Continuous conductivity measurement method and system with hydrophobic recovery sampling branch de-sensing

Abstract

This invention discloses a continuous conductivity measurement method and system for a hydrophobic recovery sampling branch under cooling conditions, relating to the field of conductivity measurement. It collects sample water temperature, conductivity electrode internal temperature, and flow rate data during the hydrophobic recovery sampling branch cooling process, establishing a dynamic time series reflecting thermal response lag. Based on the time series characteristics, the electrode temperature response rhythm is adjusted to determine the gradual change zone and extract time nodes to construct a synchronous compensation benchmark. The flow rate rhythm is adjusted in conjunction with the time nodes in the gradual change zone, achieving dynamic temperature alignment through flow delay. Under aligned conditions, the weights of the temperature compensation curve are redistributed, shifting the lagging temperature nodes to instantaneous nodes. The conductivity signal is smoothed based on the compensation results, eliminating instantaneous errors. This invention achieves time synchronization between temperature compensation and the actual sample water temperature through time series and flow rate control, ensuring that the conductivity results accurately reflect water quality changes. Furthermore, continuous smoothing control eliminates instantaneous fluctuations, improving the reliability and accuracy of online monitoring.

Description

Technical Field

[0001] This invention relates to the field of conductivity measurement technology, specifically to a continuous conductivity measurement method and system for cooling a hydrophobic recovery sampling branch. Background Technology

[0002] A condensate recovery sampling branch is an independent bypass pipeline drawn from equipment or pipelines to collect condensate (water vapor condensate) samples and return them to the condensate recovery system. This branch is typically installed on the condensate recovery line of urea plants, steam drums, or condensation systems, and its function is to sample, de-temperature, detect, and recover condensate without affecting the operation of the main system. Its core function is to divert a small portion of the condensate sample before it enters the main recovery tank, performing de-temperature and online analysis to continuously monitor condensate quality indicators (such as conductivity and redox potential).

[0003] Continuous conductivity measurement of the hydrophobic recovery sampling branch under cooling conditions refers to real-time, continuous conductivity detection of the flowing hydrophobic sample water after the sampling branch has undergone cooling treatment. The specific process is as follows: After the hydrophobic sample water is extracted, it is first cooled by a cooler, reducing the temperature from approximately 100℃ to a stable range of 20-30℃ to avoid damage to the conductivity electrodes from high temperatures and ensure accurate temperature compensation. Subsequently, the sample water enters the online conductivity detection unit under continuous flow conditions after passing through the cooling section. The detection unit continuously reads the conductivity value of the sample water to reflect the ion concentration in the hydrophobic water and any potential contaminants (such as urea leakage, corrosion products, scale, etc.). This method enables real-time quality monitoring and anomaly warning of the urea station's hydrophobic recovery process, ensuring both the stability and accuracy of electrode measurements and the safety and closed-loop water quality control of the hydrophobic recovery system.

[0004] The existing technology has the following shortcomings:

[0005] When fluctuations occur in the cooling process of the hydrophobic recovery sampling branch, the sample water temperature often changes rapidly. However, due to its inherent heat capacity and limitations imposed by its internal heat transfer characteristics, the conductivity electrode typically exhibits a significant lag in its temperature response, making it difficult to reflect the true temperature state of the sample water in a timely manner. In this case, the temperature compensation curve used for conductivity measurement will be corrected based on the lag temperature within the electrode, resulting in a time deviation between the compensation result and the actual temperature of the sample water. Consequently, the overall measurement reading lags behind the true trend of change. This phenomenon is particularly pronounced during frequent adjustments to the cooling water flow or seasonal switching of operating conditions, easily causing the conductivity change curve to be excessively smoothed, weakening the sensitivity to sudden changes in hydrophobic water quality, and consequently affecting the timely identification and accuracy of the online monitoring system in judging abnormal operating conditions.

[0006] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to provide a continuous conductivity measurement method and system for cooling the hydrophobic recovery sampling branch, so as to solve the problems in the background art mentioned above.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a continuous conductivity measurement method for cooling of a hydrophobic recovery sampling branch, comprising the following steps:

[0009] Step 1: Collect real-time sample water temperature, conductivity electrode internal temperature, and sample water flow rate change data during the cooling process of the hydrophobic recovery sampling branch. Establish a dynamic time series reflecting the thermal response hysteresis characteristics between sample water temperature and electrode temperature, as a continuous reference basis for temperature response regulation.

[0010] Step 2: Based on the temperature lag characteristics represented in the dynamic time series, the temperature response rhythm inside the collected conductivity electrode is adjusted in time segments. The temperature lag interval is identified as the gradual change zone, and the time nodes of the gradual change zone are extracted to construct a transition benchmark for synchronous compensation of sample water temperature and electrode temperature.

[0011] Step 3: Combine the time nodes of the gradual change zone, implement transient flow fine-tuning of the sample water inflow rhythm, and use the temperature gradient in the gradual change zone as the control basis. By delaying the flow, the sample water temperature change curve and the thermal response rhythm of the conductivity electrode are dynamically aligned in time, thereby obtaining a temperature synchronization state.

[0012] Step 4: Under the dynamic temperature alignment state, the time weight distribution of the temperature compensation curve used for conductivity measurement is real-time redistributed. The synchronization rhythm formed during the flow delay is used as the time reference. The compensation weight of the original lagging temperature node is adjusted and shifted to the instantaneous temperature node of the sample water, so that the conductivity correction calculation process remains continuous and consistent in the time dimension, forming a temperature compensation result consistent with the temperature change time of the sample water.

[0013] Step 5: Based on the temperature compensation results after time-series consistency processing, continuous smooth control is performed on the conductivity output signal. The instantaneous error in the measurement process is dissipated by the redistributed time weight, and a dynamic conductivity curve synchronized with the actual temperature change process of the sample water is obtained, thereby realizing the stability and accuracy of online monitoring of the hydrophobic recovery sampling branch.

[0014] Preferably, the step of establishing a dynamic time series reflecting the thermal response hysteresis characteristics between the sample water temperature and the internal temperature of the conductivity electrode includes:

[0015] The measurement location of the cooling section of the hydrophobic recovery sampling branch is selected to collect real-time parameters of the hydrophobic sample water operation status. The first temperature measurement unit is used to continuously measure the instantaneous temperature of the hydrophobic sample water, the second temperature measurement unit is used to detect the internal temperature of the conductivity electrode, and the flow measurement unit is used to record the change of sample water flow. The three are recorded under a unified time reference to form the original dataset.

[0016] The collected data on sample water temperature, internal temperature of conductivity electrode, and flow rate changes were organized in chronological order to establish a continuous dynamic time series. The time difference between the rate of change of sample water temperature and the rate of response of internal temperature of conductivity electrode was recorded to obtain the influence law of hydrophobic sample water operating state on thermal response hysteresis characteristics.

[0017] Based on the dynamic time series analysis, the correspondence between the sample water temperature and the internal temperature of the conductivity electrode is analyzed to identify the temperature stable region, the temperature rapid change region, and the temperature difference recovery region. The time interval of the electrode temperature response lag is determined, and the start and end nodes are marked in the time series to form a time reference chain for subsequent temperature response control.

[0018] Preferably, the step of constructing a transitional benchmark for synchronous compensation of sample water temperature and electrode temperature at the time point of extraction of the gradually changing region includes:

[0019] In the dynamic time series, time correlation analysis was performed on the changes in hydrophobic sample water temperature, internal temperature of conductivity electrode and hydrophobic flow rate to determine the time interval between the starting point of sample water temperature change and the starting point of electrode temperature response, and this time interval was defined as the temperature lag interval.

[0020] Based on the time characteristics of the temperature lag interval, the internal temperature response rhythm of the conductivity electrode is adjusted by time segmentation. The time period in which the sample water temperature change has not yet caused the electrode temperature response is defined as the initial response segment, the time period in which the temperature difference persists is defined as the core segment of the slow change zone, and the time period in which the temperature gradually stabilizes is defined as the stable segment. The duration and flow status of each time period are recorded simultaneously.

[0021] Starting from the core section of the gradually changing zone, continuous time nodes are extracted according to the sampling time interval, and the sample water temperature, electrode temperature and hydrophobic flow data of each time node are recorded to form a node sequence arranged in chronological order.

[0022] The time nodes in the gradual change zone are connected in chronological order to establish a temperature correspondence table. The correspondence between sample water temperature and electrode temperature is transformed into a time-corresponding compensation transition benchmark. The hydrophobic flow rate status is recorded synchronously in the compensation benchmark to achieve time coordination of the temperature compensation process.

[0023] Preferably, the time node of the core section of the slow change zone is determined according to the difference between the rate of change of the sample water temperature and the internal temperature of the conductivity electrode. When the difference in the rate of change of temperature continues to decrease, the corresponding time node is marked as a key node, and the temperature difference change trend between adjacent key nodes is used as the basis for adjusting the temperature synchronous compensation, so as to ensure the continuous correspondence between the sample water temperature change and the electrode temperature response on the time axis.

[0024] Preferably, the step of dynamically aligning the sample water temperature change curve with the thermal response rhythm of the conductivity electrode in time through the flow rate delay process includes:

[0025] The relationship between sample water temperature, internal temperature of conductivity electrode and hydrophobic flow rate at the time nodes in the gradual change zone is analyzed. The sample water temperature value, electrode temperature value and temperature difference between adjacent nodes are recorded to form a temperature gradient distribution table, and the time delay direction and time span of the internal temperature response of conductivity electrode are determined.

[0026] Based on the changing characteristics of the temperature gradient in the gradually changing zone, the transient flow rate is finely adjusted according to the time node as the control benchmark. The flow rate is reduced when the rate of change of the sample water temperature increases and increased when the rate of change of the sample water temperature slows down. Temperature and flow rate data are recorded simultaneously to form a complete temperature and flow rate correspondence.

[0027] During the flow rate delay process, the temperature gradient time distribution in the slow change zone is used as the control benchmark. The sample water flow rate is adjusted to maintain a stable temperature change. By recording the temperature at continuous time points, it is confirmed that the time difference between the temperature change curve and the electrode temperature response curve gradually decreases and achieves dynamic alignment.

[0028] The time node at the end of the flow delay process is used as the temperature synchronization start point. The sample water flow rate is continuously monitored with the time node of the slow change zone as a reference. When the sample water temperature shows a changing trend, the flow rate is adjusted in real time so that the sample water temperature change and the internal temperature response of the conductivity electrode remain synchronized in the time series.

[0029] Preferably, during the transient flow rate fine-tuning process, the adjustment range of the sample water flow rate is determined based on the continuous change rate of the temperature gradient in the slow-change zone. When the temperature difference between adjacent time nodes decreases continuously, the flow rate is kept stable. When the temperature difference increases continuously, the flow rate is gradually reduced to prolong the residence time of the sample water in the cooling path, so that the sample water temperature change curve and the internal temperature response curve of the conductivity electrode form a consistent synchronous relationship on the time axis.

[0030] Preferably, the step of adjusting and shifting the compensation weight originally corresponding to the hysteresis temperature node to the instantaneous temperature node of the sample water includes:

[0031] The relationship between sample water temperature, internal temperature of conductivity electrode and flow rate changes at the time node of the slow change zone is analyzed. Based on the synchronous rhythm formed by the flow rate delay process, the node where the sample water temperature and internal temperature of conductivity electrode are consistent in the time dimension is determined and marked as the instantaneous temperature node, and a one-to-one correspondence between the lag temperature node and the instantaneous temperature node is established.

[0032] Based on the correspondence between instantaneous temperature nodes and lag temperature nodes, the time weight distribution of the temperature compensation curve used in conductivity measurement is reorganized. Taking the time rhythm formed during the flow delay process as the time reference, the compensation weight of the lag temperature node is moved forward along the time axis to the corresponding instantaneous temperature node, and the weight change value is recorded to form a synchronous distribution.

[0033] Based on the shifted time series, the time weight distribution of the temperature compensation curve is continuously optimized. The weight transition of adjacent nodes is adjusted according to the temperature change trend of the sample water, so that the temperature compensation curve forms a complete and continuous distribution structure in the time dimension, ensuring that the compensation weight of each instantaneous temperature node corresponds to the actual temperature state of the sample water.

[0034] Using the optimized temperature compensation curve as the time reference, the corresponding instantaneous temperature node compensation weight value is read in real time during the conductivity measurement process, and conductivity correction calculation is performed to form a conductivity correction time series, so that the conductivity measurement process remains continuous and consistent in the time dimension.

[0035] Preferably, when continuously optimizing the time weight distribution of the temperature compensation curve used for conductivity measurement, the weight change rate is limited according to the actual trend of sample water temperature change. When the weight change span of adjacent time nodes exceeds the set change span threshold, a gradual transition adjustment is performed according to the direction of sample water temperature change, so that the weight change process of each time node in the temperature compensation curve remains balanced, thereby ensuring the continuity and stability of conductivity correction calculation in the time dimension.

[0036] Preferably, the steps of using the redistributed time weights to dissipate instantaneous errors during the measurement process and obtaining a dynamic conductivity curve synchronized with the actual temperature change of the sample water include:

[0037] The output signal of conductivity and the temperature compensation result are matched in time and synchronously. Based on the temperature compensation time series, the sample water temperature, the internal temperature of conductivity electrode and the flow rate change data are reorganized in time order. The sampling time of conductivity signal and the temperature compensation node are compared point by point on the time axis so that the two correspond continuously under the same time reference.

[0038] Based on the redistributed time weights, continuous smoothing control is implemented on the conductivity output signal. The conductivity measurement values ​​are read sequentially starting from the first node of the time series, and smoothing is performed by combining the time weights of adjacent time nodes. When the signal fluctuates, the instantaneous error is distributed to adjacent time nodes through the time weights, so that the conductivity signal remains consistent in the time dimension.

[0039] After smoothing control is completed, the conductivity output signal is reconstructed into a time series. The smoothed conductivity values ​​are connected in time order to form a dynamic change curve covering the entire process of hydrophobic water sampling and cooling. The conductivity value at each time node corresponds to the sample water temperature node, and the continuity and synchronization of the curve are maintained under the action of time weight.

[0040] A continuous conductivity measurement system with de-cooling of hydrophobic recovery sampling branch includes a dynamic time series establishment module, a temperature difference hysteresis segmentation module, a flow rate rhythm control module, a time weight redistribution module, and a conductivity smoothing control module.

[0041] Dynamic time series establishment module: Collect real-time sample water temperature, conductivity electrode internal temperature and sample water flow rate change data during the cooling process of hydrophobic recovery sampling branch, and establish a dynamic time series reflecting the thermal response hysteresis characteristics between sample water temperature and electrode temperature.

[0042] Temperature lag segmentation module: Based on the temperature lag characteristics represented in the dynamic time series, the temperature response rhythm inside the collected conductivity electrode is adjusted in time segments, the temperature lag interval is identified as the gradual change zone, and the time nodes of the gradual change zone are extracted to construct a transition benchmark for synchronous compensation of sample water temperature and electrode temperature.

[0043] Flow rhythm control module: Combined with the time nodes of the gradual change zone, the transient flow rate of the sample water inflow rhythm is adjusted. The temperature gradient in the gradual change zone is used as the control basis. Through the flow delay process, the sample water temperature change curve and the thermal response rhythm of the conductivity electrode are dynamically aligned in time.

[0044] Time weight redistribution module: Under the temperature dynamic alignment state, the time weight distribution of the temperature compensation curve used for conductivity measurement is redistributed. The synchronization rhythm formed during the flow delay process is used as the time reference. The compensation ratio of the original lagging temperature node is adjusted and shifted to the instantaneous temperature node of the sample water to form a temperature compensation result consistent with the sample water temperature change time.

[0045] Conductivity smoothing control module: Based on the temperature compensation results, it performs continuous smoothing control on the conductivity output signal and uses the redistributed time weight to dissipate the instantaneous error in the measurement process.

[0046] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0047] This invention constructs a dynamic time series relating sample water temperature, the internal temperature of the conductivity electrode, and sample water flow rate. Based on this, it introduces mechanisms for identifying gradual change zones, flow rate delay, and time weight redistribution, ensuring that temperature compensation during conductivity measurement remains consistent with the actual temperature changes of the sample water over time. This avoids compensation offset caused by temperature response lag, allowing the conductivity correction results to reflect the actual changes in hydrophobic water quality in real time. The dynamic conductivity curve no longer exhibits delayed following or passive smoothing, improving the synchronization of measurement results with temperature fluctuations and water quality changes, and providing a more reliable measurement basis for continuous monitoring of the hydrophobic recovery sampling branch.

[0048] This invention, based on temperature and time alignment, implements continuous smooth control of the conductivity output signal. By rationally distributing time weights between adjacent time nodes, it effectively dissipates instantaneous fluctuations generated during the measurement process, ensuring that the conductivity change curve accurately reflects the true trend of hydrophobic water quality while maintaining continuity. This method avoids interference from instantaneous disturbances on the monitoring results while preserving the true dynamic characteristics of water quality changes. It enables online monitoring to maintain stable output even under conditions of switching operating modes and operational fluctuations, thereby effectively improving the reliability and accuracy of online monitoring in the hydrophobic recovery sampling branch. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0050] Figure 1 This is a flowchart of the conductivity measurement method of the present invention;

[0051] Figure 2 A flowchart for constructing a synchronous compensation transition reference for sample water temperature and electrode temperature in this invention;

[0052] Figure 3 This is a flowchart illustrating the dynamic temporal alignment of the sample water temperature change curve with the thermal response rhythm of the conductivity electrode according to the present invention.

[0053] Figure 4 This is a schematic diagram of the conductivity measurement system of the present invention. Detailed Implementation

[0054] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0055] This invention provides, for example Figures 1 to 3 The continuous conductivity measurement method for the hydrophobic recovery sampling branch cooling shown includes the following steps:

[0056] Step 1: Collect real-time sample water temperature, conductivity electrode internal temperature, and sample water flow rate change data during the cooling process of the hydrophobic recovery sampling branch. Establish a dynamic time series reflecting the thermal response hysteresis characteristics between sample water temperature and electrode temperature, as a continuous reference basis for temperature response regulation.

[0057] A dynamic time series reflecting the thermal response hysteresis characteristics between sample water temperature and electrode temperature is established. The specific steps are as follows:

[0058] First, a suitable measurement location is selected in the cooling section of the hydrophobic recovery sampling branch to collect real-time parameters of the hydrophobic sample water's operating status. A first temperature measurement unit is fixed in the sample water flow area of ​​the hydrophobic cooling section to continuously measure the instantaneous temperature of the hydrophobic sample water after passing through the cooling device. A second temperature measurement unit is placed in the thermal response detection area inside the conductivity electrode to capture temperature changes caused by heat transfer within the electrode material. To simultaneously reflect changes in hydrophobic flow velocity and cooling intensity, a flow measurement unit is installed at a suitable location in the sample water outlet direction to record the flow rate of the hydrophobic sample water in real time. The three measurement units simultaneously collect corresponding parameters, enabling continuous recording of temperature and flow rate changes in chronological order. The first and second temperature measurement units transmit stable signals through sensing elements and acquisition ports, ensuring that the sample water temperature and the internal temperature of the conductivity electrode are recorded at the same time reference. The output signal of the flow measurement unit and the temperature data are archived with a unified time signature, thus forming a raw dataset reflecting the correspondence between hydrophobic flow, temperature distribution, and the internal thermal response of the electrode. By continuously collecting data on the temperature of the hydrophobic sample water, the internal temperature of the conductivity electrode, and the flow rate changes, the heat transfer behavior of the hydrophobic sample during the cooling phase can be fully captured, providing continuous input for subsequent data analysis.

[0059] Secondly, the collected hydrophobic sample water temperature sequence, conductivity electrode internal temperature sequence, and flow rate change sequence were organized chronologically to construct a dynamic time series with temporal continuity. During data processing, the sample water temperature data and electrode temperature data were mapped one-to-one on the time axis, and the flow rate data was simultaneously associated with the corresponding temperature information, forming a mapping relationship between the three parameters in the time dimension. Using time as the primary index, the sample water temperature, electrode temperature, and flow rate at different time points were arranged sequentially according to the sampling time sequence, forming a continuous temperature response record chain. During the processing, the response delay when the sample water temperature rises or falls was marked, and the time difference between the rate of change of the sample water temperature and the rate of change of the electrode temperature was recorded. By synchronously recording the flow rate change and the time difference between the two sets of temperature changes, the influence of flow rate change on the temperature response delay can be observed. The final generated dynamic time series comprehensively describes the continuous change trend of the hydrophobic sample water temperature, conductivity electrode internal temperature, and flow rate change throughout the entire cooling process, clearly demonstrating the change state of the temperature lag phenomenon on the time axis. This dynamic time series covers the entire process from when the hydrophobic sample water enters the cooling zone to when the sample water passes through the conductivity electrode for detection, truly reflecting the relationship between hydrophobic temperature transfer and electrode thermal response.

[0060] Finally, the dynamic time series was used as a continuous reference for temperature response regulation to analyze and classify the temperature difference variation range during the hydrophobic cooling process. Based on the correspondence between the sample water temperature and the internal temperature of the conductivity electrode in the time series, the main stages of temperature change were identified, including the stage where both the sample water temperature and the electrode temperature were stable simultaneously, the stage where the sample water temperature changed rapidly while the electrode temperature was still in a slow response, and the recovery stage where the temperature difference gradually decreased. The time intervals of the change curves of the hydrophobic sample water temperature and the internal temperature of the conductivity electrode were divided, and the time period in which the sample water temperature had completed its change but the internal temperature of the conductivity electrode had not yet fully responded was extracted and defined as the temperature lag interval. The temperature lag interval reflects the delayed characteristics of the electrode's thermal response, and its length is closely related to the hydrophobic flow rate, cooling efficiency, and heat transfer path. The temperature difference at each time node within the temperature lag interval was continuously recorded and paired with the corresponding flow rate data to obtain the influence of the hydrophobic flow state on the temperature response delay. Based on this law, the lag range of the internal temperature response of the conductivity electrode under different flow rate conditions and the temporal distribution characteristics of temperature change can be determined. By marking the start and end times of the temperature lag interval in the dynamic time series, a complete time reference chain is formed. This allows for the selection of corresponding time points for comparison and synchronization based on different hydrophobic operating states when subsequently regulating the temperature response. Through this process, the temperature response regulation process can achieve a temporal correlation between changes in the hydrophobic sample water temperature and changes in the electrode thermal response, using the dynamic time series as a benchmark.

[0061] It should be noted that:

[0062] In identifying the stages of temperature changes in the sample water and the internal temperature of the conductivity electrode, a threshold method can be used to determine the temperature change rate and temperature difference ratio. When the rate of change of both the sample water temperature and the internal temperature of the conductivity electrode are lower than the preset temperature change threshold within a continuous sampling period, and the temperature difference between them is within a stable range, this stage is identified as a stage where both the sample water temperature and the electrode temperature are stable, i.e., the temperature stability zone. When the rate of change of the sample water temperature exceeds the temperature change threshold, while the rate of change of the internal temperature of the conductivity electrode is still lower than the temperature change threshold, and the temperature difference between them gradually increases, this stage is identified as a stage where the sample water temperature changes rapidly while the electrode temperature is still responding slowly, i.e., the rapid temperature change zone. When the rate of change of the sample water temperature begins to decrease and falls below the temperature change threshold, while the rate of change of the internal temperature of the conductivity electrode gradually increases and the temperature difference continues to decrease, this stage is identified as a recovery stage where the temperature difference gradually decreases, i.e., the temperature difference recovery zone.

[0063] The period during which the internal temperature of the conductivity electrode has not fully responded refers to the time interval during which, after the temperature of the hydrophobic sample water has changed, the electrode's internal temperature is still gradually rising or falling due to its own heat capacity and heat transfer delay. During this period, the sample water temperature has reached a new steady state, but the internal temperature of the conductivity electrode has not yet kept pace with the sample water temperature, resulting in a continuous temperature difference between the two. This time interval is the stage of electrode temperature response lag.

[0064] Through the implementation of the above steps, the synchronous acquisition and dynamic time series establishment of real-time sample water temperature, conductivity electrode internal temperature, and flow rate changes during the cooling process of the hydrophobic recovery sampling branch were completed. The entire process, based on a time sequence, relied on continuous data acquisition and precise time matching to achieve synchronous expression of sample water temperature and electrode temperature over time. The resulting dynamic time series can accurately characterize the delayed behavior of temperature changes during the hydrophobic cooling process and provide a continuous reference for subsequent temperature compensation and synchronous adjustment.

[0065] Step 2: Based on the temperature lag characteristics represented in the dynamic time series, the temperature response rhythm inside the collected conductivity electrode is adjusted in time segments. The temperature lag interval is identified as the gradual change zone, and the time nodes of the gradual change zone are extracted to construct a transition benchmark for synchronous compensation of sample water temperature and electrode temperature.

[0066] The time points of the gradually changing region are extracted to construct a transitional benchmark for synchronous compensation of sample water temperature and electrode temperature. The specific steps are as follows:

[0067] In the established dynamic time series, time correlation analysis was performed on the continuous changes in hydrophobic sample water temperature, internal temperature of the conductivity electrode, and hydrophobic flow rate. Following the chronological order, the change curves of the sample water temperature and the internal temperature of the conductivity electrode were correlated point-by-point on the same time axis. Using the point when the sample water temperature began to change as the starting point, the moment when the internal temperature response of the conductivity electrode began to deviate was tracked, and the interval between the two curves on the time axis was used as the initial boundary of the temperature lag interval. During this process, the sample water temperature data in the time series was continuously read to determine the trend of temperature increase or decrease, and each temperature change point was used as a reference node to find the corresponding response amplitude of the internal temperature of the conductivity electrode at the same time. When the sample water temperature has changed significantly while the internal temperature of the conductivity electrode has not yet changed sufficiently, this time period was recorded as the temperature lag interval. As time progresses, when the internal temperature of the conductivity electrode begins to change in the same direction as the sample water temperature, it is marked as the electrode temperature response initiation node. By continuously analyzing the temperature change rate and response delay duration at each time node, the temporal distribution characteristics of the internal temperature response of the conductivity electrode relative to the sample water temperature were obtained. This process establishes the temperature lag range of the electrode thermal response in the time dimension, providing a time basis for subsequent segmented adjustments.

[0068] After identifying the temperature lag intervals, the temperature response rhythm within the conductivity electrode was adjusted in time segments. Based on the synchronous change characteristics of sample water temperature and electrode temperature in the dynamic time series, the entire temperature change process was divided into different stages. The time period when the sample water temperature begins to change but the electrode temperature has not yet responded was defined as the initial response segment; the time period when the electrode temperature begins to respond and the rate of change is stable was defined as the gradual change segment; and the time period when the sample water temperature and electrode temperature change trends are consistent and eventually converge to the same temperature value was defined as the stable segment. During the segmentation process, the boundaries of each stage were precisely calibrated according to the continuity of the temperature change rate to ensure that the transition time points between each stage are continuously connected in the dynamic time series. Data points within each stage are arranged in chronological order to avoid time discontinuities. For intervals where the difference between the electrode temperature change rate and the sample water temperature change rate exceeds a set threshold range, this interval was designated as the main temperature lag interval. Within this temperature lag interval, the temperature difference persists and changes relatively slowly, thus defining it as the core part of the gradual change zone. After the division is completed, the duration, temperature difference range and flow rate changes of each stage are recorded synchronously to ensure that the time structure of the temperature response rhythm inside the conductivity electrode is consistent with the dynamic characteristics of the temperature change rhythm of the sample water.

[0069] After segmented adjustments, the time nodes in the gradually changing zone are extracted in detail. Based on the dynamic time series, starting from the beginning of the gradually changing zone, data for each time node is extracted sequentially according to the sampling time interval. At each time node, the actual values ​​of sample water temperature, internal temperature of the conductivity electrode, and hydrophobic flow rate are recorded. By calculating the temperature difference between consecutive nodes, the continuous trend of temperature difference change is determined. For time periods where the rate of temperature difference change is stable and gradually decreases, these time nodes are marked as key nodes in the gradually changing zone. To ensure the continuity of nodes, each key node is compared with the preceding and following time nodes to confirm its positional relationship in the gradually changing zone, and the corresponding sample water temperature, electrode temperature, and flow rate values ​​are recorded. This process forms a node sequence arranged chronologically, with each node containing complete temperature and flow rate information, allowing for a complete characterization of the thermal response behavior of the gradually changing zone in the time dimension. Through this continuous node extraction process, the variation patterns of sample water temperature and electrode temperature can be accurately expressed in the form of time nodes, providing a specific time reference for establishing a synchronous compensation benchmark.

[0070] After obtaining the time node sequence of the gradually changing region, a transitional benchmark for synchronous compensation of sample water temperature and electrode temperature is constructed. The time nodes within the gradually changing region are connected sequentially to form a continuous time chain. The corresponding values ​​of sample water temperature and electrode temperature at each time node are matched to establish a temperature correspondence table. Using the time nodes as the horizontal axis and the correspondence between sample water temperature and electrode temperature as the vertical axis, the temperature difference distribution within the gradually changing region is transformed into a time-corresponding compensation benchmark. During the construction process, the hydrophobic flow rate state corresponding to each time node is recorded simultaneously to ensure consistency between the temperature compensation benchmark and the flow state. In this way, the synchronous relationship between sample water temperature and electrode temperature is clearly represented on the time axis, forming a dynamic transitional basis for temperature compensation. When the hydrophobic flow rate or sample water temperature changes, the corresponding compensation time period can be quickly located based on this time benchmark, achieving synchronous adjustment of the temperature response. This transitional benchmark can provide a continuous time reference during the temperature compensation process of subsequent conductivity measurements, ensuring that changes in sample water temperature and electrode temperature response remain coordinated in the time dimension, thereby achieving synchronous compensation of the temperature change process during measurement and ensuring that the conductivity correction result is consistent with the true temperature state of the hydrophobic flow.

[0071] By executing the above steps, the entire process follows a time-series approach, ensuring continuous data flow across each stage. This method quantifies the temporal correspondence between sample water temperature and the internal temperature of the conductivity electrode, making the time nodes in the gradual change zone the core reference for subsequent temperature synchronization compensation. Thus, the thermal response delay during the hydrophobic cooling process is effectively characterized, providing a stable temporal basis and accurate temperature correspondence for continuous conductivity measurement, enabling the measurement results to accurately reflect the actual changes in the hydrophobic sample water.

[0072] Step 3: Combine the time nodes of the gradual change zone, implement transient flow fine-tuning of the sample water inflow rhythm, and use the temperature gradient in the gradual change zone as the control basis. By delaying the flow, the sample water temperature change curve and the thermal response rhythm of the conductivity electrode are dynamically aligned in time, thereby obtaining a temperature synchronization state.

[0073] The sample water temperature change curve is dynamically aligned with the thermal response rhythm of the conductivity electrode in time by a flow rate delay process. The specific steps are as follows:

[0074] Based on the time nodes of the gradually changing zone determined in the previous stage, a detailed analysis of the correspondence between sample water temperature, internal temperature of the conductivity electrode, and hydrophobic flow rate is conducted. The time nodes within the gradually changing zone are arranged in the order of data collection, and the sample water temperature value and internal temperature value of the conductivity electrode corresponding to each time node are recorded. The difference in sample water temperature change between adjacent time nodes is calculated to obtain the distribution of the temperature gradient within the gradually changing zone. By continuously comparing the rate of change of sample water temperature with the rate of temperature response inside the conductivity electrode, the direction and span of the time delay of the electrode thermal response relative to the change of sample water temperature can be determined. During the analysis, a period of stable sample water temperature change is selected as the starting segment of the gradually changing zone, and the amplitude of temperature change is recorded point by point to reflect the heat transfer characteristics within the gradually changing zone. Subsequently, based on the trend of temperature difference changes between time nodes, the slow segment of temperature change and the segment of increasing temperature change rate within the gradually changing zone are separated to form a complete temperature gradient change table, providing a basis for subsequent flow rate control. In this stage, the time distribution of the temperature gradient can accurately determine the hysteresis law of the internal thermal response of the electrode and provide a clear target direction for flow rate adjustment.

[0075] Subsequently, based on the temperature gradient variation characteristics of the gradually changing zone, and using time nodes as the control benchmark, transient flow rate fine-tuning was implemented on the sample water inflow rhythm. During this process, the sample water flow rate at the inlet of the gradually changing zone was used as the initial reference flow rate, and the time series of sample water temperature changes under this flow rate condition was recorded. Then, guided by the trend of the temperature gradient change, the sample water flow rate was gradually adjusted. When the rate of sample water temperature change accelerated, the flow rate was reduced to prolong the residence time of the sample water in the cooling path, allowing for more thorough heat exchange as the sample water passed through the cooling section, thereby slowing down the temperature change process and giving the conductivity electrode internal temperature time to complete the corresponding thermal response. When the rate of sample water temperature change slowed down, the flow rate was appropriately increased to accelerate the heat transfer rate of the sample water in the cooling section, ensuring that the sample water temperature change and the conductivity electrode internal temperature response remained nearly synchronized in time. At each stage of flow rate adjustment, the sample water temperature, conductivity electrode internal temperature, and condensate flow rate were recorded synchronously to establish a complete temperature-flow rate correspondence at the time nodes of the gradually changing zone. Through this continuous fine-tuning, the temperature change curve of the sample water gradually approaches the internal temperature response curve of the conductivity electrode over time, thereby forming a time-aligned trend of the thermal response rhythm.

[0076] After the transient adjustment of the sample water flow rate, a flow rate retardation process is initiated to dynamically align the sample water temperature change curve with the internal thermal response rhythm of the electrode. During this stage, the time distribution of the temperature gradient within the gradually changing zone is used as the control benchmark, and the sample water flow rate is adjusted to a state that maintains stable temperature changes for a certain duration. By recording temperature changes at continuous time points, the positional relationship between the sample water temperature change curve and the internal temperature response curve of the conductivity electrode on the time axis can be observed. When the internal temperature response of the conductivity electrode still lags behind the sample water temperature change, the flow rate is further fine-tuned to slow down the rate of change in sample water temperature, gradually reducing the difference between the two curves in the time dimension. Throughout this process, the sample water flow is kept stable to maintain the continuity of the temperature change trend and avoid abrupt temperature or flow rate changes. When the deviation between the sample water temperature change curve and the internal temperature response curve of the conductivity electrode on the time axis decreases to a negligible range, it indicates that the sample water temperature change process and the electrode thermal response process have achieved dynamic alignment. As time progresses, the changing trends of the two curves remain consistent, and the temperature lag phenomenon is effectively eliminated. During the flow rate slowdown process, the temperature and flow rate values ​​at each time point are continuously recorded, ensuring that the timing of flow rate adjustments corresponds perfectly with the timing of temperature changes, thus providing a complete data foundation for subsequent temperature synchronization.

[0077] After the sample water temperature change curve and the internal thermal response rhythm of the electrode are dynamically aligned, the temperature synchronization state is maintained. The time point at the end of the flow slack process is used as the starting point for temperature synchronization, and the sample water temperature, the internal temperature of the conductivity electrode, and the flow rate at this point are recorded as the initial conditions for temperature synchronization. Subsequently, during the operation of the hydrophobic recovery sampling branch, the sample water temperature is continuously monitored using the time point of the gradual change zone as a reference. When the sample water temperature shows an upward or downward trend, the flow rate is finely adjusted in real time according to the temperature gradient characteristics of the gradual change zone, ensuring that the sample water temperature change curve remains synchronized with the internal temperature response curve of the conductivity electrode in the new time series. Through this continuous time matching and flow control, the temperature synchronization state is stably maintained throughout the entire cooling process of the hydrophobic recovery sampling branch. The internal temperature response of the electrode remains consistent with the change in sample water temperature over time, thus ensuring that the temperature compensation parameters used for conductivity measurement completely correspond to the actual temperature of the sample water. In this state, the conductivity measurement results can accurately reflect the true situation of ion concentration changes in the hydrophobic sample water with temperature, eliminating measurement errors caused by temperature lag.

[0078] Through the implementation of the above steps, the entire process of transient fine-tuning of sample water flow rate based on the time node of the gradual change zone, delaying flow rate according to the temperature gradient of the gradual change zone, and dynamically aligning the sample water temperature change curve with the internal thermal response rhythm of the electrode in time while maintaining temperature synchronization was completed. The entire process revolves around the time node and uses the temperature gradient as the control basis. Through continuous flow control, a stable time correspondence is established between sample water temperature changes and electrode temperature responses. Using this method, the hydrophobic recovery sampling branch achieves dynamic matching of thermal response during the cooling process, providing a continuous and accurate time basis for subsequent temperature compensation and conductivity measurement. This ensures consistency throughout the monitoring process in the time dimension, thereby achieving precise tracking and real-time reflection of the temperature state and water quality changes of the hydrophobic recovery sampling branch.

[0079] Step 4: Under the dynamic temperature alignment state, the time weight distribution of the temperature compensation curve used for conductivity measurement is real-time redistributed. The synchronization rhythm formed during the flow delay process is used as the time reference. The compensation weight of the original lagging temperature node is adjusted and shifted to the instantaneous temperature node of the sample water, so that the conductivity correction calculation process remains continuous and consistent in the time dimension.

[0080] The compensation weight that originally corresponded to the hysteresis temperature node was adjusted and shifted to the instantaneous temperature node of the sample water. The specific steps are as follows:

[0081] After dynamically aligning the sample water temperature change curve with the internal temperature response curve of the conductivity electrode, a comprehensive analysis was conducted on the relationship between time points and temperature changes during the flow retardation process within the slow-change zone. Based on the time-matching data obtained in the previous stage, the sample water temperature change curve, the internal temperature response curve of the conductivity electrode, and the flow rate change curve were arranged into a continuous time series in chronological order. Using the stable synchronous rhythm formed during the flow retardation process as a reference, the segment where the sample water temperature change rate and the electrode temperature response rate remained consistent was selected as the time analysis interval. Each time point within this time analysis interval was read one by one, recording the sample water temperature value, the internal temperature value of the conductivity electrode, and the corresponding flow rate value, and calculating the temperature change difference between time points. Based on this, the nodes where the sample water temperature and the internal temperature of the conductivity electrode remained consistent in the time dimension were identified, and these nodes were marked as instantaneous temperature nodes. All instantaneous temperature nodes were arranged on the time axis according to the acquisition order and numbered, so that their correspondence formed a one-to-one mapping with the lag temperature nodes. In this process, the temperature difference, flow rate, and direction of temperature change of each instantaneous temperature node are recorded along with those of its preceding and following time nodes, providing accurate data reference for subsequent time weight adjustments to the temperature compensation curve. In this way, a time correspondence between lagging temperature nodes and instantaneous temperature nodes is established, enabling each lagging point on the time axis to find its corresponding real-time temperature node in a synchronized state.

[0082] After obtaining the one-to-one correspondence between instantaneous temperature nodes and lag temperature nodes, the time weight distribution of the temperature compensation curve used for conductivity measurement is reorganized. Using the time rhythm formed during the flow delay as the time reference, the entire measurement time axis is divided into multiple consecutive time periods, each corresponding to a stage where the sample water temperature and electrode temperature change synchronously. Within each stage, the time weight data in the original temperature compensation curve is read to confirm the weight values ​​and their time order corresponding to each time node in the temperature compensation curve. Based on the position of the instantaneous temperature node, the compensation weights originally allocated to the lag temperature nodes are shifted forward along the time axis to correspond to the actual temperature change time of the sample water. During the shifting process, the weight change value of each time node is recorded to ensure that the transfer of each weight point is consistent with the rhythm of the sample water temperature change. When the sample water temperature rises, the weights of the lag temperature nodes in the temperature compensation curve are shifted forward to the sample water heating time node; when the sample water temperature falls, the weight values ​​are synchronously shifted to the corresponding cooling node. Through this process, the temperature compensation curve, which originally had a time offset, was adjusted to a distribution form synchronized with the sample water temperature, and the compensation process no longer lagged behind the actual temperature change.

[0083] After completing the time weight shift adjustment, the overall time weight distribution of the conductivity-temperature compensation curve is continuously optimized to ensure a smooth and consistent time distribution. Based on the shifted time series, the magnitude of weight changes between each time node is analyzed to check for abrupt changes or discontinuities in the weight change rate. When the weight change span between certain time nodes exceeds the set threshold, it is gradually transitioned according to the actual trend of sample water temperature change, making the weight distribution continuously change. A point-by-point smoothing method is used to maintain a balanced weight change process between time nodes. Subsequently, the optimized weight distribution is remapped onto the time axis, ensuring that the weight of each instantaneous temperature node maintains the same rate of change as its adjacent nodes. Through this continuous adjustment, the weight distribution of the temperature compensation curve forms a complete continuous structure in the time dimension, ensuring that the compensation weight at each time node corresponds to the actual temperature state of the sample water, eliminating time jumps or compensation gaps. At this point, the temperature correction in the conductivity measurement process can be updated in real time with changes in sample water temperature, and the trend of the conductivity correction curve is completely consistent with the trend of hydrophobic temperature change.

[0084] It should be noted that:

[0085] The threshold for the change span is determined based on the normal range of time weight variation between consecutive time nodes and the actual rate of change of sample water temperature. Its purpose is to limit the maximum allowable range of weight adjustment between adjacent time nodes, thereby preventing abrupt changes in weight distribution along the time axis. Specifically, under stable operating conditions, the time weight sequence after translation adjustment is continuously sampled. The normal fluctuation range of the weight difference between adjacent time nodes is statistically analyzed, and the upper limit of this fluctuation range is calculated as a basic reference range. Subsequently, combined with the maximum rate of change of sample water temperature during the cooling process, this reference range is matched with the weight change requirements corresponding to the rate of change of sample water temperature. The value that can cover normal temperature dynamic changes without causing compensation jumps is selected as the change span threshold. This change span threshold can be limited by the absolute value of the weight change per unit time, for example, by setting the weight change between two adjacent sampling periods to not exceed a certain proportion of the weight value of the previous node, and maintaining this proportion consistently throughout the entire time series. When the operating conditions change, the corresponding upper limit of the ratio can be reselected according to the current rate of change of the sample water temperature, but the principle of setting the threshold of the change span remains unchanged, that is, to ensure that the change of weight is consistent with and continuous with the rhythm of change of sample water temperature.

[0086] The threshold for the range of change set in this way is derived from actual operating data and matches the trend of sample water temperature change, thereby ensuring that the time weight distribution remains smooth and consistent during the continuous adjustment process, without producing time jumps or compensation faults.

[0087] After optimizing the continuity of the time weight distribution of the temperature compensation curve, the time synchronization stage of conductivity correction calculation begins. Using the optimized temperature compensation curve as the time reference, the compensation weight value of the corresponding instantaneous temperature node is read in real time at each time point of conductivity measurement, and this weight value is applied to the conductivity correction process. In this stage, the conductivity correction calculation for each time point is performed based on the compensation weight value of its corresponding instantaneous sample water temperature node, ensuring that the conductivity measurement is completely synchronized with the temperature change of the sample water in the time dimension. By continuously recording temperature changes, weight distribution, and conductivity correction values, a complete conductivity correction time series can be formed. Each data point in this conductivity correction time series is consistent with the sample water temperature change process, thus ensuring that the trend of conductivity measurement results matches the actual temperature fluctuation of the hydrophobic sample water. The synchronization rhythm formed during the flow delay process is continuously applied as the time reference, ensuring that the time distribution of conductivity measurement compensation is always coordinated with the hydrophobic flow rhythm. Through this process, the temporal continuity of conductivity correction calculation is ensured, and the conductivity measurement results are no longer delayed or lagging, so that the measurement process of the entire hydrophobic recovery sampling branch remains consistent and coherent in the time dimension.

[0088] Through the above implementation steps, based on the time rhythm of flow delay formation, time node matching, weight shift adjustment, continuity optimization, and time synchronization calculation are performed sequentially. This allows the weight distribution of the temperature compensation curve to be transformed from a lagging state to a synchronized state. This method ensures that the conductivity correction calculation and the sample water temperature change remain consistent in time, maintaining stable continuity and temporal coordination throughout the entire hydrophobic sampling process. This ensures that the conductivity measurement results accurately reflect the true changes in the hydrophobic sample water, guaranteeing high accuracy and temporal consistency in the online monitoring of the hydrophobic recovery sampling branch during operation.

[0089] Step 5: Based on the temperature compensation results after time-series consistency processing, continuous smooth control is performed on the conductivity output signal. The instantaneous error in the measurement process is dissipated by the redistributed time weight, and a dynamic conductivity curve synchronized with the actual temperature change process of the sample water is obtained, thereby realizing the stability and accuracy of online monitoring of the hydrophobic recovery sampling branch.

[0090] By utilizing the redistributed time weights to dissipate the instantaneous errors during the measurement process, a dynamic conductivity curve synchronized with the actual temperature change of the sample water is obtained. The specific steps are as follows:

[0091] After the temperature compensation curve undergoes time-series consistency processing, the conductivity output signal and temperature compensation results are time-corresponded and synchronized. Using the temperature compensation time series generated in the previous stage, the sample water temperature, conductivity electrode internal temperature, and flow rate change data are reorganized according to the sampling time sequence, ensuring all measurement points remain consistent under the same time reference. Based on each time node in the temperature compensation time series, the conductivity output signal is matched point-by-point with the temperature compensation result. Each time node records the real-time temperature value of the sample water, the internal temperature value of the conductivity electrode, and the original conductivity measurement value at that time, along with the corresponding weight distribution in the temperature compensation curve. This matching ensures that the time distribution of the conductivity output signal is completely synchronized with the time characteristics of the sample water temperature change. During synchronization, using the time axis as a reference, the sampling time of the conductivity output signal is compared one by one with the time nodes in the temperature compensation curve. When there is a time offset, fine adjustments are made according to the time sequence to ensure that the sampling points of the conductivity signal strictly coincide with the temperature compensation nodes. Through this synchronization matching process, a continuous correspondence is formed between the conductivity output signal and the temperature compensation time series, and the time reference remains unified, providing continuous time support for the subsequent smooth control process.

[0092] After the conductivity output signal and the temperature compensation result are synchronized in time, continuous smoothing control is applied to the conductivity output signal based on the redistributed time weights. Starting from the first matching node in the temperature compensation time series, the conductivity measurement value of each time node is read sequentially according to time order, and the signal change is smoothed by combining the time weights of adjacent nodes. In this process, the conductivity value of the current time node works together with the compensation weights of the previous and next nodes to keep the conductivity signal change process on the time axis consistent. When the conductivity output signal experiences short-term fluctuations, the fluctuations are diffused over time by the redistributed time weights, distributing the instantaneous error to adjacent time nodes, resulting in a smooth transition in time. For periods of frequent temperature changes, the time weights are densely distributed, and the conductivity signal response is more continuous; while for periods of stable temperature changes, the time weights are evenly distributed, and the conductivity signal maintains a stable output. Throughout the smoothing control process, the data at all time nodes are continuously adjusted based on the time weights to ensure that the conductivity output signal forms an uninterrupted change curve in the time dimension. Under the influence of time weighting, signal mutations are naturally extended, instantaneous errors are uniformly absorbed, the shape of the conductivity output curve is synchronized with the sample water temperature change curve in time, and the measurement process maintains a stable response state throughout the operation.

[0093] When the output signal of conductivity experiences short-term fluctuations, the fluctuations are diffused over time using a redistributed time weight, distributing the instantaneous error across adjacent time nodes and creating a smooth transition in time for the signal change. The following specific examples further explain the implementation of this process:

[0094] For example, during the cooling process of the hydrophobic recovery sampling branch, assuming the sample water temperature rapidly drops from 35℃ to 28℃ within a certain period, due to the instantaneous change in cooling water flow, the conductivity electrode experiences a sudden peak in the signal received within a short time. This sudden increase does not represent a real change in the hydrophobic water quality, but rather a lag in the electrode temperature response caused by the temperature abrupt change, resulting in an instantaneous measurement deviation. In this case, the temperature compensation curve, after time-series consistency processing, will perform time-diffusion processing on the weight of this sudden signal based on the redistribution results of the time nodes. Specifically:

[0095] The high conductivity values, originally concentrated at a single time point, are processed sequentially over time. Specifically, the conductivity increment corresponding to that time point is refined and allocated according to the proportion of adjacent time intervals in the temperature compensation time series. A portion of the conductivity change is allocated forward to the previous time point, and another portion is allocated backward to the next time point. Simultaneously, a conductivity component matching the actual temperature response rhythm is retained at the current time point. This transforms the instantaneous peak value at a single time point into a gradual increase and decrease across multiple consecutive time points. The conductivity curve changes from a sudden surge to a continuous curve with a gradual rise and fall, thus reflecting the true impact of temperature changes on the measured signal. Conversely, when the hydrophobic temperature is in a stable operating phase, such as fluctuating around 30°C, the time weight distribution is relatively uniform, and the compensation ratio at each time point is basically consistent. The conductivity output signal does not exhibit abrupt changes but maintains a smooth output state.

[0096] Through this dynamic time weighting adjustment, the conductivity output curve can dissipate instantaneous errors during periods of drastic temperature changes and maintain stable data during periods of stable temperature, so that the entire conductivity change process continuously and naturally corresponds to the true thermal state of the sample water.

[0097] After continuous smoothing control of the conductivity output signal, the dynamic changes in conductivity are reconstructed over time to form a dynamic conductivity curve that perfectly matches the actual temperature change process of the sample water. This process uses the smoothed conductivity signal as a basis, connecting the conductivity values ​​at each time point in chronological order to form a complete dynamic curve. This curve covers the entire sampling and cooling process of the hydrophobic sample water on the time axis, with each time point's conductivity value corresponding to a specific sample water temperature node. By continuously recording the sample water temperature, the internal temperature of the conductivity electrode, and the flow rate changes, the characteristics of the conductivity curve's changes over different time periods can be tracked in real time. When the sample water temperature experiences rapid rises or falls, the dynamic conductivity curve changes synchronously with the same time rhythm, reflecting the changes in ion concentration in the hydrophobic sample water under different thermal states. When the sample water temperature enters a stable phase, the conductivity curve remains stable, avoiding deviations caused by temperature compensation lag or signal delay. As time progresses, the conductivity dynamic curve continuously reflects the conductivity change trajectory of the hydrophobic sample water throughout the entire cooling process, ensuring that the measurement results at each time point accurately correspond to the true thermal state of the sample water. During this process, the redistributed time weights continuously play a balancing role, naturally dissipating minute instantaneous measurement errors and maintaining the continuity of the curve. The conductivity change trend corresponds perfectly with the sample water temperature change trend over time, forming a consistent time response relationship. Through this dynamic curve, the online monitoring of the hydrophobic recovery sampling branch can display the conductivity change process of the hydrophobic sample water in real time, thereby achieving continuous monitoring and accurate judgment of the hydrophobic quality during operation.

[0098] Through the implementation of the above steps, temperature compensation was completed. The entire process, centered on time series analysis, utilizes time matching, smoothing control, and dynamic curve reconstruction to maintain the continuity and consistency of the conductivity output signal across the time dimension. The redistributed time weights continue to act at each stage of signal processing, enabling the conductivity measurement to achieve dynamic balance and real-time response during temperature changes. The resulting dynamic conductivity curve accurately reflects the true conductivity change of the hydrophobic sample water during the cooling process, ensuring the stability and accuracy of online monitoring in the hydrophobic recovery sampling branch, and maintaining time coordination and data reliability throughout the continuous operation of the entire measurement process.

[0099] Beneficial effect 1:

[0100] This invention constructs a dynamic time series relating sample water temperature, the internal temperature of the conductivity electrode, and sample water flow rate. Based on this, it introduces mechanisms for identifying gradual change zones, flow rate delay, and time weight redistribution, ensuring that temperature compensation during conductivity measurement remains consistent with the actual temperature changes of the sample water over time. This avoids compensation offset caused by temperature response lag, allowing the conductivity correction results to reflect the actual changes in hydrophobic water quality in real time. The dynamic conductivity curve no longer exhibits delayed following or passive smoothing, improving the synchronization of measurement results with temperature fluctuations and water quality changes, and providing a more reliable measurement basis for continuous monitoring of the hydrophobic recovery sampling branch.

[0101] Benefit 2:

[0102] This invention, based on temperature and time alignment, implements continuous smooth control of the conductivity output signal. By rationally distributing time weights between adjacent time nodes, it effectively dissipates instantaneous fluctuations generated during the measurement process, ensuring that the conductivity change curve accurately reflects the true trend of hydrophobic water quality while maintaining continuity. This method avoids interference from instantaneous disturbances on the monitoring results while preserving the true dynamic characteristics of water quality changes. It enables online monitoring to maintain stable output even under conditions of switching operating modes and operational fluctuations, thereby improving the reliability and accuracy of online monitoring in the hydrophobic recovery sampling branch.

[0103] This invention provides, for example Figure 4 The continuous conductivity measurement system with hydrophobic recovery sampling branch cooling shown includes a dynamic time series establishment module, a temperature difference hysteresis segmentation module, a flow rate rhythm control module, a time weight redistribution module, and a conductivity smoothing control module.

[0104] Dynamic time series establishment module: Collect real-time sample water temperature, conductivity electrode internal temperature and sample water flow rate change data during the cooling process of hydrophobic recovery sampling branch, and establish a dynamic time series reflecting the thermal response hysteresis characteristics between sample water temperature and electrode temperature.

[0105] Temperature lag segmentation module: Based on the temperature lag characteristics represented in the dynamic time series, the temperature response rhythm inside the collected conductivity electrode is adjusted in time segments, the temperature lag interval is identified as the gradual change zone, and the time nodes of the gradual change zone are extracted to construct a transition benchmark for synchronous compensation of sample water temperature and electrode temperature.

[0106] Flow rhythm control module: Combined with the time nodes of the gradual change zone, the transient flow rate of the sample water inflow rhythm is adjusted. The temperature gradient in the gradual change zone is used as the control basis. Through the flow delay process, the sample water temperature change curve and the thermal response rhythm of the conductivity electrode are dynamically aligned in time.

[0107] Time weight redistribution module: Under the temperature dynamic alignment state, the time weight distribution of the temperature compensation curve used for conductivity measurement is redistributed. The synchronization rhythm formed during the flow delay process is used as the time reference. The compensation ratio of the original lagging temperature node is adjusted and shifted to the instantaneous temperature node of the sample water to form a temperature compensation result consistent with the sample water temperature change time.

[0108] Conductivity smoothing control module: Based on the temperature compensation results, it performs continuous smoothing control on the conductivity output signal and uses the redistributed time weight to dissipate the instantaneous error in the measurement process.

[0109] The continuous conductivity measurement method for cooling of the hydrophobic recovery sampling branch provided in this embodiment of the invention is implemented by the aforementioned continuous conductivity measurement system for cooling of the hydrophobic recovery sampling branch. For details of the specific method and process of the continuous conductivity measurement system for cooling of the hydrophobic recovery sampling branch, please refer to the embodiment of the above-mentioned continuous conductivity measurement method for cooling of the hydrophobic recovery sampling branch, which will not be repeated here.

[0110] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the present invention.

Claims

1. A continuous conductivity measurement method for a hydrophobic recovery sampling branch under cooling, characterized in that, Includes the following steps: Real-time data on sample water temperature, internal temperature of conductivity electrode, and sample water flow rate changes were collected during the cooling process of the hydrophobic recovery sampling branch. A dynamic time series reflecting the thermal response hysteresis characteristics between sample water temperature and electrode temperature was established. Based on the temperature lag characteristics represented in the dynamic time series, the temperature response rhythm inside the collected conductivity electrode is adjusted in time segments. The temperature lag interval is identified as the gradual change zone, and the time nodes of the gradual change zone are extracted to construct a transition benchmark for synchronous compensation of sample water temperature and electrode temperature. By combining the time nodes of the gradual change zone, the flow rate of the sample water inflow rhythm is adjusted transiently. The temperature gradient in the gradual change zone is used as the basis for regulation. The flow rate delay process is used to dynamically align the sample water temperature change curve with the thermal response rhythm of the conductivity electrode in time. Under dynamic temperature alignment, the time weight distribution of the temperature compensation curve used for conductivity measurement is redistributed. The synchronous rhythm formed during the flow delay is used as the time reference. The compensation weight of the original lagging temperature node is adjusted and shifted to the instantaneous temperature node of the sample water to form a temperature compensation result consistent with the temperature change time of the sample water. Based on the temperature compensation results, continuous smooth control is performed on the conductivity output signal, and the instantaneous error in the measurement process is dissipated by the redistributed time weight.

2. The continuous conductivity measurement method for hydrophobic recovery sampling branch cooling according to claim 1, characterized in that, The steps for establishing a dynamic time series reflecting the thermal response hysteresis characteristics between the sample water temperature and the internal temperature of the conductivity electrode include: The measurement location of the cooling section of the hydrophobic recovery sampling branch is selected to collect real-time parameters of the hydrophobic sample water operation status. The first temperature measurement unit is used to continuously measure the instantaneous temperature of the hydrophobic sample water, the second temperature measurement unit is used to detect the internal temperature of the conductivity electrode, and the flow measurement unit is used to record the change in sample water flow rate. The collected data on sample water temperature, internal temperature of conductivity electrode, and flow rate changes were organized in chronological order to establish a continuous dynamic time series. The time difference between the rate of change of sample water temperature and the rate of response of internal temperature of conductivity electrode was recorded to obtain the influence law of hydrophobic sample water operating state on thermal response hysteresis characteristics. Based on the dynamic time series analysis, the relationship between the sample water temperature and the internal temperature of the conductivity electrode was analyzed. By setting thresholds for the rate of temperature change and the temperature difference comparison, the temperature stable zone, the temperature rapid change zone, and the temperature difference recovery zone were identified.

3. The continuous conductivity measurement method for hydrophobic recovery sampling branch cooling according to claim 2, characterized in that, The steps for constructing a transitional baseline for synchronous compensation of sample water temperature and electrode temperature at the time point of extraction of the gradually changing region include: In the dynamic time series, time correlation analysis was performed on the changes in hydrophobic sample water temperature, internal temperature of conductivity electrode and hydrophobic flow rate to determine the time interval between the starting point of sample water temperature change and the starting point of electrode temperature response, and this time interval was defined as the temperature lag interval. Based on the time characteristics of the temperature lag interval, the internal temperature response rhythm of the conductivity electrode is adjusted by time segmentation. The time period in which the sample water temperature change has not yet caused the electrode temperature response is defined as the initial response segment, the time period in which the temperature difference persists is defined as the core segment of the slow change zone, and the time period in which the temperature gradually stabilizes is defined as the stable segment. The duration and flow status of each time period are recorded simultaneously. Starting from the core section of the gradually changing zone, continuous time nodes are extracted according to the sampling time interval, and the sample water temperature, electrode temperature and hydrophobic flow data of each time node are recorded to form a node sequence arranged in chronological order. Connect the time nodes in the gradual change zone in chronological order and establish a temperature correspondence table. Transform the correspondence between sample water temperature and electrode temperature into a time-corresponding compensation transition benchmark, and synchronously record the hydrophobic flow status in the compensation benchmark.

4. The continuous conductivity measurement method for hydrophobic recovery sampling branch cooling according to claim 3, characterized in that, The time nodes in the core section of the slow-change zone are determined according to the difference between the rate of change of the sample water temperature and the internal temperature of the conductivity electrode. When the difference in the rate of change of temperature continues to decrease, the corresponding time node is marked as a critical node, and the trend of temperature difference between adjacent critical nodes is used as the basis for adjusting temperature synchronous compensation.

5. The continuous conductivity measurement method for hydrophobic recovery sampling branch cooling according to claim 3, characterized in that, The steps to dynamically align the sample water temperature change curve with the thermal response rhythm of the conductivity electrode over time through a flow rate delay process include: The relationship between sample water temperature, conductivity electrode internal temperature and hydrophobic flow rate at the time nodes in the gradual change zone was analyzed. The sample water temperature value, electrode temperature value and temperature difference between adjacent nodes were recorded to form a temperature gradient distribution table. Based on the changing characteristics of the temperature gradient in the slow-change zone, the flow rate of the sample water inflow is adjusted transiently with time nodes as the control benchmark. The flow rate is reduced when the rate of change of sample water temperature increases and increased when the rate of change of sample water temperature slows down. During the flow delay process, the time distribution of the temperature gradient in the slow change zone is used as the control benchmark. By continuously recording the temperature changes at each time node, the time difference between the sample water temperature change curve and the electrode temperature response curve is confirmed to decrease, and finally the dynamic alignment of the sample water temperature change curve and the electrode temperature response curve in the time dimension is achieved. The time point at the end of the flow delay process is used as the starting point for temperature synchronization. The sample water flow rate is continuously monitored with reference to the time point of the gradual change zone. The flow rate is adjusted in real time when the sample water temperature shows a changing trend.

6. The continuous conductivity measurement method for the hydrophobic recovery sampling branch under cooling according to claim 5, characterized in that, During transient flow rate adjustment, the adjustment range of the sample water flow rate is determined based on the continuous rate of change of the temperature gradient in the slow-change zone. When the temperature difference between adjacent time points decreases continuously, the flow rate is kept stable; when the temperature difference increases continuously, the flow rate is gradually reduced.

7. The continuous conductivity measurement method for hydrophobic recovery sampling branch cooling according to claim 5, characterized in that, The steps to adjust and shift the compensation weight that originally corresponded to the hysteresis temperature node to the instantaneous temperature node of the sample water include: The relationship between sample water temperature, internal temperature of conductivity electrode and flow rate changes at the time node of the slow change zone is analyzed. Based on the synchronous rhythm formed by the flow rate delay process, the node where the sample water temperature and internal temperature of conductivity electrode are consistent in the time dimension is determined and marked as the instantaneous temperature node, and a one-to-one correspondence between the lag temperature node and the instantaneous temperature node is established. Based on the correspondence between instantaneous temperature nodes and lag temperature nodes, the time weight distribution of the temperature compensation curve used in conductivity measurement is reorganized. Taking the time rhythm formed during the flow delay process as the time reference, the compensation weight of the lag temperature node is moved forward along the time axis to the corresponding instantaneous temperature node, and the weight change value is recorded to form a synchronous distribution. Based on the shifted time series, the time weight distribution of the temperature compensation curve is continuously optimized, and the weight transition of adjacent nodes is adjusted according to the temperature change trend of the sample water. Using the optimized temperature compensation curve as the time reference, the corresponding instantaneous temperature node compensation weight value is read in real time during the conductivity measurement process, and conductivity correction calculation is performed to form a conductivity correction time series.

8. The continuous conductivity measurement method for the hydrophobic recovery sampling branch under cooling according to claim 7, characterized in that, When continuously optimizing the time weight distribution of the temperature compensation curve used for conductivity measurement, the weight change rate is limited according to the actual trend of sample water temperature change. When the weight change span between adjacent time nodes exceeds the set change span threshold, a gradual transition adjustment is performed according to the direction of sample water temperature change.

9. The continuous conductivity measurement method for the hydrophobic recovery sampling branch under cooling according to claim 7, characterized in that, The steps to obtain a dynamic conductivity curve synchronized with the actual temperature change of the sample water by dissipating instantaneous errors during the measurement process using the redistributed time weights include: The output signal of conductivity and the temperature compensation result are matched in time and synchronously. Based on the temperature compensation time series, the sample water temperature, the internal temperature of conductivity electrode and the flow rate change data are reorganized in time order. Based on the redistributed time weights, continuous smoothing control is implemented on the conductivity output signal. The conductivity measurement value is read sequentially starting from the first node of the time series, and smoothing is performed by combining the time weights of adjacent time nodes. When the signal fluctuates, the instantaneous error is distributed to adjacent time nodes through the time weights. After the smoothing control is completed, the conductivity output signal is reconstructed in time series, and the smoothed conductivity values ​​are connected in time order to form a dynamic change curve covering the entire process of hydrophobic water sampling and cooling.

10. A continuous conductivity measurement system for cooling of a hydrophobic recovery sampling branch, used to implement the continuous conductivity measurement method for cooling of a hydrophobic recovery sampling branch as described in any one of claims 1-9, characterized in that, It includes a dynamic time series establishment module, a temperature difference lag segmentation module, a flow rate rhythm control module, a time weight redistribution module, and a conductivity smoothing control module; Dynamic time series establishment module: Collect real-time sample water temperature, conductivity electrode internal temperature and sample water flow rate change data during the cooling process of hydrophobic recovery sampling branch, and establish a dynamic time series reflecting the thermal response hysteresis characteristics between sample water temperature and electrode temperature. Temperature lag segmentation module: Based on the temperature lag characteristics represented in the dynamic time series, the temperature response rhythm inside the collected conductivity electrode is adjusted in time segments, the temperature lag interval is identified as the gradual change zone, and the time nodes of the gradual change zone are extracted to construct a transition benchmark for synchronous compensation of sample water temperature and electrode temperature. Flow rhythm control module: Combined with the time nodes of the gradual change zone, the transient flow rate of the sample water inflow rhythm is adjusted. The temperature gradient in the gradual change zone is used as the control basis. Through the flow delay process, the sample water temperature change curve and the thermal response rhythm of the conductivity electrode are dynamically aligned in time. Time weight redistribution module: Under the temperature dynamic alignment state, the time weight distribution of the temperature compensation curve used for conductivity measurement is redistributed. The synchronization rhythm formed during the flow delay process is used as the time reference. The compensation ratio of the original lagging temperature node is adjusted and shifted to the instantaneous temperature node of the sample water to form a temperature compensation result consistent with the sample water temperature change time. Conductivity smoothing control module: Based on the temperature compensation results, it performs continuous smoothing control on the conductivity output signal and uses the redistributed time weight to dissipate the instantaneous error in the measurement process.

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