CN107180162A - A kind of multi-modal decision system framework of O＆M based on GPB algorithms - Google Patents
A kind of multi-modal decision system framework of O＆M based on GPB algorithms Download PDFInfo
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- CN107180162A CN107180162A CN201710518611.9A CN201710518611A CN107180162A CN 107180162 A CN107180162 A CN 107180162A CN 201710518611 A CN201710518611 A CN 201710518611A CN 107180162 A CN107180162 A CN 107180162A
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Abstract
The present invention discloses a kind of multi-modal decision system framework of O＆M based on GPB algorithms, and sampling sensor model and shooting head model are distinguished by the moment of k 1；Distinguish sampling sensor model and shooting head model by the k moment；Respective state estimation, and evaluated error covariance matrix are carried out using Kalman algorithms；Then the synthesis of state estimation, and corresponding covariance matrix are calculated；Be finally state estimation merges output with covariance, to realize that accident automatic early-warning is taken precautions against.
Description
Technical field
The present invention relates to a kind of multi-modal decision system framework of O＆M based on GPB algorithms
Background technology
With cloud computing and virtualization, the features such as " extensive ", " high density ", " high energy consumption ", " complication " is showed, is built
If with development New Generation of IDC, lifting data center infrastructure management will become increasingly important, the basis of data center
The new trend that framework fusion management will develop with intelligence as data center.
At present, O＆M lacks automation means, and passive O＆M, inefficiency, extensive IT facilities bring government pressure.Need
The automatically-monitored of data center is realized, the timely alarm ability of system and ambient parameter is improved, system is improved and environment is different
The response speed and monitoring level often changed.Using sensor and the first-class various means perception informations of shooting, unification can be achieved with
Service management software platform.
Data that Multi-source Information Fusion is produced by awareness tool obtain information.Information fusion is related to a variety of different senses
Know device and different actuators, different awareness apparatus can produce different types of data.How these multimodes are effectively merged
State data so correctly reflection O＆M state be highly important research topic.
Sensor subsystem is environmental detection device, acts on detection environmental change in real time and for data fusion subsystem
Related data is provided；Decision support subsystem carries out situation estimation in time using the structure of data fusion, and the result is again sensing
Device management provides important evidence；Sensor management subsystem is provided according to the feedback information that above several stages provide to sensor
Source adjust and optimize in real time.
Camera target detection be using the state of target as tracking original state, while to Target Modeling, obtaining phase
The descriptive model of latent structure target is closed, object module is then utilized in follow-up image, mesh is estimated by the way of filtering
Target current state, while updating object module using current state.
The optimal estimation of fixed model collection is full hypothesis estimation, that is, etching system is possible to pattern when considering each.Its
Models Sets are predetermined, are time-varying in itself without tube model.Thus, it is necessary to utilize some hypothesis administrative skills
To set up more effective non-hypothesis tree algorithm, to ensure remaining hypothesis quantity within the specific limits.The pseudo- Bayes side of so-called broad sense
Method (GPB), is exactly, in moment k, to carry out only considering that system goes over the mesh in limited sampling time interval during system state estimation
Mark model history.
The invention provides a kind of multi-modal decision system framework of O＆M based on GPB algorithms, sampled respectively by the k-1 moment
Sensor model and shooting head model；Distinguish sampling sensor model and shooting head model by the k moment；Entered using Kalman algorithms
The respective state estimation of row, and evaluated error covariance matrix；Then the synthesis of state estimation, and corresponding covariance matrix are calculated；
Be finally state estimation merges output with covariance, to realize that accident automatic early-warning is taken precautions against.
The content of the invention
It is an object of the invention to provide a kind of multi-modal decision system framework of O＆M based on GPB algorithms.Present invention bag
Include following characteristics：
Inventive technique scheme
1. a kind of multi-modal decision-making system framework of O＆M based on GPB algorithms, it is comprised the following steps that：
1) sampling sensor model and shooting head model are distinguished by the k-1 moment；
2) sampling sensor model and shooting head model are distinguished by the k moment；
3) respective state estimation, and evaluated error covariance matrix are carried out using Kalman algorithms；
4) and then the synthesis of state estimation, and corresponding covariance matrix are calculated；
5) to be finally state estimation merge output with covariance.
Brief description of the drawings
Fig. 1 is the multi-modal decision system Organization Chart of O＆M based on GPB algorithms.
Embodiment
The multi-modal decision system framework of this O＆M based on GPB algorithms, comprises the following steps：
1) sampling sensor model and shooting head model are distinguished by the k-1 moment；
2) sampling sensor model and shooting head model are distinguished by the k moment；
3) respective state estimation, and evaluated error covariance matrix are carried out using Kalman algorithms；
4) and then the synthesis of state estimation, and corresponding covariance matrix are calculated；
5) to be finally state estimation merge output with covariance.
Claims (1)
1. a kind of multi-modal decision system framework of O＆M based on GPB algorithms, it is comprised the following steps that：
1) sampling sensor model and shooting head model are distinguished by the k-1 moment；
2) sampling sensor model and shooting head model are distinguished by the k moment；
3) respective state estimation, and evaluated error covariance matrix are carried out using Kalman algorithms；
4) and then the synthesis of state estimation, and corresponding covariance matrix are calculated；
5) to be finally state estimation merge output with covariance.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201710518611.9A CN107180162A (en) | 2017-06-30 | 2017-06-30 | A kind of multi-modal decision system framework of O＆M based on GPB algorithms |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201710518611.9A CN107180162A (en) | 2017-06-30 | 2017-06-30 | A kind of multi-modal decision system framework of O＆M based on GPB algorithms |
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| CN107180162A true CN107180162A (en) | 2017-09-19 |
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| CN201710518611.9A Pending CN107180162A (en) | 2017-06-30 | 2017-06-30 | A kind of multi-modal decision system framework of O＆M based on GPB algorithms |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113344072A (en) * | 2021-06-02 | 2021-09-03 | 上海蓝色帛缔智能工程有限公司 | GPB algorithm-based operation and maintenance multi-mode decision method and system and cloud server |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103776654A (en) * | 2014-02-21 | 2014-05-07 | 黑龙江省科学院自动化研究所 | Method for diagnosing faults of multi-sensor information fusion |
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2017
- 2017-06-30 CN CN201710518611.9A patent/CN107180162A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103776654A (en) * | 2014-02-21 | 2014-05-07 | 黑龙江省科学院自动化研究所 | Method for diagnosing faults of multi-sensor information fusion |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113344072A (en) * | 2021-06-02 | 2021-09-03 | 上海蓝色帛缔智能工程有限公司 | GPB algorithm-based operation and maintenance multi-mode decision method and system and cloud server |
| CN113344072B (en) * | 2021-06-02 | 2023-04-07 | 上海蓝色帛缔智能工程有限公司 | GPB algorithm-based operation and maintenance multi-mode decision method and system and cloud server |
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Application publication date: 20170919 |
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