CN112412426A - Fracturing truck control method and device and fracturing truck - Google Patents
Fracturing truck control method and device and fracturing truck Download PDFInfo
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
- E21B43/25—Methods for stimulating production
- E21B43/26—Methods for stimulating production by forming crevices or fractures
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D29/00—Controlling engines, such controlling being peculiar to the devices driven thereby, the devices being other than parts or accessories essential to engine operation, e.g. controlling of engines by signals external thereto
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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- F02D31/001—Electric control of rotation speed
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B49/00—Control, e.g. of pump delivery, or pump pressure of, or safety measures for, machines, pumps, or pumping installations, not otherwise provided for, or of interest apart from, groups F04B1/00 - F04B47/00
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Abstract
The invention discloses a fracturing truck control method, a fracturing truck control device and a fracturing truck, wherein the fracturing truck control method comprises the following steps: acquiring current working condition parameters, wherein the current working condition parameters comprise current actual displacement and actual pressure; inquiring an optimal operation state database based on the current working condition parameters to obtain matched operation parameters of the current working condition parameters; and controlling the fracturing truck based on the current working condition parameters and the matched operation parameters. The invention has fast control speed and high energy efficiency of the whole machine.
Description
Technical Field
The invention relates to the technical field of fracturing truck control, in particular to a fracturing truck control method and device and a fracturing truck.
Background
The fracturing truck is a special vehicle for injecting high-pressure and large-discharge fracturing fluid into a well, fracturing a stratum and extruding a propping agent into a crack, is mainly used for various fracturing operations of oil, gas and water wells, and plays an important role in the exploitation operation of energy sources such as oil, gas and the like.
In the existing fracturing truck control method, the whole speed of an engine is generally increased to the maximum, and a hydraulic pump and a hydraulic motor are regulated and controlled at the same time. The control method can cause that the engine cannot run in the optimal state under the set power, the hydraulic system can also be in a subnormal state, so that a large amount of energy cannot be output as useful energy, but only can be output in the form of heat energy, and the efficiency of the whole machine is reduced.
Disclosure of Invention
The invention solves the problem that the overall efficiency of the existing fracturing truck control method is too low.
In order to solve the problems, the invention provides a fracturing truck control method, which comprises the following steps:
acquiring current working condition parameters, wherein the current working condition parameters comprise current actual displacement and actual pressure;
inquiring an optimal operation state database based on the current working condition parameters to obtain matched operation parameters of the current working condition parameters;
and controlling the fracturing truck based on the current working condition parameters and the matched operation parameters.
Optionally, the fracturing truck control method further includes:
acquiring a historical construction data set;
analyzing the historical construction data set based on a preset machine learning algorithm to obtain optimal operation state parameters, and forming the optimal operation state database by a plurality of optimal operation state parameters.
Optionally, the querying an optimal operating state database based on the current operating condition parameters, and obtaining the matching operating parameters of the current operating condition parameters includes:
and obtaining an optimal operation state parameter with lowest energy consumption, wherein the difference between the pressure and the actual pressure is smaller than a first preset value, the difference between the displacement and the actual displacement is smaller than a second preset value, and the optimal operation state parameter is the matching operation parameter of the current working condition parameter.
Optionally, the controlling the fracturing truck based on the current operating condition parameters and the matched operating parameters includes:
acquiring a first oil consumption value corresponding to the current working condition parameter and a second oil consumption value corresponding to the matched operation parameter;
and when the first oil consumption value is larger than the second oil consumption value and the difference value between the first oil consumption value and the second oil consumption value is larger than a third preset value, controlling the fracturing truck according to the matched operation parameters.
Optionally, the controlling the fracturing truck according to the matched operating parameters includes:
obtaining the matched displacement from the matched parameters;
when the actual displacement is not equal to the matching displacement and the difference between the actual displacement and the matching displacement is greater than a fourth preset value, adjusting the current of a hydraulic pump and a hydraulic motor based on the difference between the actual displacement and the matching displacement.
Optionally, after controlling the fracturing truck according to the matched operating parameters, the method further includes:
acquiring signal feedback of each part of the fracturing truck;
judging whether the running state of the fracturing truck reaches the running state corresponding to the matched running parameters or not based on the signal feedback of each component;
and if the running state of the fracturing truck does not reach the running state corresponding to the matched running parameters after the preset duration, outputting an abnormal prompt signal.
Optionally, the analyzing the historical construction data set based on a preset machine learning algorithm to obtain an optimal operating state parameter further includes:
performing cluster analysis on the historical construction data set by taking pressure, discharge capacity and oil consumption as variables to obtain multi-cluster working condition data;
calculating the average value of oil consumption of each cluster of working condition data;
and respectively determining the optimal running state parameters from the working condition data of each cluster based on the average oil consumption value of the working condition data of each cluster.
The invention also provides a fracturing truck control device, which comprises:
the system comprises an acquisition unit, a control unit and a control unit, wherein the acquisition unit is used for acquiring current working condition parameters, and the current working condition parameters comprise current actual displacement and actual pressure;
the optimizing unit is used for inquiring an optimal operation state database based on the current working condition parameters to obtain matched operation parameters of the current working condition parameters;
and the control unit is used for controlling the fracturing truck based on the current working condition parameters and the matched operation parameters.
The invention also provides a fracturing truck control device, which comprises a computer readable storage medium and a processor, wherein the computer readable storage medium is used for storing a computer program, and the computer program is read by the processor and runs to realize the fracturing truck control method.
The invention further provides a fracturing truck which comprises the fracturing truck control device.
The optimal running state parameter with the lowest energy consumption is used as the matching running parameter of the current working condition parameter by finding that the pressure is close to the actual pressure, the discharge capacity is close to the actual discharge capacity and the optimal running state parameter with the lowest energy consumption is used for the control of the fracturing truck in the follow-up control, so that the running state of each component of the fracturing truck at least can reach the historical optimal state at present, the higher overall efficiency is ensured, the energy is saved, the query process is simple, the speed for obtaining the optimal running state parameter is higher, and the rapid adjustment can be further carried out.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a fracturing truck control method of the present invention;
FIG. 2 is a schematic diagram of another embodiment of the fracturing truck control method of the present invention;
FIG. 3 is a state diagram of an energy saving and consumption reduction algorithm in the fracturing truck control method of the invention;
fig. 4 is a schematic view of a fracturing truck control device according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
In the field application process of the equipment, the actual bottom structure is different from the actual displacement input, and the power output by the whole machine is different. Therefore, in the actual use process of the fracturing truck, under the condition that the net power output by the complete machine is constant, the more useless work the complete machine does, the lower the efficiency of the complete machine is. The power source engine has different efficiencies in different rotating speeds and load operation intervals, and the efficiency and the speed of heat loss generated under different flow rates are different in the process of transmitting energy by the power transmission part, namely the hydraulic pump and the motor. The normal operation of the whole machine mainly comprises the matched operation of various parts, if the parameters of the operation process of the whole machine are well matched, the efficiency of the whole machine is greatly improved, the engine works in an optimal working area, a hydraulic system is in an optimal thermal balance state, and the aim of saving energy can be fulfilled. Therefore, the invention provides a control method which enables the whole machine to operate in a state that the operation parameters of all parts are well matched as much as possible.
The invention provides a fracturing truck control method.
Referring to fig. 1, in an embodiment of the fracturing truck control method of the present invention, the fracturing truck control method includes:
step S10, obtaining current working condition parameters, wherein the current working condition parameters comprise current actual displacement and actual pressure;
the current actual displacement is the current actual displacement value of the fracturing truck, and the actual pressure is the current actual pressure value of the fracturing truck.
Step S20, inquiring an optimal operation state database based on the current working condition parameters to obtain matching operation parameters of the current working condition parameters;
and the optimal operation state database is obtained based on the analysis of the historical construction data set, and the operation state data with the lowest energy consumption under different working conditions are stored in the optimal operation state database. Along with fracturing unit truck is constantly used, can produce more construction data, based on the construction data that continuously increases, can constantly optimize optimum operating parameter, complete machine efficiency also improves gradually.
The optimal operating state database may be stored in the form of a typical condition optimal operating data table. During actual construction, typical working conditions are limited, so that the speed of an optimization process (i.e. a process of querying an optimal running state database based on current working condition parameters) is high, the optimal running state parameters can be obtained as soon as possible, corresponding control is executed, and quick control is realized.
Optionally, the fracturing truck control method further includes: acquiring a historical construction data set; analyzing the historical construction data set based on a preset machine learning algorithm to obtain optimal operation state parameters, and forming the optimal operation state database by a plurality of optimal operation state parameters.
The historical construction database can be constructed and used for storing historical construction data, and the historical construction data set is historical construction data stored in the historical construction database. Each construction data at least comprises construction pressure, construction displacement and engine oil consumption ratio, and also comprises main system oil pressure, overall efficiency, number of engines, engine speed, engine load and fan speed.
Optionally, the analyzing the historical construction data set based on a preset machine learning algorithm to obtain an optimal operating state parameter includes: performing cluster analysis on the historical construction data set by taking pressure, discharge capacity and oil consumption as variables to obtain multi-cluster working condition data; calculating the average value of oil consumption of each cluster of working condition data; and respectively determining the optimal running state parameters from the working condition data of each cluster based on the average oil consumption value of the working condition data of each cluster.
The cluster analysis may use a kmeans algorithm and/or a DBSCAN algorithm, among others. Clustering analysis is carried out, working condition data with the same/similar pressure, discharge capacity and oil consumption are clustered into a cluster, the working condition data in one cluster is equivalent to the working condition data under one working condition, and the working condition data in one cluster comprises one or more pieces of working condition data.
Clustering working condition data with the same/similar pressure, displacement and oil consumption into a cluster, and calculating the average value of the oil consumption of the cluster of data to represent the oil consumption state of the cluster of working condition data. Determining an optimal operation state parameter from the cluster working condition data respectively based on the average value of the oil consumption of the cluster working condition data, firstly determining the optimal working condition parameter, then determining the operation state parameter corresponding to the optimal working condition parameter as the optimal operation state parameter, wherein the optimal working condition parameter comprises pressure, discharge capacity and oil consumption, the optimal operation state parameter comprises hydraulic pump current, motor current, engine rotating speed, number of engines, fan rotating speed and the like, and finally storing the optimal working condition parameter and the optimal operation state parameter into an optimal operation state database together. Specifically, the working condition data of the upper and lower preset intervals (such as upper and lower 5%) of the average value of the oil consumption can be used as the optimal working condition parameters, and the front N pieces of working condition data with the lowest oil consumption can be taken from the working condition data of the upper and lower preset intervals of the average value of the oil consumption as the optimal working condition parameters, wherein N can be 3.
In one embodiment, displacement, pressure and oil consumption are used as variable data, wherein the oil consumption is used as label data, a kmeans function and a DBSCAN function are called through a cluster analysis algorithm to perform cluster analysis, the number of classification clusters is defined according to the typical working condition number, 6 noise points can be adopted, working condition data with the same pressure, displacement and oil consumption are divided into one cluster, each cluster is working condition data with the same or similar working conditions, the oil consumption data are analyzed by taking the cluster as a unit, and then the optimal operation state parameter with the lowest oil consumption under each working condition is quickly found.
The method comprises the steps of firstly carrying out cluster analysis on historical construction data to obtain a plurality of classification clusters so as to distinguish different working conditions, then calculating the average value of oil consumption of the working condition data of each cluster, and respectively determining the optimal running state parameters in the working condition data of each cluster based on the average value of the oil consumption, so that the data processing efficiency can be improved, the learning efficiency can be improved, the optimal running state parameters can be quickly determined, and an optimal running state database can be formed.
Optionally, step S20 includes:
and obtaining an optimal operation state parameter with lowest energy consumption, wherein the difference between the pressure and the actual pressure is smaller than a first preset value, the difference between the displacement and the actual displacement is smaller than a second preset value, and the optimal operation state parameter is the matching operation parameter of the current working condition parameter.
And traversing and screening in a best operation state database based on the actual displacement and the actual pressure, and searching a best operation state parameter with the lowest energy consumption, which is the same as or similar to the actual displacement and the actual pressure, as a matching operation parameter of the current working condition parameter.
The optimal operation state parameters which are the same as or similar to the actual discharge capacity and the actual pressure, namely the optimal operation state parameters which are the same as or similar to the actual working conditions are screened out from the optimal operation state database to be used as matching operation parameters, so that the obtained matching operation parameters can be effectively applied to the current actual working conditions, and further energy conservation and efficiency improvement are guaranteed.
And step S30, controlling the fracturing truck based on the current working condition parameters and the matched operation parameters.
Specifically, the current working condition parameters and the matched operation parameters can be compared, relatively better parameters are determined, and the relatively better parameters are used as control parameters of the fracturing truck. If the energy/efficiency status of the current working condition parameter is more optimal, maintaining the current control state; and if the matched operation parameters are more optimal, switching to control the fracturing truck according to the matched operation parameters.
After step S30, the method may return to step S10 at a preset time interval for timing optimization. And in consideration of the possibility of the change of the current working condition parameters, the current working condition parameters are obtained again at certain intervals, and the current working condition parameters are optimized in the optimal running state database based on the latest obtained current working condition parameters.
When the fracturing truck is controlled, the control target is realized by adjusting relevant parameters of an engine, the current of a hydraulic pump, the current of a motor and the like.
By utilizing a machine learning technology, big data analysis is carried out on historical construction data, the running state parameter with the highest overall efficiency under different discharge capacities and pressures is found, and corresponding control is carried out based on the running state parameter with the highest overall efficiency, so that the aims of rapid control and energy conservation are fulfilled. Specifically, the optimal running state parameter with the pressure close to the actual pressure, the discharge capacity close to the actual discharge capacity and the lowest energy consumption is searched in the optimal running state database and serves as the matching running parameter of the current working condition parameter, so that the optimal running state parameter obtained based on historical construction data in the subsequent control is applied to the fracturing truck control, the running states of all components of the fracturing truck at present can at least reach the historical optimal state, the high overall efficiency is guaranteed, energy is saved, the query process is simple, the speed for obtaining the optimal running state parameter is high, and the rapid adjustment can be carried out.
Optionally, step S30 includes:
step S31, acquiring a first oil consumption value corresponding to the current working condition parameter and a second oil consumption value corresponding to the matched operation parameter;
and step S32, when the first oil consumption value is larger than the second oil consumption value and the difference value between the first oil consumption value and the second oil consumption value is larger than a third preset value, controlling the fracturing truck according to the matching operation parameters.
And judging which of the current working condition parameters and the matched operation parameters is more optimal based on the oil consumption value. When the first oil consumption value is larger than the second oil consumption value and the difference value between the first oil consumption value and the second oil consumption value is larger than a third preset value, the oil consumption of the current working condition parameter is larger, the larger amplitude is not low, the fracturing truck is controlled according to the matched operating parameters, and a better operating state can be obtained, so that the fracturing truck is controlled according to the matched operating parameters. When the first oil consumption value is smaller than the second oil consumption value, or although the first oil consumption value is larger than the second oil consumption value, the difference value between the first oil consumption value and the second oil consumption value is smaller than or equal to a third preset value, the running state corresponding to the current working condition parameter is not worse than the running state corresponding to the matched running parameter, and at the moment, the energy-saving purpose can be realized by maintaining the current control state.
The third preset value can be selected as m% of the second fuel consumption value, wherein the value range of m is 4-6.
When the oil consumption value corresponding to the current working condition parameter is larger and the large amplitude is not low, the fracturing truck is controlled according to the matched operating parameter so as to control the fracturing truck according to a better operating state parameter, and further the fracturing truck always operates according to a better operating state parameter, so that a smaller loss rate is kept, and the energy-saving target is realized.
Optionally, the controlling the fracturing truck according to the matched operating parameters in step S32 includes:
step S320, obtaining the matched displacement from the matching parameters;
at the moment, the matched discharge capacity is equivalent to the set discharge capacity of the fracturing truck and is the discharge capacity target of the fracturing truck at the moment.
And S321, when the actual displacement is not equal to the matched displacement and the difference between the actual displacement and the matched displacement is greater than a fourth preset value, adjusting the currents of a hydraulic pump and a hydraulic motor based on the difference between the actual displacement and the matched displacement.
The fourth preset value can be selected as j% of the matched displacement, wherein the value range of j is 4-6.
When the actual displacement is larger than the matched displacement and the difference value between the actual displacement and the matched displacement is larger than a fourth preset value, adjusting the current of the hydraulic pump and the hydraulic motor to reduce the actual displacement so as to approach the matched displacement; and when the actual displacement is smaller than the matched displacement and the difference value between the actual displacement and the matched displacement is larger than a fourth preset value, adjusting the current of the hydraulic pump and the hydraulic motor to enable the actual displacement to rise so as to approach the matched displacement.
And if the actual displacement is larger than or smaller than the matched displacement, but the difference value between the actual displacement and the matched displacement is smaller than a fourth preset value, the current of the hydraulic pump and the hydraulic motor does not need to be adjusted.
Optionally, before step S320, performing: acquiring the actual rotating speed of the engine, and acquiring the matched rotating speed of the engine from the matched operating parameters; and when the actual rotating speed of the engine is not equal to the matching rotating speed of the engine and the difference value between the actual rotating speed of the engine and the matching rotating speed of the engine is greater than a fifth preset value, adjusting the rotating speed of the engine to enable the actual rotating speed of the engine to approach the matching rotating speed of the engine. Specifically, when the actual rotating speed of the engine is greater than the engine matching rotating speed and the difference value between the actual rotating speed of the engine and the engine matching rotating speed is greater than a fifth preset value, the actual rotating speed of the engine is reduced; and when the actual rotating speed of the engine is less than the matching rotating speed of the engine and the difference value between the actual rotating speed of the engine and the matching rotating speed of the engine is greater than a fifth preset value, the actual rotating speed of the engine is increased. Wherein, the fifth preset value can be selected as 10 revolutions.
To facilitate understanding, given an embodiment, as shown in fig. 2, the fracturing truck control method comprises:
firstly, judging whether the mode is an automatic energy-saving mode;
if the fracturing truck is in the automatic energy-saving mode, acquiring matched operation parameters after the fracturing truck is controlled according to the matched operation parameters;
and judging whether the actual rotating speed of the engine is not equal to the matching rotating speed and the difference value between the actual rotating speed and the matching rotating speed is greater than T (namely a fifth preset value), if so, adjusting the rotating speed of the engine, and if so, reducing the rotating speed of the engine, and if so, increasing the rotating speed of the engine.
Judging whether the actual displacement is less than 0.95 of the matched displacement;
if the actual displacement is less than the matched displacement by 0.95, judging whether the pump current is greater than the maximum current; when the pump current is larger than the maximum current, further judging whether the motor current is larger than the maximum current, and when the motor current is larger than the maximum current, setting the motor current as the motor maximum current; when the pump current is less than or equal to the maximum current, increasing the pump current, and specifically making the pump set current equal to the current actual pump current + displacement deviation K;
if the actual displacement is greater than or equal to the matched displacement 0.95, judging whether the actual displacement is greater than the matched displacement 1.05 or not; when the actual displacement is larger than the matched displacement by 1.05, judging whether the motor current is smaller than the minimum current or not; when the motor current is not less than the minimum current, reducing the motor current, and enabling the motor set current to be the current actual motor current-displacement deviation K; when the motor current is smaller than the minimum current, judging whether the pump actual current is smaller than the minimum current or not, when the pump actual current is smaller than the minimum current, making the pump set current be the pump minimum current, and when the pump actual current is not smaller than the minimum current, making the pump set current be the pump actual current-displacement deviation K.
And if the actual displacement is smaller than the matched displacement x 0.95, manually setting a parameter table, and executing the steps of judging whether the actual displacement is smaller than the matched displacement x 0.95 and the subsequent steps.
The current of the hydraulic pump and the hydraulic motor is adjusted through the difference value between the actual discharge capacity and the matched discharge capacity, so that the actual running state of the fracturing pump approaches to the matched running parameter, the fracturing truck runs in a state with lower energy consumption, and the efficiency of the whole machine is improved.
Optionally, step S32 is followed by:
step S33, acquiring signal feedback of each part of the fracturing truck;
the components include, but are not limited to, a hydraulic pump, a hydraulic motor, an engine and a fracturing pump, and the signal feedback of the components includes, but is not limited to, the fuel consumption of the engine, the functional parameters of the engine, the current of a control hydraulic system and the rotating speed of the fracturing pump.
Step S34, judging whether the running state of the fracturing truck reaches the running state corresponding to the matched running parameters or not based on the signal feedback of each component;
and step S35, if the running state of the fracturing truck does not reach the running state corresponding to the matched running parameters after the preset duration, outputting an abnormal prompt signal.
Because the running state corresponding to the matched running parameter comprises the state parameters of each part, in the process of adjusting the fracturing truck according to the matched running parameter, the fracturing truck reaches the running state corresponding to the matched running parameter after a certain time in a normal state. For example, in the operating state parameters corresponding to the matched operating parameters, when the motor current reaches C, the main system oil pressure is H, and in a normal case, in the process of adjusting the fracturing truck according to the matched operating parameters, when the motor current reaches C, the main system oil pressure will also reach H, but if the trip is abnormal, when the motor current is 2C, the main system oil pressure reaches H, it is indicated that there is an abnormality, and at this time, an abnormality prompt signal is output.
The state parameters fed back by each component are received in real time after the component is controlled to the corresponding running state according to the matched running parameters, if the corresponding running state of the matched running parameters is not reached all the time, the component is indicated to be abnormal, an abnormal prompt signal is output to remind people to check and solve, so that the fracturing truck enters the normal running state as soon as possible, the energy loss caused by abnormality is avoided, and the purpose of saving energy is achieved.
Alternatively, in order to facilitate understanding of the present invention, an embodiment is further provided, and referring to fig. 3, the fracturing truck control method includes:
s1, constructing a historical construction database.
Each piece of construction data in the historical construction database at least comprises construction pressure, construction displacement and engine oil consumption ratio, and also comprises one or more of main system oil pressure, overall efficiency, the number of engines, engine rotating speed and engine load.
And S2, performing big data analysis on the historical construction database through a machine learning algorithm, searching optimal operation state data under different working conditions, and generating an optimal operation data table under typical working conditions.
The method comprises the steps of setting up a big data analysis platform to carry out big data analysis on historical construction data, searching for operation state parameters with the highest fuel efficiency of the whole machine in the historical construction data through the big data analysis platform, generating a typical working condition optimal operation data table, wherein the typical working condition optimal operation data table stores the optimal operation state parameters under different working conditions, and the typical working condition optimal operation data table can iterate step by step and the data accuracy can increase step by step as historical construction data samples increase. During actual construction, typical working conditions are limited, so that the speed of the optimization process is high, and the optimal running state parameters can be obtained as soon as possible to execute corresponding control and realize quick control.
And S3, periodically carrying out big data analysis on the latest running state parameters, searching for a relatively optimal working condition, and continuously perfecting an optimal running data table under a typical working condition.
As time goes on, construction data can be continuously increased, new operation state parameters can be obtained, in order to fully utilize the latest data, a big data analysis sample is increased, big data analysis is regularly carried out on the latest operation state parameters, and an optimal operation data table under typical working conditions is continuously perfected.
And S4, according to the current working condition parameters, carrying out timing optimization in the typical working condition optimal operation data table to obtain the optimal operation state parameters corresponding to the current working condition parameters, wherein the timing optimization refers to reacquiring the current working condition parameters at intervals of a certain time, and carrying out optimization in the typical working condition optimal operation data table based on the latest obtained current working condition parameters.
And traversing and sectionally screening the optimal operation data table under the typical working condition based on the current working condition parameters in each optimization process, and screening the first N operation state parameters with the lowest energy consumption. And under the manual energy-saving mode, the user selects the optimal running state parameter under the corresponding displacement. And in the automatic energy-saving mode, the fracturing truck control device automatically determines the optimal running state parameters according to the rule of 'the current pressure, the discharge capacity is similar and the energy consumption is lowest'.
S5, comparing the energy consumption value corresponding to the selected optimal operation state parameter with the actual energy consumption value corresponding to the current operation state parameter, and if the energy consumption value corresponding to the selected optimal operation state parameter is larger than the actual energy consumption value or the energy consumption value corresponding to the optimal operation state parameter is smaller than the actual energy consumption value by less than 5%, taking the current operation state parameter of the fracturing truck as the optimal operation state parameter and directly operating with the current operation state parameter; if the energy consumption value corresponding to the selected optimal operation state parameter is less than the actual energy consumption value by more than 5 percent (including 5 percent), the fracturing truck is switched to control operation based on the optimal operation state parameter, the deviation between the actual displacement and the displacement under the optimal working condition is calculated in real time, when the displacement deviation is within the range of plus or minus 5 percent, current inching adjustment is carried out on the hydraulic pump or the hydraulic motor (the hydraulic pump is adjusted firstly, and the motor parameter is adjusted only when the current of the hydraulic pump reaches the maximum), the operation state of the transmitter, and the currents of the hydraulic pump and the hydraulic motor are adjusted, and finally the preset current is reached.
S6, the output displacement and pressure parameters of the fracturing pump are detected through a hydraulic pump, a hydraulic motor driving part, engine bus interface hardware, and the engine fuel consumption and the engine function parameters in the running state process are read in real time, the current of a hydraulic system and the rotating speed of the fracturing pump are controlled, and state signal feedback is provided for the adjusting process; if the optimal working condition state is not achieved in the running process of the whole machine, the system can automatically analyze and prompt for abnormality, and optionally, abnormal parts can be prompted.
The invention further provides a fracturing truck control device. In an embodiment of the present invention, the fracturing truck control device includes:
the system comprises an acquisition unit, a control unit and a control unit, wherein the acquisition unit is used for acquiring current working condition parameters, and the current working condition parameters comprise current actual displacement and actual pressure;
the optimizing unit is used for inquiring an optimal operation state database based on the current working condition parameters to obtain matched operation parameters of the current working condition parameters;
and the control unit is used for controlling the fracturing truck based on the current working condition parameters and the matched operation parameters.
The invention further provides a fracturing truck control device. As shown in fig. 4, in an embodiment of the fracturing truck control device of the present invention, the fracturing truck control device includes: a computer readable storage medium and a processor storing a computer program which, when read and executed by the processor, implements a fracturing truck control method as in any of the above.
The invention further provides a fracturing truck which comprises the fracturing truck control device.
Although the present invention has been disclosed above, the scope of the present invention is not limited thereto. Various changes and modifications may be made by those skilled in the art without departing from the spirit and scope of the invention, and these changes and modifications are intended to be within the scope of the invention.
Claims (10)
1. A fracturing truck control method is characterized by comprising the following steps:
acquiring current working condition parameters, wherein the current working condition parameters comprise current actual displacement and actual pressure;
inquiring an optimal operation state database based on the current working condition parameters to obtain matched operation parameters of the current working condition parameters;
and controlling the fracturing truck based on the current working condition parameters and the matched operation parameters.
2. The fracturing truck control method of claim 1, further comprising:
acquiring a historical construction data set;
analyzing the historical construction data set based on a preset machine learning algorithm to obtain optimal operation state parameters, and forming the optimal operation state database by a plurality of optimal operation state parameters.
3. The fracturing truck control method of claim 1, wherein said querying an optimal operating state database based on said current operating condition parameters, obtaining matching operating parameters for said current operating condition parameters comprises:
and obtaining an optimal operation state parameter with lowest energy consumption, wherein the difference between the pressure and the actual pressure is smaller than a first preset value, the difference between the displacement and the actual displacement is smaller than a second preset value, and the optimal operation state parameter is the matching operation parameter of the current working condition parameter.
4. The fracturing truck control method of any one of claims 1 to 3, wherein said controlling the fracturing truck based on the current operating condition parameters and the matched operating parameters comprises:
acquiring a first oil consumption value corresponding to the current working condition parameter and a second oil consumption value corresponding to the matched operation parameter;
and when the first oil consumption value is larger than the second oil consumption value and the difference value between the first oil consumption value and the second oil consumption value is larger than a third preset value, controlling the fracturing truck according to the matched operation parameters.
5. The fracturing truck control method of claim 4, wherein said controlling the fracturing truck in accordance with the matched operating parameters comprises:
obtaining the matched displacement from the matched parameters;
when the actual displacement is not equal to the matching displacement and the difference between the actual displacement and the matching displacement is greater than a fourth preset value, adjusting the current of a hydraulic pump and a hydraulic motor based on the difference between the actual displacement and the matching displacement.
6. The fracturing truck control method of claim 5, wherein after controlling the fracturing truck in accordance with the matched operating parameters, further comprising:
acquiring signal feedback of each part of the fracturing truck;
judging whether the running state of the fracturing truck reaches the running state corresponding to the matched running parameters or not based on the signal feedback of each component;
and if the running state of the fracturing truck does not reach the running state corresponding to the matched running parameters after the preset duration, outputting an abnormal prompt signal.
7. The fracturing truck control method of claim 2, wherein said analyzing said historical construction data set based on a preset machine learning algorithm to obtain optimal operating condition parameters further comprises:
performing cluster analysis on the historical construction data set by taking pressure, discharge capacity and oil consumption as variables to obtain multi-cluster working condition data;
calculating the average value of oil consumption of each cluster of working condition data;
and respectively determining the optimal running state parameters from the working condition data of each cluster based on the average oil consumption value of the working condition data of each cluster.
8. A fracturing truck control apparatus, comprising:
the system comprises an acquisition unit, a control unit and a control unit, wherein the acquisition unit is used for acquiring current working condition parameters, and the current working condition parameters comprise current actual displacement and actual pressure;
the optimizing unit is used for inquiring an optimal operation state database based on the current working condition parameters to obtain matched operation parameters of the current working condition parameters;
and the control unit is used for controlling the fracturing truck based on the current working condition parameters and the matched operation parameters.
9. A fracturing truck control apparatus comprising a computer readable storage medium storing a computer program and a processor, the computer program being read and executed by the processor to implement the fracturing truck control method of any one of claims 1 to 7.
10. A fracturing truck comprising the fracturing truck control of claim 9.
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