CN1256550C - On-line fault diagnosis system for centarl air conditioner water system temp and flow sensor - Google Patents
On-line fault diagnosis system for centarl air conditioner water system temp and flow sensor Download PDFInfo
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- CN1256550C CN1256550C CN 200410017182 CN200410017182A CN1256550C CN 1256550 C CN1256550 C CN 1256550C CN 200410017182 CN200410017182 CN 200410017182 CN 200410017182 A CN200410017182 A CN 200410017182A CN 1256550 C CN1256550 C CN 1256550C
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Abstract
The present invention relates to an on-line fault diagnosis system for central air-conditioning water system temperature and flow sensors, which mainly comprises a data collection module, a noise filtration module, a steady-state data judgment module, a fault detection module, a storage module, a fault diagnosis module, a diagnostic result confidence level judgement module, a data recovery module and an output module. The drift fault of a temperature and flow rate sensor of an air-conditioning water system is diagnosed on line on the basis of systematic energy conservation and mass conservation by adopting the way of statistical mathematics. The present invention can effectively diagnose the faults of a plurality of sensors, and can accurately diagnose the position and the severity of the faults.
Description
Technical field:
What the present invention relates to is the fault diagnosis system of a kind of central air conditioning water system temperature and flow sensor, particularly a kind of method of statistical mathematics that adopts is carried out the central air conditioning water system temperature of online detection, diagnosis and the online system failure diagnosis of flow sensor to sensor, belongs to architectural environment equipment and control technology field.
Background technology:
The appearance of building intelligent control system is had higher requirement to the sensor in the central air-conditioning.Make the central air conditioner system operation normal, good control and monitoring system just must be arranged, and the measuring-signal of sensor is the basis and the foundation of control and monitoring system, for control system can be played a role effectively, the measurement of sensor must be reliable, otherwise will cause the instability of system's operation, and then cause air-conditioning system can not satisfy requirements such as human settlements are comfortable, energy-conservation.In addition,, the diagnosis of sensor fault is difficult to be undertaken by the method for manual detection, therefore, in building intelligent control system, introduces on-line fault diagnosis and be necessary because control system just becoming and become increasingly complex.
The fault of sensor roughly can be divided three classes.The first kind is meant that sensor is malfunctioning suddenly, be also referred to as the hard fault of sensor, this class failure ratio is better diagnosed, if from building management system (BMS) or the variation that whether is necessary of the reading that provides of corresponding sensor whether just can judge sensor malfunctioning fully; Have high-frequency signal in the measured value of the second class sensor, this class fault can be found with the method for filter; The 3rd class fault is meant that slowly drift takes place sensor, is also referred to as the soft fault of sensor, the most difficult discovery of this class fault, but it is a kind of typical fault in the central air conditioner system really, it is a kind of process of gradual change, makes the people subtle, must detect by special method, proofread and correct.Simultaneously, it is to the energy resource consumption of central air conditioner system, and monitoring and control optimization all have very big influence.
Current research to the sensor fault diagnosis direction mainly concentrates on sensor measurement value drift aspect.In the prior art, current diagnostic method to drifting fault mainly contains two classes: based on the diagnostic method of model with based on the method for pattern-recognition.At first obtain the standard value of system features amount by model based on the diagnostic method of model, the characteristic quantity during then by actual motion relatively and the size of standard feature amount judge whether to break down according to the characteristic of characteristic quantity deviation.The prerequisite of this method is to need a relatively precise math model.At first the various operation conditions of system are learnt (no matter whether fault is arranged) based on the diagnostic method of pattern-recognition,, use various didactic reasonings and whether fault is existed do a judgement then at the operation conditions of a certain reality.There is the following shortcoming in these current diagnostic methods: 1). be difficult to detect a plurality of sensor faults; 2). there is certain difficulty in the quantification to fault; 3). be difficult to carry out inline diagnosis.Therefore, need to seek a kind of new diagnostic method and overcome the existing defective of present common methods.
Summary of the invention:
For overcoming the deficiency and the defective of existing fault diagnosis technology, the present invention proposes a kind of sensor diagnostic method based on statistical mathematics, online diagnosis has the relevant temperature of central air conditioning water system and the fault that flow sensor takes place.
The present invention mainly comprises data acquisition, filtering noise, and steady state data is judged, fault detect, the data storage, fault diagnosis, the confidence level of diagnostic result is judged, modules such as data recovery.
Data collecting module collected is to the measured value of each temperature of water system, flow sensor, and the filtering noise module is eliminated the noise of each sensor signal that collects.Then it is sent into the steady state data judge module, in this module, the data of being gathered are screened, the exceptional value that eliminating is run in measuring process, make it to meet the requirement of stable state, when guaranteeing that these data are used for the diagnostic equation group, can obtain accurate diagnostic results.
Fault detection module detects the data through the stable state screening, judges whether intrasystem sensor fault (judge on the whole, and specifically do not judge out of order occurrence positions, size etc.) has taken place.If there is not fault, then by output module output result.If the fault of detecting in two kinds of situation, if detect the failure of removal of break down into sensor, is then directly given output module output the result; Otherwise, the data that drifting fault takes place are sent into memory module preserve.
Fault detection module will provide the signal of " breaking down " then, start fault diagnosis module simultaneously.Diagnostic module calls the fault data of the accumulation in the memory module, diagnoses according to the conservation of energy and the principle of mass conservation of system, diagnoses out the size of sensor breaks down in the system quantity, position and fault.Then diagnostic result is delivered to the confidence level judge module, the result's that diagnostic module is diagnosed out accuracy is estimated.The data of by data recovery module the sensor that breaks down being surveyed according to diagnostic result and confidence level thereof are recovered then, and reject fault data.At last, the result is delivered to output module output.
Adopting " online system failure diagnosis of central air conditioning water system temperature and flow sensor " to carry out sensor fault (failure of removal and drifting fault) diagnosis has the following advantages:
The first, metrizability.Method proposed by the invention not only can be judged the position of out of order generation, and can calculate the size that fault takes place, thereby Fault Diagnosis and reparation can be carried out in the BMS system, has improved the automatization level of fault diagnosis greatly.
The second, multiple spot.Promptly can diagnose out the fault of all temperature sensors in the system simultaneously, this is that a lot of diagnostic methods are incomparable.
The 3rd, in linearity.Can carry out on-line fault diagnosis to the sensor of system, thereby shorten interval between diagnosis, save diagnostic fees usefulness, retrieve economic loss.
Description of drawings:
Fig. 1 is the logical construction schematic diagram of sensor fault diagnosis of the present invention system.
Among the figure, 1-data acquisition module, 2-filtering noise module, 3-steady state data judge module, 4-fault detection module, 5-memory module, 6-fault diagnosis module, the confidence level judge module of 7-diagnostic result, 8-data recovery module, 9-output module.
The specific embodiment:
Below in conjunction with accompanying drawing concrete enforcement of the present invention is further described.
As shown in Figure 1, the present invention mainly comprises data acquisition module 1, filtering noise module 2, steady state data judge module 3, fault detection module 4, memory module 5, fault diagnosis module 6, the confidence level judge module 7 of diagnostic result, data recovery module 8 and output module 9.
The output of data acquisition module 1 is electrically connected with the input of filtering noise module 2, the output of filtering noise module 2 is electrically connected with the input of steady state data judge module 3, the output of steady state data judge module 3 is electrically connected with the input of fault detection module 4, the output of fault detection module 4 is electrically connected with the input of memory module 5, the output of memory module 5 is electrically connected with the input of fault diagnosis module 6, fault diagnosis module 6 outputs are electrically connected with the input of the confidence level judge module 7 of diagnostic result, the output of the confidence level judge module 7 of diagnostic result is electrically connected with the input of data recovery module 8, and the input of the output of data recovery module 8 and output module 9 is electrically connected.
Claims (1)
1. the online system failure diagnosis of central air conditioning water system temperature and flow sensor, comprise data acquisition module (1), filtering noise module (2), steady state data judge module (3), fault detection module (4), memory module (5), fault diagnosis module (6), the confidence level judge module (7) of diagnostic result, data recovery module (8) and output module (9), it is characterized in that, the output of data acquisition module (1) is electrically connected with the input of filtering noise module (2), the output of filtering noise module (2) is electrically connected with the input of steady state data judge module (3), the output of steady state data judge module (3) is electrically connected with the input of fault detection module (4), the output of fault detection module (4) is electrically connected with the input of memory module (5), the output of memory module (5) is electrically connected with the input of fault diagnosis module (6), fault diagnosis module (6) output is electrically connected with the input of the confidence level judge module (7) of diagnostic result, the output of the confidence level judge module (7) of diagnostic result is electrically connected with the input of data recovery module (8), and the input of the output of data recovery module (8) and output module (9) is electrically connected.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200410017182 CN1256550C (en) | 2004-03-25 | 2004-03-25 | On-line fault diagnosis system for centarl air conditioner water system temp and flow sensor |
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| Application Number | Priority Date | Filing Date | Title |
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| CN 200410017182 CN1256550C (en) | 2004-03-25 | 2004-03-25 | On-line fault diagnosis system for centarl air conditioner water system temp and flow sensor |
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| Publication Number | Publication Date |
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| CN1563827A CN1563827A (en) | 2005-01-12 |
| CN1256550C true CN1256550C (en) | 2006-05-17 |
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| CN 200410017182 Expired - Fee Related CN1256550C (en) | 2004-03-25 | 2004-03-25 | On-line fault diagnosis system for centarl air conditioner water system temp and flow sensor |
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Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4337923B2 (en) | 2007-09-27 | 2009-09-30 | ダイキン工業株式会社 | Device monitoring device and remote monitoring system |
| WO2012050474A1 (en) | 2010-10-11 | 2012-04-19 | General Electric Company | Systems, methods, and apparatus for detecting shifts in redundant sensor signals |
| US20130197849A1 (en) * | 2010-10-11 | 2013-08-01 | General Electric Company | Systems, methods, and apparatus for detecting irregular sensor signal noise |
| KR20120046821A (en) * | 2010-10-27 | 2012-05-11 | 파웰테크윈주식회사 | Apparatus and method for self-diagnosing the status of any kind of sensors |
| CN104765354B (en) * | 2014-01-10 | 2018-02-09 | 北京博锐尚格节能技术股份有限公司 | A kind of method for diagnosing faults, the apparatus and system of sensor and executive component |
| CN106123201A (en) * | 2016-06-13 | 2016-11-16 | 珠海格力电器股份有限公司 | Air-conditioning and fault detection method thereof and device |
| CN112556087B (en) * | 2020-11-20 | 2021-12-10 | 珠海格力电器股份有限公司 | Unit fault diagnosis method and device and controller |
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