A water quality fingerprinting traceability method and system based on big data

Abstract

The application provides a water quality fingerprint tracing method and system based on big data, which comprises the following steps: detecting the three-dimensional fluorescence spectrum of a water quality sample by using a preset detection instrument; establishing a three-dimensional fluorescence fingerprint characteristic spectrum library of related enterprises by using the three-dimensional fluorescence spectrum; collecting a water quality sample to be detected; analyzing the three-dimensional fluorescence fingerprint characteristic spectrum of the water quality sample to be detected; comparing the three-dimensional fluorescence fingerprint characteristic spectrum with the three-dimensional fluorescence fingerprint characteristic spectrum library; matching suspicious polluting enterprises; and determining a matching result.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of big data and water quality detection, and particularly relates to a water quality fingerprint tracing method and system based on big data. BACKGROUND

[0002] With the sustained development of China's economy, the number of industrial enterprises is increasing, and the industrial wastewater generated is large in quantity, various in type and complex in composition, making it difficult to treat. The illegal and irregular discharge behaviors of industrial enterprise wastewater, such as over-standard discharge, will directly pollute the receiving water environment and even cause pollution accidents. Therefore, diagnosing the pollution source has become the primary task of environmental law enforcement and pollution emergency disposal, and is also a difficult point to be solved. However, the conventional organic matter monitoring indicators such as permanganate index and total organic carbon only reflect the total amount and cannot reflect the toxicity of organic matter and give pollution source information, so it is difficult to provide key and operable information for the supervision or emergency disposal of the pollution source. Therefore, a method for quickly identifying the main components of pollution and the possible industry and accurately locking the suspected pollution source is needed. SUMMARY

[0003] The present application provides a water quality fingerprint tracing method and system based on big data to solve the above problems.

[0004] The present application provides a water quality fingerprint tracing method based on big data, comprising:

[0005] Detecting the three-dimensional fluorescence spectrum of the water quality sample by using a preset detection instrument, and establishing a three-dimensional fluorescence fingerprint characteristic spectrum library of related enterprises through the three-dimensional fluorescence spectrum;

[0006] Collecting a water quality sample to be detected, and analyzing the three-dimensional fluorescence fingerprint characteristic spectrum of the water quality sample to be detected;

[0007] Comparing the three-dimensional fluorescence fingerprint characteristic spectrum with the three-dimensional fluorescence fingerprint characteristic spectrum library, matching the suspected polluting enterprises, and determining the matching result.

[0008] As an embodiment of the present technical solution, the detection instrument at least comprises a fluorescence spectrophotometer.

[0009] As an embodiment of the present technical solution, the three-dimensional fluorescence spectrum comprises an excitation wavelength, an emission wavelength and a fluorescence intensity.

[0010] As an embodiment of the present technical solution, the comparison of the three-dimensional fluorescence fingerprint characteristic spectrum with the three-dimensional fluorescence fingerprint characteristic spectrum library, the matching of the suspected polluting enterprises, and the determination of the matching result comprise:

[0011] Locating the n-dimensional characteristic vector of the three-dimensional fluorescence fingerprint characteristic spectrum library through the three-dimensional fluorescence fingerprint characteristic spectrum, and locking the corresponding n enterprises through the n-dimensional characteristic vector.

[0012] Calculate the enterprise contribution rate of n enterprises, screen the enterprises with enterprise contribution rate greater than the preset threshold, and determine the first screening result;

[0013] By sampling along the upstream of the river, the three-dimensional fluorescence fingerprint characteristics of the water quality sample are detected, and by arranging points along the river basin, the suspicious area of the river basin is locked;

[0014] Through the locking of the suspicious area of the river basin, the enterprises in the screening result are screened again to determine the second screening result;

[0015] The pollutant contribution rate of the enterprise in the second screening result is calculated one by one, and the main component of the pollutant is analyzed through the pollutant contribution rate;

[0016] Through the main component, the pollutant contribution rate of the enterprise in the second screening result, match the suspected polluting enterprise, determine the matching result.

[0017] As an embodiment of the technical solution, the comparison of the three-dimensional fluorescence fingerprint characteristic map and the three-dimensional fluorescence fingerprint characteristic map library, matching the suspected polluting enterprise, determining the matching result, further comprises:

[0018] When the number of suspected polluting enterprises in the matching result is greater than the preset number, collect the historical three-dimensional fluorescence fingerprint characteristic map of the suspected polluting enterprise;

[0019] Calculate the similarity of the three-dimensional fluorescence fingerprint characteristic map and the historical three-dimensional fluorescence fingerprint characteristic map of the suspected polluting enterprise;

[0020] Determine the suspected polluting enterprise with similarity within the preset similarity threshold range, and feed back to the terminal device.

[0021] As an embodiment of the technical solution, the n enterprises are one-to-one corresponding to the n-dimensional feature vectors.

[0022] The technical solution provides a water quality fingerprint tracing system based on big data, which comprises:

[0023] The characteristic map library establishment module is used for detecting the three-dimensional fluorescence spectrum of the water quality sample by using a preset detection instrument, and establishing a three-dimensional fluorescence fingerprint characteristic map library of related enterprises through the three-dimensional fluorescence spectrum;

[0024] The three-dimensional fluorescence fingerprint characteristic module is used for collecting the water quality sample to be detected, and analyzing the three-dimensional fluorescence fingerprint characteristics of the water quality sample to be detected;

[0025] The matching module is used for comparing the three-dimensional fluorescence fingerprint characteristics and the three-dimensional fluorescence fingerprint characteristic map library, matching the suspected polluting enterprise, and determining the matching result.

[0026] As an embodiment of the technical solution, the matching module comprises:

[0027] The enterprise locking unit is configured to locate n-dimensional feature vectors of the three-dimensional fluorescent fingerprint feature spectrum library through the three-dimensional fluorescent fingerprint features, and lock corresponding n enterprises through the n-dimensional feature vectors;

[0028] The first screening unit is configured to calculate enterprise contribution rates of the n enterprises, screen enterprises with enterprise contribution rates greater than a preset threshold, and determine a first screening result;

[0029] The river basin locking unit is configured to collect and detect three-dimensional fluorescent fingerprint features of river basin water quality samples, and lock suspicious areas of the river basin through river basin along-line distribution points;

[0030] The second screening unit is configured to perform secondary screening on the enterprises in the screening result by locking the suspicious areas of the river basin, and determine a second screening result;

[0031] The component analysis unit is configured to calculate pollutant contribution rates of the enterprises in the second screening result one by one, and analyze main components of pollutants through the pollutant contribution rates;

[0032] The matching result unit is configured to match suspicious polluting enterprises through the main components and the pollutant contribution rates of the enterprises in the second screening result, and determine a matching result.

[0033] Other features and advantages of the present application will be described in the following description, and some will become apparent from the description, or will be understood by those skilled in the art. The purpose and other advantages of the present application can be achieved and obtained by the structure specifically pointed out in the written description and the accompanying drawings.

[0034] The technical solution of the present application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0035] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, together with the embodiments of the present application, to explain the present application, and do not constitute a limitation of the present application. In the drawings:

[0036] Figure 1 A method flowchart of a water quality fingerprint tracing method based on big data in an embodiment of the present application. DETAILED DESCRIPTION

[0037] The preferred embodiments of the present application will be described below in conjunction with the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and do not limit the present application.

[0038] Embodiment one

[0039] According to Figure 1 The embodiment of the application provides a water quality fingerprint tracing method based on big data, which comprises the following steps:

[0040] The three-dimensional fluorescence spectrum of the water quality sample is detected by using a preset detection instrument, and a three-dimensional fluorescence fingerprint characteristic spectrum library of related enterprises is established through the three-dimensional fluorescence spectrum.

[0041] A water quality sample to be detected is collected, and a three-dimensional fluorescence fingerprint characteristic map of the water quality sample to be detected is analyzed.

[0042] The three-dimensional fluorescence fingerprint characteristic map is compared with the three-dimensional fluorescence fingerprint characteristic spectrum library, a suspicious polluting enterprise is matched, and a matching result is determined.

[0043] The working principle and beneficial effects of the above technical solution are as follows:

[0044] The embodiment of the application provides a water quality fingerprint tracing method based on big data, which comprises the following steps: a three-dimensional fluorescence spectrum of a water quality sample is detected by using a preset detection instrument, and a three-dimensional fluorescence fingerprint characteristic spectrum library of related enterprises is established through the three-dimensional fluorescence spectrum; a water quality sample to be detected is collected, and a three-dimensional fluorescence fingerprint characteristic map of the water quality sample to be detected is analyzed; the three-dimensional fluorescence fingerprint characteristic map is compared with the three-dimensional fluorescence fingerprint characteristic spectrum library, a suspicious polluting enterprise is matched, and a matching result is determined. Therefore, the efficiency of artificial detection is improved, and a suspicious enterprise can be located and matched more quickly.

[0045] The technical solution provides an embodiment, and the detection instrument at least comprises a fluorescence spectrophotometer.

[0046] The working principle and beneficial effects of the above technical solution are as follows:

[0047] The technical solution can analyze the fluorescence spectrum of water quality through the detection instrument, which at least comprises a fluorescence spectrophotometer.

[0048] The technical solution provides an embodiment, and the three-dimensional fluorescence spectrum comprises an excitation wavelength, an emission wavelength and fluorescence intensity.

[0049] The working principle and beneficial effects of the above technical solution are as follows:

[0050] The technical solution comprises an excitation wavelength, an emission wavelength and fluorescence intensity through the three-dimensional fluorescence spectrum.

[0051] The technical solution provides an embodiment, and the comparison of the three-dimensional fluorescence fingerprint characteristic map and the three-dimensional fluorescence fingerprint characteristic spectrum library, the matching of a suspicious polluting enterprise and the determination of a matching result comprise the following steps:

[0052] locating n-dimensional feature vectors of the three-dimensional fluorescence fingerprint characteristic map library through the three-dimensional fluorescence fingerprint characteristic map, and locking n enterprises corresponding to the n-dimensional feature vectors;

[0053] calculating enterprise contribution rates of the n enterprises, screening enterprises with enterprise contribution rates greater than a preset threshold, and determining a first screening result;

[0054] locating a suspicious area of the river basin by sampling and detecting three-dimensional fluorescence fingerprint characteristics of water quality samples along the river basin;

[0055] performing secondary screening on the enterprises in the screening result by the located suspicious area of the river basin, and determining a second screening result;

[0056] calculating pollutant contribution rates of the enterprises in the second screening result one by one, and analyzing main components of pollutants through the pollutant contribution rates;

[0057] matching suspicious polluting enterprises through the main components and the pollutant contribution rates of the enterprises in the second screening result, and determining a matching result.

[0058] The working principle and beneficial effects of the above technical solution are as follows:

[0059] The technical solution compares the three-dimensional fluorescence fingerprint characteristic map with the three-dimensional fluorescence fingerprint characteristic map library, matches suspicious polluting enterprises, determines a matching result, and includes: locating n-dimensional feature vectors of the three-dimensional fluorescence fingerprint characteristic map library through the three-dimensional fluorescence fingerprint characteristic map, and locking n enterprises corresponding to the n-dimensional feature vectors; calculating enterprise contribution rates of the n enterprises, screening enterprises with enterprise contribution rates greater than a preset threshold, and determining a first screening result; locating a suspicious area of the river basin by sampling and detecting three-dimensional fluorescence fingerprint characteristics of water quality samples along the river basin; performing secondary screening on the enterprises in the screening result by the located suspicious area of the river basin, and determining a second screening result; calculating pollutant contribution rates of the enterprises in the second screening result one by one, and analyzing main components of pollutants through the pollutant contribution rates; matching suspicious polluting enterprises through the main components and the pollutant contribution rates of the enterprises in the second screening result, and determining a matching result. The technical solution matches suspicious polluting enterprises through the characteristics of the fingerprint characteristic map library, thereby investigating suspicious industries and enterprises, improving the efficiency of detection, and improving the accuracy of positioning.

[0060] Preferably, the screening process includes:

[0061] Screening the enterprises with the enterprise contribution rate greater than the preset threshold value according to the enterprise contribution rate of the n enterprises to determine a first screening result; screening the enterprises in the first screening result again according to the locking watershed to determine a second screening result; calculating the pollutant contribution rate of the enterprises in the second screening result one by one and automatically sorting the pollutant contribution rate to generate a pollutant contribution rate array of the enterprises in the second screening result and a corresponding enterprise number array, and the specific steps include,

[0062] Step A1: screening the enterprises with the enterprise contribution rate greater than the preset threshold value according to the enterprise contribution rate of the n enterprises by formula (1) to determine a first screening result and generate a first screening result array

[0063]

[0064] Wherein A(a) represents the numerical value of the a-th element in the first screening result array; D(a) represents the first screening value of the a-th enterprise; G(a) represents the enterprise contribution rate of the a-th enterprise; G0 represents the preset threshold value of the enterprise contribution rate; || represents the absolute value;

[0065] Step A2: screening the enterprises in the first screening result again according to the locking watershed by formula (2) to determine a second screening result and generate a second screening result array B(a) = A(a) × F[r(a) ∈ R] (2)

[0066] Wherein B(a) represents the numerical value of the a-th element in the second screening result array; F[r(a) ∈ R] represents the detection function value of the a-th enterprise belonging to the locking watershed, and the function value is 1 if the a-th enterprise is in the locking watershed, and the function value is 0 otherwise;

[0067] Step A3: automatically sorting the pollutant contribution rate according to the pollutant contribution rate of the enterprises in the second screening result by formula (3) to generate a corresponding enterprise number array of the pollutant contribution rate of the enterprises in the second screening result

[0068]

[0069] Wherein P[B(a)] represents the bit value of the enterprise number B(a) in the enterprise number array (if the P[B(a)] values are the same, the enterprise numbers corresponding to the same values are arranged in the array according to the bit value B(a) from large to small in the order from small to large); n represents the total number of enterprises; G[B(a)] represents the enterprise contribution rate of the B(a)-th enterprise; G[B(i)] represents the enterprise contribution rate of the B(i)-th enterprise; Z{} represents a judgment function, and the function value is 1 if the algorithm in the bracket is true, and the function value is 0 if the function value in the bracket is not true;

[0070] Thus, the pollutant contribution rate of the corresponding enterprise is obtained through the enterprise number array, so that the main components of the pollutants can be analyzed, and the efficiency is improved.

[0071] The beneficial effects of the above technical solution are: according to the enterprise contribution rate of n enterprises, the enterprises with enterprise contribution rate greater than the preset threshold value are screened by using formula (1) of step A1 to determine the first screening result, and the first screening result array is generated, so that the array is used for subsequent calculation, which is convenient for calculation and can accurately and quickly locate the data; then, according to the locking basin, the enterprises in the first screening result are screened again by using formula (2) of step A2 to determine the second screening result, and the second screening result array is generated, the process of generating the array is fully automated and intelligent, which embodies the intelligent characteristics of the system; finally, according to the pollutant contribution rate of the enterprises in the second screening result, the pollutant contribution rate is automatically sorted by using formula (3) of step A3 to generate the enterprise number array corresponding to the pollutant contribution rate of the enterprises in the second screening result, so that the pollutant contribution rate of the corresponding enterprise is obtained through the enterprise number array, which is convenient for analyzing the main components of the pollutants and improving the overall efficiency of the system.

[0072] The technical solution provides an embodiment, wherein the three-dimensional fluorescent fingerprint feature map and the three-dimensional fluorescent fingerprint feature map library are compared, the suspected polluting enterprise is matched, and the matching result is determined.

[0073] When the number of the suspected polluting enterprises in the matching result is greater than a preset number, the historical three-dimensional fluorescent fingerprint feature map of the suspected polluting enterprise is collected.

[0074] The similarity between the three-dimensional fluorescent fingerprint feature map and the historical three-dimensional fluorescent fingerprint feature map of the suspected polluting enterprise is calculated.

[0075] The suspected polluting enterprise with the similarity within a preset similarity threshold range is determined, and feedback is fed back to the terminal device.

[0076] The working principle and beneficial effects of the above technical solution are:

[0077] The technical solution compares the three-dimensional fluorescent fingerprint feature map and the three-dimensional fluorescent fingerprint feature map library, matches the suspected polluting enterprise, determines the matching result, and further comprises: when the number of the suspected polluting enterprises in the matching result is greater than a preset number, the historical three-dimensional fluorescent fingerprint feature map of the suspected polluting enterprise is collected; the similarity between the three-dimensional fluorescent fingerprint feature map and the historical three-dimensional fluorescent fingerprint feature map of the suspected polluting enterprise is calculated; the suspected polluting enterprise with the similarity within a preset similarity threshold range is determined, and feedback is fed back to the terminal device. Thus, the efficiency of artificial detection is improved, so that the suspected enterprise can be located and matched faster.

[0078] The technical scheme provides an embodiment, and the n enterprises are one-to-one corresponding to n-dimensional characteristic vectors.

[0079] The technical scheme provides an embodiment, which comprises:

[0080] A characteristic spectrum library establishing module is configured to detect the three-dimensional fluorescence spectrum of the water quality sample by using a preset detection instrument, and establish a three-dimensional fluorescence fingerprint characteristic spectrum library of related enterprises by using the three-dimensional fluorescence spectrum.

[0081] A three-dimensional fluorescence fingerprint characteristic module is configured to collect a water quality sample to be detected, and analyze the three-dimensional fluorescence fingerprint characteristic of the water quality sample to be detected.

[0082] A matching module is configured to compare the three-dimensional fluorescence fingerprint characteristic with the three-dimensional fluorescence fingerprint characteristic spectrum library, match a suspected polluting enterprise, and determine a matching result.

[0083] The technical scheme provides an embodiment, and the matching module comprises:

[0084] An enterprise locking unit is configured to locate the n-dimensional characteristic vector of the three-dimensional fluorescence fingerprint characteristic spectrum library by using the three-dimensional fluorescence fingerprint characteristic, and lock the corresponding n enterprises by using the n-dimensional characteristic vector.

[0085] A first screening unit is configured to calculate the enterprise contribution rate of the n enterprises, screen the enterprises with the enterprise contribution rate greater than a preset threshold value, and determine a first screening result.

[0086] A river basin locking unit is configured to collect and detect the three-dimensional fluorescence fingerprint characteristic of the river basin water quality sample, and lock a suspected area of the river basin by using the distribution points along the river basin.

[0087] A second screening unit is configured to perform secondary screening on the enterprises in the screening result by using the locked suspected area of the river basin, and determine a second screening result.

[0088] A component analysis unit is configured to calculate the pollutant contribution rate of the enterprises in the second screening result one by one, and analyze the main component of the pollutant by using the pollutant contribution rate.

[0089] A matching result unit is configured to match the suspected polluting enterprise by using the main component and the pollutant contribution rate of the enterprises in the second screening result, and determine a matching result.

[0090] Embodiment two

[0091] In this embodiment, three three-dimensional fluorescence fingerprint feature spectrum libraries can be established: a main pollutant fingerprint spectrum library, an industry fingerprint spectrum library, and a specific enterprise fingerprint spectrum library in a specified area. The main pollutant fingerprint spectrum library stores fingerprint information of main pollutants, the industry fingerprint spectrum library stores fingerprint information of different industries, and the specific enterprise fingerprint spectrum library in a specified area stores fingerprint information of enterprises in the specified area. When performing pollutant matching, four-dimensional matching is performed to improve the accuracy of tracing: 1) industry category matching: when pollution is found downstream of a river, the three-dimensional fluorescence fingerprint feature is used to decompose the industry contribution rate to roughly determine which industry; 2) pollutant matching: decompose into different pollutant contribution rates to confirm the main component; 3) enterprise matching: decompose into the contribution rate of enterprises in the river basin to preliminarily determine the enterprise; 4) region matching: points are arranged along the river basin, and the industry, component, and possible enterprise of the pollution are obtained by comparing the three libraries to lock the enterprise within a certain range.

[0092] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A water quality fingerprinting method based on big data, characterized in that, The application relates to a method for identifying suspicious polluting enterprises. The method comprises the following steps: a three-dimensional fluorescence spectrum of a water quality sample is detected by using a preset detection instrument, a three-dimensional fluorescence fingerprint characteristic spectrum library of related enterprises is established by using the three-dimensional fluorescence spectrum, a water quality sample to be detected is collected, and a three-dimensional fluorescence fingerprint characteristic spectrum of the water quality sample to be detected is analyzed; the three-dimensional fluorescence fingerprint characteristic spectrum is compared with the three-dimensional fluorescence fingerprint characteristic spectrum library, suspicious polluting enterprises are matched, and a matching result is determined; the comparison of the three-dimensional fluorescence fingerprint characteristic spectrum and the three-dimensional fluorescence fingerprint characteristic spectrum library, the matching of the suspicious polluting enterprises, and the determination of the matching result comprise the following steps: a n-dimensional characteristic vector of the three-dimensional fluorescence fingerprint characteristic spectrum library is located by using the three-dimensional fluorescence fingerprint characteristic spectrum, n enterprises corresponding to the n-dimensional characteristic vector are locked by using the n-dimensional characteristic vector, enterprise contribution rates of the n enterprises are calculated, enterprises with enterprise contribution rates greater than a preset threshold value are screened, a first screening result is determined, three-dimensional fluorescence fingerprints of water quality samples are detected by sampling along an upstream of a river, a suspicious area of a river basin is locked by sampling along a line of the river basin, the enterprises in the screening result are secondarily screened by locking the suspicious area of the river basin, a second screening result is determined, pollutant contribution rates of the enterprises in the second screening result are calculated one by one, main components of pollutants are analyzed by using the pollutant contribution rates, the main components, the pollutant contribution rates of the enterprises in the second screening result, and the suspicious polluting enterprises are matched, and a matching result is determined; and the method comprises the following steps: （1） wherein represents a value of an element at the i-th position in the first screening result array; represents a first screening value of the i-th enterprise; represents a business contribution rate of the i-th enterprise; represents a business contribution rate of a preset threshold value; represents an absolute value;​​​ Step A1: according to the enterprise contribution rates of the n enterprises, enterprises with enterprise contribution rates greater than a preset threshold value are screened by using formula (1), a first screening result is determined, and a first screening result array is generated （2） wherein represents the value of the element at the th position in the second screening result array; represents the value of the detection function of the th enterprise belonging to the lock-in watershed, which is 1 if the th enterprise is within the lock-in watershed, and 0 otherwise. Step A2: according to the locking of the river basin, the enterprises in the first screening result are secondarily screened by using formula (2), a second screening result is determined, and a second screening result array is generated （3） wherein represents the enterprise number represents the bit value in the enterprise number array, if the same value, the enterprise numbers corresponding to the same value are arranged in the array according to the bit value from small to large in the order from large to small; represents the total number of enterprises; represents the enterprise contribution rate of the th enterprise; represents the enterprise contribution rate of the th enterprise; represents the enterprise contribution rate of the represents the judgment function, if the formula in the parentheses is true, the function value is 1, if the function value in the parentheses is not true, the function value is 0; Step A3: according to the pollutant contribution rates of the enterprises in the second screening result, the pollutant contribution rates are automatically sorted to generate an enterprise number array corresponding to the pollutant contribution rates of the enterprises in the second screening result 2. The water quality fingerprinting and tracing method based on big data according to claim 1, characterized in that, so that the pollutant contribution rates of the corresponding enterprises are obtained through the enterprise number array.

3. The water quality fingerprinting and tracing method based on big data according to claim 1, characterized in that, The detection instrument at least comprises a fluorescence spectrophotometer.

4. The water quality fingerprinting and tracing method based on big data according to claim 1, characterized in that, The three-dimensional fluorescence spectrum comprises an excitation wavelength, an emission wavelength and a fluorescence intensity. The comparison of the three-dimensional fluorescence fingerprint characteristic spectrum and the three-dimensional fluorescence fingerprint characteristic spectrum library, the matching of the suspicious polluting enterprises, and the determination of the matching result further comprise the following steps: when the number of the suspicious polluting enterprises in the matching result is greater than a preset number, historical three-dimensional fluorescence fingerprint characteristic spectra of the suspicious polluting enterprises are collected; a similarity between the three-dimensional fluorescence fingerprint characteristic spectrum and the historical three-dimensional fluorescence fingerprint characteristic spectrum of the suspicious polluting enterprises is calculated; 5. The water quality fingerprinting and tracing method based on big data according to claim 1, characterized in that, suspected polluting enterprises with a similarity within a preset similarity threshold range are determined, and the suspected polluting enterprises are fed back to a terminal device.

6. A water quality fingerprinting system based on big data, employing the water quality fingerprinting method of any one of claims 1-5, characterized in that, The n enterprises correspond to the n-dimensional characteristic vectors one by one. The application further relates to a method for identifying suspicious polluting enterprises. The method comprises the following steps: a characteristic spectrum library establishing module is used to detect a three-dimensional fluorescence spectrum of a water quality sample by using a preset detection instrument, a three-dimensional fluorescence fingerprint characteristic spectrum library of related enterprises is established by using the three-dimensional fluorescence spectrum, The three-dimensional fluorescence fingerprint characteristic module is used for collecting a water quality sample to be detected and analyzing three-dimensional fluorescence fingerprint characteristics of the water quality sample to be detected. The matching module is used for comparing the three-dimensional fluorescence fingerprint characteristics with a three-dimensional fluorescence fingerprint characteristic atlas library, matching a suspected polluting enterprise, and determining a matching result.

7. The water quality fingerprinting and tracing system based on big data according to claim 6, wherein, The matching module comprises: An enterprise locking unit is used for locating n-dimensional characteristic vectors of the three-dimensional fluorescence fingerprint characteristic atlas library through the three-dimensional fluorescence fingerprint characteristics, and locking corresponding n enterprises through the n-dimensional characteristic vectors. A first screening unit is used for calculating enterprise contribution rates of the n enterprises, screening enterprises with enterprise contribution rates greater than a preset threshold, and determining a first screening result. A river basin locking unit is used for collecting and detecting three-dimensional fluorescence fingerprint characteristics of river basin water quality samples, locking a suspected area of the river basin through distribution of points along the river basin, and determining a second screening result. A second screening unit is used for performing secondary screening on the enterprises in the screening result through the locking of the suspected area of the river basin, and determining a second screening result. A component analysis unit is used for calculating pollutant contribution rates of the enterprises in the second screening result one by one, and analyzing main components of pollutants through the pollutant contribution rates. A matching result unit is used for matching a suspected polluting enterprise through the main components and the pollutant contribution rates of the enterprises in the second screening result, and determining a matching result.

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