Salinized soil corrosivity detection system and detection method

Abstract

The invention relates to the technical field of soil corrosion detection, and discloses a corrosion detection system and detection method for saline soil, a sensor module is used for measuring basic data of saline soil in real time; the data acquisition module is used for being connected with the sensor module and converting an analog signal which is output by the sensor module and contains basic data into a digital signal to obtain initial soil data; the data processing module is used for performing data preprocessing on the initial soil data output by the data acquisition module to obtain intermediate soil data; the data analysis module is used for performing data analysis on the intermediate soil data, performing early warning on the corrosion condition of the saline soil and outputting a data analysis result; the wireless communication module is used for converting a data analysis result obtained by the data analysis module into a detection report and sending the detection report to a remote monitoring center or a mobile terminal of a user; the potential corrosion risk can be found in time, and engineering accidents and economic losses caused by soil corrosion are avoided.

Description

Technical Field

[0001] The invention relates to the technical field of soil corrosivity detection, and in particular to a saline soil corrosivity detection system and a detection method. Background Art

[0002] Saline soil is a general term for soil with varying degrees of salinization, which is widely distributed around the world. The salt in saline soil (such as chlorides, sulfates, etc.) will corrode metal structures buried in it (such as oil pipelines, steel bars in building foundations, etc.), which will reduce the strength of the structure, shorten its service life, and even cause safety accidents.

[0003] At present, there are certain limitations in the detection methods for the corrosiveness of saline soil. Traditional detection methods can often only detect the impact of a single factor on corrosiveness. For example, they only focus on the impact of soil salt content or humidity on corrosion, and lack a comprehensive evaluation of the combined effects of multiple factors. Moreover, the detection process may require multiple different devices to measure different parameters. The operation is cumbersome and time-consuming, and the detection efficiency is low. In addition, some existing detection equipment is difficult to perform accurate measurements in situ, and soil samples need to be collected and brought back to the laboratory for analysis. During this process, the properties of the soil samples may change, thereby affecting the accuracy of the test results. Summary of the invention

[0004] The purpose of the present invention is to solve the above problems and to design a saline soil corrosivity detection system and detection method.

[0005] A first aspect of the present invention provides a saline soil corrosion detection system, the saline soil corrosion detection system comprises a sensor module, a data acquisition module, a data processing module, a data analysis module and a wireless communication module, wherein:

[0006] Sensor module for real-time measurement of basic data of saline soil;

[0007] A data acquisition module, connected to the sensor module, converts the analog signal containing the basic data output by the sensor module into a digital signal to obtain initial soil data;

[0008] A data processing module, used for performing data preprocessing on the initial soil data output by the data acquisition module to obtain intermediate soil data;

[0009] A data analysis module is used to analyze the intermediate soil data, issue an early warning for the corrosion of saline soil, and output the data analysis results;

[0010] The wireless communication module is used to convert the data analysis results obtained by the data analysis module into a detection report and send it to a remote monitoring center or a user's mobile terminal.

[0011] Optionally, in a first implementation of the first aspect of the present invention, the sensor module includes a salt sensor, a humidity sensor, a temperature sensor and a metal electrode assembly, wherein:

[0012] Salt sensor, used to measure the salt content in saline soil in real time, using ion selective electrode technology to distinguish the content of different types of salt;

[0013] Humidity sensor, using capacitive humidity sensor, real-time measurement of humidity data of saline soil;

[0014] Temperature sensor, using thermistor temperature sensor, real-time measurement of saline soil temperature data;

[0015] The metal electrode assembly is used to detect the corrosion potential of saline soil to different metals, and is composed of electrodes made of multiple different metals.

[0016] Optionally, in a second implementation of the first aspect of the present invention, the data processing module includes a data cleaning submodule, a data standardization submodule and a data dimension reduction submodule, wherein:

[0017] A data cleaning submodule, configured to receive the initial soil data output by the data acquisition module, perform data cleaning on the initial soil data, fill in missing values ​​and delete abnormal values, so as to obtain first soil data;

[0018] A data standardization submodule, used for performing data standardization processing on the first soil data by adopting Z-score standardization to obtain second soil data;

[0019] The data dimension reduction submodule is used to perform data dimension reduction processing on the second soil data, convert the second soil data into low-dimensional space data for feature extraction, and integrate various features to obtain intermediate soil data.

[0020] Optionally, in a third implementation of the first aspect of the present invention, the data dimension reduction submodule includes a decentralized operation unit, a matrix construction unit, a feature decomposition unit and a feature extraction unit, wherein:

[0021] A decentralized operation unit is used to perform a decentralized operation on the second soil data to obtain

[0022]

[0023] Where X represents the second soil data, n represents the number of data values ​​contained in the second soil data, and μ represents the mean vector of the second soil data. Represents the decentralized Second Soil data, x i represents the i-th eigenvalue;

[0024] Construct a matrix unit to construct the covariance matrix V:

[0025]

[0026] In the formula, T represents the transposition operator;

[0027] The eigendecomposition unit is used to perform eigendecomposition on V and calculate the eigenvalue λ i and its corresponding eigenvector w i , extract the first d eigenvalues ​​and vectors in descending order as the basis of the new subspace, and get the d principal components:

[0028] A=diag[λ1,λ2,…,λ d ]

[0029] W d =[w1,w2,…,w d ]

[0030]

[0031] In the formula, λ i represents the eigenvalue of the covariance matrix V, w i represents the eigenvector of the covariance matrix V, d represents the number of principal components, A represents the first d eigenvalues, W d represents the matrix of the first d eigenvectors, and F represents the principal component matrix;

[0032] A feature extraction unit is used to extract features from the second soil data and integrate the features to obtain intermediate soil data:

[0033] X'=WF+μ

[0034] Where X' represents the second soil data after dimensionality reduction, that is, the intermediate soil data.

[0035] Optionally, in a fourth implementation of the first aspect of the present invention, the data analysis module includes a decomposition submodule, a variable screening submodule, a calculation submodule and an output submodule, wherein:

[0036] A decomposition submodule, used for acquiring intermediate soil data, decomposing the intermediate soil data by using EEMD decomposition, and dividing the intermediate soil data into an IMF component and a residual component;

[0037] The variable screening submodule is used to screen the variables of IMF components and residual components using the LASSO algorithm;

[0038] The calculation submodule is used to establish a differential equation using the GM (1, N) model, solve the established differential equation, and obtain the calculation result;

[0039] The output submodule is used to warn of the corrosion of saline soil based on the calculation results and output data analysis results.

[0040] Optionally, in a fifth implementation of the first aspect of the present invention, in the GM (1, N) model, the corrosion rate is the dependent variable, and the corrosion influencing factors in the N-1 intermediate soil data are the independent variables. Let the dependent variable be n is the number of data, and the independent variable is i∈[2,N];

[0041] Calculate the first-order cumulative series of the independent variable and dependent variable series calculate The adjacent mean sequence of

[0042]

[0043] The differential equation is established, and the linear correction h1 and the gray action h2 are introduced to correct the random error:

[0044]

[0045] In the formula, a, b i They respectively represent the development coefficient and driving coefficient, reflecting the growth trend and data fluctuation.

[0046] A second aspect of the present invention provides a method for detecting the corrosiveness of saline soil, the method comprising the following steps:

[0047] In the saline soil area to be detected, a salt sensor, a humidity sensor, a temperature sensor and a metal electrode assembly are buried in the soil, basic data of the saline soil is measured in real time by each sensor, and the analog signal output by the sensor containing the basic data is converted into a digital signal to obtain initial soil data;

[0048] Performing data preprocessing on the initial soil data output by the data acquisition module to obtain intermediate soil data;

[0049] Performing data analysis on the intermediate soil data, issuing early warnings on the corrosion of saline soil, and outputting data analysis results;

[0050] The data analysis results obtained by the data analysis module are converted into a detection report and sent to a remote monitoring center or a user's mobile terminal.

[0051] Optionally, in a first implementation of the second aspect of the present invention, the performing data preprocessing on the initial soil data output by the data acquisition module to obtain intermediate soil data includes:

[0052] Receiving the initial soil data output by the data acquisition module, performing data cleaning processing on the initial soil data, filling missing values ​​and deleting abnormal values, to obtain first soil data;

[0053] Performing data standardization processing on the first soil data by using Z-score standardization to obtain second soil data;

[0054] The second soil data is subjected to data dimensionality reduction processing, and the second soil data is converted into low-dimensional space data for feature extraction, and each feature is integrated to obtain intermediate soil data.

[0055] Optionally, in a second implementation of the second aspect of the present invention, performing data analysis on the intermediate soil data, issuing an early warning for the corrosion of saline soil, and outputting data analysis results include:

[0056] Acquire intermediate soil data, and decompose the intermediate soil data by using EEMD decomposition to divide the intermediate soil data into an IMF component and a residual component;

[0057] The LASSO algorithm is used to screen variables of IMF components and residual components;

[0058] The GM (1, N) model is used to establish the difference equation, and the established difference equation is solved to obtain the calculation result;

[0059] Based on the calculation results, an early warning is issued for the corrosion of saline soil and data analysis results are output.

[0060] In the technical solution provided by the present invention, the detection system and detection method of the present invention can comprehensively consider the influence of various factors such as salt, humidity, temperature, etc. in saline soil on the corrosiveness, and can evaluate the corrosiveness of saline soil more comprehensively and accurately than traditional detection methods; the detection system adopts an integrated design, and the sensor module, data acquisition module, data processing module, data analysis module and wireless communication module work together, which is simple and convenient to operate, reduces the complexity and workload of manual operation, and improves the detection efficiency; the detection system and detection method of the present invention can perform in-situ detection, avoid the problem of sample property changes that may occur during soil sample collection and transportation, and further ensure the accuracy of the detection results; the long-term monitoring function helps to deeply understand the changing law of saline soil corrosiveness, and can continuously optimize the model according to the monitoring results, improve the reliability of detection, and warn of the corrosion of saline soil, so as to timely discover potential corrosion risks and avoid engineering accidents and economic losses caused by soil corrosion. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the following detailed description of the preferred embodiment.The drawings are only for the purpose of illustrating the preferred embodiments and are not to be construed as limiting the invention.

[0062] Figure 1 A schematic diagram of an embodiment of a method for detecting the corrosiveness of saline soil provided by an embodiment of the present invention;

[0063] Figure 2 A schematic diagram of the structure of a saline soil corrosivity detection system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0065] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 A schematic diagram of an embodiment of a method for detecting the corrosiveness of saline soil provided in an embodiment of the present invention, the method specifically comprises the following steps:

[0066] Step 101: bury a salt sensor, a humidity sensor, a temperature sensor and a metal electrode assembly in the soil in a saline soil area to be detected, measure the basic data of the saline soil in real time through each sensor, convert the analog signal containing the basic data output by the sensor into a digital signal, and obtain initial soil data;

[0067] Step 102: preprocessing the initial soil data output by the data acquisition module to obtain intermediate soil data;

[0068] In this embodiment, the initial soil data output by the data acquisition module is received, and the initial soil data is cleaned to fill missing values ​​and delete outliers to obtain first soil data; the first soil data is standardized using Z-score standardization to obtain second soil data; the second soil data is reduced in dimension to convert it into low-dimensional space data for feature extraction, and the features are integrated to obtain intermediate soil data.

[0069] Step 103: Analyze the intermediate soil data, issue an early warning for the corrosion of saline soil, and output the data analysis results;

[0070] In this embodiment, intermediate soil data is obtained, and the intermediate soil data is decomposed by EEMD decomposition to divide the intermediate soil data into IMF components and residual components; the LASSO algorithm is used to screen variables of the IMF components and the residual components; the GM (1, N) model is used to establish a differential equation, and the established differential equation is solved to obtain a calculation result; based on the calculation result, an early warning is issued for the corrosion of saline soil, and the data analysis result is output.

[0071] In the present embodiment, LASSO (Least Absolute Shrinkage and Selection Operator) is a statistical method for variable selection and parameter estimation. LASSO algorithm adds L1 regularization term on the basis of traditional linear regression. The goal of linear regression is to minimize the residual sum of squares, and LASSO adds a penalty term for the absolute value sum of regression coefficients in this objective function. LASSO algorithm compresses the regression coefficients so that the coefficients of some unimportant variables become zero, thereby realizing variable selection. This helps to reduce the complexity of the model, improve the interpretability and prediction accuracy of the model, and while selecting variables, LASSO also performs parameter estimation on variables with non-zero coefficients. Due to the effect of regularization, the estimated parameters are more stable and are not easily affected by noise and collinearity.

[0072] Step 104: Convert the data analysis results obtained by the data analysis module into a detection report and send it to a remote monitoring center or a user's mobile terminal.

[0073] See also Figure 2 , a schematic diagram of the structure of a saline soil corrosivity detection system provided by an embodiment of the present invention, the system includes a sensor module, a data acquisition module, a data processing module, a data analysis module and a wireless communication module, wherein,

[0074] Sensor module 201, used for real-time measurement of basic data of saline soil;

[0075] The data acquisition module 202 is used to connect with the sensor module, convert the analog signal containing basic data output by the sensor module into a digital signal, and obtain initial soil data;

[0076] The data processing module 203 is used to perform data preprocessing on the initial soil data output by the data acquisition module to obtain intermediate soil data;

[0077] The data analysis module 204 is used to analyze the intermediate soil data, issue an early warning for the corrosion of saline soil, and output the data analysis results;

[0078] The wireless communication module 205 is used to convert the data analysis results obtained by the data analysis module into a detection report and send it to a remote monitoring center or a user's mobile terminal.

[0079] In this embodiment, the sensor module includes a salt sensor, a humidity sensor, a temperature sensor and a metal electrode assembly, wherein:

[0080] Salt sensor, used to measure the salt content in saline soil in real time, using ion selective electrode technology to distinguish the content of different types of salt;

[0081] Humidity sensor, using capacitive humidity sensor, real-time measurement of humidity data of saline soil;

[0082] Temperature sensor, using thermistor temperature sensor, real-time measurement of saline soil temperature data;

[0083] The metal electrode assembly is used to detect the corrosion potential of saline soil to different metals, and is composed of electrodes made of multiple different metals.

[0084] In this embodiment, the data processing module includes a data cleaning submodule, a data standardization submodule and a data dimension reduction submodule, wherein:

[0085] A data cleaning submodule is used to receive the initial soil data output by the data acquisition module, perform data cleaning on the initial soil data, fill in missing values ​​and delete abnormal values, and obtain first soil data;

[0086] A data standardization submodule, used for performing data standardization processing on the first soil data by adopting Z-score standardization to obtain second soil data;

[0087] The data dimension reduction submodule is used to perform data dimension reduction processing on the second soil data, convert the second soil data into low-dimensional space data for feature extraction, and integrate various features to obtain intermediate soil data.

[0088] In this embodiment, the data dimension reduction submodule includes a decentralized operation unit, a matrix construction unit, a feature decomposition unit and a feature extraction unit, wherein:

[0089] A decentralized operation unit is used to perform a decentralized operation on the second soil data to obtain

[0090]

[0091] Where X represents the second soil data, n represents the number of data values ​​contained in the second soil data, and μ represents the mean vector of the second soil data. Represents the decentralized Second Soil data, x i represents the i-th eigenvalue;

[0092] Construct a matrix unit to construct the covariance matrix V:

[0093]

[0094] In the formula, T represents the transposition operator;

[0095] The eigendecomposition unit is used to perform eigendecomposition on V and calculate the eigenvalue λ i and its corresponding eigenvector w i , extract the first d eigenvalues ​​and vectors in descending order as the basis of the new subspace, and get the d principal components:

[0096] A=diag[λ1,λ2,…,λ d ]

[0097] w d =[w1,w2,…,w d ]

[0098]

[0099] In the formula, λ i represents the eigenvalue of the covariance matrix V, wi represents the eigenvector of the covariance matrix V, d represents the number of principal components, A represents the first d eigenvalues, W d represents the matrix of the first d eigenvectors, and F represents the principal component matrix;

[0100] The feature extraction unit is used to extract features from the second soil data and integrate the features to obtain intermediate soil data:

[0101] X'=WF+μ

[0102] Where X' represents the second soil data after dimensionality reduction, that is, the intermediate soil data.

[0103] In this embodiment, the data analysis module includes a decomposition submodule, a variable screening submodule, a calculation submodule and an output submodule, wherein:

[0104] The decomposition submodule is used to obtain the intermediate soil data, decompose the intermediate soil data using EEMD decomposition, and divide the intermediate soil data into IMF components and residual components;

[0105] The variable screening submodule is used to screen the variables of IMF components and residual components using the LASSO algorithm;

[0106] The calculation submodule is used to establish a differential equation using the GM (1, N) model, solve the established differential equation, and obtain the calculation result;

[0107] The output submodule is used to warn of the corrosion of saline soil based on the calculation results and output data analysis results.

[0108] In this embodiment, in the GM (1, N) model, the corrosion rate is the dependent variable, and the corrosion influencing factors in the N-1 intermediate soil data are the independent variables. Let the dependent variable be n is the number of data, and the independent variable is i∈[2,N];

[0109] Calculate the first-order cumulative series of the independent variable and dependent variable series calculate The adjacent mean sequence of k∈[2,n];

[0110] The differential equation is established, and the linear correction h1 and the gray action h2 are introduced to correct the random error:

[0111]

[0112] In the formula, a, b i They respectively represent the development coefficient and driving coefficient, reflecting the growth trend and data fluctuation.

[0113] Through the implementation of the above scheme, the effects of various factors such as salt, humidity, temperature, etc. in saline soil on corrosivity can be comprehensively considered. Compared with traditional detection methods, the corrosivity of saline soil can be evaluated more comprehensively and accurately. With an integrated design, the sensor module, data acquisition module, data processing module, data analysis module and wireless communication module work together, which is simple and convenient to operate, reduces the complexity and workload of manual operation, and improves the detection efficiency. In-situ detection can be carried out to avoid the problem of sample property changes that may occur during soil sample collection and transportation, and further ensure the accuracy of the test results. The long-term monitoring function helps to gain an in-depth understanding of the changing laws of saline soil corrosivity, and can continuously optimize the model based on the monitoring results, improve the reliability of detection, and issue early warnings on the corrosion of saline soil, so as to timely discover potential corrosion risks and avoid engineering accidents and economic losses caused by soil corrosion.

[0114] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A saline soil corrosivity detection system, characterized in that: The saline soil corrosivity detection system comprises a sensor module, a data acquisition module, a data processing module, a data analysis module and a wireless communication module, wherein: Sensor module for real-time measurement of basic data of saline soil; A data acquisition module, connected to the sensor module, converts the analog signal containing the basic data output by the sensor module into a digital signal to obtain initial soil data; A data processing module, used for performing data preprocessing on the initial soil data output by the data acquisition module to obtain intermediate soil data; A data analysis module is used to analyze the intermediate soil data, issue an early warning for the corrosion of saline soil, and output the data analysis results; The wireless communication module is used to convert the data analysis results obtained by the data analysis module into a detection report and send it to a remote monitoring center or a user's mobile terminal.

2. A saline soil corrosivity detection system as claimed in claim 1, characterized in that: The sensor module includes a salt sensor, a humidity sensor, a temperature sensor and a metal electrode assembly, wherein: Salt sensor, used to measure the salt content in saline soil in real time, using ion selective electrode technology to distinguish the content of different types of salt; Humidity sensor, using capacitive humidity sensor, real-time measurement of humidity data of saline soil; Temperature sensor, using thermistor temperature sensor, real-time measurement of saline soil temperature data; The metal electrode assembly is used to detect the corrosion potential of saline soil to different metals, and is composed of electrodes made of multiple different metals.

3. The saline soil corrosivity detection system according to claim 1, characterized in that: The data processing module includes a data cleaning submodule, a data standardization submodule and a data dimension reduction submodule, wherein: A data cleaning submodule, configured to receive the initial soil data output by the data acquisition module, perform data cleaning on the initial soil data, fill in missing values ​​and delete abnormal values, so as to obtain first soil data; A data standardization submodule, used for performing data standardization processing on the first soil data by adopting Z-score standardization to obtain second soil data; The data dimension reduction submodule is used to perform data dimension reduction processing on the second soil data, convert the second soil data into low-dimensional space data for feature extraction, and integrate various features to obtain intermediate soil data.

4. A saline soil corrosivity detection system as claimed in claim 3, characterized in that: The data dimension reduction submodule includes a decentralized operation unit, a matrix construction unit, a feature decomposition unit and a feature extraction unit, wherein: A decentralized operation unit is used to perform a decentralized operation on the second soil data to obtain Where X represents the second soil data, n represents the number of data values ​​contained in the second soil data, and μ represents the mean vector of the second soil data. Represents the decentralized Second Soil data, x i represents the i-th eigenvalue; Construct a matrix unit to construct the covariance matrix V: In the formula, T represents the transposition operator; The eigendecomposition unit is used to perform eigendecomposition on V and calculate the eigenvalue λ i and its corresponding eigenvector w i , extract the first d eigenvalues ​​and vectors in descending order as the basis of the new subspace, and get the d principal components: A=diag[λ1,λ2,…,λ d IN d =[w1,w2,…,w d ] In the formula, λ i represents the eigenvalue of the covariance matrix V, w i represents the eigenvector of the covariance matrix V, d represents the number of principal components, A represents the first d eigenvalues, W d represents the matrix of the first d eigenvectors, and F represents the principal component matrix; A feature extraction unit is used to extract features from the second soil data and integrate the features to obtain intermediate soil data: X'=WF+μ Where X' represents the second soil data after dimensionality reduction, that is, the intermediate soil data.

5. The saline soil corrosivity detection system according to claim 1, characterized in that: The data analysis module includes a decomposition submodule, a variable screening submodule, a calculation submodule and an output submodule, wherein: A decomposition submodule, used for acquiring intermediate soil data, decomposing the intermediate soil data by using EEMD decomposition, and dividing the intermediate soil data into an IMF component and a residual component; The variable screening submodule is used to screen the variables of IMF components and residual components using the LASSO algorithm; The calculation submodule is used to establish a differential equation using the GM (1, N) model, solve the established differential equation, and obtain the calculation result; The output submodule is used to warn of the corrosion of saline soil based on the calculation results and output data analysis results.

6. The saline soil corrosivity detection system according to claim 1, characterized in that: In the GM (1, N) model, the corrosion rate is the dependent variable, and the corrosion influencing factors in the N-1 intermediate soil data are the independent variables. Let the dependent variable be n is the number of data, and the independent variable is i∈[2,N]; Calculate the first-order cumulative series of the independent variable and dependent variable series calculate The adjacent mean sequence of k∈[2,n]; The differential equation is established, and the linear correction h1 and the gray action h2 are introduced to correct the random error: In the formula, a, b i They respectively represent the development coefficient and driving coefficient, reflecting the growth trend and data fluctuation.

7. A method for detecting the corrosiveness of saline soil, characterized in that: The corrosiveness detection method of saline soil comprises the following steps: In the saline soil area to be detected, a salt sensor, a humidity sensor, a temperature sensor and a metal electrode assembly are buried in the soil, basic data of the saline soil is measured in real time by each sensor, and the analog signal output by the sensor containing the basic data is converted into a digital signal to obtain initial soil data; Performing data preprocessing on the initial soil data output by the data acquisition module to obtain intermediate soil data; Performing data analysis on the intermediate soil data, issuing early warnings on the corrosion of saline soil, and outputting data analysis results; The data analysis results obtained by the data analysis module are converted into a detection report and sent to a remote monitoring center or a user's mobile terminal.

8. A method for detecting the corrosiveness of saline soil according to claim 7, characterized in that: The step of performing data preprocessing on the initial soil data output by the data acquisition module to obtain intermediate soil data includes: Receiving the initial soil data output by the data acquisition module, performing data cleaning processing on the initial soil data, filling missing values ​​and deleting abnormal values, to obtain first soil data; The first soil data is subjected to data standardization processing by adopting Z-score standardization to obtain second soil data; The second soil data is subjected to data dimensionality reduction processing, and the second soil data is converted into low-dimensional space data for feature extraction, and each feature is integrated to obtain intermediate soil data.

9. A method for detecting the corrosiveness of saline soil according to claim 7, characterized in that: The data analysis is performed on the intermediate soil data, and an early warning is given for the corrosion of saline soil, and the data analysis results are output, including: Acquire intermediate soil data, and decompose the intermediate soil data by using EEMD decomposition to divide the intermediate soil data into an IMF component and a residual component; The LASSO algorithm is used to screen variables of IMF components and residual components; The GM (1, N) model is used to establish the difference equation, and the established difference equation is solved to obtain the calculation result; Based on the calculation results, an early warning is issued for the corrosion of saline soil and data analysis results are output.

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