CN102944216B - Three-redundant ship dynamic positioning heading measurement method based on improved voting algorithm - Google Patents
Three-redundant ship dynamic positioning heading measurement method based on improved voting algorithm Download PDFInfo
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- CN102944216B CN102944216B CN201210419913.8A CN201210419913A CN102944216B CN 102944216 B CN102944216 B CN 102944216B CN 201210419913 A CN201210419913 A CN 201210419913A CN 102944216 B CN102944216 B CN 102944216B
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Abstract
The invention relates to a three-redundant ship dynamic positioning heading measurement method based on an improved voting algorithm. The method comprises the following steps: 1, measuring a heading value: 2, adopting a variance self-learning weighting method to obtain respective weight values; 3, carrying out weighting on the measured mean, respectively subtracting a weighted mean from an input value of a sensor, calculating an absolute value, and comparing the absolute value with a threshold t1, wherein the absolute value less than the threshold t1 is considered that no failure exists so as to directly perform data fusion, and it is considered that the failure exists if the absolute value greater than t1 exists, such that failure redetermination is required to be performed; 4, obtaining difference between the current input value and the previous output value, and calculating an absolute value, wherein a normal state is determined when the absolute value is less than t2 and a heading change rate at the current time is similar to heading change rates of the current rudder angle and the ship speed, and otherwise a failure is determined; and 5, carrying out weighting on the remaining data reassignment weight values after excluding the failure data. With the present invention, a lot of failure determinations are achieved, such that the output result has high precision.
Description
Technical field
The present invention relates to dynamic positioning of vessels device, particularly relating to a kind of based on improving the triple redundance dynamic positioning of vessels bow of voting algorithm to measuring method.
Background technology
Bow to measuring system be in ship's navigation for measure ship bow to the system of geographic north to angle.Existing bow generally includes to system: (1) gyro compass, for measure bow to; (2) magnetic compass: as for subsequent use measurement mechanism of bow to measuring system; (3) central computer, carries out breakdown judge and Data Fusion to the bow that gyro compass records to data.Generally, the bow of boats and ships is only equipped with a set of gyro compass usually to measuring system, for providing data for bow to measurement.Because bow has key effect to for Ship Dynamic Positioning Systems Based, mistake bow is to causing a series of serious consequences such as vessel position loss.Therefore, International Maritime Organization (IMO) and the classification societies all specify to need to install three bows to sensor for 3 grades of dynamic positioning systems simultaneously.The redundancy bow that three bows are formed to sensor to measuring system, when should guarantee that wherein single bow is to sensor fault, system should judge fault sensor and provide remove fault effects bow to metrical information.Therefore, in order to improve the reliability that bow is measured to measuring system, the list cover of above-mentioned existing bow to gyro compass in measuring system being equipped with, rising to three cover gyro compasses and be equipped with, namely there are three cover gyro compasses for measurement data, are commonly referred to: the bow of triple redundance type dynamic positioning system is to measuring system.The method of normal employing in measuring system, adopts voting algorithm to process to metrical information to bow at triple redundance bow.
As shown in Figure 1, for the structure that the bow of a typical triple redundance dynamic positioning system adopts to measuring system, it is made up of three gyro compasses 1, three gyro compasses 1 measure bow respectively to data, then, gyro compass 1 passes through serial communication interface, central computer 2 is sent to information by measuring the ship bow obtained, central computer 2 gathers port by data acquisition and handling procedure control data, real-time reception is from the measurement data of gyro compass 1, and by the measurement data that receives through majority votinl and data fusion, in fusion process, be worth to fusion by the bow that calculates of the voting module 3 in central computer 2 and weighting block 4, each sensor is endowed identical weights usually, finally export bow to value.
After adopting this redundancy, bow increases to the more single compass measurement of reliability of measuring system, but above-mentioned redundancy structure still has the following disadvantages:
(1) due in system, the weights of each Data Fusion of Sensor distribute inabundant to the performance difference in each sensor actual measurement, and fusion accuracy also improves a lot space.
(2) the majority votinl mode adopted, cannot accurately realize in the fault voting having two gyro compasses to break down in situation.
Summary of the invention
Fundamental purpose of the present invention is the above-mentioned shortcoming overcoming prior art existence, and provides a kind of based on improving the triple redundance dynamic positioning of vessels bow of voting algorithm to measuring method, and it can realize most breakdown judge, makes Output rusults have higher precision.
The object of the invention is to be realized by following technical scheme:
Based on improving the triple redundance dynamic positioning of vessels bow of voting algorithm to a measuring method, it is characterized in that: adopt following steps:
The first step: measure bow to value to measuring unit by bow;
Second step: by weights allocation units, bow is measured the bow of gained to value to measuring unit, then obtain respective weights by the method for variance self study weighting;
3rd step: by fault just judging unit bow be weighted to the measured value of measuring unit try to achieve measurement average
and the input value of three sensors is deducted weighted mean value respectively
again it is asked and thoroughly deserve E1, E2, E3, then, E1, E2, E3 and threshold value t1 are made comparisons, if be all less than threshold value t1, then think and directly enter non-fault data fusion unit and carry out data fusion; If there is any one to be greater than t1 in E1, E2, E3, then thinks and break down, need to carry out fault and judge again;
4th step: by fault again judging unit respectively the output valve of input value current for sensor and previous moment system is done difference, take absolute value again, if absolute value is less than predetermined threshold value t2, and the bow that the bow of sensor nearest a period of time survey will determine with current rudder angle and the speed of a ship or plane to rate of change is close to rate of change, then think that this sensor is normal; Otherwise, be judged as fault;
5th step: after the data of fault being got rid of by data fusion unit, weights are redistributed to remaining data and is weighted.
Described bow is made up of to measuring unit three gyro compasses.
Described weights allocation units adopt a kind of Multisensor Data Fusion Algorithm based on variance self study weighting, and this algorithm treats old measurement data and new measurement data gives different weight coefficients, make the process that measurement variance is progressively tending towards optimum.
Described fault just judging unit inputs data, weighted mean module by gyro compass, makes differential mode block and threshold value judges that four parts are composed in series successively.
Described fault again judging unit is by obtaining gyro compass measurement data in fault just judging unit, try to achieve the measurement variation rate of each gyro compass, and bow in the mathematical model of itself and ship motion is compared to rate of change, try to achieve difference, judge that II realizes breakdown judge by threshold value again, the information of comparison is that the bow that determines of the current value rate of change of each gyro compass and current ship motion model is to rate of change.
Weights in described second step are
Wherein,
be the estimated value of i-th sensor-measurement variance when kth time is sampled.
Described fault is also provided with fault auxiliary judgment unit, the kinematic parameter speed of a ship or plane of fault auxiliary judgment unit as ship motion process and the mathematical model of rudder angle and ship motion in judging unit again, carries out fault decide by vote for auxiliary.
Beneficial effect of the present invention: the present invention is owing to adopting technique scheme, and it can realize most breakdown judge, makes Output rusults have higher precision.
Accompanying drawing explanation
Fig. 1 is that existing triple redundance bow is to measurement mechanism structural drawing.
Fig. 2 fault of the present invention just decides by vote cellular construction schematic diagram.
Fig. 3 is that fault of the present invention decides by vote cellular construction schematic diagram again.
Fig. 4 is schematic flow sheet of the present invention.
Fig. 5 is measurement of the present invention and fused data figure.
Major label description in figure:
1. gyro compass, 2. central computer, 3. voting module, 4. weighting block, 5. gyro compass input data, 6. weighted mean module, 7. make differential mode block, 8. threshold value judgement, 9. gyro compass measurement data, 10. gyro compass measurement variation rate, 11. bows to rate of change, 12. differences, 13. threshold values judgements, 14. bows to measuring unit, 15. weights allocation units, 16. faults just judging unit, 17. auxiliary judgment unit, 18. faults judging unit, 19. data fusion unit again.
Embodiment
As shown in figs 2-4, the present invention includes: bow to measuring unit 14, weights allocation units 15, fault is judging unit 16 just, auxiliary judgment unit 17, and fault is judging unit 18 and data fusion unit 19 again, wherein, bow is be made up of three gyro compasses 1 to measuring unit 14; Weights allocation units 15 adopt a kind of Multisensor Data Fusion Algorithm based on variance self study weighting, it treats old measurement data and new measurement data gives different weight coefficients, while consideration most recent data plays Main Function in the estimation, make full use of empirical data in the past, thus, make the process that measurement variance is progressively tending towards optimum; Fault just judging unit 16 inputs data 5, weighted mean module 6 by gyro compass, makes differential mode block 7 and threshold value judges that 8 four parts are composed in series (as shown in Figure 2) successively.
Fault again judging unit 18 is by obtaining gyro compass measurement data 9 in fault just judging unit 16, try to achieve the measurement variation rate 10 of each gyro compass 1, and bow in the mathematical model of itself and ship motion is compared to rate of change 11, try to achieve difference 12, judge that 13 realize breakdown judge by second threshold value again, the information of comparison is that the bow that determines of the current value rate of change of each gyro compass 1 and current ship motion model is to rate of change 11.(as shown in Figure 3).
Specific implementation of the present invention comprises following step:
The first step: bow is to measurement: measure bow to value to the gyro compass of three in measuring unit 14 1 by bow;
Second step: weights distribute: by weights allocation units 15, bow each gyro compass 1 in measuring unit 14 is measured the bow of gained to value, then obtain respective weights by the method for variance self study weighting
Wherein,
be the estimated value of i-th sensor-measurement variance when kth time is sampled.
3rd step: fault just judges: bow measured value of each gyro compass 1 in measuring unit 14 is weighted by the first judging unit 16 of fault tries to achieve measurement average
and the input value of three sensors is deducted weighted mean value respectively
again it is asked and thoroughly deserve E1, E2, E3, then, E1, E2, E3 and threshold value t1 are made comparisons, if be all less than threshold value t1, then think and directly enter non-fault data fusion unit and carry out data fusion; If there is any one to be greater than t1 in E1, E2, E3, then thinks and break down, then need to carry out fault and judge again;
4th step: fault judges again: the output valve of input value current for sensor and previous moment system is done difference by fault again judging unit 18 respectively, take absolute value again, if absolute value is less than predetermined threshold value t2, and the bow that the bow of sensor nearest a period of time survey will determine with current rudder angle and the speed of a ship or plane to rate of change is close to rate of change, then think that this sensor is normal; Otherwise, be judged as fault; In addition, fault is also provided with the kinematic parameter speed of a ship or plane of fault auxiliary judgment unit 17 as ship motion process and the mathematical model of rudder angle and ship motion in judging unit 18 again, carries out fault decide by vote for auxiliary;
5th step: data fusion: data fusion unit 19 is redistributed weights to remaining data and is weighted after the data of fault being got rid of.Such as, when sensor 1 is judged to be fault, now the weights of sensor 2 become W2 '=W2/ (W2+W3), and the weights of sensor 3 are then W3 '=W3/ (W2+W3), and fusion output valve is now
(as shown in Figure 4).
Embodiment: as shown in Figure 5, in laboratory environments, the gyration of simulation boats and ships, carries out the emulation experiment of two gyro compass faults, and adopts above-mentioned steps to carry out data processing to system to bow.Its result is as exported data for merging in Fig. 5 d, and Fig. 5 a, Fig. 5 b, Fig. 5 c are the measurement data of gyro compass 1.
The present invention improves weighting algorithm and multistage breakdown judge mechanism owing to adopting, and can guarantee the accuracy of breakdown judge, and have that measuring error is little, the advantage such as regulating power is strong, real-time and ease for use.
The above, it is only preferred embodiment of the present invention, not any pro forma restriction is done to the present invention, every above embodiment is done according to technical spirit of the present invention any simple modification, equivalent variations and modification, all still belong in the scope of technical solution of the present invention.
Claims (6)
1., based on improving the triple redundance dynamic positioning of vessels bow of voting algorithm to a measuring method, it is characterized in that: adopt following steps:
The first step: measure bow to value to measuring unit by bow;
Second step: by weights allocation units, bow is measured the bow of gained to value to measuring unit, then obtain respective weights by the method for variance self study weighting; These weights are
Wherein,
be the estimated value of i-th sensor-measurement variance when kth time is sampled;
3rd step: by fault just judging unit bow be weighted to the measured value of measuring unit try to achieve measurement average
and the input value of three sensors is deducted weighted mean value respectively
again it is asked and thoroughly deserve E1, E2, E3, then, E1, E2, E3 and threshold value t1 are made comparisons, if be all less than threshold value t1, then think and directly enter non-fault data fusion unit and carry out data fusion; If there is any one to be greater than t1 in E1, E2, E3, then thinks and break down, need to carry out fault and judge again;
4th step: by fault again judging unit respectively the output valve of input value current for sensor and previous moment system is done difference, take absolute value again, if absolute value is less than predetermined threshold value t2, and the bow that the bow of sensor nearest a period of time survey will determine with current rudder angle and the speed of a ship or plane to rate of change is close to rate of change, then think that this sensor is normal; Otherwise, be judged as fault;
5th step: after the data of fault being got rid of by data fusion unit, weights are redistributed to remaining data and is weighted.
2. according to claim 1 based on improving the triple redundance dynamic positioning of vessels bow of voting algorithm to measuring method, it is characterized in that: described bow is made up of to measuring unit three gyro compasses.
3. according to claim 1 based on improving the triple redundance dynamic positioning of vessels bow of voting algorithm to measuring method, it is characterized in that: described weights allocation units adopt a kind of Multisensor Data Fusion Algorithm based on variance self study weighting, this algorithm treats old measurement data and new measurement data gives different weight coefficients, makes the process that measurement variance is progressively tending towards optimum.
4. according to claim 1 based on improving the triple redundance dynamic positioning of vessels bow of voting algorithm to measuring method, it is characterized in that: described fault just judging unit inputs data, weighted mean module by gyro compass, makes differential mode block and threshold value judges that four parts are composed in series successively.
5. according to claim 1 based on improving the triple redundance dynamic positioning of vessels bow of voting algorithm to measuring method, it is characterized in that: described fault again judging unit is by obtaining gyro compass measurement data in fault just judging unit, try to achieve the measurement variation rate of each gyro compass, and bow in the mathematical model of itself and ship motion is compared to rate of change, try to achieve difference, judge that II realizes breakdown judge by threshold value again, the information of comparison is that the bow that determines of the current value rate of change of each gyro compass and current ship motion model is to rate of change.
6. according to claim 1 based on improving the triple redundance dynamic positioning of vessels bow of voting algorithm to measuring method, it is characterized in that: described fault is also provided with fault auxiliary judgment unit in judging unit again, the kinematic parameter speed of a ship or plane of fault auxiliary judgment unit as ship motion process and the mathematical model of rudder angle and ship motion, carry out fault decide by vote for auxiliary.
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Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103466067B (en) * | 2013-09-11 | 2015-09-30 | 哈尔滨工程大学 | A kind of boats and ships redundant power position fixing system dedicated manipulator |
| CN105005232A (en) * | 2015-05-28 | 2015-10-28 | 孙军 | Degradable triple redundancy synchronous voting computer control system and method |
| CN105354586B (en) * | 2015-09-24 | 2018-10-26 | 哈尔滨工程大学 | Multirate sensor level based adjustment device and method with packet loss phenomenon |
| CN105334747B (en) * | 2015-09-24 | 2018-08-17 | 哈尔滨工程大学 | A kind of dynamic positioning of vessels triple redundance computer data voting synchronous method |
| US11385632B2 (en) * | 2018-12-21 | 2022-07-12 | The Boeing Company | Sensor fault detection and identification using residual failure pattern recognition |
| CN109828449A (en) * | 2019-01-25 | 2019-05-31 | 杭州电子科技大学 | A kind of triplication redundancy control calculating voting system and method |
| CN110347033A (en) * | 2019-06-28 | 2019-10-18 | 中国船舶重工集团公司第七0七研究所 | A kind of triple redundance dynamic positioning system voting algorithm based on improvement historical information |
| EP3770342A1 (en) * | 2019-07-24 | 2021-01-27 | Metalogenia Research & Technologies S.L. | Method for monitoring a status of attachment of a ground engaging tool, corresponding system and machine |
| CN111338259A (en) * | 2020-03-16 | 2020-06-26 | 朱勇 | Intelligent redundant system for position and heading information |
| CN113204732B (en) * | 2021-05-14 | 2023-05-16 | 四川腾盾科技有限公司 | Method, system, computer program and storage medium for voting secondary redundancy data of unmanned aerial vehicle sensor |
| CN113946122B (en) * | 2021-10-22 | 2024-02-13 | 中国科学院工程热物理研究所 | Gas turbine parameter redundancy voting method based on confidence weight floating |
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Address after: 100010 Chaoyangmen North Street, Dongcheng District, Dongcheng District, Beijing Co-patentee after: OFFSHORE OIL ENGINEERING Co.,Ltd. Patentee after: CHINA NATIONAL OFFSHORE OIL Corp. Co-patentee after: HARBIN ENGINEERING University Address before: 100010 Chaoyangmen North Street, Dongcheng District, Dongcheng District, Beijing Co-patentee before: OFFSHORE OIL ENGINEERING Co.,Ltd. Patentee before: CHINA NATIONAL OFFSHORE OIL Corp. Co-patentee before: HARBIN ENGINEERING University |
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