CN104635704A - Ship energy efficiency management and control platform and method based on fuzzy clustering and genetic algorithm - Google Patents

Abstract

The invention provides a ship energy efficiency management and control platform based on fuzzy clustering and a genetic algorithm. The ship energy efficiency management and control platform comprises a sensor group, a lower computer system and an upper computer system, wherein the upper computer system comprises an upper computer communication module, a data storage module, a data processing module and a ship energy efficiency comprehensive management and control module; the data processing module is used for calling parameters in the data storage module, resolving all the received parameters and providing the resolved parameters to the ship energy efficiency comprehensive management and control module; the ship energy efficiency comprehensive management and control module is used for computing the current energy efficiency operation index of a ship in real time based on fuzzy clustering and the genetic algorithm by using the resolved parameters in order to provide references for a ship operator; through the system, optimal navigational speed, power supply form and load working state of the ship can be determined, and control commands can be output automatically. According to the ship energy efficiency management and control platform, the energy consumption state of the ship can be monitored in real time, the influences of environmental factors on the energy consumption of the ship can be eliminated or lowered, and the irrationality of the navigational speed can be set in advance, so that the aims of saving energy and reducing emission are fulfilled.

Description

Based on boats and ships energy efficiency management parametric controller and the method for fuzzy clustering and genetic algorithm

Technical field

The present invention relates to boats and ships energy efficiency monitoring and lift technique field, particularly relate to a kind of boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm and method.

Background technology

Along with global warming and CO ₂the increase of greenhouse gas emission; " MARPOL " (MARPOL pact) supplemental provisions VI contracting party adopted unanimously in Marine Environmental Protection Committee's the 62nd meeting on July 15th, 2011, indicated that the Global Green House Gas Emissions Reduction regulation enforcing effect that has of world's stem professional has been born.Shipping business faces increasing energy-saving and emission-reduction pressure, and how taking rational measure to improve boats and ships efficiency, reduce discharge is shipping business problem demanding prompt solution.International Maritime Organization (IMO) (IMO) has formulated Energy design index (EEDI) and efficiency operation index (EEOI) evaluation index, manages two aspects to explore the effective way improving boats and ships efficiency respectively from design and running.Boats and ships due to the impact by environment, make boats and ships deviate from best operating point, thus make boats and ships most time operate in the lower state of efficiency in the process of navigation.In addition, deck officer cannot obtain the current power consumption state information of boats and ships intuitively in the process of operation, is in most cases control boats and ships by rule of thumb to run under the set speed of a ship or plane, not only reduces the economy of boats and ships and add CO ₂discharge.

Summary of the invention

The technical problem to be solved in the present invention is: provide a kind of boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm and method, the power consumption state of Real-Time Monitoring boats and ships, and eliminate or reduce environmental factor to the impact of boats and ships energy consumption, avoid the irrationality presetting the speed of a ship or plane, thus reach the object of energy-saving and emission-reduction.

The present invention for solving the problems of the technologies described above taked technical scheme is: a kind of boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm, is characterized in that: it comprises:

Sensor group, for gathering the parameter needed for control;

Lower computer system, comprise data acquisition module and slave computer communication module, data acquisition module is for gathering discrete type parameter, obtaining the parameter of sensor group collection, and slave computer communication module is used for all parameters all being uploaded, receiving control command and send to corresponding topworks;

Master system, comprises Upper machine communication module, data memory module, data processing module and boats and ships efficiency integrated management control module; Upper machine communication module for receive slave computer communication module and upload all parameters, send control command to slave computer communication module; Data memory module is used for all parameters to store; Data processing module is used for parameter in calling data memory module, all Parameter analysis of electrochemicals received are supplied to boats and ships efficiency integrated management control module; Boats and ships efficiency integrated management control module is for utilizing the parameter after parsing, based on fuzzy clustering and genetic algorithm, the efficiency operation index that real-time Ship ' is current, determines the duty of the optimum speed of boats and ships, power-supplying forms and load, and can automatic output control order.

By such scheme, described master system also comprises man-machine interface, for show all parameters and the current efficiency operation index of boats and ships, data memory module is provided call port and input of control commands.

By such scheme, described sensor group comprises fuel consume sensor, torque speed sensor, wind speed wind direction sensor, speed of a ship or plane heading sensor, water velocity sensor, host parameter sensor, electrical network parameter sensor group and water depth sensor.

By such scheme, between described Upper machine communication module and slave computer communication module, comprise three kinds of communication type: the next two CAN communication, serial communication and upper pair of Redundant Ethernet communication; The next two CAN communication is by CAN mouth server unified collection discrete type parameter and communication is uploaded to host computer; The parameter that the sensor group that serial communication gathers each port by serial server gathers, by gathering next all Parameter Mappings to Ethernet in CAN mouth server and serial server, for host computer system access.

Utilize the control method that the above-mentioned boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm realizes, it is characterized in that: utilize all parameters collected, the method of fuzzy clustering is taked to carry out cluster analysis to navigation environment, and the dynamic response relation of operation of ship index and navigation environment is obtained by the method for Multiple Non-linear Regression Analysis, minimum for target with operation of ship index, take engine speed as optimized variable, to meet the power demand of full ship for constraint, genetic algorithm is taked to carry out dynamic optimization, determine the main frame optimum speed under different navigation environment, the duty of power-supplying forms and load, automatic output control order.

As stated above, described all parameters comprise oil consumption, moment of torsion rotating speed, wind speed and direction, speed of a ship or plane course, water velocity and bathymetric data.

As stated above, the method also comprises man-machine interface and manual mode,

Man-machine interface for show all parameters and the current efficiency operation index of boats and ships, data memory module is provided call port and input of control commands;

Under manual mode, the all parameters shown according to man-machine interface by operating personnel and the current efficiency of boats and ships are operated index, determine the duty of the main frame optimum speed under different navigation environment, power-supplying forms and load, manually inputted by man-machine interface and send control command to corresponding topworks.

As stated above, described control command comprises engine speed control command, Self-tipping control command and/or a main axle of sending out and sends out switching control command, wherein main send out an axle send out switch control command is mainly send out generator, axle band sends out generator and switches control command.

As stated above, describedly take the method for fuzzy clustering to carry out cluster analysis to navigation environment to be specially: all parameters collected form navigation environment factor datas, are represented in vector form by the navigation environment factor data of whole leg; Fuzzy transmission closure is adopted to classify to navigation environment key element.

As stated above, the described dynamic response relation being obtained operation of ship index and navigation environment by the method for Multiple Non-linear Regression Analysis, is specially:

The classification of the navigation environment key element utilizing the method for fuzzy clustering to draw, the efficiency operation index extracting congener navigation environment factor data and calculate, draw the scatter diagram between efficiency operation index and each navigation environment key element respectively, adopt the relation of Multiple Non Linear Regression function determination efficiency operation index and each navigation environment key element, thus efficiency operation formula of index is revised, obtain the efficiency operation formula of index under variety classes navigation environment key element.

As stated above, describedly take genetic algorithm to carry out dynamic optimization to be specially:

Engine speed is encoded to chromosome, utilize the mode of iteration to carry out selecting, intersect and mutation operator to exchange chromosomal information in population, final generation meets the chromosome of optimization aim, namely meet the minimum corresponding main frame optimum speed value of efficiency operation index under constraint condition, export control command according to this optimum speed value.

Beneficial effect of the present invention is: by designing a kind of boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm and method, under different navigation environments, the power consumption state that Real-Time Monitoring boats and ships are current is also shown in real time by man-machine interface, thus provide reference for Ship Controling person, and can pass through based on the engine speed corresponding to fuzzy clustering and the boats and ships efficiency integrated management of genetic algorithm and the optimum speed of Controlling model determination boats and ships, when navigation environment allows, can run under this rotating speed by automatic control host machine, can the efficiency level of ship-lifting by the rotating speed of optimal control main frame, and eliminate or reduce environmental factor to the impact of boats and ships energy consumption, evade the irrationality of the default speed of a ship or plane, thus energy-conserving and environment-protective, reduce discharge.

Accompanying drawing explanation

Fig. 1 is the structural representation of one embodiment of the invention.

Fig. 2 is the Principle of Communication figure of one embodiment of the invention.

Fig. 3 is the control flow chart of one embodiment of the invention.

Embodiment

Below will provide detailed description to embodiments of the invention.Although the present invention will carry out setting forth and illustrating in conjunction with some embodiments, it should be noted that the present invention is not merely confined to these embodiments.On the contrary, the amendment carry out the present invention or equivalent replacement, all should be encompassed in the middle of right of the present invention.

In addition, in order to better the present invention is described, in embodiment hereafter, give numerous details.It will be understood by those skilled in the art that do not have these details, the present invention can implement equally.In other example, known method, flow process, element and circuit are not described in detail, so that highlight purport of the present invention.

Fig. 1 is the structural representation of one embodiment of the invention, boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm comprises: sensor group, for gathering the parameter (in the present embodiment, sensor group comprises fuel consume sensor, torque speed sensor, wind speed wind direction sensor, speed of a ship or plane heading sensor, water velocity sensor, host parameter sensor, electrical network parameter sensor group and water depth sensor) needed for control; Lower computer system, comprise data acquisition module and slave computer communication module, data acquisition module is for gathering discrete type parameter, obtaining the parameter of sensor group collection, and slave computer communication module is used for all parameters all being uploaded, receiving control command and send to corresponding topworks; Master system, comprises Upper machine communication module, data memory module, data processing module and boats and ships efficiency integrated management control module; Upper machine communication module for receive slave computer communication module and upload all parameters, send control command to slave computer communication module; Data memory module is used for all parameters to store; Data processing module is used for parameter in calling data memory module, all Parameter analysis of electrochemicals received are supplied to boats and ships efficiency integrated management control module; Boats and ships efficiency integrated management control module is for utilizing the parameter after parsing, based on fuzzy clustering and genetic algorithm, efficiency operation index (EEOI) that real-time Ship ' is current, determines the duty of the optimum speed of boats and ships, power-supplying forms and load, and automatic output control order.

Three kinds of communication type are comprised: the next two CAN communication, serial communication and upper pair of Redundant Ethernet communication between Upper machine communication module and slave computer communication module.As shown in Figure 2, the next two CAN communication gathers discrete type parameter and communication is uploaded to host computer by CAN mouth server is unified; The parameter that the sensor group that serial communication gathers each port by serial server gathers, by gathering next all Parameter Mappings to Ethernet in CAN mouth server and serial server, for host computer system access.In the present embodiment, wherein, sensor gathers speed of a ship or plane course, rotating speed moment of torsion, longitude and latitude, oil consumption, wind speed and direction, water velocity and bathymetric data are uploaded to Ethernet by RS485 bus through serial service device; In addition, other discrete points data, as digital quantity input, export, the discrete variable such as analog input, output data are then uploaded to Ethernet by CAN through CAN mouth server.

All types of data on Ethernet store in a database by data memory module according to actual needs, and database adopts SQL database, in actual use, if desired to call or query-relevant data completes indirectly by data processing module.Wherein, the record of data is stored on the hard disk of Platform Server with database mode.Circulation archiving method is taked in information management and according to storage space and time interval appointed information filing quantity, stale information will be substituted automatically by fresh information.

Each communication data frame is resolved rear for boats and ships efficiency integrated management control module by data processing module.If inquire about historical data or parameter, also call by data processing module.Host computer reads uploading data by the form of client-access server.

Preferably, master system also comprises man-machine interface, for show all parameters and the current efficiency operation index of boats and ships, data memory module is provided call port.Man-machine interface, as the medium of man-machine interaction, play display data and send the effect of ordering, mainly comprising main interface, environmental parameter display interface, host parameter display and control inerface, network of ship parameter display interface, energy consumption parameter display interface, optimum management control inerface.It is characterized in that described man-machine interface has been write by C# language.The wherein the next data gathered, software can read, as environmental parameter, host parameter from network voluntarily; The comprehensive parameter of part then by carrying out corresponding display after the boats and ships efficiency integrated management control module process of described master system, as the main frame optimum speed under current boats and ships efficiency operation index (EEOI), current environment.

Utilize the control method that the above-mentioned boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm realizes, as shown in Figure 3, master system obtains navigation environment factor data (these data to be gathered by lower computer system and are uploaded to Ethernet, comprise oil consumption, moment of torsion rotating speed, wind speed and direction, speed of a ship or plane course, water velocity and bathymetric data) from Ethernet; The method of fuzzy clustering is taked to carry out cluster analysis to navigation key element, and the dynamic response relation of operation of ship index and navigation environment is obtained by the method for Multiple Non-linear Regression Analysis, namely the EEOI computing formula under variety classes navigation environment key element, this formula is set up in advance when system does not come into operation and for subsequent use; When practical application, a needs determines navigation environment key element generic at that time according to the real-time navigation environment factor data that Ethernet obtains, and chooses the EEOI computing formula under this type of navigation environment key element; Minimum for target with operation of ship index E EOI, take engine speed as optimized variable, to meet the power demand of full ship for constraint, genetic algorithm is taked to carry out dynamic optimization, determine the duty of the main frame optimum speed under different navigation environment, power-supplying forms and load, control command under output main frame optimum speed state, to ECU, is carried out rotating speed control to main frame, is guaranteed that boats and ships run under high energy efficiency state.

Preferably, the method also comprises man-machine interface and manual mode.Man-machine interface for show all parameters and the current efficiency operation index of boats and ships, data memory module is provided call port and input of control commands; Under manual mode, the all parameters shown according to man-machine interface by operating personnel and the current efficiency of boats and ships are operated index, determine the duty of the main frame optimum speed under different navigation environment, power-supplying forms and load, manually inputted by man-machine interface and send control command to corresponding topworks.

Described control command comprises engine speed control command, Self-tipping control command and/or master's axle and sends out switching control command, and wherein a main axle sends out switching control command is main generator, axle generator switching control command.

According to the efficiency operation index being shown by human-computer interaction interface of computing formula (1) Ship ' of boats and ships efficiency operation index (EEOI), think that Ship Controling person provides reference.

$\mathrm{EEOI}=\frac{C_{\mathrm{Fj}}}{m_{c\arg o}}\×\frac{q_j}{V_{\mathrm{ground}}}---\left(1\right)$

In formula: j is fuel type; C _fjj fuel oil CO ₂emission factor; q _jfor the oil consumption of main frame unit interval; V _groundfor the speed on the ground of boats and ships; m _cargofor the total amount of ship loading goods.

But, for a certain specific ship, its fuel type j, CO ₂emission factor C _fjvalue all for determining, therefore boats and ships efficiency operation index (EEOI) is mainly by the oil consumption of main frame unit interval and the impact of boats and ships speed on the ground, wherein, the oil consumption of main frame unit interval and boats and ships speed on the ground can represent by formula (2), formula (3) respectively.

$q_j=\frac{{\mathrm{RV}}_s}{{\mathrm{\η}}_{\mathrm{total}}}\·\mathrm{ge}---\left(2\right)$

V _ground＝V _S±V _Water(3)

Resistance when wherein R represents ship's navigation; Ge represents the amount of fuel that unit per hour useful power consumes; V _srepresent that boats and ships are to the water speed of a ship or plane; V _waterrepresent water velocity; η _totalrepresent the total efficiency of propulsion system.

Boats and ships its resistance R in the process of navigation mainly comprises frictional resistance R _f, Added Resistance R _wave, windage R _windwith resistance in shallow water R _shallow, respectively such as formula shown in (4)-(7).

$R_f=\frac{1}{2}{C}_f\mathrm{\ρ}{\mathrm{SV}}_S^2---\left(4\right)$

$R_{\mathrm{wave}}=\frac{1}{2}\frac{0.065}{{\left(F_r\right)}^2}{\left(\frac{h_{\mathrm{wave}}}{L_{w1}}\right)}^2\mathrm{\ρ}{\mathrm{SV}}_S^2---\left(5\right)$

$R_{\mathrm{wind}}=\frac{1}{2}{C}_{\mathrm{wind}}{\mathrm{\ρ}}_{\mathrm{air}}{A}_T{V}_{\mathrm{wind}}^2---\left(6\right)$

R _shallow＝f _s·R _deep(7)

In formula, C _frepresent coefficient of frictional resistance; S represents wetted surface; ρ represents the density of water; h _waverepresent that wave is high; Fr is your moral number of Fu; Lw1 is the length of boats and ships; R _shallowrepresent resistance in shallow water; V _windfor relative wind velocity; C _windrepresent air resistance coefficient, ρ _airrepresent atmospheric density; A _trepresent front face area; R _deeprepresent deep-water resistance (i.e. frictional resistance R _f, Added Resistance R _wavewith windage R _windsum), f _srepresent reduction coefficient, available formula (8) represents, H _waterfor the depth of water; D is drauht.

$f_s=1+\frac{{0.065V}_S^2}{(\frac{H_{\mathrm{water}}}{d}-1)\sqrt{d}}---\left(8\right)$

In addition, the corresponding relation of ship speed and engine speed can represent with formula (9), and wherein J represents advance coefficient; D represents airscrew diameter; n _speedrepresent engine speed; W represents semi-fluid coefficient.

$J=\frac{(1-w)\·V_S}{n_{\mathrm{speed}}\·D}---\left(9\right)$

To sum up, boats and ships efficiency operation index E EOI can be expressed as the depth of water, high, the boats and ships of wave to the function of the water speed of a ship or plane, engine speed, wind speed and water velocity, and it is available represents as shown in the formula (10).

EEOI＝f(H _water,h _wave,V _s,n _speed,V _wind,V _water) (10)

But the calculating carrying out EEOI by above-mentioned listed formula is comparatively complicated, and part formula is experimental formula, is not suitable for variety classes boats and ships, calculates time error comparatively large, is not easy to the application of real ship.Formula (10) is in different navigation environment key element situations simultaneously, for maintaining the computational accuracy of formula, the coefficient of each parameter should adjust accordingly according to navigation environment key element, therefore navigation environment key element is considered to carry out fuzzy cluster analysis, by choosing suitable confidence value, navigation environment key element is divided into variety classes, then, under each navigation environment key element, method for gathered data acquisition Multiple Non-linear Regression Analysis carrys out amendment type (10), thus be simplified, relatively accurate EEOI computing formula.

Concrete grammar: the sensor installed by boats and ships obtains the navigation environment factor data of whole leg, and represents in vector form, X ₁={ H _{water_1}, h _{wave_1}, V _{wind_1}, V _{water_1}..., X _n={ H _{water_n}, h _{wave_n}, V _{wind_n}, V _{water_n}, wherein X ₁x _nrepresent different navigation environment key element during ship's navigation, altogether n group; Fuzzy transmission closure is adopted to classify to navigation environment key element.First, known characteristic index matrix X ^*as follows:

$X^{*}=\left[\begin{array}{c}{X}_1\\ \·\\ \·\\ \·\\ X_n\end{array}\right]\⇒X_0=\left[\begin{array}{ccccc}{x}_{11}& \·& \·& \·& x_{1n}\\ \·& \·& & \·& \·\\ \·& & \·& & \·\\ \·& \·& & \·& \·\\ x_{n1}& \·& \·& \·& x_{\mathrm{nn}}\end{array}\right]---\left(11\right)$

Secondly, adopt maximum specification to X ^*standardize, obtain normalized matrix X ₀, shown in (11), wherein, maximum specification formula is such as formula shown in (12)

$x_{\mathrm{ij}}^{\′}=\frac{x_{\mathrm{ij}}}{M_j}---\left(12\right)$

Wherein x _ijrepresenting matrix X ^*the i-th row, jth arrange; X' _ijrepresenting matrix X ₀the i-th row, jth arrange; M _j=max (x _1j, x _2j..., x _nj).

Moreover, adopt minimax method to construct fuzzy similarity matrix R=(r _ij) _{n × n}; r _iji-th row of representing matrix R, jth arranges; Utilization square asks transitive closure t (R) from synthetic method; By choosing suitable confidence value thus navigation environment key element can being divided into variety classes.

Then, the EEOI data extracted congener navigation environment factor data and calculate, draw the scatter diagram between EEOI and each navigation environment key element respectively, analyzing EEOI and respectively opening the navigation or air flight between key element is linear relationship or nonlinear relationship, adopt Matlab Multiple Non Linear Regression function regress (), determine the relation of EEOI and each navigation environment key element, thus comparatively simplify, the relatively accurate EEOI computing formula under obtaining variety classes navigation environment key element, its form such as formula shown in (13), wherein a ₁-a ₇represent corresponding coefficient, under variety classes navigation environment key element, the related coefficient in formula and contained item are by different.

EEOI＝a ₁·H _water±a ₂·h _wave±a ₃·V _s±a ₄·n±a ₅·V _wind±a ₆·V _water±a ₇·V _s ²...(13)

Finally, after determining the EEOI formula under variety classes navigation environment key element, minimum for target with operation of ship index E EOI, take engine speed as optimized variable, to meet the electricity needs of full ship and hours underway for constraint, adopt genetic algorithm to carry out dynamic optimization, determine the main frame optimum speed under variety classes navigation environment key element, system is the power-supplying forms of certainty annuity and the duty of load under this optimum speed, and automatic output control order.Genetic algorithm is that problem parameter is encoded to chromosome, the mode of recycling iteration carries out selecting, intersect and the computing such as variation to exchange chromosomal information in population, finally generate the chromosome meeting optimization aim.It does not rely on gradient information when optimizing calculating, and does not require the continuous of objective function and can lead, and makes it be suitable for solving insoluble extensive, the nonlinear combinatorial optimization problem of conventional search methods.

Concrete grammar is as follows: (1) random initializtion population.Setting Population Size, maximum genetic algebra and individual lengths, determine that the constraint condition of feasible solution is such as formula (14), wherein f _timen () represents the hours underway under different rotating speeds, t _maxrepresent maximum hours underway, n _min, n _maxrepresent the minimum of main frame and maximum (top) speed respectively, and the feasible solution of required problem is expressed as chromosome or the individuality in hereditary space by binary coding; (2) fitness value of population is calculated.Be the minimum value asking EEOI in formula (15) in the present embodiment, therefore consider the fitness value of the inverse of functional value as individuality, the individuality that functional value is less, its adaptive value is larger, therefore therefrom can find out optimum individual; (3) operation is selected.Individual selected probability is closely related with fitness value, and ideal adaptation angle value is higher, and selected probability is larger, this example employing roulette method; (4) interlace operation.Adopt real number bracketing method, by two chromosomal exchange combinations, the outstanding feature of father's string is entailed word string, thus produces new excellent individual; (5) mutation operation; (6) judge whether evolution terminates, and if not, returns step (2); Final acquisition meets the chromosome of optimization aim, and namely meet the minimum corresponding main frame optimum speed value of EEOI under constraint condition, system exports control command according to this optimum speed value.

$\left\{\begin{array}{cc}s.t& f_{\mathrm{time}}\left(n\right)<t_{\max }\\ & n_{\min }<n<n_{\max }\end{array}\right.---\left(14\right)$

$\min \mathrm{EEOI}=f_{\mathrm{EEOI}}\left(n\right)\&DoubleRightArrow;\max \frac{1}{f_{\mathrm{EEOI}}\left(n\right)}---\left(15\right)$

In the process of actual motion, first system detects the classification belonging to current environment key element, then choose under this classification through revised EEOI computing formula, and then by the optimum speed of above-mentioned genetic algorithm determination main frame, and under this optimum speed the power-supplying forms of certainty annuity and the duty of load, namely when main frame operates under this optimum speed, as axle generator output power can not meet the electricity needs of full ship, then automatically lay down secondary load, as the electricity needs of full ship still can not be met after unloading, then automatically switching to main generator is that full ship is powered.The output of control command mainly comprises digital output and analog output, wherein digital output needs mainly for data the output some operating mode being carried out to relevant control after treatment, as main generator, axle generator switch control, Self-tipping control signal; Analog output mainly for system data after treatment some variable signal carry out output control, the rotating speed as main frame controls.

In sum, the invention provides a kind of boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm, system automatically can export corresponding control signal according to current efficiency level and control marine propuision system and run under best energy efficiency state.Compared with prior art, the present invention overcomes the shortcoming that when traditional boats and ships navigate by water under the setting speed of a ship or plane, energy efficiency is low, take into full account the impact of navigation environment on boats and ships energy consumption, energy efficiency monitoring and the optimal control of marine propuision system can be realized under different navigation environments, boats and ships are made to operate in the Best Point of efficiency all the time, evade the irrationality of the default speed of a ship or plane, thus improve boats and ships efficiency, energy-conserving and environment-protective.

Embodiment and accompanying drawing are only the conventional embodiment of the present invention above.Obviously, various supplement, amendment and replacement can be had under the prerequisite not departing from the present invention's spirit that claims define and invention scope.It should be appreciated by those skilled in the art that the present invention can change in form, structure, layout, ratio, material, element, assembly and other side under the prerequisite not deviating from invention criterion according to concrete environment and job requirement in actual applications to some extent.Therefore, be only illustrative rather than definitive thereof in the embodiment of this disclosure, the scope of the present invention is defined by appended claim and legal equivalents thereof, and is not limited thereto front description.

Claims (11)

1., based on a boats and ships energy efficiency management parametric controller for fuzzy clustering and genetic algorithm, it is characterized in that: it comprises:

Sensor group, for gathering the parameter needed for control;

Lower computer system, comprise data acquisition module and slave computer communication module, data acquisition module is for gathering discrete type parameter, obtaining the parameter of sensor group collection, and slave computer communication module is used for all parameters all being uploaded, receiving control command and send to corresponding topworks;

Master system, comprises Upper machine communication module, data memory module, data processing module and boats and ships efficiency integrated management control module; Upper machine communication module for receive slave computer communication module and upload all parameters, send control command to slave computer communication module; Data memory module is used for all parameters to store; Data processing module is used for parameter in calling data memory module, all Parameter analysis of electrochemicals received are supplied to boats and ships efficiency integrated management control module; Boats and ships efficiency integrated management control module is for utilizing the parameter after parsing, and based on fuzzy clustering and genetic algorithm, the efficiency operation index that real-time Ship ' is current, determines the duty of the optimum speed of boats and ships, power-supplying forms and load, provide control command.

2. the boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm according to claim 1, it is characterized in that: described master system also comprises man-machine interface, for show all parameters and the current efficiency operation index of boats and ships, data memory module is provided call port and input of control commands.

3. the boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm according to claim 1, is characterized in that: described sensor group comprises fuel consume sensor, torque speed sensor, wind speed wind direction sensor, speed of a ship or plane heading sensor, water velocity sensor, host parameter sensor, electrical network parameter sensor group and water depth sensor.

4. the boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm according to claim 1, is characterized in that: comprise three kinds of communication type between described Upper machine communication module and slave computer communication module: the next two CAN communication, serial communication and upper pair of Redundant Ethernet communication; The next two CAN communication is by CAN mouth server unified collection discrete type parameter and communication is uploaded to host computer; The parameter that the sensor group that serial communication gathers each port by serial server gathers, by gathering next all Parameter Mappings to Ethernet in CAN mouth server and serial server, for host computer system access.

5. utilize the control method that the boats and ships energy efficiency management parametric controller based on fuzzy clustering and genetic algorithm described in claim 1 realizes, it is characterized in that: utilize all parameters collected, the method of fuzzy clustering is taked to carry out cluster analysis to navigation environment, and the dynamic response relation of operation of ship index and navigation environment is obtained by the method for Multiple Non-linear Regression Analysis, minimum for target with operation of ship index, take engine speed as optimized variable, to meet the power demand of full ship for constraint, genetic algorithm is taked to carry out dynamic optimization, determine the main frame optimum speed under different navigation environment, the duty of power-supplying forms and load, automatically control command is provided.

6. control method according to claim 5, is characterized in that: described all parameters comprise oil consumption, moment of torsion rotating speed, wind speed and direction, speed of a ship or plane course, water velocity and bathymetric data.

7. control method according to claim 5, is characterized in that: the method also comprises man-machine interface and manual mode,

Man-machine interface for show all parameters and the current efficiency operation index of boats and ships, data memory module is provided call port and input of control commands;

Under manual mode, the all parameters shown according to man-machine interface by operating personnel and the current efficiency of boats and ships are operated index, determine the duty of the main frame optimum speed under different navigation environment, power-supplying forms and load, manually inputted by man-machine interface and send control command to corresponding topworks.

8. the control method according to claim 5 or 7, it is characterized in that: described control command comprises engine speed control command, Self-tipping control command and/or master's axle and sends out switching control command, wherein a main axle sends out switching control command is main generator, axle generator switching control command.

9. control method according to claim 5, it is characterized in that: the described method of fuzzy clustering of taking carries out cluster analysis to navigation environment, be specially: all parameters collected form navigation environment factor data, are represented in vector form by the navigation environment factor data of whole leg; Fuzzy transmission closure is adopted to classify to navigation environment key element.

10. control method according to claim 9, is characterized in that: the described dynamic response relation being obtained operation of ship index and navigation environment by the method for Multiple Non-linear Regression Analysis, is specially:

The classification of the navigation environment key element utilizing the method for fuzzy clustering to draw, the efficiency operation index extracting congener navigation environment factor data and calculate, draw the scatter diagram between efficiency operation index and each navigation environment key element respectively, adopt the relation of Multiple Non Linear Regression function determination efficiency operation index and each navigation environment key element, thus efficiency operation formula of index is revised, obtain the efficiency operation formula of index under variety classes navigation environment key element.

11. control methods according to claim 10, is characterized in that: described genetic algorithm of taking carries out dynamic optimization, is specially:

Engine speed is encoded to chromosome, utilize the mode of iteration to carry out selecting, intersect and mutation operator to exchange chromosomal information in population, final generation meets the chromosome of optimization aim, namely meet the minimum corresponding main frame optimum speed value of efficiency operation index under constraint condition, export control command according to this optimum speed value.