Multi-element thermal fluid generator system operation control system

Abstract

The invention relates to the technical field of heavy oil thermal recovery, in particular to a multi-element thermal fluid generator system operation control system which comprises a data acquisition module used for acquiring working parameters of a multi-element thermal fluid generator during working, and the working parameters comprise multi-element thermal fluid parameters, working pressure, working temperature, water flow, gas amount and air flow; the trend identification module is used for identifying change trends of the working parameters at different positions, selecting the change trends of the corresponding working parameters according to different types of abnormal states when the working parameters are in abnormal states, and judging fault positions and processing measures of the working parameters according to the change trends; the work adjusting module is used for acquiring the parameter proportion and the distribution quantity of the working parameters according to the fault positions of the working parameters, and setting adjusting factors of the working parameters according to the parameter proportion and the distribution quantity of the working parameters; the stability, reliability and operation efficiency of the system are improved, and the maintenance cost is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of thermal recovery of heavy oil, in particular to an operation control system of a multi-element thermal fluid generator system. Background Art

[0002] The working principle of the traditional multi-element thermal fluid generation system is to utilize the combustion injection mechanism of the space rocket engine, fix the high-pressure combustion chamber in the cabin, and directly inject the high-temperature and high-pressure mixed gas such as water vapor, carbon dioxide, nitrogen, etc. generated after ignition and combustion into the oil layer, thereby increasing the oil layer pressure, reducing the oil layer viscosity, and increasing the oil displacement area, so as to achieve the purpose of improving the recovery rate.

[0003] For example, Chinese patent publication number CN113137217A discloses a multi-component thermal fluid generation parallel system and its startup method. The multi-component thermal fluid generation parallel system includes at least two multi-component thermal fluid generators; the high-mineralization water inlet of each multi-component thermal fluid generator is connected to the high-mineralization water distribution header, and a heat recovery and temperature adjustment device is provided on the connected pipeline; the air inlet, slag discharge outlet, material inlet and product outlet of each multi-component thermal fluid generator are respectively connected to the air compressor, slag discharge device, material distribution header and heat recovery and temperature adjustment device, and the heat recovery and temperature adjustment device is connected to the back pressure adjustment device.

[0004] The prior art explains how to control the multi-element thermal fluid generator by explaining the method of starting the multi-element thermal fluid generator in parallel. However, the prior art ignores the need to constantly monitor the data changes of the machine when controlling the multi-element thermal fluid generator, as well as the correlation between the output, input, and stability-related parameters within a relative time, so as to determine whether the current machine is operating normally and whether the generation of the multi-element thermal fluid is completed normally. Summary of the invention

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: a multi-component thermal fluid generator system operation control system, including: a data acquisition module, used to collect the working parameters of the multi-component thermal fluid generator during operation, the working parameters including multi-component thermal fluid parameters, working pressure, working temperature, water flow, gas flow, and air flow.

[0006] The trend recognition module is used to identify the change trend of working parameters at different positions. When the working parameters are in an abnormal state, the corresponding change trend of the working parameters is selected according to the type of abnormal state, and the fault location and treatment measures of the working parameters are determined according to the change trend.

[0007] The working adjustment module is used to obtain the parameter ratio and distribution amount of the working parameter according to the fault position of the working parameter, and set the adjustment factor of the working parameter according to the parameter ratio and distribution amount of the working parameter.

[0008] The control action constraint module is used to predict the change of the working parameters according to the processing measures of the working parameters, and determine the control actions and constraint factors corresponding to the working parameters.

[0009] The operation evaluation module is used to evaluate the working condition of the current multi-element thermal fluid generator according to the adjustment factor and the constraint factor, and obtain the evaluation result between the currently executed control action and the working parameters.

[0010] The trend identification module also includes the following contents: an input control unit, which is used to identify the change trends of water flow, gas flow and air flow, and determine the input control coefficient of the multi-element thermal fluid generator.

[0011] The operation control unit is used to identify the change trend of the working pressure and the working temperature, and obtain the working stability coefficient of the multi-element thermal fluid generator during normal operation.

[0012] The output control unit is used to verify the multi-element thermal fluid parameters, determine the change trend of the multi-element thermal fluid parameters, and obtain the output control coefficient of the multi-element thermal fluid generator.

[0013] The beneficial effects of the present invention are as follows: through real-time monitoring and fault prediction, the current solution of the present invention can timely discover and handle abnormal situations in the system, thereby avoiding system shutdown or damage caused by faults, and improving the stability and reliability of the system; by accurately locating the fault location and optimizing the processing measures, the current solution can reduce unnecessary repair and replacement costs, and reduce the maintenance cost of the system; by optimizing the system adjustment and control strategy, the current solution can ensure that the system operates in the best state, thereby improving the operating efficiency of the system; by introducing technical means such as trend identification, intelligent selection of processing measures and quantitative evaluation, the current solution significantly improves the intelligence level of the system, and provides strong support for the automated operation and intelligent management of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0015] Figure 1 The present invention is a system framework diagram of a multi-element thermal fluid generator system operation control system.

[0016] Figure 2 The present invention is a system flow chart of a multi-element thermal fluid generator system operation control system.

[0017] Figure 3 The present invention is a system framework diagram of a trend identification module of an operation control system of a multi-element thermal fluid generator system. DETAILED DESCRIPTION

[0018] The embodiments of the present invention are described in detail below. The embodiments described below are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. If no specific techniques or conditions are specified in the embodiments, the techniques or conditions described in the literature in the art or the product specifications are used.

[0019] See also Figure 1-Figure 3 A multi-element thermal fluid generator system operation control system includes: a data acquisition module, a trend recognition module, a work adjustment module, a control action constraint module, and an operation evaluation module; the data acquisition module collects data and sends it to the trend recognition module, the trend recognition module identifies the corresponding trend and outputs it to the work adjustment module, the work adjustment module generates an adjustment factor and outputs it to the control action constraint module, the control action constraint module determines the constraint condition factor selected at this time, and outputs the corresponding data to the operation evaluation module, and the operation evaluation module completes the overall evaluation of the data according to the adjustment factor and the constraint condition factor.

[0020] The data acquisition module is used to collect the working parameters of the multi-element thermal fluid generator during operation. The working parameters include multi-element thermal fluid parameters, working pressure, working temperature, water flow, gas flow, and air flow.

[0021] The trend recognition module is used to identify the change trend of working parameters at different positions. When the working parameters are in an abnormal state, the corresponding change trend of the working parameters is selected according to the type of abnormal state, and the fault location and treatment measures of the working parameters are determined according to the change trend.

[0022] The working adjustment module is used to obtain the parameter ratio and distribution amount of the working parameter according to the fault position of the working parameter, and set the adjustment factor of the working parameter according to the parameter ratio and distribution amount of the working parameter.

[0023] The control action constraint module is used to predict the change of the working parameters according to the processing measures of the working parameters, and determine the control actions and constraint factors corresponding to the working parameters.

[0024] The operation evaluation module is used to evaluate the working condition of the current multi-element thermal fluid generator according to the adjustment factor and the constraint factor, and obtain the evaluation result between the currently executed control action and the working parameters.

[0025] The trend identification module also includes the following contents: an input control unit, which is used to identify the change trends of water flow, gas flow and air flow, and determine the input control coefficient of the multi-element thermal fluid generator.

[0026] The operation control unit is used to identify the change trend of the working pressure and the working temperature, and obtain the working stability coefficient of the multi-element thermal fluid generator during normal operation.

[0027] The output control unit is used to verify the multi-element thermal fluid parameters, determine the change trend of the multi-element thermal fluid parameters, and obtain the output control coefficient of the multi-element thermal fluid generator.

[0028] In the present invention, the operation mode of the multi-component thermal fluid generator is that by injecting a certain amount of water flow and air, heat and gas are generated by closed combustion in the main part of the multi-component thermal fluid generator. The gas at this time includes high-temperature water vapor, carbon dioxide, nitrogen and other gases. The gas at this time is regarded as a multi-component thermal fluid injected into the mine to heat the crude oil, thereby improving the crude oil collection efficiency; at this time, the remaining water flow will be continuously injected after treatment, so that high-temperature gases such as high-temperature water vapor, carbon dioxide and nitrogen are continuously injected into the mine.

[0029] At this time, the control method for the multi-component thermal fluid generator is to monitor the temperature and pressure during operation, and compare the water flow, gas flow, and air flow input in real time to verify the multi-component thermal fluid parameters at this time; to ensure that high-temperature gas can be accurately input when the system is working, so that the crude oil extraction efficiency can be reasonably improved; for the multi-component thermal fluid parameters, including the multi-component thermal fluid flow, multi-component thermal fluid temperature and the carbon dioxide and nitrogen components contained in the multi-component thermal fluid, to monitor whether the current output multi-component thermal fluid can reach the preset temperature range, and whether the output quantity ratio is normal, to prevent insufficient combustion, or too little water input resulting in insufficient final output gas.

[0030] The above-mentioned multi-component thermal fluid parameters can be set at the output end of the multi-component thermal fluid generator by setting a gas flow meter, a pressure sensor, and a temperature sensor. The output end of the multi-component thermal fluid generator is directly connected to the mine to heat the crude oil and reduce the viscosity of the crude oil. At this time, the gas flow meter, pressure sensor, and temperature sensor are used to measure the corresponding temperature, pressure, and flow data of the multi-component thermal fluid. At the same time, the gas flow meter is also used to calculate the flow of carbon dioxide and nitrogen to identify the flow of water vapor output at this time.

[0031] The above-mentioned working pressure refers to the pressure of the system during normal operation, usually refers to the pressure of the fluid in the system. At this time, pressure sensors are set at the pump outlet, heat exchanger inlet and outlet, etc. to monitor the working pressure of the system.

[0032] The above-mentioned operating temperature indicates the problem of normal operation of the system, and tends to obtain the overall temperature of the system during normal operation. The temperature sensors are installed at the fluid inlet and outlet, key equipment (such as heat exchanger, combustion chamber) and other locations.

[0033] The water flow rate mentioned above is the flow rate of softened water used in the system. At this time, a flow meter is placed at the location where water enters the system.

[0034] The above-mentioned gas volume refers to the flow rate of the gas in the system. The flow rate of the gas will affect the temperature and flow rate of the high-temperature gas finally output. A gas flow meter is used and installed before the gas enters the combustion chamber.

[0035] The above-mentioned air flow refers to the flow of air discharged by the air compressor to assist the combustion of the gas. At this time, the amount of air needs to be controlled to ensure complete combustion of the gas.

[0036] In one embodiment of the present invention, the trend identification module is used to identify the change trend of the working parameters at different positions.

[0037] At this time, the working parameters will be divided into multiple units according to their sources and functions for separate identification and processing. The working parameters at this time will be identified in turn to verify whether the change trend of the current working parameters is normal and whether the normal operation of the multi-element thermal fluid generator can be met under such changes.

[0038] For example, according to the input working parameters, the main working parameters observed during normal operation, and the working parameters that the system ultimately needs to output, the trend identification module is divided into three units: input control unit, operation control unit, and output control unit. The data in these three units is identified to determine the current system operation status, and the working parameters are processed in the form of time points.

[0039] The purpose of dividing into three units at this time is that when the working parameters are in an abnormal state, the change trend of the corresponding working parameters is selected according to the type of abnormal state, and the fault location and treatment measures are determined according to the change trend.

[0040] At this time, the specific implementation content of the trend identification module is to identify the changing trends of working parameters at different positions. When the working parameters are in an abnormal state, the changing trend of the corresponding working parameters is selected according to the type of abnormal state, and the fault location and treatment measures of the working parameters are determined based on the changing trend.

[0041] For the method of identifying the type of abnormal state, by comparing the current working parameters with the abnormal parameters, the values ​​of the working parameters that exceed the preset safety range are identified, and the identified working parameters are divided into a first parameter type, a second parameter type, and a third parameter type according to the location where the working parameters are obtained, wherein the first parameter type represents the parameters input into the working parameters, the second parameter type represents the parameters for stable operation of the system, and the third parameter type represents the parameters for the final output; the first parameter type, the second parameter type, and the third parameter type are processed in turn to obtain the fault location, and the processing measures are selected according to the values ​​of the working parameters.

[0042] Among them, when it is the first parameter type, the input control unit is used to process the working parameters, judge the changing trends of water flow, gas flow and air flow in the working parameters, and obtain the input control coefficient related to the input; when it is the second parameter type, the operation control unit is used to process the working parameters, judge the changing trends of working pressure and working temperature in the working parameters, and obtain the working stability coefficient related to system stability; when it is the third parameter type, the output control unit is used to process the working parameters, judge the changing trends of multi-component thermal fluid parameters in the working parameters, and obtain the output control coefficient related to the multi-component thermal fluid output.

[0043] At this time, when the working parameters are processed, it is determined whether there is a problem with the current working parameters based on the three coefficient values ​​obtained, and the working parameters with problems and the location where the working parameters are collected are recorded as the fault location at this time.

[0044] For treatment measures, based on the values ​​of the working parameters, the output ratio of the motor corresponding to the working parameters is adjusted to obtain corresponding treatment measures.

[0045] In one embodiment of the present invention, the input control unit is used to identify the change trend of water flow, gas flow, and air flow, and determine the input control coefficient of the multi-element thermal fluid generator.

[0046] The method for obtaining the input control coefficient is mainly to obtain the maximum water flow, maximum air flow, and maximum gas flow in the changing trends of water flow, gas flow, and air flow, and determine whether the changing trends of water flow, gas flow, and air flow are stable at this time.

[0047] The input control coefficient at this time can be expressed as: obtaining the integral value of water flow, gas flow, and air flow, and calculating the input control coefficient according to the integral value of water flow, gas flow, and air flow.

[0048] F in =K w ×ω w +K g ×ω g +K a ×ω a ; Among them, F in Indicates the input control coefficient, K w Indicates the integral value of water flow, K g Indicates the integral value of the gas volume, K a Indicates the integral value of air flow; ω w represents the weight of water flow, ω g Represents the weight of the gas volume, ω aIndicates the weight of air flow; at this time, the weights of water flow, gas flow, and air flow can be set to 0.375, 0.375, and 0.25 respectively.

[0049] The integral value of water flow can be expressed as: Among them, K w represents the integral value of water flow, △w represents the change of water flow, △w=max(w)-w, wherein max(w) represents the maximum value of water flow, and w represents the current value of water flow; at this time, the difference between the current water flow and the maximum water flow is calculated to determine the change trend of the water flow at this time, and the maximum water flow is set to 8t / h at this time; the smaller the integral value is, the closer it is to the set maximum water flow, otherwise it means that the water flow fluctuation is greater.

[0050] The integral value of gas volume and air flow is calculated in the same way as the integral value of water flow. At this time, the maximum gas volume and maximum air flow are also set for adjustment. The maximum gas volume is set to 250Nm 3 / h; the maximum air flow setting value is 2400m 3 / h.

[0051] If the current input control coefficient value is a negative number, it means that the water flow, gas flow, and air flow of the current system exceed the set standard values. The current system situation needs to be adjusted, and the control processing of the current system needs to be adjusted according to the value of the input control coefficient at different time points; for example, use the input control coefficient as a retrieval condition to retrieve historical data with the same change trend as the current working parameter, and select the corresponding processing measures in the historical data to deal with the current abnormality.

[0052] In one embodiment of the present invention, the operation control unit is used to identify the change trend of the working pressure and the working temperature, and obtain the working stability coefficient of the multi-element thermal fluid generator during normal operation.

[0053] The working stability coefficient is obtained by sequentially obtaining the standard boundary value of the working pressure and the standard boundary range value of the working temperature, standardizing the working pressure and the working temperature, and calculating the working stability coefficient.

[0054] F sc =K p ×ω p +K tem ×ω tem ; Among them, F sc Indicates the working stability coefficient, K p Indicates the value of working pressure after standardization. Where p represents the value of working pressure, p′ represents the standard boundary value of working pressure; Ktem Indicates the value of the working temperature after standardization. tem represents the value of operating temperature, tem max Indicates the upper limit of the standard boundary range of the operating temperature, tem min Indicates the lower limit of the standard boundary range of the operating temperature; ω p represents the weight of work pressure, ω tem Indicates the weight of the working temperature; at this time, the weights of the working pressure and working temperature settings are 0.6 and 0.4 respectively.

[0055] At this time, the standard boundary range of the working temperature is -20 to 45°C. The boundary value of the working pressure is divided into heat carrier outlet pressure and air compressor output pressure according to the location of the working pressure. The boundary value of the heat carrier outlet pressure is 20MPa, and the boundary value of the air compressor output pressure is 25MPa.

[0056] For example, we can judge whether the working pressure and working temperature exceed the normal value range based on the value of the working stability coefficient, and regard the part with large changes in the working stability coefficient in a continuous time period as the abnormal part. Set these data as the fault location according to the collection location, and find the corresponding treatment measures in combination with historical data.

[0057] In one embodiment of the present invention, the output control unit is used to verify the multi-component thermal fluid parameters, determine the change trend of the multi-component thermal fluid parameters, and obtain the output control coefficient of the multi-component thermal fluid generator.

[0058] The multi-element thermal fluid parameters include multi-element thermal fluid flow rate, multi-element thermal fluid temperature, carbon dioxide composition, and nitrogen composition.

[0059] The output control coefficient is obtained by standardizing the multi-element thermal fluid flow rate, the multi-element thermal fluid temperature, and the components of carbon dioxide and nitrogen contained in the multi-element thermal fluid to obtain the output control coefficient.

[0060] F out =K mt ×ω mt +K ft ×ω ft +K N ×ω N +K CO ×ω CO ; Among them, F out Indicates the output control coefficient, K mt represents the normalized multivariate thermal fluid flow rate, K ft represents the temperature of the multivariate thermal fluid after normalization, K CO Indicates the amount of carbon dioxide after standardization, KN represents the amount of nitrogen gas after standardization, ω mt represents the weight of the multivariate thermal fluid flow, ω ft represents the weight of the temperature of the multivariate thermal fluid, ω CO represents the weight of the carbon dioxide content, ω N Represents the weight of the nitrogen component; the weights of the multi-component thermal fluid flow rate, multi-component thermal fluid temperature, carbon dioxide component, and nitrogen component are set to 0.375, 0.375, 0.125, and 0.125 respectively.

[0061] The standardization processing method of the multi-element thermal fluid flow rate and the multi-element thermal fluid temperature is the same as the standardization processing method of the working temperature above. At this time, the standardization processing is performed by obtaining the standard boundary range of the multi-element thermal fluid flow rate and the standard boundary range value of the multi-element thermal fluid temperature, and the corresponding weights are combined to determine how the values ​​of the corresponding working parameters increase and change.

[0062] The method of standardizing the carbon dioxide and nitrogen components is the same as that of the working pressure, and the processing is performed by obtaining the standard components of carbon dioxide and nitrogen.

[0063] At this time, the standard boundary range of the multi-element thermal fluid flow rate is 1 to 11.2 t / h; the standard boundary range of the multi-element thermal fluid temperature is 120 to 350°C; the standard component of carbon dioxide is 260m 3 / t, the standard composition of nitrogen is 1874m 3 / t.

[0064] For the gas output, the current output control coefficient can be compared with the average value in the historical data to determine whether normal output can be achieved at this time, so as to find the corresponding problem, identify the fault location at this time, and find treatment measures based on historical data.

[0065] As for the method of obtaining the fault location, a retrieval data set is formed by taking the input control coefficient, the output control coefficient and the working stability coefficient as retrieval conditions, wherein the input control coefficient, the output control coefficient and the working stability coefficient in the retrieval data set correspond one to one, and each coefficient corresponds to the same time point; the correspondence here needs to ensure that the coefficient identified at this time is calculated in the same set of data, and at the same time, the equipment and environment corresponding to each parameter need to be the same.

[0066] The matching degree between the retrieval data set and the historical data is calculated. When the matching degree is greater than the preset matching degree, the position of the working parameter corresponding to the retrieval data set is used as the output fault position.

[0067] The matching degree means using the input control coefficient, output control coefficient and working stability coefficient to compare and calculate with the historical data in turn, and obtaining the matching degree of the input control coefficient, the matching degree of the working stability coefficient and the matching degree of the output control coefficient respectively; the matching degree of the input control coefficient is to compare the input control coefficient with the change ratio related to the input control coefficient in the historical data, and calculate the Pearson correlation coefficient as the matching degree of the input control coefficient at this time; the matching degree of the output control coefficient is to compare the output control coefficient with the output control coefficient in the historical data, and use the Pearson correlation coefficient to calculate the matching degree of the output control coefficient; the matching degree of the working stability coefficient tends to be calculated using the moving average of the working stability coefficient, compare the moving average of the working stability coefficient with the moving average of the working stability coefficient in the historical data, and use the Pearson correlation coefficient to calculate the matching degree of the working stability coefficient. The moving average is selected by comparing the average value of the data every 15 minutes with the average value of the corresponding working stability coefficient in the historical data. The average value here is obtained by moving average, and finally the average value of the working stability coefficient is obtained.

[0068] At this time, the input control coefficient tends to obtain the corresponding integral values ​​of the instantaneous internal water flow, air flow, and gas flow, focusing on the change ratio of the working parameters in continuous time. The change ratio represents the ratio of each value of the input control coefficient in the historical data to the average value of the input control coefficient, to calculate whether the input control coefficient at this time is the same as the change trend of the historical data, so as to determine the fault location at this time.

[0069] The working stability coefficient tends to be more stable than the overall working stability, so the moving average method is used to calculate whether the data fluctuates every 15 minutes, and the corresponding fault location is found by taking the part with the same continuous value as the moving average in the historical data.

[0070] The output control coefficient tends to directly determine whether the output content meets the requirements. Therefore, the output control coefficient is directly compared with the output control coefficient in the historical data to determine whether there is a problem with the data output at this time, and the part with the problem is recorded as the fault location.

[0071] The preset matching degree mentioned above will be set to 0.8, 0.7, and 0.75 respectively according to the input control coefficient, output control coefficient, and working stability coefficient; to select whether there is data related to abnormal trends in historical data.

[0072] As for the method of obtaining treatment measures, according to the acquired fault location, the treatment plans corresponding to multiple matching degrees are selected, and the treatment plans corresponding to the maximum matching degrees are used as the output treatment measures; when the fault location is obtained, the historical data will set the treatment plans in the corresponding change trend. At this time, the corresponding treatment plans can be obtained by completing the matching degree calculation, and a group of treatment plans with the largest matching degree value are selected as the treatment measures used at this time.

[0073] In one embodiment of the present invention, the working adjustment module is used to obtain the parameter ratio and distribution amount of the working parameter according to the fault location of the working parameter, and set the adjustment factor of the working parameter according to the parameter ratio and distribution amount of the working parameter.

[0074] Parameter ratio indicates the relative relationship between operating parameters, usually expressed as the ratio of one parameter to other parameters.

[0075] In this module, the adjustment factor is determined according to the relative relationship and relative distribution of the working parameters. The distribution at this time will be expressed by the probability of the corresponding data, or the frequency of the parameter occurrence will be used to quantify the distribution. The relative relationship is the ratio between the working parameters with the same calculation unit. When the final output and the rated value are fixed, the value of the parameter ratio should also be a relatively fixed value. At this time, it is necessary to verify whether the calculated ratio is consistent with the expected value, to verify whether certain adjustments are needed at this time, to adjust the working condition of the current multi-element thermal fluid generator; the parameter ratio needs to verify the ratio of the corresponding working parameters in the working parameters when a fault occurs, so as to quantify the situation of the current fault location.

[0076] For example, the ratio of gas volume to air flow: It represents the ratio between gas volume and air flow at a certain moment, which is usually used to evaluate combustion efficiency.

[0077] Ratio of carbon dioxide flow to nitrogen flow: Indicates the ratio between carbon dioxide and nitrogen in the combustion products, used to evaluate the degree of completeness of combustion.

[0078] This type of parameter can be used to obtain the parameter ratio of the working parameters, and then evaluate the relative relationship between different working parameters.

[0079] The distribution at this time represents the value of the working parameter at different positions, so that the corresponding distribution can be obtained, that is, the distribution represents the frequency value of each working parameter in different time periods, and the corresponding adjustment amount is selected in combination with the frequency value and parameter ratio at this time.

[0080] Since the present invention focuses on the final output multi-component thermal fluid, the parameter ratio is expressed as a parameter ratio related to the flow rate; the parameter ratio is expressed as the ratio between the multi-component thermal fluid flow rate, air flow rate, gas flow rate, water flow rate, nitrogen component amount, and carbon dioxide component amount.

[0081] The adjustment factor is obtained by obtaining a first ratio value between the multi-element thermal fluid flow rate and the water flow rate, a second ratio value between the nitrogen component and the carbon dioxide component, and a third ratio value between the air flow rate and the gas flow rate; obtaining the distribution amounts corresponding to the first ratio value, the second ratio value, and the third ratio value, and calculating the adjustment factor of the working parameter.

[0082] The distribution amounts corresponding to the first ratio value, the second ratio value, and the third ratio value represent the frequency of occurrence of the corresponding combination of parameters during a fault. For example, the distribution amount of the second ratio value between the nitrogen component and the carbon dioxide component can represent the frequency of occurrence of the values ​​of the nitrogen component and the carbon dioxide component when taking the corresponding numerical values, and the distribution amounts corresponding to the three ratio values ​​are obtained in turn.

[0083] The adjustment factors are expressed as shown below.

[0084] Among them, AF is the adjustment factor, PV 1 Indicates the first ratio value, DQ 1 Indicates the distribution of the first proportional value, PV 2 Indicates the second ratio value, DQ 2 Indicates the distribution of the second proportional value, PV 3 Indicates the third ratio value, DQ 3 Indicates the distribution of the third ratio value, PV 1 ′ represents the standard value of the first proportional value, PV 2 ′ represents the standard value of the second ratio value, PV 3 ' represents the standard value of the third ratio value. At this time, the standard values ​​of the first ratio value, the second ratio value and the third ratio value are the average values ​​of the first ratio value, the second ratio value and the third ratio value in the historical data.

[0085] Based on the adjustment factor at this time, it can be determined that the system needs to adjust the current working parameters to the value set at this time, and adjust according to the corresponding content of this part combined with the subsequent processing method, so that the overall control of the system can better meet the use requirements.

[0086] In one embodiment of the present invention, the control action constraint module is used to predict the change of the working parameters according to the processing measures of the working parameters, and determine the control actions and constraint factors corresponding to the working parameters.

[0087] After selecting the treatment measures, determine the working parameters that need to be adjusted at this time, and combine the change trend of the current working parameters to predict the change value of the working parameters after the treatment measures are executed, as well as the control actions that need to be performed on the working parameters. The control action is expressed as the behavior of adjusting a certain working parameter in the treatment measures, and the constraint factor is expressed as a safety requirement, that is, the current working parameter cannot exceed the safety range set by the system after adjustment.

[0088] To predict the changes in working parameters, the predicted value of the final output can be analyzed in the form of a time series, and the predicted value can be compared with the safe range of the working parameters to obtain the constraint factor. The control action is to extract the behavior corresponding to the current constraint factor from the treatment measures.

[0089] The safety range here can be set according to the boundary range value and boundary value mentioned in the trend identification module. The output constraint factor will mark the working parameters, such as adding valid, invalid, valid, and invalid marks on different working parameter marks to determine which parameters in the working parameters can be adjusted at this time. The behavior on these adjustable parameters is regarded as control behavior; these marks are converted into specific constraint factors, such as how many values ​​are adjusted to reach the upper limit of temperature, the lower limit of pressure, and the flow range. The constraint factor at this time is the value of the corresponding working parameter selected for adjustment in the treatment measure; the control behavior is used to clarify which parameters can be safely adjusted and which parameters need to be paid attention to or avoided adjustment; the constraint factor is used to clarify the adjustment range limit after the treatment measure is implemented to prevent the adjustment range from being too large, resulting in system instability, or a large number of parameter values ​​exceeding the safety range, and limit the adjustment range of each implemented treatment measure.

[0090] Therefore, the implementation method for obtaining the control action and constraint factor at this time is to obtain the target parameter corresponding to the treatment measure of the working parameter, determine the target change of the target parameter after the treatment measure is implemented, compare the target change with the safety range of the working parameter, mark the compared target change, obtain the target mark, and select the control action and constraint factor of the working parameter according to the target mark; here, the target change is the adjustment range limit described in the constraint factor, which is used to determine whether the adjustment range exceeds the limit at this time; at the same time, the constraint factor selected at this time will include a judgment value in addition to the numerical value of the adjustment of the working parameter in the treatment measure. This judgment value is set by the target change. If the target change does not exceed the safety range, it is set to 1. If it exceeds the safety range, it is set to 0 to indicate that the constraint factor does not exist at this time.

[0091] The operation evaluation module is used to evaluate the working condition of the current multi-element thermal fluid generator according to the adjustment factor and the constraint factor, and obtain the evaluation result between the currently executed control action and the working parameters.

[0092] The evaluation results are obtained in the following way: recording the values ​​of adjustment factors and constraint factors over a period of time, and quantifying the evaluation results at corresponding time points to obtain the evaluation results between the currently executed control action and the working parameters; by recording the changes in the values ​​of the adjustment factors and constraint factors set by the working parameters in continuous time, it is possible to observe whether the current evaluation results have changed.

[0093] Where ξ represents the index value of the evaluation result, n represents the number of time points, i ranges from 1 to n, e represents the exponential constant, and AF i represents the adjustment factor at the i-th time point, AF′ represents the average value of the adjustment factor, and AF i+1 Indicates the adjustment factor at the i+1th time point; CF i represents the constraint factor at the i-th time point, CF′ represents the average value of the constraint factor, ε i It represents the judgment value corresponding to the constraint factor at the i-th time point. This judgment value is used to determine whether the value of the constraint factor selected at this time can be used as the value of the adjustment working parameter. If it can be adjusted, it is set to 1, and if it cannot be adjusted, it is set to 0; ε′ represents the average value of the judgment value corresponding to the constraint factor; ω 2 represents the weight of the adjustment factor, ω 1 Represents the weight of the constraint factor.

[0094] The current multi-element thermal fluid generator is detected and controlled according to the index value of the evaluation result, and the data is observed to see if there are any abnormalities. The data is transmitted to the external processing control center to monitor the status and problems of the current machine in real time, thereby completing the optimization processing of the machine-related devices.

[0095] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention and they are still covered by the protection scope of the present invention.

Claims

1. A multi-element thermal fluid generator system operation control system, characterized in that: include: A data acquisition module is used to collect the working parameters of the multi-element thermal fluid generator during operation, the working parameters including multi-element thermal fluid parameters, working pressure, working temperature, water flow, gas flow, and air flow; The trend recognition module is used to identify the change trend of working parameters at different positions. When the working parameters are in an abnormal state, the corresponding change trend of the working parameters is selected according to the type of abnormal state, and the fault location and treatment measures of the working parameters are determined according to the change trend; A working adjustment module, used for obtaining a parameter ratio and a distribution amount of the working parameter according to a fault position of the working parameter, and setting an adjustment factor of the working parameter according to the parameter ratio and the distribution amount of the working parameter; The control action constraint module is used to predict the change of the working parameters according to the processing measures of the working parameters, and determine the control actions and constraint factors corresponding to the working parameters; An operation evaluation module is used to evaluate the current working condition of the multi-element thermal fluid generator according to the adjustment factor and the constraint factor, and obtain the evaluation result between the currently executed control action and the working parameter; The trend identification module also includes the following: An input control unit is used to identify the changing trends of water flow, gas flow and air flow, and determine the input control coefficient of the multi-element thermal fluid generator; An operation control unit is used to identify the change trend of the working pressure and the working temperature, and obtain the working stability coefficient of the multi-element thermal fluid generator in normal operation; The output control unit is used to verify the multi-element thermal fluid parameters, determine the change trend of the multi-element thermal fluid parameters, and obtain the output control coefficient of the multi-element thermal fluid generator.

2. A multi-element thermal fluid generator system operation control system according to claim 1, characterized in that: The type of abnormal state is identified by comparing the current working parameters with the abnormal parameters, identifying the values ​​of the working parameters that exceed the preset safety range, and dividing the identified working parameters into the first parameter type, the second parameter type, and the third parameter type according to the location where the working parameters are obtained, wherein the first parameter type represents the parameters input in the working parameters, the second parameter type represents the parameters for stable operation of the system, and the third parameter type represents the parameters for the final output; the first parameter type, the second parameter type, and the third parameter type are processed in turn to obtain the fault location, and the processing measures are selected according to the values ​​of the working parameters; Among them, when it is the first parameter type, the input control unit is used to process the working parameters, judge the changing trends of water flow, gas flow and air flow in the working parameters, and obtain the input control coefficient related to the input; when it is the second parameter type, the operation control unit is used to process the working parameters, judge the changing trends of working pressure and working temperature in the working parameters, and obtain the working stability coefficient related to system stability; when it is the third parameter type, the output control unit is used to process the working parameters, judge the changing trends of multi-component thermal fluid parameters in the working parameters, and obtain the output control coefficient related to the multi-component thermal fluid output.

3. The multi-element thermal fluid generator system operation control system according to claim 1, characterized in that: The input control coefficient can be expressed as follows: the integral value of water flow, gas flow, and air flow is obtained, and the input control coefficient is calculated according to the integral value of water flow, gas flow, and air flow; F in =K w ×ω w +K g ×ω g +K a ×ω a ; Among them, F in Indicates the input control coefficient, K w Indicates the integral value of water flow, K g Indicates the integral value of the gas volume, K a Indicates the integral value of air flow; ω w represents the weight of water flow, ω g Represents the weight of the gas volume, ω a Indicates the weight of air flow.

4. The multi-element thermal fluid generator system operation control system according to claim 1, characterized in that: The working stability coefficient is obtained by sequentially obtaining the standard boundary value of the working pressure and the standard boundary range value of the working temperature, performing standard processing on the working pressure and the working temperature, and calculating the working stability coefficient; F sc =K p ×ω p +K tem ×ω tem ; Among them, F sc Indicates the working stability coefficient, K p Indicates the value of working pressure after standardization. Where p represents the value of working pressure, p′ represents the standard boundary value of working pressure; K tem Indicates the value of the working temperature after standardization. tem represents the value of operating temperature, tem max Indicates the upper limit of the standard boundary range of the operating temperature, tem min Indicates the lower limit of the standard boundary range of the operating temperature; ω p represents the weight of work pressure, ω tem Indicates the weight of the operating temperature.

5. The multi-element thermal fluid generator system operation control system according to claim 1, characterized in that: The multi-component thermal fluid parameters include multi-component thermal fluid flow rate, multi-component thermal fluid temperature, carbon dioxide composition, and nitrogen composition; The output control coefficient is obtained by normalizing the multi-element thermal fluid flow rate, the multi-element thermal fluid temperature, and the carbon dioxide and nitrogen components contained in the multi-element thermal fluid to obtain the output control coefficient; F out =K mt ×ω mt +K ft ×ω ft +K N ×ω N +K CO ×ω CO ; Among them, F out Indicates the output control coefficient, K mt represents the normalized multivariate thermal fluid flow rate, K ft represents the temperature of the multivariate thermal fluid after normalization, K CO Indicates the amount of carbon dioxide after standardization, K N represents the amount of nitrogen gas after standardization, ω mt represents the weight of the multivariate thermal fluid flow, ω ft represents the weight of the temperature of the multivariate thermal fluid, ω CO represents the weight of the carbon dioxide content, ω N Indicates the weight of the nitrogen component amount.

6. The multi-element thermal fluid generator system operation control system according to claim 1, characterized in that: As for the acquisition method of the fault location, the input control coefficient, the output control coefficient and the working stability coefficient are used as the search conditions to form a search data set; The matching degree between the retrieval data set and the historical data is calculated. When the matching degree is greater than the preset matching degree, the position of the working parameter corresponding to the retrieval data set is used as the output fault position.

7. A multi-element thermal fluid generator system operation control system according to claim 6, characterized in that: As for the method of obtaining the treatment measures, according to the acquired fault location, the treatment plans corresponding to the multiple matching degrees are selected, and the treatment plan corresponding to the maximum value of the multiple matching degrees is used as the output treatment measure.

8. The multi-element thermal fluid generator system operation control system according to claim 1, characterized in that: The adjustment factor is obtained by obtaining a first ratio value between the multi-element thermal fluid flow rate and the water flow rate, a second ratio value between the nitrogen component amount and the carbon dioxide component amount, and a third ratio value between the air flow rate and the gas flow rate; obtaining the distribution amount corresponding to the first ratio value, the second ratio value, and the third ratio value, and calculating the adjustment factor of the working parameter; The adjustment factors are expressed as shown below; Among them, AF represents the adjustment factor, PV1 represents the first proportion value, DQ1 represents the distribution amount of the first proportion value, PV2 represents the second proportion value, DQ2 represents the distribution amount of the second proportion value, PV3 represents the third proportion value, DQ3 represents the distribution amount of the third proportion value, PV1′ represents the standard value of the first proportion value, PV2′ represents the standard value of the second proportion value, and PV3′ represents the standard value of the third proportion value.

9. The multi-element thermal fluid generator system operation control system according to claim 1, characterized in that: The implementation method for obtaining control actions and constraint factors is to obtain the target parameters corresponding to the treatment measures of the working parameters, determine the target change of the target parameters after the treatment measures are implemented, compare the target change with the safety range of the working parameters, mark the compared target change to obtain the target mark, and select the control action and constraint factors of the working parameters according to the target mark.

10. The multi-element thermal fluid generator system operation control system according to claim 1, characterized in that: The evaluation results are obtained in the following way: recording the values ​​of adjustment factors and constraint factors over a period of time, and quantifying the evaluation results according to the corresponding time points to obtain the evaluation results between the currently executed control actions and the working parameters; Where ξ represents the index value of the evaluation result, n represents the number of time points, i ranges from 1 to n, e represents the exponential constant, and AF i represents the adjustment factor at the i-th time point, AF′ represents the average value of the adjustment factor, and AF i+1 Indicates the adjustment factor at the i+1th time point; CF i represents the constraint factor at the i-th time point, CF′ represents the average value of the constraint factor, ε i represents the judgment value corresponding to the constraint factor at the i-th time point; ε′ represents the average value of the judgment value corresponding to the constraint factor; ω2 represents the weight of the adjustment factor, and ω1 represents the weight of the constraint factor.

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