A remote real-time control system and method for equipment used in port sewage treatment

Abstract

This invention discloses a remote real-time control system and method for port sewage treatment equipment, specifically relating to the field of sewage treatment technology: It utilizes interface testing tools to capture data packets and parse protocols on the communication interface to ensure that the communication rate of the new system matches that of the oil-water separator; when the rates do not match, it evaluates the effectiveness of the new system's command transmission and determines the accuracy of the oil-water separator's response to control commands through power consumption stability analysis, classifying response accuracy into high and low accuracy categories. For low-accuracy responses, it uses anomaly index analysis and prediction to reduce the influent flow rate of the oil-water separator when the anomaly level is high. This not only ensures the system maintains efficient and stable operation when updating remote control software or hardware but also avoids equipment damage and system failure caused by incompatibility, thereby improving the operational reliability and maintenance efficiency of the oil-water separator.

Description

Technical Field

[0001] The present invention relates to the technical field of sewage treatment, and in particular to a remote real-time control system and method for equipment used in port sewage treatment. Background Art

[0002] Remote real-time control of equipment used for port sewage treatment refers to the real-time monitoring and adjustment of port sewage treatment equipment through remote communication technology and automation systems. Such systems usually rely on sensors, data transmission networks and control software to achieve real-time monitoring of the operating status and parameters (such as flow rate, pollutant concentration, etc.) of sewage treatment equipment, and can remotely adjust the working mode or parameters of the equipment according to actual conditions to ensure efficient and stable operation of the sewage treatment process.

[0003] Port sewage usually contains oil from ships and mechanical equipment. Oil-water separators are used to remove oil and fat from water. Oil-water separators use gravity separation, flotation technology or membrane separation technology to separate oil from water, reducing the impact of oil pollutants on the environment.

[0004] The prior art has the following deficiencies:

[0005] When the operating status and parameters of the oil-water separator are monitored and operated through the remote monitoring system, the remote monitoring system needs to be highly compatible with the oil-water separator equipment. If the remote control software or hardware is not adapted to the existing oil-water separator equipment when it is updated, the equipment may not respond to control commands, or command errors may occur, resulting in system failure. For example, the data from the sensor may not match the performance of the actual equipment, causing the separator to operate under incorrect conditions, resulting in the inability to separate oil and pollutants and excessive discharge of sewage. If the equipment fails to respond to the correct instructions, it may continue to operate in the wrong mode, causing overload or mechanical damage. For example, the separator may operate at a pressure or speed that exceeds its design capacity, causing wear, overheating or rupture of key components. Equipment failure may result in long periods of downtime for maintenance, affecting the entire sewage treatment process and further exacerbating the pollution problem. Summary of the invention

[0006] The purpose of the present invention is to provide a remote real-time control system and method for equipment used in port sewage treatment to overcome the shortcomings of the background technology.

[0007] In order to achieve the above object, the present invention provides the following technical solution: a remote real-time control method for equipment used for port sewage treatment, comprising the following steps:

[0008] S1; when updating the remote control system, the communication interface between the oil-water separator and the new remote control system is captured and the protocol is analyzed through the interface test tool, and whether the communication rate of the new system matches the communication rate of the oil-water separator is determined according to the analysis results;

[0009] S2: When the communication rate of the new system does not match the communication rate of the oil-water separator, control instructions are sent through the remote monitoring system, and the effectiveness of the new system instruction transmission is evaluated based on the response time and amplitude of the power consumption change of the oil-water separator;

[0010] S3: Calculate the separation efficiency of the oil-water separator after receiving the control command, analyze the difference in separation efficiency of the oil-water separator before and after the command, and evaluate the stability of the separation efficiency of the oil-water separator after receiving the control command;

[0011] S4: Determine the accuracy of the oil-water separator responding to the control command based on the effectiveness of the new system command transmission and the stability of the separation efficiency after the oil-water separator receives the control command;

[0012] S5: Divide the accuracy of the oil-water separator response control command into different levels, and divide it into two categories: high accuracy response and low accuracy response;

[0013] S6: For high-accuracy response, the oil-water separator performance data under high-accuracy response is used as the operating baseline and for subsequent monitoring; for low-accuracy response, the abnormal degree of the accuracy of the oil-water separator response control instruction within a fixed time is predicted, and when the abnormal degree is high, the water inlet flow rate of the oil-water separator is reduced.

[0014] Preferably, in S1, the total number of instructions sent within a period of time is captured, the number of instructions sent per second is calculated, the frequency of the oil-water separator receiving and processing instructions per second is counted by capturing the feedback data packet of the oil-water separator, and the instruction sending frequency of the new control system is compared with the receiving frequency of the oil-water separator; if the sending frequency is equal to the receiving frequency, the two match and the system can work normally; if the sending frequency is not equal to the receiving frequency, the two do not match.

[0015] Preferably, in S2, a response power consumption deviation index is generated according to the response time and amplitude of the power consumption change of the oil-water separator, and the method for obtaining the response power consumption deviation index is:

[0016] Constructing Actual Power Consumption Sequences , which indicates the power consumption response of the device after receiving the control instruction, and the sampling time is , the sequence is:

[0017] ; Build target power consumption sequence , which represents the power consumption of the device after executing the control instruction under ideal conditions, and the sampling time is , the sequence is: ; Define a two-dimensional matrix D with a dimension of m×n to store the Euclidean distance between the actual power consumption and the target power consumption at each moment. Each element D(i,j) in the matrix represents the actual power consumption of the ith moment. and the jth target power consumption The Euclidean distance between them is expressed as: ; Construct the cumulative cost matrix C to record the minimum cost path from the starting point (1,1) to the current point (i,j). The initial conditions are: ; The values ​​of the remaining matrices are obtained by recursive calculation: ; Among them, the min operation ensures that the minimum cost of the cumulative path is selected. Starting from the lower right corner of the cumulative cost matrix C(m,n), it is traced back to (1,1) to find the best alignment path W between the actual power consumption curve and the target power consumption curve. The total length of path W is L. By tracking the path To obtain the matching point pairs at each time point; by averaging the costs of all point pairs on path W, the response power consumption deviation index is calculated, and the expression is: ; In the formula, In response to the power consumption deviation index, It is the Euclidean distance between the actual power consumption and the target power consumption of each point pair on the path.

[0018] Preferably, in S3, the separation efficiency difference of the oil-water separator before and after the instruction is analyzed to generate a separation efficiency difference fluctuation index, and the method for obtaining the separation efficiency difference fluctuation index is:

[0019] The separation efficiency data of the oil-water separator before and after the instruction execution is obtained through real-time monitoring. The data sequence is defined as ,in is the separation efficiency value at the kth time point; the original separation efficiency data is resampled to generate time series of different scales, and g time scale τ values ​​are set, each time scale corresponds to a different time interval, where, ; Resample the original sequence to generate a new time series with a length of , the expression is:

[0020] in is the mean of the jth resampling point, indicating the separation efficiency within the jth time window, generating each time scale Corresponding resampling sequence; set an embedding dimension m, the dimension represents the comparison length of consecutive data points; set the tolerance threshold r, and construct the delay vector , and calculate the distance between each delay vector and all vectors, and count all Similar vector pairs, calculate the number of similar vector pairs , represents the similarity between the delay vector and other vectors, increase the embedding dimension to calculate the similarity logarithm: increase the embedding dimension to m+1, and recalculate the similarity logarithm ; Calculate the separation efficiency difference fluctuation index, the expression is: ; In the formula, and are the similarity vector logarithms with embedding dimensions m+1 and m, respectively. is the separation efficiency difference fluctuation index.

[0021] Preferably, in S4, the accuracy of the oil-water separator responding to the control instruction is determined according to the effectiveness of the transmission of the new system instruction and the stability of the separation efficiency after the oil-water separator receives the control instruction;

[0022] The response power consumption deviation index and the separation efficiency difference fluctuation index are converted into the first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model uses each group of first eigenvectors to predict the accuracy value label of the oil-water separator response control instruction as the prediction target, and takes minimizing the sum of prediction errors of the accuracy value labels of all oil-water separator response control instructions as the training target. The machine learning model is trained until the sum of prediction errors converges and the model training is stopped. The accuracy value of the oil-water separator response control instruction is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0023] Preferably, in S5, the accuracy of the oil-water separator response control instruction is divided into different levels, which are divided into two categories of high accuracy response and low accuracy response;

[0024] The acquired accuracy value of the oil-water separator response control instruction is compared with the preset reference threshold of the accuracy value. If the accuracy value of the oil-water separator response control instruction is greater than or equal to the reference threshold of the accuracy value, it means that the accuracy of the oil-water separator response control instruction is high. At this time, a high-accuracy response signal is generated and it is classified as a high-accuracy response; if the accuracy value of the oil-water separator response control instruction is less than the reference threshold of the accuracy value, it means that the accuracy of the oil-water separator response control instruction is low. At this time, a low-accuracy response signal is generated and it is classified as a low-accuracy response.

[0025] Preferably, in S6, for low accuracy response, the abnormal degree of the accuracy of the oil-water separator response control instruction within a fixed time is predicted, and when the abnormal degree is high, the water inlet flow rate of the oil-water separator is reduced, specifically:

[0026] For low accuracy response, that is, the accuracy value of the oil-water separator response control instruction within a fixed time period is less than the reference threshold of the accuracy value, the accuracy values ​​of the oil-water separator response control instructions generated in the subsequent fixed time period that are less than the reference threshold of the accuracy value are collected, and a corresponding data set is established to calculate the abnormal index of the accuracy of the oil-water separator response control instruction, that is, calculate the standard deviation of the data set.

[0027] Preferably, the acquired abnormal index of the accuracy of the oil-water separator response control instruction is compared with the abnormal index reference threshold in the historical data. If the abnormal index is greater than or equal to the abnormal index reference threshold, it means that the abnormal degree of the accuracy of the oil-water separator response control instruction in the subsequent fixed time period is high. At this time, a warning signal is generated to reduce the water inlet flow rate of the oil-water separator; if the abnormal index is less than the abnormal index reference threshold, it means that the abnormal degree of the accuracy of the oil-water separator response control instruction in the subsequent fixed time period is low. At this time, no warning signal is generated, and the system continues to operate normally, but continuous monitoring should still be carried out.

[0028] The present invention also provides a remote real-time control system for equipment used in port sewage treatment, including a communication protocol analysis module, a power consumption response analysis module, a separation efficiency calculation module, an instruction response accuracy evaluation module, an accuracy classification module and a control module;

[0029] Communication protocol analysis module: when updating the remote control system, the communication interface between the oil-water separator and the new remote control system is captured and the protocol is analyzed through the interface test tool, and the communication rate of the new system is determined to match the communication rate of the oil-water separator according to the analysis results;

[0030] Power consumption response analysis module: When the communication rate of the new system does not match the communication rate of the oil-water separator, control instructions are sent through the remote monitoring system to evaluate the effectiveness of the new system instruction transmission based on the response time and amplitude of the oil-water separator power consumption change;

[0031] Separation efficiency calculation module: calculates the separation efficiency of the oil-water separator after receiving the control command, analyzes the difference in separation efficiency of the oil-water separator before and after the command, and evaluates the stability of the separation efficiency of the oil-water separator after receiving the control command;

[0032] Command response accuracy evaluation module: Determine the accuracy of the oil-water separator's response to the control command based on the effectiveness of the new system command transmission and the stability of the separation efficiency after the oil-water separator receives the control command;

[0033] Accuracy classification module: divides the accuracy of the oil-water separator response control instruction into different levels, and divides it into two categories: high accuracy response and low accuracy response;

[0034] Control module: For high-accuracy response, the oil-water separator performance data under high-accuracy response is used as the operating baseline and for subsequent monitoring; for low-accuracy response, the abnormal degree of the accuracy of the oil-water separator response control instruction within a fixed time is predicted, and when the abnormal degree is high, the water inlet flow of the oil-water separator is reduced.

[0035] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0036] 1. The present invention ensures that the oil-water separator can effectively respond to the new system control instructions and maintain high efficiency and stability during the system operation through multi-level analysis methods such as communication rate matching verification, power consumption response deviation analysis, separation efficiency calculation and fluctuation evaluation. At the same time, a machine learning model is introduced, characterized by the response power consumption deviation index and separation efficiency difference fluctuation index, to further optimize the accuracy prediction of instruction transmission and improve the intelligent management level of the system.

[0037] 2. The present invention also evaluates system performance in real time based on the accuracy of equipment response, uses high-accuracy response data as the operating baseline, and predicts low-accuracy responses through abnormal index analysis. When the abnormality is high, early warning is given and the water flow rate of the oil-water separator is reduced to ensure that the system can take measures before potential problems occur. This not only improves the reliability and fault response capabilities of the system, but also reduces equipment downtime and maintenance costs, ensuring the continued stable operation of the port sewage treatment system. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0039] Figure 1 The present invention is a flow chart of the method.

[0040] Figure 2 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Example 1, please refer to Figure 1 As shown, the remote real-time control method for equipment for port sewage treatment described in this embodiment includes the following steps:

[0043] S1; when updating the remote control system, the communication interface between the oil-water separator and the new remote control system is captured and the protocol is analyzed through the interface test tool, and whether the communication rate of the new system matches the communication rate of the oil-water separator is determined according to the analysis results;

[0044] S2: When the communication rate of the new system does not match the communication rate of the oil-water separator, control instructions are sent through the remote monitoring system, and the effectiveness of the new system instruction transmission is evaluated based on the response time and amplitude of the power consumption change of the oil-water separator;

[0045] S3: Calculate the separation efficiency of the oil-water separator after receiving the control command, analyze the difference in separation efficiency of the oil-water separator before and after the command, and evaluate the stability of the separation efficiency of the oil-water separator after receiving the control command;

[0046] S4: Determine the accuracy of the oil-water separator responding to the control command based on the effectiveness of the new system command transmission and the stability of the separation efficiency after the oil-water separator receives the control command;

[0047] S5: Divide the accuracy of the oil-water separator response control command into different levels, and divide it into two categories: high accuracy response and low accuracy response;

[0048] S6: For high-accuracy response, the oil-water separator performance data under high-accuracy response is used as the operating baseline and for subsequent monitoring; for low-accuracy response, the abnormal degree of the accuracy of the oil-water separator response control instruction within a fixed time is predicted, and when the abnormal degree is high, the water inlet flow rate of the oil-water separator is reduced.

[0049] Among them, in S1, when updating the remote control system, the communication interface between the oil-water separator and the new remote control system is captured and the protocol is parsed through the interface test tool, and whether the communication rate of the new system matches the communication rate of the oil-water separator is determined based on the analysis results.

[0050] Obtain the technical parameters of the existing communication system of the oil-water separator, including the communication protocol type (such as Modbus, OPC, Profibus, etc.), communication rate, interface type (such as RS-485, Ethernet, etc.), and data transmission format (such as data frame length, CRC check mechanism, etc.). Determine the communication settings and rates (such as baud rate, packet size, transmission frequency, etc.) of the current control system so that it can be compared with the new system during subsequent testing. Select test tools that can support the communication protocol and interface type (such as WireShark, Modscan, OPC Analyzer, etc.). Equip hardware devices (such as serial port debuggers, network cable sniffers) and software tools that can capture communication data packets to ensure that the communication traffic between the oil-water separator and the remote monitoring system can be captured in real time.

[0051] Connect the interface test tool to the communication line of the oil-water separator. For example, if the oil-water separator uses an Ethernet connection, connect the test tool to the communication interface of the controller and the separator through an Ethernet cable. Configure the test tool to monitor the communication link of the current system to ensure that the data flow between the oil-water separator and the existing remote control system can be captured. Start the interface test tool and start capturing the communication data packets between the existing control system and the oil-water separator. By monitoring the device for a period of time, obtain the data packet flow under normal operation. During the capture process, record the time point when the device receives the command and the response time of the feedback, especially paying attention to key parameters such as transmission rate and data packet size. Use the protocol parsing function of the interface test tool to perform protocol parsing on the captured data packets. Check the structure of the data packet to confirm whether the protocol type, data frame format, data verification method (such as CRC), address field and instruction field format meet the protocol standard. Based on the parsing results, extract information such as the communication rate and data transmission frequency of the current system to confirm whether the communication rate between the device and the system settings matches.

[0052] Connect the new remote control system to the oil-water separator to replace the original control system. Prepare to start packet capture and protocol matching test without affecting the normal operation of the equipment. Obtain its original communication rate (such as baud rate, packet size, data transmission frequency, etc.) from the technical documentation of the oil-water separator. For example, common baud rate values ​​may be 9600, 19200 or 115200 bps. Use the interface test tool to capture packets of the existing control system and calculate the frequency of command sending (for example, how many times per second). The frequency of control command sending can be determined based on the number of packets captured per unit time.

[0053] Connect the new control system to the oil-water separator and use an interface test tool (such as WireShark or other adapted industrial communication protocol analysis tools) to capture the communication data packets under the new system. Use the parsing tool to extract the baud rate and data transmission rate of the data packet, record the actual communication rate of the new control system, and ensure that it is consistent with the technical specifications of the oil-water separator equipment. Capture the control instructions sent by the new control system over a period of time, count the number of instructions sent per unit time, and calculate the sending frequency.

[0054] Capture the total number of instructions sent within a period of time (such as 1 minute) and calculate the number of instructions sent per second. For example, assume that 600 control instruction packets are captured within 60 seconds, and the instruction sending frequency is 10 / second. By capturing the feedback data packet of the oil-water separator, count the frequency of the oil-water separator receiving and processing instructions per second. For example, if the oil-water separator successfully processes 500 instruction packets in the same time period, its receiving frequency is 8.33 / second. Compare the instruction sending frequency of the new control system with the receiving frequency of the oil-water separator; if the sending frequency is equal to the receiving frequency (for example, a sending frequency of 10 / second corresponds to a receiving frequency of 10 / second), it is considered that the two match and the system can work normally. If the sending frequency is not equal to the receiving frequency (for example, a sending frequency of 10 / second corresponds to a receiving frequency of 8 / second), it is considered that the two do not match.

[0055] S2: When the communication rate of the new system does not match the communication rate of the oil-water separator, control instructions are sent through the remote monitoring system, and the effectiveness of the new system instruction transmission is evaluated based on the response time and amplitude of the power consumption change of the oil-water separator.

[0056] The interface test tool found that the communication rate between the new system and the oil-water separator was inconsistent. This may cause delays, packet loss, or failure to execute instructions during transmission. Therefore, before further evaluation, confirm the existence of communication rate mismatch.

[0057] Send a clear control command to the oil-water separator through the remote monitoring system. Usually, this command needs to be able to directly affect the operating status of the equipment, such as changing the pump speed, increasing or decreasing the flow rate, or adjusting the working mode of the oil-water separation efficiency. For example, send a command to increase the pump speed to observe the load changes of the equipment. Make sure to record the sending time of the command when sending the control command so that the synchronization of power consumption changes can be evaluated in subsequent steps.

[0058] Monitor the response time of the power consumption change after the command is sent. Ideally, the change in the device's power consumption should be highly synchronized with the time the control command is sent. If the power consumption change responds immediately, it means that the device has executed the command quickly. In addition to time synchronization, the magnitude of the power consumption change also needs to be consistent with the control command expectations. If a command is sent to increase the device's workload (such as increasing the pump speed), the device's power consumption should increase significantly. If the power consumption change is insufficient or too large, it may reflect that the device is not executing the command correctly or is over-operating. Normal amplitude: The magnitude of the power consumption change is consistent with expectations (such as a significant increase in power consumption after increasing the pump speed), indicating that the device is responding normally. Abnormal amplitude: If the magnitude of the power consumption change is not as expected, the device may not respond to the command correctly, or may even be operating under incorrect conditions (such as too low or too high power consumption).

[0059] The response power consumption deviation index is generated according to the response time and amplitude of the oil-water separator power consumption change to evaluate the effectiveness of the new system command transmission. The method for obtaining the response power consumption deviation index is as follows:

[0060] Constructing Actual Power Consumption Sequences , which indicates the power consumption response of the device after receiving the control instruction, and the sampling time is , the sequence is: ; Build target power consumption sequence , which indicates the power consumption that the device should achieve after executing the control instruction under ideal conditions. The sampling time is , the sequence is: ; Define a two-dimensional matrix D with a dimension of m×n to store the Euclidean distance between the actual power consumption and the target power consumption at each moment. Each element D(i,j) in the matrix represents the actual power consumption of the ith moment. and the jth target power consumption The Euclidean distance between them is expressed as:

[0061] ; Construct the cumulative cost matrix C to record the minimum cost path from the starting point (1,1) to the current point (i,j). The initial conditions are: ; The values ​​of the remaining matrices are obtained by recursive calculation:

[0062] ; Among them, the min operation ensures that the minimum cost of the cumulative path is selected. Starting from the lower right corner of the cumulative cost matrix C(m,n), it is traced back to (1,1) to find the best alignment path W between the actual power consumption curve and the target power consumption curve. The total length of path W is L. By tracking the path To obtain the matching point pairs at each time point; by averaging the costs of all point pairs on path W, the response power consumption deviation index is calculated, and the expression is: ; In the formula, In response to the power consumption deviation index, It is the Euclidean distance between the actual power consumption and the target power consumption of each point pair on the path.

[0063] When the response power consumption deviation index is large, it means that there is a large gap between the actual power consumption change of the oil-water separator and the expected target, reflecting the poor effectiveness of the new system command transmission. Large deviations may indicate that the device responds to commands with lag, large fluctuations or instability, or even fails to execute commands correctly. At this time, the device operation may not meet the set performance indicators, affecting the reliability and efficiency of the overall system.

[0064] On the contrary, when the response power consumption deviation index is small, it indicates that the actual power consumption change of the device is highly consistent with the expected target, reflecting the high effectiveness of the new system instruction transmission. A small deviation index indicates that the device can execute control instructions accurately and timely, and the power consumption curve is stable and matches the target curve. Such a system has high transmission efficiency and stable device operation, indicating that the instruction transmission and execution process is relatively reliable.

[0065] S3: Calculate the separation efficiency of the oil-water separator after receiving the control command, analyze the difference in separation efficiency of the oil-water separator before and after the command, and evaluate the stability of the separation efficiency of the oil-water separator after receiving the control command.

[0066] The separation efficiency (η) of the oil-water separator can be calculated by comparing the oil concentration at the inlet and outlet, using the formula: ;in: is the oil concentration at the water inlet of the oil-water separator (unit: mg / L), It is the oil concentration at the outlet of the oil-water separator (unit: mg / L).

[0067] Before the control command is issued, record the separation efficiency of the oil-water separator It is necessary to continuously record the separation efficiency for a period of time (such as 5-10 minutes) when the equipment is in a stable operating state in order to obtain a representative value. After the control command is issued, continue to monitor the separation efficiency of the oil-water separator . Within a few minutes after the command is issued (depending on the device response time), the change in separation efficiency is continuously recorded until the system returns to a new stable state. Calculate the difference in separation efficiency before and after the command , the expression is: .

[0068] The separation efficiency difference fluctuation index is generated by analyzing the difference in separation efficiency of the oil-water separator before and after the instruction, and the stability of the separation efficiency of the oil-water separator after receiving the control instruction is evaluated. The method for obtaining the separation efficiency difference fluctuation index is:

[0069] Through real-time monitoring, a series of separation efficiency data of the oil-water separator before and after the instruction execution are obtained. The data sequence is defined as ,in is the separation efficiency value at the kth time point; the original separation efficiency data is resampled to generate time series of different scales, and g time scale τ values ​​are set, each time scale corresponds to a different time interval, where, ; Resample the original sequence to generate a new time series with a length of , the expression is: in is the mean of the jth resampling point, indicating the separation efficiency within the jth time window, generating each time scale Corresponding resampled sequence; set an embedding dimension m, the common value is m=2, the dimension represents the comparison length of consecutive data points; set the tolerance threshold r, the common value is 0.1 to 0.25 times the standard deviation of the entire time series. This threshold is used to determine similarity, that is, if the difference between two data segments is less than r, the two segments are considered similar. Construct delay vector , and calculate the distance between each delay vector and all vectors, and count all Similar vector pairs, calculate the number of similar vector pairs , represents the similarity between the delay vector and other vectors, increase the embedding dimension to calculate the similarity logarithm: increase the embedding dimension to m+1, and recalculate the similarity logarithm ; Calculate the separation efficiency difference fluctuation index, the expression is: ; In the formula, and are the similarity vector logarithms with embedding dimensions m+1 and m, respectively. is the separation efficiency difference fluctuation index.

[0070] When the separation efficiency difference fluctuation index is large, it means that the separation efficiency of the oil-water separator fluctuates greatly after receiving the control command, and the system operation is unstable. This means that the equipment has significant separation efficiency fluctuations at different time scales, which may be caused by command transmission lag, inaccurate equipment adjustment, or unstable external conditions. A large fluctuation index indicates that the equipment responds inconsistently to the control command and the operating status fluctuates frequently, making it difficult to maintain the separation effect at a stable level.

[0071] On the contrary, the separation efficiency difference fluctuation index is small, indicating that the separation efficiency of the device is relatively stable after receiving the control command. The separation efficiency is stable at different time scales, indicating that the device can respond to the control command quickly and consistently and adjust to the expected working state. This small fluctuation index reflects the high reliability of the system, good control effect, and the separation efficiency can be maintained in a stable state for a long time, indicating that the system operation is optimized.

[0072] S4: Determine the accuracy of the oil-water separator's response to the control command based on the effectiveness of the new system command transmission and the stability of the separation efficiency after the oil-water separator receives the control command.

[0073] The response power consumption deviation index and the separation efficiency difference fluctuation index are converted into the first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model uses each group of first eigenvectors to predict the accuracy value label of the oil-water separator response control instruction as the prediction target, and takes minimizing the sum of prediction errors of the accuracy value labels of all oil-water separator response control instructions as the training target. The machine learning model is trained until the sum of prediction errors converges and the model training is stopped. The accuracy value of the oil-water separator response control instruction is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0074] The method for obtaining the accuracy value of the oil-water separator response control instruction is: from the first eigenvector training data of the trained machine learning model, obtain the corresponding function expression: ; In the formula, is the output function of the model, In response to the power consumption deviation index, is the separation efficiency difference fluctuation index, It is the accuracy value of the oil-water separator’s response to the control command.

[0075] S5: The accuracy of the oil-water separator response control instruction is divided into different levels, which are divided into two categories: high-accuracy response and low-accuracy response.

[0076] The acquired accuracy value of the oil-water separator response control instruction is compared with the preset reference threshold of the accuracy value. If the accuracy value of the oil-water separator response control instruction is greater than or equal to the reference threshold of the accuracy value, it means that the accuracy of the oil-water separator response control instruction is high. At this time, a high-accuracy response signal is generated and it is classified as a high-accuracy response; if the accuracy value of the oil-water separator response control instruction is less than the reference threshold of the accuracy value, it means that the accuracy of the oil-water separator response control instruction is low. At this time, a low-accuracy response signal is generated and it is classified as a low-accuracy response.

[0077] S6: For high-accuracy response, the oil-water separator performance data under high-accuracy response is used as the operating baseline and for subsequent monitoring; for low-accuracy response, the abnormal degree of the accuracy of the oil-water separator response control instruction within a fixed time is predicted, and when the abnormal degree is high, the water inlet flow rate of the oil-water separator is reduced.

[0078] With high accuracy response, the performance data of the oil-water separator (such as separation efficiency, power consumption, operating temperature, etc.) show a stable and ideal operating state. These data can be used as the operating baseline, that is, the standard performance indicators of the equipment under optimal conditions. By recording and archiving these baseline data, operators can compare the current equipment performance with the baseline during subsequent monitoring. If the actual data in subsequent monitoring deviates from the baseline, potential problems can be quickly identified, such as equipment performance degradation, control system failure, or changes in environmental conditions, so that timely adjustments and maintenance can be made to ensure that the equipment continues to operate efficiently.

[0079] For low accuracy response, the abnormal degree of the accuracy of the oil-water separator response control command within a fixed time is predicted, and when the abnormal degree is high, the water inlet flow of the oil-water separator is reduced, specifically:

[0080] For low accuracy response, that is, the accuracy value of the oil-water separator response control instruction within a fixed time period is less than the reference threshold of the accuracy value, the accuracy values ​​of the oil-water separator response control instructions generated in the subsequent fixed time period that are less than the reference threshold of the accuracy value are collected, and a corresponding data set is established to calculate the abnormal index of the accuracy of the oil-water separator response control instruction, that is, calculate the standard deviation of the data set.

[0081] The obtained abnormal index of the accuracy of the oil-water separator response control command is compared with the abnormal index reference threshold in the historical data. If the abnormal index is greater than or equal to the abnormal index reference threshold, it means that the abnormal degree of the accuracy of the oil-water separator response control command in the subsequent fixed time period is high. At this time, an early warning signal is generated and the water inlet flow of the oil-water separator is reduced; in order to prevent the oil-water separator from causing more serious failures due to overload or other operating problems, the system will automatically reduce the water inlet flow of the oil-water separator. This helps to reduce the equipment load and alleviate the operating pressure caused by inaccurate command response, thereby reducing the processing pressure of the equipment and reducing the risk of failure. After reducing the water inlet flow, the system will continue to monitor the performance parameters of the oil-water separator. If the equipment responds normally after reducing the water inlet flow, the system will gradually increase the water inlet flow until the equipment returns to a stable state. At the same time, if the equipment has not recovered, the system can continue to adjust or maintain a low flow until the problem is completely resolved.

[0082] If the abnormality index is less than the abnormality index reference threshold, it means that the abnormality of the accuracy of the oil-water separator response control command in the subsequent fixed time period is low, and no warning signal is generated at this time. In this case, due to the low degree of abnormality, the system can continue to operate normally, but continuous monitoring should still be carried out. It is recommended to record accuracy data regularly and predict possible potential problems through trend analysis so that maintenance measures can be taken in advance to avoid problems from worsening.

[0083] In this embodiment, in the process of updating the remote control system, the communication data packet between the oil-water separator and the new control system is first captured by the interface test tool, and its protocol is parsed to determine whether the communication rate matches. When the rate does not match, the effectiveness of the instruction transmission is evaluated by monitoring the power consumption response of the oil-water separator. Subsequently, the separation efficiency is calculated and the efficiency difference before and after the instruction is analyzed to evaluate the stability of the system. Based on the stability of the transmission effectiveness and the separation efficiency, the accuracy of the oil-water separator response instruction is determined and divided into two categories: high accuracy and low accuracy. For high-accuracy responses, the relevant performance data is recorded as the operating baseline for subsequent monitoring; for low-accuracy responses, the degree of abnormality is predicted by analyzing the abnormality index within a fixed time, and a warning signal is issued when the degree of abnormality is high, and the water inlet flow of the oil-water separator is reduced.

[0084] Example 2, please refer to Figure 2 As shown, the remote real-time control system for equipment used for port sewage treatment described in this embodiment includes a communication protocol parsing module, a power consumption response analysis module, a separation efficiency calculation module, an instruction response accuracy evaluation module, an accuracy classification module and a control module;

[0085] Communication protocol analysis module: when updating the remote control system, the communication interface between the oil-water separator and the new remote control system is captured and the protocol is analyzed through the interface test tool, and the communication rate of the new system is determined to match the communication rate of the oil-water separator according to the analysis results;

[0086] Power consumption response analysis module: When the communication rate of the new system does not match the communication rate of the oil-water separator, control instructions are sent through the remote monitoring system to evaluate the effectiveness of the new system instruction transmission based on the response time and amplitude of the oil-water separator power consumption change;

[0087] Separation efficiency calculation module: calculates the separation efficiency of the oil-water separator after receiving the control command, analyzes the difference in separation efficiency of the oil-water separator before and after the command, and evaluates the stability of the separation efficiency of the oil-water separator after receiving the control command;

[0088] Command response accuracy evaluation module: Determine the accuracy of the oil-water separator's response to the control command based on the effectiveness of the new system command transmission and the stability of the separation efficiency after the oil-water separator receives the control command;

[0089] Accuracy classification module: divides the accuracy of the oil-water separator response control instruction into different levels, and divides it into two categories: high accuracy response and low accuracy response;

[0090] Control module: For high-accuracy response, the oil-water separator performance data under high-accuracy response is used as the operating baseline and for subsequent monitoring; for low-accuracy response, the abnormal degree of the accuracy of the oil-water separator response control instruction within a fixed time is predicted, and when the abnormal degree is high, the water inlet flow of the oil-water separator is reduced.

[0091] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0092] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0093] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0094] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0095] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0096] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A remote real-time control method for equipment used in port sewage treatment, characterized in that: The following steps are involved: S1; when updating the remote control system, the communication interface between the oil-water separator and the new remote control system is captured and the protocol is analyzed through the interface test tool, and whether the communication rate of the new system matches the communication rate of the oil-water separator is determined according to the analysis results; S2: When the communication rate of the new system does not match the communication rate of the oil-water separator, control instructions are sent through the remote monitoring system, and the effectiveness of the new system instruction transmission is evaluated based on the response time and amplitude of the power consumption change of the oil-water separator; The step S2 specifically includes: generating a response power consumption deviation index according to the response time and amplitude of the power consumption change of the oil-water separator, and the method for obtaining the response power consumption deviation index is: Constructing Actual Power Consumption Sequences , which indicates the power consumption response of the device after receiving the control instruction, and the sampling time is , the sequence is: ; Build target power consumption sequence , which represents the power consumption of the device after executing the control instruction under ideal conditions, and the sampling time is , the sequence is: ; Define a two-dimensional matrix D with a dimension of m×n to store the Euclidean distance between the actual power consumption and the target power consumption at each moment. Each element D(i,j) in the matrix represents the actual power consumption of the ith moment. and the jth target power consumption The Euclidean distance between them is expressed as: ; Construct the cumulative cost matrix C to record the minimum cost path from the starting point (1,1) to the current point (i,j). The initial conditions are: ; The values ​​of the remaining matrices are obtained by recursive calculation: ; Among them, the min operation ensures that the minimum cost of the cumulative path is selected. Starting from the lower right corner of the cumulative cost matrix C(m,n), it is traced back to (1,1) to find the best alignment path W between the actual power consumption curve and the target power consumption curve. The total length of path W is L. By tracking the path To obtain the matching point pairs at each time point; by averaging the costs of all point pairs on path W, the response power consumption deviation index is calculated, and the expression is: ; In the formula, In response to the power consumption deviation index, is the Euclidean distance between the actual power consumption and the target power consumption of each point pair on the path; S3: Calculate the separation efficiency of the oil-water separator after receiving the control command, analyze the difference in separation efficiency of the oil-water separator before and after the command, and evaluate the stability of the separation efficiency of the oil-water separator after receiving the control command; S4: Determine the accuracy of the oil-water separator responding to the control command based on the effectiveness of the new system command transmission and the stability of the separation efficiency after the oil-water separator receives the control command; The step S3 specifically includes: analyzing the separation efficiency difference of the oil-water separator before and after the instruction to generate a separation efficiency difference fluctuation index, and the method for obtaining the separation efficiency difference fluctuation index is: The separation efficiency data of the oil-water separator before and after the instruction execution is obtained through real-time monitoring. The data sequence is defined as ,in is the separation efficiency value at the kth time point; the original separation efficiency data is resampled to generate time series of different scales, and g time scale τ values ​​are set, each time scale corresponds to a different time interval, where, ; Resample the original sequence to generate a new time series with a length of , the expression is: in is the mean of the jth resampling point, indicating the separation efficiency within the jth time window, generating each time scale Corresponding resampling sequence; set an embedding dimension m, the dimension represents the comparison length of consecutive data points; set the tolerance threshold r, and construct the delay vector , and calculate the distance between each delay vector and all vectors, and count all Similar vector pairs, calculate the number of similar vector pairs , represents the similarity between the delay vector and other vectors, increase the embedding dimension to calculate the similarity logarithm: increase the embedding dimension to m+1, and recalculate the similarity logarithm ; Calculate the separation efficiency difference fluctuation index, the expression is: ; In the formula, and are the similarity vector logarithms with embedding dimensions m+1 and m, respectively. is the separation efficiency difference fluctuation index; S5: Divide the accuracy of the oil-water separator response control command into different levels, and divide it into two categories: high accuracy response and low accuracy response; S6: For high-accuracy response, the oil-water separator performance data under high-accuracy response is used as the operating baseline and for subsequent monitoring; for low-accuracy response, the abnormal degree of the accuracy of the oil-water separator response control instruction within a fixed time is predicted, and when the abnormal degree is high, the water inlet flow rate of the oil-water separator is reduced.

2. The remote real-time control method for equipment used for port sewage treatment according to claim 1 is characterized in that: In S1, the total number of instructions sent within a period of time is captured, the number of instructions sent per second is calculated, the frequency of the oil-water separator receiving and processing instructions per second is counted by capturing the feedback data packet of the oil-water separator, and the instruction sending frequency of the new control system is compared with the receiving frequency of the oil-water separator; if the sending frequency is equal to the receiving frequency, the two match and the system can work normally; if the sending frequency is not equal to the receiving frequency, the two do not match.

3. The remote real-time control method for equipment used for port sewage treatment according to claim 2 is characterized in that: In S4, the accuracy of the oil-water separator responding to the control command is determined according to the effectiveness of the new system command transmission and the stability of the separation efficiency after the oil-water separator receives the control command; The response power consumption deviation index and the separation efficiency difference fluctuation index are converted into the first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model uses each group of first eigenvectors to predict the accuracy value label of the oil-water separator response control instruction as the prediction target, and takes minimizing the sum of prediction errors of the accuracy value labels of all oil-water separator response control instructions as the training target. The machine learning model is trained until the sum of prediction errors converges and the model training is stopped. The accuracy value of the oil-water separator response control instruction is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

4. The remote real-time control method for equipment used for port sewage treatment according to claim 3 is characterized in that: In S5, the accuracy of the oil-water separator response control instruction is divided into different levels, which are divided into two categories: high accuracy response and low accuracy response; The acquired accuracy value of the oil-water separator response control instruction is compared with the preset reference threshold of the accuracy value. If the accuracy value of the oil-water separator response control instruction is greater than or equal to the reference threshold of the accuracy value, it means that the accuracy of the oil-water separator response control instruction is high. At this time, a high-accuracy response signal is generated and it is classified as a high-accuracy response; if the accuracy value of the oil-water separator response control instruction is less than the reference threshold of the accuracy value, it means that the accuracy of the oil-water separator response control instruction is low. At this time, a low-accuracy response signal is generated and it is classified as a low-accuracy response.

5. The remote real-time control method for equipment used for port sewage treatment according to claim 1 is characterized in that: In S6, for low accuracy response, the abnormal degree of the accuracy of the oil-water separator response control instruction within a fixed time is predicted, and when the abnormal degree is high, the water inlet flow rate of the oil-water separator is reduced, specifically: For low accuracy response, that is, the accuracy value of the oil-water separator response control instruction within a fixed time period is less than the reference threshold of the accuracy value, the accuracy values ​​of the oil-water separator response control instructions generated in the subsequent fixed time period that are less than the reference threshold of the accuracy value are collected, and a corresponding data set is established to calculate the abnormal index of the accuracy of the oil-water separator response control instruction, that is, calculate the standard deviation of the data set.

6. A remote real-time control method for equipment for port sewage treatment according to claim 5, characterized in that: The acquired abnormal index of the accuracy of the oil-water separator response control instruction is compared with the abnormal index reference threshold in the historical data. If the abnormal index is greater than or equal to the abnormal index reference threshold, it means that the abnormal degree of the accuracy of the oil-water separator response control instruction in the subsequent fixed time period is high. At this time, a warning signal is generated to reduce the water inlet flow of the oil-water separator; if the abnormal index is less than the abnormal index reference threshold, it means that the abnormal degree of the accuracy of the oil-water separator response control instruction in the subsequent fixed time period is low. At this time, no warning signal is generated and the system continues to operate normally, but continuous monitoring should still be carried out.

7. A remote real-time control system for equipment used for port sewage treatment, used to implement a remote real-time control method for equipment used for port sewage treatment according to any one of claims 1 to 6, characterized in that: It includes a communication protocol parsing module, a power consumption response analysis module, a separation efficiency calculation module, a command response accuracy evaluation module, an accuracy classification module and a control module; Communication protocol analysis module: when updating the remote control system, the communication interface between the oil-water separator and the new remote control system is captured and the protocol is analyzed through the interface test tool, and the communication rate of the new system is determined to match the communication rate of the oil-water separator according to the analysis results; Power consumption response analysis module: When the communication rate of the new system does not match the communication rate of the oil-water separator, control instructions are sent through the remote monitoring system to evaluate the effectiveness of the new system instruction transmission based on the response time and amplitude of the oil-water separator power consumption change; Separation efficiency calculation module: calculates the separation efficiency of the oil-water separator after receiving the control command, analyzes the difference in separation efficiency of the oil-water separator before and after the command, and evaluates the stability of the separation efficiency of the oil-water separator after receiving the control command; Command response accuracy evaluation module: Determine the accuracy of the oil-water separator's response to the control command based on the effectiveness of the new system command transmission and the stability of the separation efficiency after the oil-water separator receives the control command; Accuracy classification module: divides the accuracy of the oil-water separator response control instruction into different levels, and divides it into two categories: high accuracy response and low accuracy response; Control module: For high-accuracy response, the oil-water separator performance data under high-accuracy response is used as the operating baseline and for subsequent monitoring; for low-accuracy response, the abnormal degree of the accuracy of the oil-water separator response control instruction within a fixed time is predicted, and when the abnormal degree is high, the water inlet flow of the oil-water separator is reduced.

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