CN104808642A - Pump group automatic diagnosis method based on internet of things - Google Patents
Pump group automatic diagnosis method based on internet of things Download PDFInfo
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- CN104808642A CN104808642A CN201510081825.5A CN201510081825A CN104808642A CN 104808642 A CN104808642 A CN 104808642A CN 201510081825 A CN201510081825 A CN 201510081825A CN 104808642 A CN104808642 A CN 104808642A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0275—Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
- G05B23/0278—Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0208—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the configuration of the monitoring system
- G05B23/0216—Human interface functionality, e.g. monitoring system providing help to the user in the selection of tests or in its configuration
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Abstract
The invention relates to a pump group automatic diagnosis method based on the internet of things, and belongs to the technical field of equipment intelligent diagnosis. The method comprises 1) an internet of things based data acquisition and storage portion which refers to that sensors are installed at key measuring points, measured vibration values of the key measuring points are stored in a data application manager through a wired or wireless transmission mode, thereby realizing collection and unified management of data; 2) a data analyzing and processing portion which refers to that data analysis and processing is carried out on the collected data, characteristic values of the data are extracted, a fact value matching base is established, and fault analysis is carried out by using the measured data characteristics values; and 3) an expert system diagnosis portion which refers to that an expert diagnosis system is started, a corresponding task is selected, rules corresponding to the task are activated, and fact value matching is carried out on the activated rules by using the fact value matching base established by the characteristic values until a fault set is outputted. The method provided by the invention can realize real-time monitoring and diagnosis for a pump group, thereby being capable of mastering operating conditions and faults of the pump group in real time.
Description
Technical field
The invention belongs to equipment intelligent diagnosis technical field, relate to fault diagnosis expert system.
Background technology
Technology of Internet of things is by information sensing equipment, by all article connecting Internets, realizes Weigh sensor management.The core of technology of Internet of things and basis are Internet technologies, and be a kind of network technology of extension on Internet technology basis and expansion, its user side extends and extend between any article and article, carries out message exchange and communication.Group of pump automatic diagnosis based on Internet of Things utilizes Internet of Things thought, adopts in-circuit diagnostic system to be got up by the informations such as the vibration data of group of pump, utilize software systems to carry out unified treatment and analyses, reach the object of autodiagnosis.
The automatic diagnosis of group of pump is realized by expert system, expert system is as a branch of artificial intelligence, produce in phase early 1960s and grow up and become an emerging applied science, it is a kind of system of intelligence, use the computer model of mankind's expert reasoning to carry out the challenge needing expert to make explanations in the Coping with Reality world, and draw the conclusion of expert system.Since coming out towards the expert system MYCIN of diagnostic field from 1974, Knowledge based engineering diagnostic problem solving becomes a research focus in artificial intelligence.
Centrifugal pump is widely used in the industries such as refinery, oil recovery, electric power, metallurgy, and whether whether it normally run and directly affect enterprise and can keep the safety in production, and therefore, carry out fault diagnosis to centrifugal pump, preventer generation major accident tool is of great significance.The research such as the Wang Tao of Xihua Univ is based on the centrifugal pump fault diagnostic expert system of fuzzy technology, case and rule-based reasoning technology are applied in expert system by the Hu Zhongyu of Chongqing communication institute, Tay, Rough Set Technique is applied in expert system by Francis E.H, and the Jiang Zhinong of Beijing University of Chemical Technology etc. propose the fault diagnosis expert system of task based access control.For centrifugal pump rolling bearing fault diagnosis expert system, current research mainly concentrates on the research of expert system reasoning diagnostic method, comprise: Process Based, case-based reasioning, based on the inference method etc. that fuzzy model reasoning and the reasoning of Corpus--based Method method and multiple reasoning diagnostic method be combined with each other.
The centrifugal pump rolling bearing fault diagnosis expert system mentioned in the present invention is through the fault diagnosis expert system for centrifugal pump shaft system fault and rolling bearing fault thereof that the accumulation of diagnostic experiences for many years sums up on Process Based basis.
At present, traditional expert system is the expert system (Rule-Based Reasoning adopting Process Based, RBR), also known as production system, it can utilize abstract method, the experimental knowledge of expert in a certain field is summed up out, and is generalized into the rule that computing machine can receive.The general type of production rule is:
If< precondition collection >then< conclusion > (< rule degree of confidence >)
Wherein any model of precondition set representations and Data Matching, conclusion represents the integrated conclusion that immediately can draw of precondition.The expert system of Process Based is understood because its form of expression is simply easy to user, therefore becomes most important knowledge representation method.
But the diagnostic reasoning of the expert system of Process Based tree is very complicated, is not easy to understand and reads, revise difficulty simultaneously, tracing trouble is single, if when unit has various faults simultaneously, conventional diagnostic reasoning tree often can not a certain fault of accurate lock, and can fail to pinpoint a disease in diagnosis fault.
Summary of the invention
The object of the invention is the shortcoming overcoming prior art, provide a set of newly, can realize the method for group of pump self diagnosis easier and accurately.The method has easy understand, is convenient to safeguard amendment, can realize the advantages such as multi-fault Diagnosis.
The invention discloses a kind of group of pump automatic diagnosis method based on Internet of Things, comprise the steps:
1) image data, by wired sensor in-circuit diagnostic system or wireless senser in-circuit diagnostic system, gather the vibration data of the horizontal measuring point of pump pump drive end bearing, the vertical measuring point of pump drive end bearing, the horizontal measuring point of pump anti-drive end, the vertical measuring point of pump anti-drive end, stored in data application management device after data processing.
2) analyze data, extract eigenwert, the true value coupling storehouse of structure is to carry out fact value coupling to corresponding rule.
3) start expert system diagnosis, the rule that activation is relevant is gone forward side by side and is acted real assignment.
4) carry out initialization operation, the dependency rule this task related to and the fact, fault set are loaded in expert system internal memory.
5) the consequence collection of executing the task relevant, comprises rule, fault and true type.
6) travel through the rule being in state of activation in internal memory, if there is the rule of state of activation, then these rules are packaged as a rule set to be matched, otherwise jump to step 9).
7) obtain all true value of rule set to be matched, if existed facts is not assigned, then carry out assignment by Knowledge interaction interface.
8) treat matched rule collection and carry out pattern match, according to the result of coupling, perform the operation of corresponding consequence collection, after end of operation, jump to step 5).
9) travel through the fault being in generation state in internal memory, these faults are packaged as fault set, and these faults are the result of diagnosis.
Wherein, step 1) data acquisition comprises and includes line sensor in-circuit diagnostic system and wireless senser in-circuit diagnostic system.Wired sensor in-circuit diagnostic system includes linearly coupled sensor, data acquisition unit and data application management device composition.Wireless senser in-circuit diagnostic system is made up of wireless vibration sensor, radio network gateway, data application management device.Based on in-circuit diagnostic system, group of pump and control data corporation are coupled together with Internet of Things pattern, realize message exchange and the communication of group of pump and control data corporation.
Wherein, step 2) in for the eigenwert forming the required extraction in true value coupling storehouse include speed shake value, speed dominant frequency, speed often accompanies frequency, acceleration shakes value, acceleration dominant frequency, acceleration often accompany frequency, gIE Long-term change trend mode, gIE dominant frequency, gIE often accompany frequency, axial Long-term change trend mode, radial Long-term change trend mode.
Group of pump self-diagnosing method is the expert system based on traditional Process Based, have employed fault inference engine of expert system and realizes self diagnosis reasoning process.
The Rule Expression of the fault diagnosis expert system of tradition Process Based is R={A, CY, CN, T}, wherein:
A--represents regular former piece collection, is the Matching Model of one or more fact;
CY--represents the consequent collection that former piece is set up;
CN--represents the invalid consequent collection of former piece;
T--represents task belonging to rule, is the set T={R of multiple rule
i;
When former piece collection A is empty (A=null), represent that rule does not have Rule of judgment, directly perform the consequent collection set up, representation is R={NULL, CY, CN, T}, and regular executive mode is
Group of pump self-diagnosing method proposes a kind of concurrent fault diagnostic reasoning rule tree method.Concurrent fault diagnostic reasoning rule tree method is set up parallel for the inference rule of different faults tree, makes rule tree succinctly clear, easily reads.Be independent of each other between each diagnosis rule tree, make the foundation of the amendment of rule and new regulation more convenient.In addition, also 8 kinds of parallel pump fault diagnosis expert system diagnostic rule derivation trees are summarized for pump based on practical engineering experience for many years.
Accompanying drawing explanation
Fig. 1 group of pump Internet of Things process flow diagram
Fig. 2 vibration monitoring interface
Fig. 3 pump expert system diagnosis process flow diagram;
The expert system reasoning tree of Fig. 4 tradition Process Based
Fig. 5 rule-based reasoning block flow diagram
Fig. 6 imbalance fault diagnostic rule;
Fig. 7 misaligns Failure Diagnostic Code;
Fig. 8 rolling bearing fault diagnosis rule;
Fig. 9 bearing run off diagnostic rule;
Figure 10 cavitates Failure Diagnostic Code;
Figure 11 finds time Failure Diagnostic Code;
Figure 12 impeller and the eccentric diagnostic rule of pump case fault;
Figure 13 connects loosening diagnostic rule;
Embodiment
Below in conjunction with accompanying drawing, automatic diagnosis method of the present invention is described further.
As shown in Figure 3, Figure 4, flow process of the present invention comprises:
1) image data, by wired sensor in-circuit diagnostic system or wireless senser in-circuit diagnostic system, gathers the vibration data of the crucial measuring point of pump, stored in data application management device after data processing.
2) analyze data, extract eigenwert, the true value coupling storehouse of structure is to carry out fact value coupling to corresponding rule.
3) start expert system diagnosis, the rule that activation is relevant is gone forward side by side and is acted real assignment.
4) carry out initialization operation, the dependency rule this task related to and the fact, fault set are loaded in expert system internal memory.
5) the consequence collection of executing the task relevant, comprises rule, fault and true type.
6) travel through the rule being in state of activation in internal memory, if there is the rule of state of activation, then these rules are packaged as a rule set to be matched, otherwise jump to step 9).
7) obtain all true value of rule set to be matched, if existed facts is not assigned, then carry out assignment by Knowledge interaction interface.
8) treat matched rule collection and carry out pattern match, according to the result of coupling, perform the operation of corresponding consequence collection, after end of operation, jump to step 5).
9) travel through the fault being in generation state in internal memory, these faults are packaged as fault set, and these faults are the result of diagnosis.
Utilize accompanying drawing 7 rotor misalignment diagnosis rule to set for certain chemical enterprise rotating machinery unit rotor misalignment fault diagnosis case to be below further elaborated content of the present invention.
1) fault is misaligned
By be arranged on the horizontal measuring point of pump drive end bearing, the vertical measuring point of pump drive end bearing, the horizontal measuring point of pump anti-drive end, the vertical measuring point of pump anti-drive end sensor can Real-time Collection to unit coupled vibration data and be stored in data application management device, carry out after Treatment Analysis extracts eigenwert, obtaining vibrational waveform figure as shown in Figure 1 and spectrogram to data, and the eigenwerts such as speed dominant frequency can be extracted.Open expert diagnostic system, the task that activation is relevant and the rule corresponding to task are with true, it is then the true "Yes" of vibration alarming rule match because vibration speed value is excessive, the strictly all rules be connected with true "Yes" then can be activated after having mated, can find out that the eigenwert of speed dominant frequency is 2X by the data after accompanying drawing 2 processes, it can be then the true value " 2X " of rule " speed dominant frequency " coupling, activate coupled rule, for other rules be activated are as corresponding eigenwerts of coupling such as gIE values, activate and exit rule.Traversal is in the rule of state of activation, finds random coupled, then traversal is in the fault of state of activation, and find that misaligning fault is activated, export and misalign fault, then automatic diagnosis result is for misaligning fault.
2) imbalance fault
Open expert diagnostic system, the task that activation is relevant and the rule corresponding to task, with true, be then the true "Yes" of vibration alarming rule match because vibration speed value is excessive, then can activate the strictly all rules be connected with true "Yes" after having mated.For the true value " 1X " of rule " speed dominant frequency " coupling, activate coupled rule, for other rules be activated are as corresponding eigenwerts of coupling such as gIE values, activate and exit rule.Traversal is the rule that 1X is connected with speed dominant frequency, is activated " axial Long-term change trend mode " rule match fact value that " is less than 5% ".Activate coupled rule, traversal is in the rule of state of activation, finds random coupled, then traversal is in the fault of state of activation, and find that imbalance fault is activated, export imbalance fault, then automatic diagnosis result is imbalance fault.
3) rolling bearing fault
Open expert diagnostic system, the task that activation is relevant and the rule corresponding to task, with true, be then the true "Yes" of vibration alarming rule match because vibration acceleration value is excessive, then can activate the strictly all rules be connected with true "Yes" after having mated.For the true value of rule " gIE Long-term change trend mode " coupling " is greater than 5% ", activate coupled rule, for other rules be activated are as corresponding eigenwerts of coupling such as speed dominant frequencies, activate and exit rule.Traversal is greater than 5% strictly all rules be connected with gIE Long-term change trend mode, is activated " gIE composes dominant frequency " coupling true value " bearing fault characteristics frequency " fact value.Activate coupled rule, traversal is in the rule of state of activation, finds random coupled, then traversal is in the fault of state of activation, and find that rolling bearing fault is activated, export rolling bearing fault, then automatic diagnosis result is rolling bearing fault.
4) bearing run off fault
Open expert diagnostic system, the task that activation is relevant and the rule corresponding to task, with true, be then the true "Yes" of vibration alarming rule match because vibration acceleration value is excessive, then can activate the strictly all rules be connected with true "Yes" after having mated.For the true value of rule " gIE Long-term change trend mode " coupling " is greater than 5% ", activate coupled rule, for other rules be activated are as corresponding eigenwerts of coupling such as speed dominant frequencies, activate and exit rule.Traversal is greater than 5% strictly all rules be connected with gIE Long-term change trend mode, is activated " gIE composes dominant frequency " coupling true value " power frequency, frequency multiplication peak value " fact value, activates connected strictly all rules.For the corresponding eigenwert of other rule match be activated, activate and exit rule.For the true value of " gIE spectrum often accompanies frequency " rule match " industrial frequency harmonic " be activated, activate coupled strictly all rules, travel through the rule be activated, find random coupled, then traversal is in the fault of state of activation, find that bearing run off fault is activated, export bearing run off fault, then automatic diagnosis result is bearing run off fault.
5) cavitate fault
Open expert diagnostic system, the task that activation is relevant and the rule corresponding to task, with true, be then the true "Yes" of vibration alarming rule match because vibration acceleration value is excessive, then can activate the strictly all rules be connected with true "Yes" after having mated.For " acceleration dominant frequency " rule match " 300-2000Hz frequency band " fact value, activate rule connected with it, for other rules be activated are as corresponding eigenwerts of coupling such as speed dominant frequencies, activate and exit rule.Travel through the rule be activated, find random coupled, then traversal is in the fault of state of activation, finds that cavitation erosion fault is activated, exports cavitation erosion fault, then automatic diagnosis result is cavitation erosion fault.
6) to find time fault
Open expert diagnostic system, the task that activation is relevant and the rule corresponding to task, with true, be the true "Yes" of " the whether high report of vibration velocity " vibration alarming rule match, then can activate the strictly all rules be connected with true "Yes" after having mated.For " speed dominant frequency " rule match " 1X " fact value, other rules be activated, as corresponding eigenwerts of coupling such as speed dominant frequencies, activate and exit rule.For the true value "Yes" of " whether there is blade passing frequency " rule match be activated, activate rule connected with it, for other rules be activated are as corresponding eigenwerts of coupling such as speed dominant frequencies, activate and exit rule.Travel through the rule that is activated, find random coupled, then traversal is in the fault of state of activation, and the fault that finds to find time is activated, and export fault of finding time, then automatic diagnosis result is fault of finding time.
7) impeller and pump case eccentric or with impeller, fault that medium is relevant
Open expert diagnostic system, the task that activation is relevant and the rule corresponding to task, with true, be then the true "Yes" of vibration alarming rule match because vibration speed value is excessive, then can activate the strictly all rules be connected with true "Yes" after having mated.For " speed dominant frequency " rule match " 1X " fact value, other rules be activated, as corresponding eigenwerts of coupling such as speed dominant frequencies, activate and exit rule.For the true value "Yes" of " whether there is blade passing frequency " rule match be activated, activate rule connected with it, for other rules be activated are as corresponding eigenwerts of coupling such as speed dominant frequencies, activate and exit rule.Travel through the rule that is activated, find random coupled, then traversal is in the fault of state of activation, and the fault that finds to find time is activated, and export fault of finding time, then automatic diagnosis result is fault of finding time.
8) looseness fault is connected
Open expert diagnostic system, the task that activation is relevant and the rule corresponding to task, with true, be then the true "Yes" of vibration alarming rule match because vibration speed value is excessive, then can activate the strictly all rules be connected with true "Yes" after having mated.For " radial Long-term change trend mode " rule match true value that " is less than 5% ", activate coupled strictly all rules, other rules be activated are as corresponding eigenwerts of coupling such as speed dominant frequencies, and rule is exited in activation.For the true value of " speed dominant frequency " coupling " power frequency, 2X, accurately frequency multiplication " be activated, activate coupled strictly all rules, for other rules be activated are as corresponding eigenwerts of coupling such as speed dominant frequencies, activate and exit rule.For the true value of " speed often accompanies frequency " rule match " industrial frequency harmonic ", activate coupled strictly all rules, for other rules be activated are as corresponding eigenwerts of coupling such as speed dominant frequencies, activate and exit rule.Travel through the rule be activated, find random coupled, then traversal is in the fault of state of activation, and find that connecting looseness fault is activated, export and connect looseness fault, then automatic diagnosis result is fault of finding time.
Claims (4)
1., based on a group of pump automatic diagnosis method for Internet of Things, its feature comprises the steps:
1) image data, by wired sensor in-circuit diagnostic system or wireless senser in-circuit diagnostic system, gather the vibration data of the horizontal measuring point of pump pump drive end bearing, the vertical measuring point of pump drive end bearing, the horizontal measuring point of pump anti-drive end measuring point vertical with pump anti-drive end, stored in data application management device after data processing;
2) analyze data, extract eigenwert, the true value coupling storehouse of structure is to carry out fact value coupling to corresponding rule;
3) start expert system diagnosis, the rule that activation is relevant is gone forward side by side and is acted real assignment;
4) carry out initialization operation, the dependency rule this task related to and the fact, fault set are loaded in expert system internal memory;
5) the consequence collection of executing the task relevant, comprises rule, fault and true type;
6) travel through the rule being in state of activation in internal memory, if there is the rule of state of activation, then these rules are packaged as a rule set to be matched, otherwise jump to step 9);
7) obtain all true value of rule set to be matched, if existed facts is not assigned, then carry out assignment by Knowledge interaction interface;
8) treat matched rule collection and carry out pattern match, according to the result of coupling, perform the operation of corresponding consequence collection, after end of operation, jump to step 5);
9) travel through the fault being in generation state in internal memory, these faults are packaged as fault set, and these faults are the result of diagnosis.
2. method according to claim 1, is characterized in that: step 1) in wired sensor in-circuit diagnostic system include linearly coupled sensor, safety barrier, data acquisition unit and data application management device; Wireless senser in-circuit diagnostic system is made up of wireless vibration sensor, radio network gateway, data application management device; By wired sensor or wireless senser, gather the vibration data of the crucial measuring point of group of pump, after utilizing radio network gateway or data acquisition unit process, be stored in data application management device.
3. method according to claim 1 and 2, is characterized in that: step 2) in for the eigenwert forming the required extraction in true value coupling storehouse include speed shake value, speed dominant frequency, speed often accompanies frequency, acceleration shakes value, acceleration dominant frequency, acceleration often accompany frequency, gIE Long-term change trend mode, gIE dominant frequency, gIE often accompany frequency, axial Long-term change trend mode and radial Long-term change trend mode.
4. method according to claim 1-3 any one, is characterized in that: group of pump self-diagnosing method is the expert system based on Process Based, have employed fault inference engine of expert system and realizes self diagnosis reasoning process;
The Rule Expression of the fault diagnosis expert system of Process Based is R={A, CY, CN, T}, wherein:
A--represents regular former piece collection, is the Matching Model of one or more fact;
CY--represents the consequent collection that former piece is set up;
CN--represents the invalid consequent collection of former piece;
T--represents task belonging to rule, is the set T={R of multiple rule
i;
When former piece collection A is empty, represent that rule does not have Rule of judgment, directly perform the consequent collection set up, representation is R={NULL, CY, CN, T}, and regular executive mode is
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| CN115163513A (en) * | 2022-06-02 | 2022-10-11 | 北京和利时系统集成有限公司 | Fault diagnosis method and device for subway submersible sewage pump |
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