of the uploading processing terminal contained in the jth class, lambda is a preset interference coefficient, and lambda belongs to N^*；

T4, taking the central point of all data of each category as a new classification center;

T5, increasing the classification number by 1, and the classification centers of the newly added classes are as follows:

wherein, F_k+1,lThe ith value of the classification center for the newly added class;

T6, repeatedly calculating T2 and T3, and judging D_K≤D_K+1And if so, classifying the data uploaded by the data uploading processing terminal into K classes, and if not, enabling the classification center to be the classification center determined by T4, otherwise, repeating T2 to T6 after K is K + 1.

6. the laboratory chemical substance detection system according to claim 1, wherein in the similar data processing algorithm, data is defined, a data set BD ═ (C2, a), and a value set C2 ═ C2₁,C2₂,C2₃…C2_P) Class set a ═ a₁,A₂,...A_KAnd for each data in the value set C2_PThe categories can be found in category set a.

7. The laboratory chemical detection system according to claim 6, wherein in said similarity data processing algorithm, a data similarity is calculated, performing the steps of:

s1, acquiring data in all numerical value sets corresponding to a certain category in the category set as a calculation data set of the category;

S2, taking the central points of all the data of the calculation data set as category centers;

S3, calculating the matching degree of all data in the calculation data set with the category center respectively;

Where ρ is_ito calculate the degree of matching between the ith piece of data in the dataset and the category center, C3_i,tTo calculate the t value, Z, of the ith piece of data in the dataset_tthe t-th value of the category center, l is the number of values contained in each element in the value set C2, i is 1,2, 3 … V, and V is the total number of data contained in the calculation data set;

S4, calculating the similarity rho of the selected categories;

and solving the similarity of all the categories to obtain a set, wherein the set is the data similarity, meanwhile, for the data which is randomly increased, calculating the matching degree of the data and all the category centers, and selecting the category with the maximum matching degree as the category of the increased data.

8. The laboratory chemical detection system of claim 1, wherein said chemical detection apparatus comprises: a detection circuit and a detection device are provided,

The detection circuit includes: a first resistor R1, a second resistor R2, a third resistor R3, a fourth resistor R4, a fifth resistor R5, a sixth resistor R6, a seventh resistor R7, an eighth resistor R8, a ninth resistor R9, a tenth resistor R10, an eleventh resistor R11, a twelfth resistor R12, a first capacitor C1, a second capacitor C2, a third capacitor C3, a fourth capacitor C4, a first diode L1, a second diode L2, a third diode L3, a fourth diode L4, a fifth diode L5, a sixth diode L6, a D flip-flop RS, an NPN transistor Q1, a power supply VCC, a ground GND, a first operational amplifier a1, and a second operational amplifier a 2;

The power source VCC is respectively connected with the cathode of a first diode L1 and one end of a first resistor R1, the anode of the first diode L1 and the other end of the first resistor R1 are respectively connected with the collector of an NPN transistor Q1, the base of the NPN transistor Q1 is connected with one end of a second resistor R2, the other end of the second resistor R2 is connected with the Q electrode of a D trigger RS, the S electrode of the D trigger RS is respectively connected with one ends of a third resistor R3 and a first capacitor C1, the R electrode of the D trigger RS is connected with one ends of a fourth resistor R4 and a second capacitor C2, and the other ends of the first capacitor C1 and the second capacitor C2 are connected with the cathode of the third diode L3;

The power supply VCC is also respectively connected with the anode of a third diode L3, one end of a third capacitor C3, the cathode of a second diode L2 and one end of the detection equipment;

the emitter of the NPN transistor Q1, the other ends of the third resistor R3 and the fourth resistor R4, the anode of the second diode L2 and the other end of the detection device are connected with the ground GND;

The other end of the third capacitor C3 is connected to one end of an eighth resistor R8, the anode of a fourth diode L4, the positive input end of a second operational amplifier a2, and one end of a fifth resistor R5; one end of the fifth resistor R5 is connected with one end of a sixth resistor R6;

the inverting input end of the second operational amplifier A2 is connected with one end of a seventh resistor R7;

the output end of the second operational amplifier a2 is connected to the other ends of an eighth resistor R8 and a fourth diode L4, respectively, and is further connected to one end of the ninth resistor R9, the other end of the ninth resistor R9 is connected to the positive input end of a first operational amplifier a1, and the reverse input end of the first operational amplifier a1 is connected to one end of a tenth resistor R10;

The output end of the first operational amplifier a1 is connected to the anode of a fifth diode L5 and the cathode of a sixth diode L6, respectively, the anode of the sixth diode L6 is connected to one end of an eleventh resistor R11, and the other end of the eleventh resistor R11 is connected to the cathode of a fifth diode L5, one end of a twelfth resistor R12 and one end of a fourth capacitor C4, respectively;

The other ends of the sixth resistor R6, the seventh resistor R7, the tenth resistor R10, the twelfth resistor R12 and the fourth capacitor C4 are connected to the ground GND.

Technical Field

The invention relates to the technical field of chemical detection, in particular to a laboratory chemical substance detection system.

Background

A Laboratory (Laboratory/Lab) is a place where a test is performed. The laboratory is a scientific cradle, is a base of scientific research and a source of scientific development, and plays a very important role in the scientific development.

In chemical substance detection, REACH is a european union regulation which is a regulation proposal related to production, trade and use safety of chemicals, and the regulation aims at protecting human health and environmental safety, maintaining and improving competitiveness of the european union chemical industry, developing innovation capability of nontoxic and harmless compounds, preventing market division, increasing use transparency of chemicals, promoting non-animal experiments, pursuing social sustainable development and the like. The REACH directive requires that chemicals imported and produced in europe must go through a comprehensive set of procedures such as registration, evaluation, authorization and restriction to better and more easily identify the chemical composition for the purpose of ensuring environmental and human safety. The instruction mainly comprises a plurality of items of registration, evaluation, authorization, limitation and the like. Any commercial product must have a registry of listed chemical components and instructions on how to use them and toxicity assessment reports. All information is entered into an ongoing database managed by a new european union agency, european chemical agency, located in helsinki, finland. The institution will evaluate each profile and if the chemical is found to have an impact on human health or the environment, they may take more rigorous measures. Depending on the evaluation of several factors, chemicals may be banned or require approval before use.

Therefore, the laboratory chemical substance detection system which has higher detection efficiency, realizes intelligent data transmission and more scientific data processing is urgently provided.

Disclosure of Invention

Aiming at the defects of the prior art, the invention discloses a laboratory chemical substance detection system, which utilizes a data classification algorithm, a data encryption algorithm and a similar data processing algorithm to process to obtain a detection result with higher safety, better accuracy and lower data redundancy, and realizes remote intelligent connection through a communication system.

The invention is realized by the following technical scheme:

the laboratory chemical substance detection system is characterized by comprising a terminal detection system and a data processing system, wherein the terminal detection system comprises chemical substance detection equipment and a data uploading processing terminal, the chemical substance detection equipment uploads detected data to the data processing system through the data uploading processing terminal, and the data processing system utilizes a data classification algorithm, a data encryption algorithm and a similar data processing algorithm to process the processed data and then transmits the processed data to a laboratory control terminal through a communication system.

Preferably, the chemical substance detection device utilizes a sensing system sensitive to various chemical substances and converts the concentration of the sensing system into an electric signal for detection; the data uploading processing terminal collects, stores, retrieves, processes, transforms and transmits data, and can be processed by manual or automatic devices.

Preferably, in the data classification algorithm, optimal planning is performed on the data uploaded to the processing terminal, so that a weight coefficient of each data belonging to each category is obtained;

Wherein the content of the first and second substances,to construct an objective functionOptimal planning with minimum value, s.t. as limiting condition, w_i,jprobability that the ith piece of data of the uploading processing terminal belongs to the jth category, d_i,jThe central distance between the ith data of the uploading processing terminal and the jth category is determined, p is the total number of data uploaded by the data uploading processing terminal, K is preset to divide the data of the uploading processing terminal into K categories, and N is the central distance between the ith data of the uploading processing terminal and the jth category^*Is a set of positive integers.

Preferably, the planning unit is configured to, during the optimal planning process,

wherein, C_i,lProcessing the ith value of the terminal's ith data for upload, F_j,lThe l value of the center of the preset j categoryAnd l is the number of values contained in each piece of data.

Preferably, the data classification algorithm determines the preset number k of classes by:

T1, initializing, and enabling K to be 2, and selecting a first piece of data and a second piece of data uploaded by a data uploading processing terminal as an initial classification center;

T2, respectively calculating the distance d between each piece of data of the uploading processing terminal and the classification center_i,jAcquiring the distance d between each piece of data uploaded by the uploading processing terminal and all the classification centers_i,jDistance d of each piece of data from all classification centers_i,jThe classification corresponding to the minimum value in the data is used as the classification of the data;

t3, calculating the overall stability of the category;

Wherein D is_Kfor the stability classified into K classes, i belongs to Fj and takes the value of i as the data of all the uploading processing terminals belonging to the j class, S_jThe total number of data of the uploading processing terminal contained in the jth class, lambda is a preset interference coefficient, and lambda belongs to N^*；

T4, taking the central point of all data of each category as a new classification center;

T5, increasing the classification number by 1, and the classification centers of the newly added classes are as follows:

Wherein, F_k+1,lThe ith value of the classification center for the newly added class;

T6, repeatedly calculating T2 and T3, and judging D_K≤D_K+1And if so, classifying the data uploaded by the data uploading processing terminal into K classes, and if not, enabling the classification center to be the classification center determined by T4, otherwise, repeating T2 to T6 after K is K + 1.

Preferably, in the similar data processing algorithm,Data are defined, data set BD ═ C2, a, and value set C2 ═ C2₁,C2₂,C2₃…C2_P) Class set a ═ a₁,A₂,...A_Kand for each data in the value set C2_PThe categories can be found in category set a.

preferably, in the similar data processing algorithm, the data similarity is calculated, and the following steps are performed:

s1, acquiring data in all numerical value sets corresponding to a certain category in the category set as a calculation data set of the category;

S2, taking the central points of all the data of the calculation data set as category centers;

S3, calculating the matching degree of all data in the calculation data set with the category center respectively;

where ρ is_ito calculate the degree of matching between the ith piece of data in the dataset and the category center, C3_i,tTo calculate the t value, Z, of the ith piece of data in the dataset_tThe t-th value of the category center, l is the number of values contained in each element in the value set C2, i is 1,2, 3 … V, and V is the total number of data contained in the calculation data set;

s4, calculating the similarity rho of the selected categories;

and solving the similarity of all the categories to obtain a set, wherein the set is the data similarity, meanwhile, for the data which is randomly increased, calculating the matching degree of the data and all the category centers, and selecting the category with the maximum matching degree as the category of the increased data.

Preferably, in the data classification algorithm, the data uploaded by the data uploading processing terminal is processed

Expressed as the following mathematical programming function

So that1≤i≤n；u_ij≥0,1≤i≤n,1≤j≤c；1≤j≤c,Furthermore, the utility model is provided withIs a spatial s-dimensional data set, where n, i, j, m, c are all natural numbers, n is the number of samples in the data set, c is the number of cluster centers, and m is a weight coefficient.

Preferably, in the mathematical programming function, d_ij＝||x_i-v_jI is the sample point x_iAnd a clustering center v_jAnd satisfyu_ijis the degree of membership, R, of the ith sample belonging to class j^sIs a particular set of data.

Preferably, the data classification algorithm comprises the following steps:

T1, initializing, selecting E >0, and enabling K to be 1 in the initial clustering;

If it isThen

where r and E are natural numbers, and if i is present, r is such that d_ij(k) when the value is equal to 0, then

U_ij(k) 1 and j ≠ r, U_ij(k)＝0；

T2, calculate V^(k+1)

T3, if V | |)^(k)-V^(k+1)If l < E stops, otherwise let k equal k +1, go back to T1.

Preferably, in the similarity data processing algorithm, data is defined, and the data set D ═ (O, a) and the object set O ═ { O ═ are set₁,o₂,....o_m}, attribute set a ═ a₁,A₂,...A_dh, the object O e O,

Attribute A_iif there are objects p e O, then there are at least K objects p e O that satisfy dist (O, p ') ≦ dist (O, p), and at most K-1 objects p e O that satisfy dist (O, p') ≦ dist (O, p), then the K-distance K-dist (O) of O.

preferably, in the similar data processing algorithm, the data similarity is calculated, d is the similarity, and O e is set as O, A_iE.g. A, then o is about the attribute A_isimilar definitions of (c) are:

Wherein

preferably, in the data encryption algorithm, the data uploaded by the data upload processing terminal is first clustered to obtain a numerical attribute data set D ═ X₁,X₂...,X_nwith X }_i＝(x₁,x₂,...,x_ip) N represents numerical data, and x represents the number of x_j＝{x_1j,x_2j,...,x_nj1,2, p represents that all the attributes are numerical values, and the analysis formula of the D factor is as follows:

wherein, a_mnRepresenting a factor analysis matrix, ∈_nRepresents the contribution ratio, F_nAnd (4) performing clustering processing on the D as a common factor, comparing the common factor with the actual problem and the meaning of the common factor, and acquiring the characteristics of different classes, so as to explain the clustering analysis result and further perform data encryption.

Preferably, in the data encryption algorithm, it is assumed that m pieces of public and non-encryption numerical data exist in a large-scale numerical database, n pieces of sensitive data exist, and the number of records in the database is s; let M be { M ═ M_ij},M_ijrecording the jth numerical data which does not need to be encrypted for the ith strip; n ═ N_ij},N_ijRecording the jth numerical data to be encrypted for the ith strip; k ═ K_ij},K_ijRecording the j encrypted key for the ith strip; then with N_ijThe corresponding key is K_ij；C＝{C_ij},C_ijrecord the jth ciphertext for the ith stripe, N_ijThe corresponding ciphertext is C_ij。

preferably, the similar data processing algorithm is used for querying and deleting the same redundant data.

Preferably, the chemical substance detecting apparatus includes: a detection circuit and a detection device are arranged on the base,

the detection circuit includes: a first resistor R1, a second resistor R2, a third resistor R3, a fourth resistor R4, a fifth resistor R5, a sixth resistor R6, a seventh resistor R7, an eighth resistor R8, a ninth resistor R9, a tenth resistor R10, an eleventh resistor R11, a twelfth resistor R12, a first capacitor C1, a second capacitor C2, a third capacitor C3, a fourth capacitor C4, a first diode L1, a second diode L2, a third diode L3, a fourth diode L4, a fifth diode L5, a sixth diode L6, a D flip-flop RS, an NPN transistor Q1, a power supply VCC, a ground GND, a first operational amplifier a1, and a second operational amplifier a 2;

The power source VCC is respectively connected with the cathode of a first diode L1 and one end of a first resistor R1, the anode of the first diode L1 and the other end of the first resistor R1 are respectively connected with the collector of an NPN transistor Q1, the base of the NPN transistor Q1 is connected with one end of a second resistor R2, the other end of the second resistor R2 is connected with the Q electrode of a D trigger RS, the S electrode of the D trigger RS is respectively connected with one ends of a third resistor R3 and a first capacitor C1, the R electrode of the D trigger RS is connected with one ends of a fourth resistor R4 and a second capacitor C2, and the other ends of the first capacitor C1 and the second capacitor C2 are connected with the cathode of the third diode L3;

The power supply VCC is also respectively connected with the anode of a third diode L3, one end of a third capacitor C3, the cathode of a second diode L2 and one end of the detection equipment;

The emitter of the NPN transistor Q1, the other ends of the third resistor R3 and the fourth resistor R4, the anode of the second diode L2 and the other end of the detection device are connected with the ground GND;

The other end of the third capacitor C3 is connected to one end of an eighth resistor R8, the anode of a fourth diode L4, the positive input end of a second operational amplifier a2, and one end of a fifth resistor R5; one end of the fifth resistor R5 is connected with one end of a sixth resistor R6;

The inverting input end of the second operational amplifier A2 is connected with one end of a seventh resistor R7;

the output end of the second operational amplifier a2 is connected to the other ends of an eighth resistor R8 and a fourth diode L4, respectively, and is further connected to one end of the ninth resistor R9, the other end of the ninth resistor R9 is connected to the positive input end of a first operational amplifier a1, and the reverse input end of the first operational amplifier a1 is connected to one end of a tenth resistor R10;

The output end of the first operational amplifier a1 is connected to the anode of a fifth diode L5 and the cathode of a sixth diode L6, respectively, the anode of the sixth diode L6 is connected to one end of an eleventh resistor R11, and the other end of the eleventh resistor R11 is connected to the cathode of a fifth diode L5, one end of a twelfth resistor R12 and one end of a fourth capacitor C4, respectively;

The other ends of the sixth resistor R6, the seventh resistor R7, the tenth resistor R10, the twelfth resistor R12 and the fourth capacitor C4 are connected to the ground GND.

The invention has the beneficial effects that:

the invention detects the substance to be detected through the chemical substance detection equipment, obtains the detection result with higher safety, better accuracy and lower data redundancy after the detection result is processed through the data processing system and the data classification algorithm, the data encryption algorithm and the similar data processing algorithm, realizes remote intelligent connection through the communication system, and has strong creativity.

drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a functional block diagram of the present invention;

FIG. 2 is a scalability of a similarity data processing algorithm to data set dimensions according to an embodiment of the present invention;

FIG. 3 is a diagram of the classification results of a data classification algorithm according to an embodiment of the present invention;

Fig. 4 is a circuit diagram of a detection circuit according to an embodiment of the invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.