An intelligent control system for water environment monitoring

Abstract

This invention relates to the field of water quality monitoring technology and discloses an intelligent control system for water environment monitoring, comprising: acquiring salinity time series through upstream and downstream monitoring units; using a signal processing module to filter the data and extract the subtidal component, and obtaining the synodic reference phase through Hilbert transform; then calculating the phase difference and converting it into an instantaneous travel delay function; then using a fusion processing module to perform time axis mapping and duration weighting based on the delay function to obtain a fused salinity time series; finally, using an intelligent control module to implement discharge regulation based on the fusion result, thereby achieving dynamic alignment and precise fusion of upstream and downstream salinity signals, and improving the accuracy and reliability of monitoring and water environment regulation.

Description

Technical Field

[0001] This invention relates to the field of water quality monitoring technology, and more specifically, to an intelligent control system for water environment monitoring. Background Technology

[0002] With the deepening of comprehensive watershed management and water ecological restoration, multi-node sensing and monitoring systems have been widely deployed in the tidal estuary and downstream main stream areas, which are key nodes for water environment regulation. These systems can collect core water quality indicators such as salinity, temperature, dissolved oxygen, and nutrients in real time, aiming to support the analysis of pollutant transport patterns and the prediction of water quality evolution trends through multi-dimensional data, thus providing basic data support for watershed water environment management. In conventional understanding, water quality signals from upstream monitoring nodes are usually regarded as the input source of downstream signals, with only a simple time transmission delay between the two. Therefore, traditional monitoring schemes are mostly designed with data processing logic based on this.

[0003] However, the unique hydrodynamic environment of tidal river sections presents significant challenges to water environment monitoring. On the one hand, tidal movements cause continuous fluctuations in downstream hydrodynamic conditions, creating a dynamic interplay between the freshwater dynamics of upstream inflows and the saline dynamics of downstream tidal currents, disrupting the stable upstream-downstream transmission relationship. On the other hand, the saline intrusion process exhibits a marked asymmetry within the semi-lunar tidal cycle. Specifically, salinity rises rapidly during the transition from neap tide to spring tide, while the rate of salinity decrease slows significantly during the decline from spring tide to neap tide. This dynamic process of rapid rise and slow fall means that, over long time scales, upstream and downstream water quality signals no longer maintain a simple lag relationship, but rather exhibit a reversed dependency and a continuous spatiotemporal misalignment.

[0004] Current mainstream water environment monitoring methods suffer from two main limitations: First, they use fixed time delays to align upstream and downstream monitoring data, ignoring the dynamic changes in hydrodynamics and salinity within a bi-weekly cycle in tidal river sections, resulting in insufficient data alignment accuracy. Second, they directly use data from the same time point for profile comparison, failing to reflect the true response relationship of water quality signals between upstream and downstream. Both of these methods are prone to serious errors under the context of bi-weekly tidal and salinity variations. They may misjudge upstream salinity anomalies as problems independently generated downstream, or incorrectly project the arrival time of pollution peaks or salt fronts, leading to distorted calculations of watershed water quality loads. These methods fail to meet the actual needs of intelligent control for precise management of the water environment in tidal river sections, resulting in uncontrolled salinity in tidal sections and further exacerbating the technical problems of aquatic environmental imbalance in these sections. Summary of the Invention

[0005] This invention provides an intelligent control system for water environment monitoring, which solves the technical problems mentioned in the background art.

[0006] This invention provides an intelligent control system for water environment monitoring, comprising:

[0007] The upstream monitoring unit is located at the upstream near-tidal boundary section and collects upstream salinity time series.

[0008] The downstream monitoring unit is located at the downstream near-tidal boundary section and collects downstream salinity time series.

[0009] The signal processing module, connected to the upstream and downstream monitoring units, is configured as follows:

[0010] The upstream and downstream salinity time series are filtered to separate the subtidal component; based on the subtidal component, the upstream and downstream synodic reference phases are obtained through Hilbert transform; the synodic phase difference across nodes and layers is calculated based on the upstream and downstream synodic reference phases, and the synodic phase difference is converted into an instantaneous travel time delay function based on the synodic beat frequency.

[0011] The fusion processing module, connected to the signal processing module, is configured as follows:

[0012] Using the synodic period as the time window, the duration parameter is calculated based on the sign duration of the instantaneous travel delay function; the upstream salinity time series is mapped onto the time axis based on the instantaneous travel delay function to obtain the aligned upstream salinity time series; the fusion weight coefficient is determined based on the duration parameter, and the aligned upstream salinity time series and the downstream salinity time series are fused according to the fusion weight coefficient to obtain the fused salinity time series;

[0013] The intelligent control module performs effluent treatment based on the fused salinity time series.

[0014] Furthermore, the upstream and downstream salinity time series are filtered to separate the subtidal component, including:

[0015] Based on the set of astronomical angular frequencies Determine the upper limit of the low-pass band. With stopband start ;in, , This represents the angular frequency of the M2 tidal constituent. This represents the angular frequency of the S2 tidal constituent. This represents the angular frequency of the K1 tidal constituent. The angular frequency of the O1 tidal constituent;

[0016] Fast Fourier transforms were performed on the upstream and downstream salinity time series respectively to obtain the upstream frequency domain spectrum. and downstream frequency domain spectrum ;

[0017] Constructing a zero-phase low-pass transfer function ;in, exist When the value is 1, When the value is 0, The timing is cosine smooth transition, and the upstream low-pass main filter is calculated. and downstream low-pass main filter ;in, It belongs to the upstream frequency domain spectrum or the downstream frequency domain spectrum;

[0018] right and Applying narrowband notch transfer function ,as follows:

[0019]

[0020] in, Indicates the notch bandwidth of M2 tidal fraction or S2 tidal fraction;

[0021] The product of the narrowband notch transfer function and the zero-phase low-pass transfer function is used as the total transfer function.

[0022] The upstream subtidal component is obtained by performing an inverse fast Fourier transform on the product of the total transfer function and the upstream low-pass main filter; the downstream subtidal component is obtained by performing an inverse fast Fourier transform on the product of the total transfer function and the downstream low-pass main filter.

[0023] Furthermore, based on the subtidal component, the upstream and downstream synodic reference phases are obtained through Hilbert transform, including:

[0024] The upstream and downstream subtidal components are respectively subjected to mean removal and standardization to obtain the standard upstream subtidal component. and standard downstream sub-tidal component ;

[0025] Will and The absolute difference is used as the synodic beat frequency;

[0026] A time-varying reference waveform is generated using the sine value of the synodic beat frequency. The reference phase of the reference waveform is calculated using the Hilbert transform. ;

[0027] The upstream analytical signals of the standard upstream subtidal component and the standard downstream subtidal component are constructed using the reference phase, respectively. and downstream analytical signals ;in, This represents the Hilbert transform operation, where i is the imaginary unit. ;

[0028] Calculate the upstream instantaneous phase of the upstream analytic signal Calculate the downstream instantaneous phase of the downstream analytical signal. ;in, Represents the arctangent function in two variables. Represents the imaginary part of an analytic signal. Analyze the real part of the signal;

[0029] Calculate the upstream synodic reference phase ;

[0030] Calculate the downstream synodic reference phase .

[0031] Furthermore, based on the upstream and downstream synodic reference phases, the synodic phase difference across nodes and layers is calculated, and the synodic phase difference is converted into an instantaneous travel delay function based on the synodic beat frequency, including:

[0032] The principal phase difference is obtained by applying the wrap function to the phase difference between the upstream synodic reference phase and the downstream reference phase; the wrap function maps the phase difference to an interval. ;

[0033] The principal phase difference is continuously expanded using unwrap to obtain a continuous phase difference;

[0034] The ratio of the continuous phase difference to the synodic beat frequency is used as the instantaneous time history delay function. .

[0035] Furthermore, using the synodic period as the time window, the duration parameter is calculated based on the symbol duration of the instantaneous travel delay function, including:

[0036] The ratio of 2π to the synodic beat frequency is used as the synodic period. ;

[0037] In time Define time window ;

[0038] Through the time window Real-time time-delay function values ​​are collected at fixed time intervals;

[0039] If the instantaneous time history delay function value is greater than 0, then the sign is positive 1;

[0040] If the instantaneous time history delay function value is less than 0, then the sign is negative 1;

[0041] If the instantaneous time-history delay function value is equal to 0, then calculate the difference between two adjacent instantaneous time-history delay function values ​​on the time scale, and determine the corresponding sign based on the sign of the difference;

[0042] Determine the moment when the instantaneous time history delay function is positive 1 to obtain the first duration;

[0043] Determine the moment when the instantaneous time history delay function value is negative 1 to obtain the second duration;

[0044] The ratio of the difference between the first and second durations to the synodic period is used as the time interval. Duration parameter.

[0045] Furthermore, based on the instantaneous travel delay function, the upstream salinity time series is time-axis mapped to obtain an aligned upstream salinity time series, including:

[0046] Calculate the difference between the upstream salinity value at time s and the instantaneous time history delay function value at time s in the upstream salinity time series, and form an initial salinity alignment sequence based on the difference;

[0047] If the initial salinity alignment value at time s in the initial alignment sequence is greater than or equal to the initial salinity alignment value at time s+1, then the initial salinity alignment sequence is optimized, including:

[0048] The first constraint includes: the initial salinity alignment value at time s is less than the initial salinity alignment value at time s+1.

[0049] The second constraint includes: calculating the square of the initial salinity alignment value at time s after optimization and the initial salinity alignment value at time s, and summing the squares at each time; and minimizing the sum of the squares.

[0050] Based on the first and second constraints, an optimized salinity alignment sequence is formed, resulting in an aligned upstream salinity time series.

[0051] Furthermore, the fusion weighting coefficients are determined based on the persistence parameter, and the aligned upstream salinity time series and downstream salinity time series are fused according to the fusion weighting coefficients to obtain the fused salinity time series, including:

[0052] A time window is constructed at time s to determine the duration parameter at time s. ;

[0053] Construct the fusion weight coefficients using the duration parameter at time s. The maximum value of the fusion weight coefficient is limited to 1 and the minimum value to 0.

[0054] Calculate the aligned upstream salinity value at time s and The first product, and the downstream salinity value at time s, and The second product of the first and second products is taken as the fused salinity value at the s-th time point to form a fused salinity time series.

[0055] Furthermore, a bleed-out process is performed based on the fused salinity time series, including:

[0056] Determine the fused salinity value of the fused salinity time series at the current moment;

[0057] If the fused salinity value is not within the preset salinity range, the flow rate of the upstream outlet will be controlled until the fused salinity value is within the preset salinity range.

[0058] The beneficial effects of this invention are as follows: by constructing the synodic phase difference, instantaneous travel delay function, duration parameter and dynamic weight fusion, dynamic phase alignment and weight allocation of salinity signals of upstream and downstream of tidal river sections are realized. This allows for accurate capture of the asymmetric response property of upstream leading and downstream lagging under the drive of semi-lunar tides, avoiding misalignment and systematic deviation, significantly improving the accuracy of monitoring data alignment and the reliability of fusion results, and enabling intelligent control of discharge to keep salinity within a reasonable range, effectively supporting the precise regulation and ecological stability of the water environment in tidal sections. Attached Figure Description

[0059] Figure 1 This is a block diagram of an intelligent control system for water environment monitoring according to the present invention. Detailed Implementation

[0060] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and changes may be made to the function and arrangement of the elements discussed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the examples. Furthermore, features described in some examples may be combined in other examples.

[0061] like Figure 1 As shown, an intelligent control system for water environment monitoring includes:

[0062] The upstream monitoring unit is located at the upstream near-tidal boundary section and collects upstream salinity time series.

[0063] The downstream monitoring unit is located at the downstream near-tidal boundary section and collects downstream salinity time series.

[0064] The signal processing module, connected to the upstream and downstream monitoring units, is configured as follows:

[0065] The upstream and downstream salinity time series are filtered to separate the subtidal component; based on the subtidal component, the upstream and downstream synodic reference phases are obtained through Hilbert transform; the synodic phase difference across nodes and layers is calculated based on the upstream and downstream synodic reference phases, and the synodic phase difference is converted into an instantaneous travel time delay function based on the synodic beat frequency.

[0066] The fusion processing module, connected to the signal processing module, is configured as follows:

[0067] Using the synodic period as the time window, the duration parameter is calculated based on the sign duration of the instantaneous travel delay function; the upstream salinity time series is mapped onto the time axis based on the instantaneous travel delay function to obtain the aligned upstream salinity time series; the fusion weight coefficient is determined based on the duration parameter, and the aligned upstream salinity time series and the downstream salinity time series are fused according to the fusion weight coefficient to obtain the fused salinity time series;

[0068] The intelligent control module performs effluent treatment based on the fused salinity time series.

[0069] It should be noted that the semi-monthly memory-type phase reversal persistence is a phenomenon in the salinity dynamics of tidal river sections. Specifically, it manifests as the phase change of salinity in the upper bottom layer leading that of the lower middle and lower layers in the semi-monthly cycle. Moreover, the sign of this leading-lagging relationship can be maintained across multiple tidal cycles. Its physical mechanisms include: the asymmetry and lag effect of salt intrusion under the modulation of spring tides; the alternation of tidal-driven and density-driven mechanisms during strong and weak tides; the response amplification caused by the reflection of tidal waves in the upper section; and the residual transport generated by the lateral salt storage and backflow process of the tidal flat. These factors work together to make the phase reversal state have significant persistence, causing physical misalignment and systematic deviation in traditional multi-node fusion methods based on fixed time delays or synchronization moments. A new monitoring strategy with dynamic phase alignment and persistence weighting is required.

[0070] It should be noted that the upstream near-tidal boundary section is located at the upstream end of the tidal section. It is a monitoring section near the limit of tidal influence propagating upward along the river channel, and also a transition zone between runoff and tidal dynamics. The upstream near-tidal boundary section is characterized by runoff dominance and tidal disturbance. Upstream runoff (freshwater) still has a certain advantage, and the overall trend of water flow is downstream. However, during high tide, under the influence of tidal backwater, a brief landward (upstream) backflow may occur at the bottom layer (especially during neap tides, when density-driven flow is enhanced), forming a rudimentary vertical circulation pattern with the surface layer flowing downward and the bottom layer upward. The salinity of the upstream near-tidal boundary section is generally low (due to dilution by upstream freshwater), but the bottom layer salinity is more sensitive to brine intrusion (the brine density is high, and it propagates preferentially along the bottom layer). It is prone to the early rise signal during the neap tide to spring tide stage, and is the initial source of the upstream leading feature in the continuous phenomenon of semi-moon memory-type phase reversal.

[0071] It should be noted that the downstream near-tidal boundary section is located at the downstream end of the tidal section, close to the estuary or the core area of ​​tidal action. It is a monitoring section of a typical response zone dominated by tidal dynamics and with relatively weak runoff influence. The downstream near-tidal boundary section is characterized by tidal dominance and runoff modulation. The ebb and flow of the tides are intense, with periodic reversals in velocity and direction (towards land during high tide and towards sea during low tide), large tidal range, high tidal velocity, and significant tidal diffusion. The salinity of the downstream near-tidal boundary section is generally high (influenced by offshore brine). The salinity in the middle and lower layers is affected by the combined effects of density circulation (landward) and tidal mixing (vertical), and its changes lag behind those in the upstream lower layers. Furthermore, due to river propagation and tidal modulation, the salinity phase exhibits a delayed accumulation.

[0072] Specifically, the calibration steps for the upstream near-tidal boundary section are as follows:

[0073] Preliminary scope determination: Temporary monitoring points (intervals of 500m to 1km) are set up along the river from upstream to downstream (towards the estuary) to continuously monitor for 7 complete tidal cycles (covering at least 1 synodic cycle), and record the flow velocity (vertical stratification), salinity (vertical stratification), and water level data at each point.

[0074] Calculate the percentage of landward flow velocity at each point during high tide: the ratio of the duration of landward flow velocity to the total high tide time. If the ratio is ≤30%, it indicates that the tidal backwater is only a temporary disturbance and the runoff still dominates.

[0075] Calculate the ratio of tidal amplitude to runoff velocity: the ratio of the water level amplitude caused by the tide to the average runoff velocity of the cross section. If the ratio is ≤0.5, it indicates that the runoff dynamics are still stronger than the tidal disturbance.

[0076] The maximum salinity of the bottom layer is ≤5‰ (significantly diluted by upstream freshwater), and the rate of salinity increase in the bottom layer during the neap tide to spring tide phase is more than 20% faster than that in the middle layer (reflecting the bottom layer's advanced response to salt intrusion).

[0077] The downstream point that satisfies the above dynamic and salinity thresholds is the upstream near-tidal boundary section.

[0078] Specifically, the calibration steps for the downstream near-tidal boundary section are as follows:

[0079] Preliminary range determination: Temporary monitoring points (intervals of 500m to 1km) were set up along the river from downstream to upstream (away from the estuary) and monitored continuously for 7 complete tidal cycles.

[0080] Calculate the percentage of landward flow velocity at each point during high tide: the ratio of the duration of landward flow velocity to the total high tide time. If the ratio is ≥60%, it indicates that the tidal backing is significant and the landward flow dominates the high tide period.

[0081] Calculate the ratio of tidal amplitude to runoff velocity: the ratio of the water level amplitude caused by the tide to the average runoff velocity of the cross section. If this value is ≥2.0 (indicating that tidal dynamics are dominant).

[0082] The maximum salinity in the middle and lower layers is ≥10% (significantly affected by offshore saline water), and the rate of increase in salinity in the middle and lower layers during the neap tide to spring tide phase lags behind the salinity in the upper bottom layer (lag time ≥12 hours, reflecting phase delay).

[0083] The upstream point that satisfies the above dynamic and salinity thresholds is the downstream near-tidal boundary section.

[0084] In one embodiment of the present invention, filtering is performed on the upstream salinity time series and the downstream salinity time series to separate the subtidal component, including:

[0085] Based on the set of astronomical angular frequencies Determine the upper limit of the low-pass band. With stopband start ;in, , This represents the angular frequency of the M2 tidal constituent. This represents the angular frequency of the S2 tidal constituent. This represents the angular frequency of the K1 tidal constituent. The angular frequency of the O1 tidal constituent;

[0086] In detail, the M2 tidal component is the main semi-diurnal tidal component generated by the lunar tidal force, with a period of approximately 12 hours and 25 minutes. It is one of the most significant tidal components in oceans and tidal river sections, with an angular frequency of approximately [value missing]. rad / s. The S2 tidal constituent is the main semi-diurnal tidal constituent generated by solar tidal force. Its period is similar to that of the M2 tidal constituent, approximately 12 hours, and its angular frequency is approximately [value missing]. rad / s, is the second most important semi-diurnal tidal component after the M2 tidal constituent. The K1 tidal constituent is the main diurnal tidal constituent produced by the combined tidal forces of the moon and the sun, with a period of approximately 23 hours and 56 minutes, and its angular frequency is approximately [value missing]. rad / s is one of the more energetic components of the diurnal tidal components. The O1 tidal constituent is a diurnal tidal constituent caused by the declination component of the moon's tidal force, with a period of approximately 25 hours and 49 minutes, and its angular frequency is approximately... rad / s is also a common diurnal tidal component in tidal waters.

[0087] It should be noted that the upper limit of the low-pass band must be less than the start of the stopband, and both must be less than the smallest angular frequency in the set. This strictly limits the passband to frequencies below diurnal and semi-diurnal tides, ensuring that only slowly varying signals with periods longer than these high-frequency tides, i.e., subtidal components, are retained; the stopband covers all major diurnal and semi-diurnal tide frequencies, thus suppressing high-frequency interference.

[0088] Fast Fourier transforms were performed on the upstream and downstream salinity time series respectively to obtain the upstream frequency domain spectrum. and downstream frequency domain spectrum ;

[0089] It should be noted that Fast Fourier Transform (FFT) is performed on the upstream and downstream salinity time series respectively to obtain the upstream and downstream frequency domain spectra. The salinity series in the time domain contains signal components of different frequencies, and FFT can decompose it into a frequency domain spectrum, which intuitively presents the energy distribution of each frequency component.

[0090] Constructing a zero-phase low-pass transfer function ;in, exist When the value is 1, When the value is 0, The timing is cosine smooth transition, and the upstream low-pass main filter is calculated. and downstream low-pass main filter ;in, It belongs to the upstream frequency domain spectrum or the downstream frequency domain spectrum;

[0091] In detail, a zero-phase low-pass transfer function is constructed. The zero-phase low-pass transfer function takes a value of 1 when the absolute value of the frequency is less than or equal to the upper limit of the low-pass band, indicating that low-frequency signals in this range are completely retained; when the absolute value of the frequency is greater than or equal to the start of the stopband, it takes a value of 0, indicating that high-frequency signals in this range are completely filtered out; between the upper limit of the low-pass band and the start of the stopband, a cosine smooth transition is used to reduce oscillation distortion caused by frequency band abrupt changes during the filtering process.

[0092] Based on the zero-phase low-pass transfer function, the upstream and downstream low-pass main filters are calculated, where represents the frequency in the upstream or downstream frequency domain spectrum. This allows for the initial suppression of high-frequency components such as diurnal and semi-diurnal tides through low-pass filtering, while the zero-phase characteristic ensures that the temporal relationship of the time series is not distorted, guaranteeing that the relative temporal relationship between upstream and downstream signals is unaffected by the filtering.

[0093] right and Applying narrowband notch transfer function ,as follows:

[0094]

[0095] in, Indicates the notch bandwidth of M2 tidal fraction or S2 tidal fraction;

[0096] In detail, the expression for the narrowband notch transfer function applied to the angular frequencies of the M2 and S2 tidal constituents is as follows: ;in The narrowband notch transfer function represents the bandwidth of the M2 or S2 tidal component, and this bandwidth must be narrow enough to avoid affecting the signal within the low-passband. The narrowband notch transfer function is used to suppress spectral leakage in the frequency domain from the M2 and S2 tidal components (the strongest semi-diurnal tidal components). Even after low-pass filtering, these strong high-frequency components may still retain residual energy in the transition region between the passband and stopband. The narrowband notch can specifically weaken these residual interferences, improving the purity of the subtidal components.

[0097] The product of the narrowband notch transfer function and the zero-phase low-pass transfer function is used as the total transfer function.

[0098] In detail, the narrowband notch transfer function and the zero-phase low-pass transfer function are multiplied to obtain the overall transfer function. The overall transfer function combines the overall suppression effect of the low-pass filter on the high-frequency range with the precise attenuation effect of the narrowband notch filter on specific strong high-frequency components, achieving a synergistic filtering effect of broad-spectrum suppression and precise removal, minimizing the interference of high-frequency tidal signals on subtidal components.

[0099] The upstream subtidal component is obtained by performing an inverse fast Fourier transform on the product of the total transfer function and the upstream low-pass main filter; the downstream subtidal component is obtained by performing an inverse fast Fourier transform on the product of the total transfer function and the downstream low-pass main filter.

[0100] In detail, the inverse fast Fourier transform converts the processed signal in the frequency domain back to the time domain, and finally outputs the subtidal components of the upstream and downstream subtidal components. The subtidal components only contain slowly varying information with periods longer than diurnal and semi-diurnal tides.

[0101] In one embodiment of the present invention, based on the subtidal component, the upstream synodic reference phase and the downstream synodic reference phase are obtained through Hilbert transform, including:

[0102] The upstream and downstream subtidal components are respectively subjected to mean removal and standardization to obtain the standard upstream subtidal component. and standard downstream sub-tidal component ;

[0103] It should be noted that the mean-removing and standardization processes performed on the upstream and downstream subtidal components respectively aim to eliminate the interference of amplitude differences on phase analysis. Mean-removing involves subtracting the average value from the subtidal component sequence to remove the overall offset of the sequence; standardization involves dividing the mean-removed sequence by its standard deviation to ensure that the amplitudes of different sequences are on the same order of magnitude. The standard upstream and downstream subtidal components obtained after mean-removing and standardization processes retain only the phase characteristics and shape information of the signal, avoiding the influence of amplitude differences caused by variations in monitoring point environments or instrument sensitivity on subsequent phase comparisons.

[0104] Will and The absolute difference is used as the synodic beat frequency;

[0105] In detail, the synodic beat frequency is determined by the absolute difference between the angular frequencies of the M2 and S2 confluences. The M2 and S2 confluences are the two most significant semi-diurnal tides, and the beat frequency formed by their angular frequency difference corresponds to a semi-monthly cycle (approximately 14.77 days). The semi-monthly cycle is a key time indicator of the persistence of the semi-monthly memory-type phase reversal phenomenon in salinity changes in tidal river sections. Using the semi-monthly cycle as the synodic beat frequency ensures the stability and traceability of the reference benchmark.

[0106] A time-varying reference waveform is generated using the sine value of the synodic beat frequency. The reference phase of the reference waveform is calculated using the Hilbert transform. ;

[0107] In detail, a sinusoidal reference waveform is generated using the synodic beat frequency as the angular frequency. This reference waveform has a strict semi-lunar period and a clearly defined phase change pattern, reflecting the phase evolution of the synodic rhythm under ideal conditions. The reference waveform is processed using a Hilbert transform to obtain its analytic signal, and then the reference phase is calculated based on this signal. The reference phase is a physical quantity describing the phase change of the reference waveform over time, reflecting the angular change of the reference waveform in the complex plane. It provides a reference phase scale for the phases of upstream and downstream subtidal components, eliminating the phase incomparability problem caused by differences in the start times of different sequences.

[0108] The upstream analytical signals of the standard upstream subtidal component and the standard downstream subtidal component are constructed using the reference phase, respectively. and downstream analytical signals ;in, This represents the Hilbert transform operation, where i is the imaginary unit. ;

[0109] In detail, an analytic signal is a complex signal that describes the phase and amplitude characteristics of a real signal, consisting of a real part and an imaginary part. For the standard upstream subtidal component, the real part of its analytic signal is the standard upstream subtidal component itself, and the imaginary part is the result of the standard upstream subtidal component after undergoing a Hilbert transform. Similarly, the real part of the analytic signal of the standard downstream subtidal component is the standard downstream subtidal component, and the imaginary part is its Hilbert transform result. The purpose of the Hilbert transform is to generate components orthogonal to the original signal, enabling the analytic signal to completely depict the phase change trajectory of the original signal in the complex plane, thus accurately extracting the instantaneous phase.

[0110] Calculate the upstream instantaneous phase of the upstream analytic signal Calculate the downstream instantaneous phase of the downstream analytical signal. ;in, Represents the arctangent function in two variables. Represents the imaginary part of an analytic signal. Analyze the real part of the signal;

[0111] In detail, the instantaneous phase represents the phase state of a signal at a certain moment, and is obtained by calculating the phase of the analytic signal using a binary arctangent function. The binary arctangent function uses the imaginary part of the analytic signal as the numerator and the real part as the denominator; its calculation result reflects the angle corresponding to the analytic signal in the complex plane, i.e., the phase of the signal at that moment. For upstream analytic signals, the calculated upstream instantaneous phase describes the phase change of the standard upstream subtidal component over time; the downstream instantaneous phase describes the phase change of the standard downstream subtidal component. This transforms the complex plane characteristics of the analytic signal into quantifiable phase values.

[0112] Calculate the upstream synodic reference phase ;

[0113] In detail, the instantaneous phase represents the phase state of a signal at a certain moment, and is obtained by calculating the phase of the analytic signal using a binary arctangent function. The binary arctangent function uses the imaginary part of the analytic signal as the numerator and the real part as the denominator; its calculation result reflects the angle corresponding to the analytic signal in the complex plane, i.e., the phase of the signal at that moment. For upstream analytic signals, the calculated upstream instantaneous phase describes the phase change of the standard upstream subtidal component over time; the downstream instantaneous phase describes the phase change of the standard downstream subtidal component. This transforms the complex plane characteristics of the analytic signal into quantifiable phase values.

[0114] Calculate the downstream synodic reference phase .

[0115] In detail, the upstream synodic reference phase is obtained by subtracting the reference phase from the upstream instantaneous phase and then taking the modulus of 2π; the downstream synodic reference phase is obtained by subtracting the reference phase from the downstream instantaneous phase and then taking the modulus of 2π. This unifies the instantaneous phases of the upstream and downstream phases to the reference phase benchmark, eliminating absolute phase differences and retaining only the phase shift relative to the synodic rhythm. Taking the modulus of 2π constrains the phase value within the range of 0 to 2π, ensuring the periodicity and comparability of the phases. The resulting upstream and downstream synodic reference phases directly reflect the phase lead or lag relationship between the upstream and downstream subtidal components and the semilunar rhythm.

[0116] In one embodiment of the present invention, the synodic phase difference across nodes and layers is calculated based on the upstream and downstream synodic reference phases, and the synodic phase difference is converted into an instantaneous travel delay function based on the synodic beat frequency, including:

[0117] The principal phase difference is obtained by applying the wrap function to the phase difference between the upstream synodic reference phase and the downstream reference phase; the wrap function maps the phase difference to an interval. ;

[0118] It should be noted that although both the upstream and downstream synodic reference phases describe the phase state using the reference phase of the reference waveform, directly calculating the difference between them may result in results outside the normal range due to the periodicity of the phase. The periodicity of the phase, whose values ​​are usually constrained within a specific interval, can lead to unreasonable differences, such as a sudden jump from near π to near -π. The wrap function is used to map this direct difference to... By adjusting the difference to conform to the inherent law of phase periodicity, the phase difference is ensured to be within a uniform and reasonable range. This eliminates the ambiguity of the difference caused by phase periodicity, making the phase difference between upstream and downstream on a directly comparable scale.

[0119] The principal phase difference is continuously expanded using unwrap to obtain a continuous phase difference;

[0120] In detail, although the principal phase difference is within a unified range, the difference between adjacent time points may jump due to crossing the range boundary. For example, the principal phase difference between adjacent time points may suddenly change from around π to around -π. This jump is not a true phase change, but rather caused by the range constraint. The unwrap function detects jumps in the principal phase difference between adjacent time points, and automatically adds or subtracts 2π to eliminate the jump when the absolute value of the jump exceeds π. After processing by the unwrap function, the originally discrete and jumping principal phase difference is transformed into a continuous phase difference that changes continuously with time. This restores the true trend of phase difference change over time, ensuring that the phase difference reflects the continuous evolution of the upstream and downstream phase relationship.

[0121] The ratio of the continuous phase difference to the synodic beat frequency is used as the instantaneous time history delay function. .

[0122] In detail, continuous phase difference, essentially an angular difference, needs to be converted into a time quantity to directly describe the lead or lag relationship between upstream and downstream. The synodic beat frequency is an angular frequency (in radians per second) based on an astronomical constant, and its relationship with the period is that the angular frequency equals 2π divided by the period. According to the physical relationship between phase and time, the phase difference equals the angular frequency multiplied by the time difference; therefore, the time difference equals the phase difference divided by the angular frequency. Dividing the continuous phase difference by the synodic beat frequency yields the instantaneous travel delay function. The instantaneous travel delay function can reflect the lead or lag of the upstream relative to the downstream in real time.

[0123] In one embodiment of the present invention, the duration parameter is calculated based on the symbol duration of the instantaneous travel delay function, using the synodic period as the time window, including:

[0124] The ratio of 2π to the synodic beat frequency is used as the synodic period. ;

[0125] In detail, the conversion relationship between angular frequency and synodic period is as follows: synodic period equals 2π divided by angular frequency. Therefore, the ratio of 2π to the synodic beat frequency is defined as the synodic period. The synodic period is determined by an astronomical constant and reflects the inherent time scale of the semi-lunar rhythm.

[0126] In time Define time window ;

[0127] In detail, a time window is defined as the interval between any given moment and the synodic period. The length of the time window is strictly equal to the synodic period, ensuring that the time-delay characteristics within the complete semi-lunar rhythm are statistically analyzed within each window.

[0128] Through the time window Real-time time-delay function values ​​are collected at fixed time intervals;

[0129] If the instantaneous time history delay function value is greater than 0, then the sign is positive 1;

[0130] If the instantaneous time history delay function value is less than 0, then the sign is negative 1;

[0131] If the instantaneous time-history delay function value is equal to 0, then calculate the difference between two adjacent instantaneous time-history delay function values ​​on the time scale, and determine the corresponding sign based on the sign of the difference;

[0132] In detail, the sign is determined to distinguish the positive and negative trends of the instantaneous time-history delay function. When the instantaneous time-history delay function value is greater than 0, the sign is positive 1, indicating that the upstream is in a leading state relative to the downstream; when the value is less than 0, the sign is negative 1, indicating that the upstream is in a lagging state relative to the downstream; when the value is equal to 0, the sign is determined by calculating the difference between two adjacent instantaneous time-history delay function values ​​on the time scale at that moment, based on the positive or negative sign of the difference.

[0133] For example, for time s-1, time s, and time s+1, calculate the difference between the instantaneous time history delay function value at time s+1 and the instantaneous time history delay function value at time s-1; if the difference is a positive integer, the sign is positive 1, otherwise the sign is negative 1.

[0134] Determine the moment when the instantaneous time history delay function is positive 1 to obtain the first duration;

[0135] Determine the moment when the instantaneous time history delay function value is negative 1 to obtain the second duration;

[0136] In detail, the first duration refers to the total time corresponding to all moments within the time window where the instantaneous time history delay function has a positive sign of 1. It is obtained by multiplying the number of sampling points with a positive sign of 1 within the statistical window by a fixed time interval. The second duration is the total time corresponding to all moments with a negative sign of 1. It is also calculated by multiplying the number of sampling points with a negative sign of 1 by a fixed time interval. The first duration and the second duration represent the actual duration occupied by the upstream leading and lagging states within the window, respectively.

[0137] The ratio of the difference between the first and second durations to the synodic period is used as the time interval. Duration parameter.

[0138] In detail, the duration parameter is obtained by dividing the difference between the first and second durations by the synodic period. This normalizes the difference in duration to... Within the interval. When the persistence parameter is greater than 0, it indicates that the upstream population is in a leading state within that window; when it is less than 0, it indicates that the population is in a lagging state; the closer the absolute value is to 1, the stronger the persistence of the corresponding leading or lagging state. The persistence parameter transforms the persistence characteristics of the time lag sign into a quantifiable and comparable indicator.

[0139] In one embodiment of the present invention, time-axis mapping of the upstream salinity time series is performed based on the instantaneous travel delay function to obtain an aligned upstream salinity time series, including:

[0140] Calculate the difference between the upstream salinity value at time s and the instantaneous time history delay function value at time s in the upstream salinity time series, and form an initial salinity alignment sequence based on the difference;

[0141] In detail, the construction of the initial salinity alignment sequence is based on adjusting the time axis of the upstream salinity time series using an instantaneous time-history delay function. Specifically, it requires calculating the difference between the upstream salinity value at time s and the instantaneous time-history delay function value at time s. This difference is used to reflect the mapping of the upstream salinity time points according to an instantaneous lag relationship, so that the upstream series is initially aligned with the reference time base of the downstream series on the time axis. The initial salinity alignment sequence formed through this mapping initially reflects the time lead or lag relationship of the upstream salinity relative to the downstream.

[0142] If the initial salinity alignment value at time s in the initial alignment sequence is greater than or equal to the initial salinity alignment value at time s+1, then the initial salinity alignment sequence is optimized, including:

[0143] The first constraint includes: the initial salinity alignment value at time s is less than the initial salinity alignment value at time s+1.

[0144] The second constraint includes: calculating the square of the initial salinity alignment value at time s after optimization and the initial salinity alignment value at time s, and summing the squares at each time; and minimizing the sum of the squares.

[0145] In detail, when the initial salinity alignment value at time s is greater than or equal to the initial salinity alignment value at time s+1 in the initial salinity alignment sequence, it indicates a temporal disorder in the timeline mapping. This disorder may stem from time folding caused by drastic fluctuations in the instantaneous travel delay function, violating the physical property of unidirectional time flow and leading to incorrect temporal correlations in subsequent data fusion. Therefore, the initial sequence must be optimized to eliminate this non-physical temporal inversion.

[0146] In detail, the first constraint requires that the initial salinity alignment value at time s-th is less than the initial salinity alignment value at time s+1-th, thus forcing the sequence to maintain strict increment. This ensures that the optimized sequence conforms to the unidirectional nature of time, ensuring that the temporal mapping of upstream salinity always progresses positively along the time axis, avoiding distortion of physical meaning caused by temporal reversal. The strict increment characteristic provides a consistent temporal benchmark for subsequent fusion with downstream sequences, guaranteeing the physical rationality of data alignment.

[0147] In detail, the second constraint requires calculating the square of the optimized salinity alignment value at time s and the initial salinity alignment value, summing the squares across all time points, and minimizing this sum. This ensures that, while maintaining strict increasing order, the optimized sequence is as close as possible to the initial sequence. Minimizing the sum of squares maximizes the preservation of salinity features from the initial sequence, avoids over-correction leading to loss of original data information, and balances physical plausibility with data fidelity.

[0148] Based on the first and second constraints, an optimized salinity alignment sequence is formed, resulting in an aligned upstream salinity time series.

[0149] It should be noted that the optimized salinity alignment sequence is ultimately formed through the synergistic effect of the first and second constraints. The first constraint ensures the temporal rationality of the sequence, while the second constraint guarantees the fidelity of the optimization result to the original data. This optimization process eliminates the temporal disorder in the initial sequence while preserving the true dynamic characteristics of the upstream salinity.

[0150] In one embodiment of the present invention, a fusion weighting coefficient is determined based on a persistence parameter, and the aligned upstream salinity time series and downstream salinity time series are fused according to the fusion weighting coefficient to obtain a fused salinity time series, including:

[0151] A time window is constructed at time s to determine the duration parameter at time s. ;

[0152] In detail, a time window is constructed based on the s-th time point, with a window length equal to the synodic period. The duration of the instantaneous time history delay function symbol is statistically analyzed within this time window to calculate the duration parameter at the s-th time point. The duration parameter quantifies the long-term stability of the upstream state relative to the downstream state at the s-th time point, and its value range is... Positive values ​​indicate that the upstream is generally leading and its stability increases with increasing value; negative values ​​indicate that the upstream is generally lagging and its stability also increases with increasing absolute value. Using the persistence parameter as the basis for fusion weights ensures that the weight allocation is closely related to the physical lead-lag law, avoiding the subjective bias of empirical weights.

[0153] Construct the fusion weight coefficients using the duration parameter at time s. The maximum value of the fusion weight coefficient is limited to 1 and the minimum value to 0.

[0154] In detail, the fusion weight coefficients are constructed based on the persistence parameter at time s. Specifically, the persistence parameter is converted into a weight value between 0 and 1 through a linear mapping. When the persistence parameter is 1, the weight coefficient is 1, indicating that upstream information completely dominates the fusion; when the persistence parameter is -1, the weight coefficient is 0, indicating that downstream information completely dominates; the intermediate value of 0.5 distributes the weights proportionally. At the same time, the maximum value of the fusion weight coefficient is strictly limited to 1 and the minimum value to 0, ensuring that the weights are physically reasonable, i.e., the sum of the contributions of upstream and downstream information is always 1, avoiding distortion of the fusion results due to abnormal weights. Thus, the stability characteristics reflected by the persistence parameter are directly transformed into operable fusion weights.

[0155] Calculate the aligned upstream salinity value at time s and The first product, and the downstream salinity value at time s, and The second product of the first and second products is taken as the fused salinity value at the s-th time point to form a fused salinity time series.

[0156] It should be noted that calculating the fused salinity value at time s requires two steps. First, calculate the first product of the aligned upstream salinity value at time s and the fusion weight coefficient. This first product reflects the contribution ratio of upstream information to the fusion result at the current time. Second, calculate the second product of the downstream salinity value at time s and 1 minus the fusion weight coefficient. This second product reflects the contribution ratio of downstream information. The sum of the first and second products is the fused salinity value at time s. This calculation process is repeated for all times to ultimately form the fused salinity time series. This weighted fusion method allows the result to dynamically reflect the dominant relationship between upstream and downstream information. When the upstream has strong leading stability, the upstream information accounts for a high proportion; when the downstream has obvious dominant characteristics, the downstream information accounts for a high proportion. This avoids the physical misalignment caused by simple averaging or fixed-weight fusion, thus improving the accuracy of the fusion result.

[0157] In one embodiment of the present invention, the bleeding process is performed based on the fused salinity time series, including:

[0158] Determine the fused salinity value of the fused salinity time series at the current moment;

[0159] If the fused salinity value is not within the preset salinity range, the flow rate of the upstream outlet will be controlled until the fused salinity value is within the preset salinity range.

[0160] In detail, the preset salinity range is determined by combining the actual water environment needs, ecological protection goals, and watershed management standards of the monitoring area. For example, if the monitoring area is an estuary spawning ground, the appropriate salinity thresholds for key aquatic organisms (such as migratory fish) in the area need to be referenced to set a salinity range that can ensure the survival and reproduction of these organisms; if it is near an industrial water intake, the range needs to be set according to the salinity requirements of industrial water use. Before system deployment, this range needs to be verified through on-site surveys, ecological experiments, and industry standards to ensure its scientific rationality and practical applicability.

[0161] In detail, when the mixed salinity value exceeds the upper limit of the preset salinity range, it indicates excessive brine intrusion in the monitored area. This could be due to increased downstream tidal dynamics, causing the brine to travel a greater distance upstream, or insufficient upstream water flow to effectively dilute the brine. In this case, the system will execute a control command to increase the flow rate at the upstream outlet: by controlling the gate opening or pump power at the upstream outlet, the input of freshwater from upstream is increased. As more freshwater enters the monitored area, it mixes thoroughly with the brine in the area, gradually reducing the overall salinity until the mixed salinity value falls back to the preset range.

[0162] In detail, when the fused salinity value falls below the lower limit of the preset salinity range, it indicates excessive freshwater input to the monitored area. This could be due to increased upstream rainfall leading to a surge in inflow, or excessively large flow rate adjustments in previous discharge control. In this case, the system will execute a control command to reduce the flow rate at the upstream discharge outlet: by reducing the gate opening at the upstream discharge outlet or decreasing the pump unit's operating power, the amount of freshwater input from upstream is reduced. As the freshwater input decreases, downstream saline water can moderately replenish the upstream area under tidal influence, gradually increasing the salinity in the region until the fused salinity value returns to the preset range.

[0163] In detail, the intelligent control module continues to monitor changes in the fused salinity value in real time. If the adjusted fused salinity value still does not fall within the preset range, the flow rate adjustment will be further adjusted according to the current deviation. If the deviation is large, the adjustment range will be increased appropriately; if the deviation is small, a fine adjustment will be made. If the adjusted fused salinity value falls within the preset range, the system will stop the flow rate adjustment and maintain the current flow rate while continuing to monitor salinity changes to ensure that the salinity remains stable within a reasonable range in the long term, thus achieving dynamic and precise control of salinity in tidal river sections.

[0164] The embodiments of this example have been described above. However, this example is not limited to the specific implementation methods described above. The specific implementation methods described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms based on the guidance of this example, and all of them are within the protection scope of this example.

Claims

1. An intelligent control system for water environment monitoring, characterized in that, include: The upstream monitoring unit is located at the upstream near-tidal boundary section and collects upstream salinity time series. The downstream monitoring unit is located at the downstream near-tidal boundary section and collects downstream salinity time series. The signal processing module, connected to the upstream and downstream monitoring units, is configured as follows: The upstream and downstream salinity time series were filtered to separate the subtidal component; Based on the subtidal component, the upstream and downstream synodic reference phases are obtained through Hilbert transform; Based on the upstream and downstream synodic reference phases, the synodic phase difference across nodes and layers is calculated, and the synodic phase difference is converted into an instantaneous travel delay function based on the synodic beat frequency. The fusion processing module, connected to the signal processing module, is configured as follows: Using the synodic period as the time window, the duration parameter is calculated based on the sign duration of the instantaneous travel delay function; the upstream salinity time series is mapped onto the time axis based on the instantaneous travel delay function to obtain the aligned upstream salinity time series; the fusion weight coefficient is determined based on the duration parameter, and the aligned upstream salinity time series and the downstream salinity time series are fused according to the fusion weight coefficient to obtain the fused salinity time series; The intelligent control module performs effluent treatment based on the fused salinity time series.

2. The intelligent control system for water environment monitoring according to claim 1, characterized in that, The upstream and downstream salinity time series are filtered to separate the subtidal component, which includes: Based on the set of astronomical angular frequencies Determine the upper limit of the low-pass band. With stopband start ;in, , This represents the angular frequency of the M2 tidal constituent. This represents the angular frequency of the S2 tidal constituent. This represents the angular frequency of the K1 tidal constituent. The angular frequency of the O1 tidal constituent; Fast Fourier transforms were performed on the upstream and downstream salinity time series respectively to obtain the upstream frequency domain spectrum. and downstream frequency domain spectrum ; Constructing a zero-phase low-pass transfer function ;in, exist When the value is 1, When the value is 0, The timing is cosine smooth transition, and the upstream low-pass main filter is calculated. and downstream low-pass main filter ;in, It belongs to the upstream frequency domain spectrum or the downstream frequency domain spectrum; right and Applying narrowband notch transfer function ,as follows: ； in, Indicates the notch bandwidth of M2 tidal fraction or S2 tidal fraction; The product of the narrowband notch transfer function and the zero-phase low-pass transfer function is used as the total transfer function. The upstream subtidal component is obtained by performing an inverse fast Fourier transform on the product of the total transfer function and the upstream low-pass main filter; the downstream subtidal component is obtained by performing an inverse fast Fourier transform on the product of the total transfer function and the downstream low-pass main filter.

3. The intelligent control system for water environment monitoring according to claim 2, characterized in that, Based on the subtidal component, the upstream and downstream synodic reference phases are obtained through Hilbert transform, including: The upstream and downstream subtidal components are respectively subjected to mean removal and standardization to obtain the standard upstream subtidal component. and standard downstream sub-tidal component ; Will and The absolute difference is used as the synodic beat frequency; A time-varying reference waveform is generated using the sine value of the synodic beat frequency. The reference phase of the reference waveform is calculated using the Hilbert transform. ; The upstream analytical signals of the standard upstream subtidal component and the standard downstream subtidal component are constructed using the reference phase, respectively. and downstream analytical signals ;in, This represents the Hilbert transform operation, where i is the imaginary unit. ; Calculate the upstream instantaneous phase of the upstream analytic signal Calculate the downstream instantaneous phase of the downstream analytical signal. ;in, Represents the arctangent function in two variables. Represents the imaginary part of an analytic signal. Represents the real part of the analytic signal; Calculate the upstream synodic reference phase ; Calculate the downstream synodic reference phase .

4. The intelligent control system for water environment monitoring according to claim 3, characterized in that, Based on the upstream and downstream synodic reference phases, the synodic phase difference across nodes and layers is calculated, and the synodic phase difference is converted into an instantaneous travel delay function based on the synodic beat frequency, including: The principal phase difference is obtained by applying the wrap function to the phase difference between the upstream synodic reference phase and the downstream reference phase; the wrap function maps the phase difference to an interval. ; The principal phase difference is continuously expanded using the unwrap function to obtain the continuous phase difference; The ratio of the continuous phase difference to the synodic beat frequency is used as the instantaneous time history delay function. .

5. The intelligent control system for water environment monitoring according to claim 4, characterized in that, Using the synodic period as the time window, the duration parameter is calculated based on the sign duration of the instantaneous travel delay function, including: The ratio of 2π to the synodic beat frequency is used as the synodic period. ; In time Define time window ; Through the time window Real-time time-delay function values ​​are collected at fixed time intervals; If the instantaneous time history delay function value is greater than 0, then the sign is positive 1; If the instantaneous time history delay function value is less than 0, then the sign is negative 1; If the instantaneous time-history delay function value is equal to 0, then calculate the difference between two adjacent instantaneous time-history delay function values ​​on the time scale, and determine the corresponding sign based on the sign of the difference; Determine the moment when the instantaneous time history delay function is positive 1 to obtain the first duration; Determine the moment when the instantaneous time history delay function value is negative 1 to obtain the second duration; The ratio of the difference between the first and second durations to the synodic period is used as the time interval. Duration parameter.

6. The intelligent control system for water environment monitoring according to claim 5, characterized in that, Based on the instantaneous travel delay function, the upstream salinity time series is time-axis mapped to obtain an aligned upstream salinity time series, including: Calculate the difference between the upstream salinity value at time s and the instantaneous time history delay function value at time s in the upstream salinity time series, and form an initial salinity alignment sequence based on the difference; If the initial salinity alignment value at time s in the initial alignment sequence is greater than or equal to the initial salinity alignment value at time s+1, then the initial salinity alignment sequence is optimized, including: The first constraint includes: the initial salinity alignment value at time s is less than the initial salinity alignment value at time s+1. The second constraint includes: calculating the square of the initial salinity alignment value at time s after optimization and the initial salinity alignment value at time s, and summing the squares at each time; and minimizing the sum of the squares. Based on the first and second constraints, an optimized salinity alignment sequence is formed, resulting in an aligned upstream salinity time series.

7. The intelligent control system for water environment monitoring according to claim 6, characterized in that, The fusion weighting coefficients are determined based on the persistence parameter, and the aligned upstream and downstream salinity time series are fused according to the fusion weighting coefficients to obtain the fused salinity time series, including: A time window is constructed at time s to determine the duration parameter at time s. ; Construct the fusion weight coefficients using the duration parameter at time s. The maximum value of the fusion weight coefficient is limited to 1 and the minimum value to 0. Calculate the aligned upstream salinity value at time s and The first product, and the downstream salinity value at time s, and The second product of the first and second products is taken as the fused salinity value at the s-th time point to form a fused salinity time series.

8. The intelligent control system for water environment monitoring according to claim 7, characterized in that, The bleeding process is performed based on the fused salinity time series, including: Determine the fused salinity value of the fused salinity time series at the current moment; If the fused salinity value is not within the preset salinity range, the flow rate of the upstream outlet will be controlled until the fused salinity value is within the preset salinity range.

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