CN-121978293-A - Water quality abnormal fluctuation monitoring method based on intelligent sensor multi-parameter analysis

CN121978293ACN 121978293 ACN121978293 ACN 121978293ACN-121978293-A

Abstract

The invention discloses a water quality abnormal fluctuation monitoring method based on intelligent sensor multi-parameter analysis, which relates to the technical field of water quality monitoring and comprises the steps of obtaining at least one electromagnetic disturbance signal; the method comprises the steps of obtaining periodic electromagnetic disturbance signals and non-periodic electromagnetic disturbance signals, obtaining reference positions, forming reverse compensation signals for the periodic electromagnetic disturbance signals attenuated after shielding processing, obtaining calibration signals, obtaining target signals, obtaining signal attenuation ratios of probes, obtaining input characteristic signals of the intelligent sensor, and carrying out target signal compensation according to the signal attenuation ratios and the input characteristic signals of the intelligent sensor. By classifying the electromagnetic disturbance signals, obtaining the reference positions and recognizing occasional abnormal signals in the calibration signals, different treatments are carried out according to the periodic and non-periodic conditions of the electromagnetic disturbance signals, so that the abrupt change conditions can be treated according to the characteristics of the electromagnetic disturbance signals, and the disturbance can be reduced more comprehensively.

Inventors

YUAN BO
HE YANG
WEI TINGTING
WANG ZINA
LI LU
Xia Yupan
MA RUILIN

Assignees

河南省水文水资源测报中心

Dates

Publication Date: 20260505
Application Date: 20251218

Claims (10)

1. The water quality abnormality fluctuation monitoring method based on the intelligent sensor multi-parameter analysis is characterized by comprising the following steps: Identifying and decomposing electromagnetic disturbance of the environment where the intelligent sensor is located to obtain at least one electromagnetic disturbance signal; classifying the electromagnetic disturbance signals to obtain periodic electromagnetic disturbance signals and non-periodic electromagnetic disturbance signals; Based on the non-periodic electromagnetic disturbance signals, a reference position is obtained, and the intelligent sensor probe and the water body to be measured are arranged at the reference position; Disturbance shielding treatment is carried out outside the intelligent sensor probe and the water body to be measured, and a reverse compensation signal is formed on the periodic electromagnetic disturbance signal attenuated after the shielding treatment; Acquiring a real-time signal captured by a probe and displayed by an intelligent sensor, superposing a reverse compensation signal and the real-time signal to obtain a calibration signal, identifying an occasional abnormal signal in the calibration signal, and removing the occasional abnormal signal to obtain a target signal; and acquiring a signal attenuation ratio of the probe, acquiring an input characteristic signal of the intelligent sensor, performing target signal compensation according to the signal attenuation ratio and the input characteristic signal of the intelligent sensor, obtaining a low disturbance signal, and performing water quality abnormality identification by using the low disturbance signal.
2. The method for monitoring abnormal water quality fluctuation based on multi-parameter analysis of intelligent sensors according to claim 1, wherein the steps of identifying and decomposing electromagnetic disturbance of the environment where the intelligent sensors are located to obtain at least one electromagnetic disturbance signal comprise the following steps: Based on the historical data, acquiring a display allowable error of the intelligent sensor, and acquiring a signal with the amplitude of waveform change equal to the display allowable error as a critical signal; Performing identification operation under the condition that the water body to be measured does not operate, and marking the identified position as a characteristic point; Identifying the environmental signals according to the frequencies of the signals, and summarizing the environmental signals with different frequencies into an environmental signal set; and deleting the environmental signals with the intensity smaller than that of the critical signals in the environmental signal set, and taking the environmental signals in the deleted environmental signal set as at least one electromagnetic disturbance signal respectively.
3. The method for monitoring abnormal water quality fluctuation based on intelligent sensor multi-parameter analysis according to claim 2, wherein the step of classifying the electromagnetic disturbance signals to obtain periodic electromagnetic disturbance signals and non-periodic electromagnetic disturbance signals comprises the following steps: sampling and fitting the electromagnetic disturbance signals to obtain a disturbance fitting function, wherein the definition domain of the disturbance fitting function is a sampling and fitting time range, the independent variable of the disturbance fitting function is time, and the dependent variable of the disturbance fitting function is the intensity of the electromagnetic disturbance signals; An image of a disturbance fitting function is made in a coordinate system and is used as a first image, a second image is arranged on the right side of the first image, the shape of the first image is consistent with that of the second image, and the right end of the first image is coincident with the left end of the second image; moving the second image leftwards by the length of the sampling fitting time range; Taking a region between the right end of the first image and the left end of the second image as a characteristic region, taking the part of the first image positioned in the characteristic region as a first part, and taking the part of the second image positioned in the characteristic region as a second part; In the moving process of the second image, if a moment exists, the first part is overlapped with the second part, the electromagnetic disturbance signal is a periodic electromagnetic disturbance signal, otherwise, the electromagnetic disturbance signal is an aperiodic electromagnetic disturbance signal.
4. The method for monitoring abnormal water quality fluctuation based on intelligent sensor multi-parameter analysis according to claim 3, wherein the obtaining the reference position based on the non-periodic electromagnetic disturbance signal comprises the following steps: Identifying the generation position of the non-periodic electromagnetic disturbance signal to obtain a non-periodic disturbance position; Connecting adjacent non-periodic disturbance positions to obtain a target area; setting test time, and uniformly dividing the test time into at least one test interval; when the non-periodic electromagnetic disturbance signal is a positive signal in the test interval, the non-periodic electromagnetic disturbance signal is used as a positive non-periodic electromagnetic disturbance signal, otherwise, the non-periodic electromagnetic disturbance signal is used as a negative non-periodic electromagnetic disturbance signal; Uniformly taking at least one identification point in the target area, calculating the distance from the identification point to the aperiodic disturbance location, and taking the distance from the feature point to the aperiodic disturbance location as a first distance and a second distance; The first distance is compared with the second distance, and signal weight of the aperiodic disturbance position is obtained; Multiplying the positive non-periodic electromagnetic disturbance signal and the negative non-periodic electromagnetic disturbance signal in the test interval with the signal weights of the corresponding non-periodic disturbance positions respectively, and then superposing the multiplied signals to obtain characteristic signals; Summarizing the identification points with the characteristic signal strength smaller than the critical signal into a characteristic set of the test interval; and taking intersection sets of the feature sets of all the test intervals to obtain a target set, and taking any one identification point in the target set as a reference position.
5. The method for monitoring abnormal water quality fluctuation based on intelligent sensor multi-parameter analysis according to claim 4, wherein the identifying the generation position of the non-periodic electromagnetic disturbance signal to obtain the non-periodic disturbance position comprises the following steps: Setting a first test point, shielding equipment for measuring the non-periodic electromagnetic disturbance signals at the first test point into a circular plate, wherein when the equipment moves, the connecting line of the circle center of the circular plate and the first test point is perpendicular to the circular plate, and the distance between the circle center of the circular plate and the first test point is a fixed value; the circular plate moves around the first test point in an omnibearing way, and signals with the same frequency as the non-periodic electromagnetic disturbance signals after shielding are obtained and used as signals after shielding; Taking the position of the circular plate with the minimum signal after shielding as a calibration position, and taking the connecting line of the circle center of the circular plate at the calibration position and the first test point as a characteristic line; and changing the position of the first test point to obtain a second test point and a characteristic line of the second test point, wherein the intersection point of the characteristic line of the first test point and the characteristic line of the second test point is a non-periodic disturbance position.
6. The method for monitoring abnormal water quality fluctuation based on multi-parameter analysis of intelligent sensor according to claim 5, wherein the disturbance shielding treatment outside the intelligent sensor probe and the water body to be measured comprises the following steps: And a shielding device is arranged outside the intelligent sensor probe and the water body to be measured, the thickness of the shielding device is smaller than the intensity of the critical signal when the maximum value of the intensity of the periodic electromagnetic disturbance signal is shielded.
7. The intelligent sensor multi-parameter analysis-based water quality anomaly fluctuation monitoring method according to claim 6, wherein the sporadic anomaly signal identification in the calibration signal comprises the steps of: Uniformly adopting the calibration signal according to time to obtain at least one correction point, taking the sampled interval as preset time, and taking the abscissa of the correction point as time and the ordinate as signal intensity; respectively taking two correction points adjacent to the correction point as a first correction point and a second correction point; The absolute value of the difference between the first correction point and the ordinate of the correction point is overlapped with the absolute value of the difference between the second correction point and the ordinate of the correction point, so that the characteristic value of the correction point is obtained; Taking the average value of the characteristic values of at least one correction point to obtain a characteristic average value, and taking twice of the characteristic average value as a characteristic threshold value; taking the correction point with the characteristic value exceeding the characteristic threshold value as a target correction point; summarizing the target correction points with the time intervals equal to the preset time into a target correction point set; fitting the abscissa and the ordinate of the target correction points in the target correction point set to obtain an abnormal fitting function, wherein the endpoints of the definition domain of the abnormal fitting function are respectively the minimum value and the maximum value of the abscissa of the target correction points in the target correction point set; and taking the signal represented by the anomaly fit function as an occasional anomaly signal.
8. The method for monitoring abnormal water quality fluctuation based on intelligent sensor multi-parameter analysis according to claim 7, wherein the step of obtaining the signal attenuation ratio of the probe comprises the following steps: counting the first intensity of at least one signal at the probe and the second intensity finally input into the intelligent sensor, wherein the second intensity is compared with the first intensity to obtain a preliminary attenuation ratio; and (5) averaging at least one preliminary attenuation ratio to obtain the signal attenuation ratio of the probe.
9. The method for monitoring abnormal water quality fluctuation based on multi-parameter analysis of intelligent sensor according to claim 8, wherein the step of obtaining the input characteristic signal of the intelligent sensor comprises the steps of: when the probe detects a 0 signal, a display signal of the intelligent sensor is acquired and used as an input characteristic signal of the intelligent sensor.
10. The method for monitoring abnormal water quality fluctuation based on multi-parameter analysis of intelligent sensor according to claim 8, wherein the target signal compensation according to the signal attenuation ratio and the input characteristic signal of the intelligent sensor comprises the following steps: subtracting the input characteristic signal from the target signal to obtain a compensation signal; the compensation signal is divided by the signal attenuation ratio to obtain a low disturbance signal.

Description

Water quality abnormal fluctuation monitoring method based on intelligent sensor multi-parameter analysis Technical Field The invention relates to the technical field of water quality monitoring, in particular to a water quality abnormal fluctuation monitoring method based on intelligent sensor multi-parameter analysis. Background Measurement interference of the water quality sensor is a key factor affecting data accuracy and stability. The disturbance may come from the sensor itself, the environmental conditions, the sample matrix and the operating process. Electromagnetic interference is particularly prevalent, and sensor signals (especially weak electrochemical signals) may be subject to electromagnetic interference from nearby motors, frequency converters, radios, and the like. When the intelligent sensor is used, electromagnetic disturbance of the environment exists, and the electromagnetic disturbance of the environment is possibly multiple and regular or irregular, so that effective disturbance elimination is difficult to perform, and a certain deviation exists in the monitoring effect of the intelligent sensor. Disclosure of Invention In order to solve the technical problems, the technical scheme solves the problems in the background technology by providing the water quality abnormality fluctuation monitoring method based on the intelligent sensor multi-parameter analysis. In order to achieve the above purpose, the invention adopts the following technical scheme: A water quality abnormality fluctuation monitoring method based on intelligent sensor multi-parameter analysis comprises the following steps: Identifying and decomposing electromagnetic disturbance of the environment where the intelligent sensor is located to obtain at least one electromagnetic disturbance signal; classifying the electromagnetic disturbance signals to obtain periodic electromagnetic disturbance signals and non-periodic electromagnetic disturbance signals; Based on the non-periodic electromagnetic disturbance signals, a reference position is obtained, and the intelligent sensor probe and the water body to be measured are arranged at the reference position; Disturbance shielding treatment is carried out outside the intelligent sensor probe and the water body to be measured, and a reverse compensation signal is formed on the periodic electromagnetic disturbance signal attenuated after the shielding treatment; Acquiring a real-time signal captured by a probe and displayed by an intelligent sensor, superposing a reverse compensation signal and the real-time signal to obtain a calibration signal, identifying an occasional abnormal signal in the calibration signal, and removing the occasional abnormal signal to obtain a target signal; and acquiring a signal attenuation ratio of the probe, acquiring an input characteristic signal of the intelligent sensor, performing target signal compensation according to the signal attenuation ratio and the input characteristic signal of the intelligent sensor, obtaining a low disturbance signal, and performing water quality abnormality identification by using the low disturbance signal. Preferably, the identifying and decomposing the electromagnetic disturbance of the environment where the intelligent sensor is located to obtain at least one electromagnetic disturbance signal includes the following steps: Based on the historical data, acquiring a display allowable error of the intelligent sensor, and acquiring a signal with the amplitude of waveform change equal to the display allowable error as a critical signal; Performing identification operation under the condition that the water body to be measured does not operate, and marking the identified position as a characteristic point; Identifying the environmental signals according to the frequencies of the signals, and summarizing the environmental signals with different frequencies into an environmental signal set; and deleting the environmental signals with the intensity smaller than that of the critical signals in the environmental signal set, and taking the environmental signals in the deleted environmental signal set as at least one electromagnetic disturbance signal respectively. Preferably, the classifying the electromagnetic disturbance signals to obtain periodic electromagnetic disturbance signals and non-periodic electromagnetic disturbance signals includes the following steps: sampling and fitting the electromagnetic disturbance signals to obtain a disturbance fitting function, wherein the definition domain of the disturbance fitting function is a sampling and fitting time range, the independent variable of the disturbance fitting function is time, and the dependent variable of the disturbance fitting function is the intensity of the electromagnetic disturbance signals; An image of a disturbance fitting function is made in a coordinate system and is used as a first image, a second image is arranged on the right side of the first image,