CN110765604B - Method and system for evaluating equipment state under operation condition and storage medium - Google Patents
Method and system for evaluating equipment state under operation condition and storage medium Download PDFInfo
- Publication number
- CN110765604B CN110765604B CN201910971512.5A CN201910971512A CN110765604B CN 110765604 B CN110765604 B CN 110765604B CN 201910971512 A CN201910971512 A CN 201910971512A CN 110765604 B CN110765604 B CN 110765604B
- Authority
- CN
- China
- Prior art keywords
- equipment
- sub
- layer
- minimum
- sensor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 26
- 238000003860 storage Methods 0.000 title claims abstract description 10
- 238000013139 quantization Methods 0.000 claims abstract description 26
- 238000011156 evaluation Methods 0.000 claims abstract description 14
- 230000006870 function Effects 0.000 claims description 21
- 238000012216 screening Methods 0.000 claims description 16
- 238000004804 winding Methods 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 5
- 238000005461 lubrication Methods 0.000 claims description 3
- 239000003638 chemical reducing agent Substances 0.000 description 15
- 238000012544 monitoring process Methods 0.000 description 6
- 239000010687 lubricating oil Substances 0.000 description 4
- 238000012545 processing Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000003921 oil Substances 0.000 description 2
- 238000011158 quantitative evaluation Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 244000309464 bull Species 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The invention discloses a method, a system and a storage medium for evaluating equipment states under an operation condition, wherein the method is characterized in that firstly, an equipment hierarchy model comprising an equipment layer, a sub-component layer and a sensor layer is constructed based on equipment to be evaluated, then real-time original data of the equipment under the operation condition are obtained through the sensor layer, the original data are quantized by using a quantization function in the sensor layer, the quantized data are screened layer by layer through the sub-component layer, the sub-equipment layer and the equipment layer, finally, the screened minimum quantized data are judged in the equipment layer, and a characteristic value is output, so that the equipment under the operation condition is in a normal state, an early warning state, an alarm state or a fault state. The evaluation method provided by the invention has the advantages of small calculated amount, accurate obtained result and capability of evaluating the equipment state in real time.
Description
Technical Field
The invention relates to the technical field of equipment state evaluation, in particular to an equipment state evaluation method and system under an operation condition and a storage medium.
Background
The electromechanical equipment is affected by mechanical, electrical, environmental and other factors in the operation process, and the operation state of the electromechanical equipment has the characteristics of complexity, variability and the like, and the traditional non-manufacturing evaluation method cannot obtain accurate and reliable evaluation results.
In practical production applications, a status monitoring system (CMS) is often provided to monitor the vibration, electrical quantity, temperature, etc. of the rotating equipment and to alarm the status. Only in terms of temperature monitoring, the temperature of each bearing and the temperature of each stator at the same rotating speed change along with the change of the ambient temperature; under the same ambient temperature, each temperature value also changes along with the change of the rotating speed; and the traditional temperature monitoring alarm value adopts a uniform static alarm threshold value, and the static alarm standard can not accurately reflect the operation condition of the equipment.
At present, a general equipment state evaluation index system and a general quantitative evaluation standard are not formed in the state quantitative evaluation method for the electromechanical equipment. Therefore, it is necessary to research an applicable and reliable equipment state quantization model and an evaluation method, and comprehensively reflect equipment state information, so as to implement quantization evaluation of equipment state, and improve the accuracy of equipment state alarm and the operation safety of equipment.
Disclosure of Invention
The invention provides a method, a system and a storage medium for evaluating equipment states under an operation condition, which are used for overcoming the defects that the operation condition of equipment cannot be accurately reflected in the prior art and the like, and realizing real-time and accurate monitoring of the operation condition of the equipment under the operation condition.
In order to achieve the above purpose, the present invention provides a method for evaluating a device state under an operating condition, including the following steps:
s1: constructing an equipment hierarchy model based on equipment to be evaluated and sub-equipment, sub-components and sensors contained in the equipment to be evaluated; the equipment hierarchy model comprises an equipment layer, a sub-component layer and a sensor layer;
s2: acquiring real-time original data of equipment under an operation condition through a sensor layer, and quantizing the original data by utilizing a quantization function input in advance in the sensor layer; the quantization is to quantize the original data all within the range of [0,1 ];
s3: inputting quantized data into a sub-component layer, screening out minimum quantized data corresponding to each sub-component in the equipment by utilizing a minimum value principle input in the sub-component layer in advance, and inputting the screened minimum quantized data corresponding to each sub-component into the sub-equipment layer;
s4: screening out the minimum quantized data corresponding to each piece of equipment by utilizing a minimum value principle input in advance in the piece of equipment layer, and inputting the screened minimum quantized data corresponding to each piece of equipment into the equipment layer;
s5: screening out minimum quantized data corresponding to the equipment by utilizing a minimum value principle input in the equipment layer in advance; and judging the minimum quantized data corresponding to the equipment by utilizing a judging function input in advance by the equipment layer, outputting a characteristic value, and judging whether the equipment is in a normal state, an early warning state, an alarm state or a fault state under the operating condition according to the characteristic value.
In order to achieve the above object, the present invention further provides a system for evaluating a state of a device under an operating condition, including a processor and a memory, where the memory stores a program for evaluating a state of a device under an operating condition, and the steps of the method are executed when the processor runs the program for evaluating a state of a device under an operating condition.
To achieve the above object, the present invention also proposes a computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method described above.
Compared with the prior art, the invention has the beneficial effects that:
the equipment state evaluation method under the operation condition comprises the steps of firstly constructing an equipment layer model comprising an equipment layer, a sub-component layer and a sensor layer based on equipment to be evaluated, then acquiring real-time original data of the equipment under the operation condition through the sensor layer, carrying out quantization processing on the original data by utilizing a quantization function in the sensor layer, screening the quantized data layer by layer through the sub-component layer, the sub-equipment layer and the equipment layer, finally judging the screened minimum quantized data in the equipment layer, outputting a characteristic value, and judging whether the equipment is in a normal state, an early warning state, an alarm state or a fault state under the operation condition according to the characteristic value. The evaluation method provided by the invention divides the equipment to be evaluated into four layers of the sensor, the sub-component, the sub-equipment and the equipment by constructing the equipment layer model, and takes all scattered components in the equipment into consideration by the layering, so that the comprehensive monitoring of all the components of the equipment can be realized, and compared with the existing method which only considers the core part in the components of the equipment, the evaluation result obtained by comprehensively considering all the components of the equipment is more accurate; however, the comprehensive consideration of all components of the equipment can lead to a significant increase in calculation amount, and if the calculation amount can be significantly reduced through layer-by-layer analysis and screening of the sub-component layers, the sub-equipment layers and the equipment layers; meanwhile, data which are not originally in an order of magnitude are all quantized to be in the range of [0,1] through quantization processing, so that data comparison is facilitated; then, the method of the invention obtains the original data in real time through the sensor layer, thereby realizing the real-time monitoring of the equipment state under the operating condition; finally, the method monitors all sensors, sub-components and sub-equipment in the equipment, considers all components of the equipment and has the same weight of all components, so that the state of the equipment under the operating condition can be obtained more accurately. In addition, the method is suitable for evaluating the states of various electromechanical devices.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for evaluating equipment status under an operating condition provided by the invention;
FIG. 2 is an exploded view of the device under evaluation in an embodiment;
FIG. 3 is a graph of the quantization function of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In addition, the technical solutions of the embodiments of the present invention may be combined with each other, but it is necessary to be based on the fact that those skilled in the art can implement the technical solutions, and when the technical solutions are contradictory or cannot be implemented, the combination of the technical solutions should be considered as not existing, and not falling within the scope of protection claimed by the present invention.
The drugs/reagents used are all commercially available without specific description.
The embodiment provides a method for evaluating equipment states under an operation condition, which comprises the following steps:
s1: constructing an equipment hierarchy model based on equipment to be evaluated and sub-equipment, sub-components and sensors contained in the equipment to be evaluated; the equipment hierarchy model comprises an equipment layer, a sub-component layer and a sensor layer;
the equipment to be evaluated in the embodiment is shown in fig. 1, and the equipment comprises three pieces of equipment, namely a motor, a speed reducer and a grinding roller;
the motor comprises four sub-components, namely system data, a free end, a driving end and a winding;
the system data includes data sensors; the free end comprises a bearing temperature rise sensor and a bearing vibration sensor; the driving end comprises a bearing temperature rise sensor and a bearing vibration sensor; the winding comprises a winding temperature rise sensor;
the speed reducer comprises four sub-components of a speed reducer bearing bush, a speed reducer input shaft, a thrust bearing and a large gear ring;
the speed reducer shaft bushing comprises a bearing bush temperature rise sensor and a lubricating oil temperature sensor; the speed reducer input shaft comprises a bearing temperature rise sensor and a bearing vibration sensor; the thrust bearing comprises a bearing vibration sensor; the large gear ring comprises a bearing vibration sensor;
the grinding roller comprises a left grinding roller and a right grinding roller;
the left grinding roller comprises a bearing vibration sensor; the right grinding roller comprises a bearing vibration sensor.
It should be noted that, because of considering the sizes of the sub-components, possible damage to the sensors, and the like, in practice, the number of each type of sensor corresponding to each sub-component is generally greater than or equal to 1, for example, in this embodiment, the system data includes data sensors, and in practice, four data sensors are set in the system data; however, in the invention, the number of each type of sensor of each sub-component is 1, and the specific processing method is as follows:
preprocessing the data collected by the four data sensors, including removing data with obvious anomalies, and then selecting an average value of the rest data or selecting the minimum value in the rest data as the collected original data. The minimum value in the rest data is selected as the acquired original data.
Preferably, in the step S1, the device hierarchy model is:
device layer: d= (SD 1, SD2, SD3, … SDm);
sub-equipment layer: sdi= (P1, P2, P3, … Pn);
sub-component layer: pa= (V1, V2, V3, … Vr);
sensor layer: vo= (xo);
wherein: d represents equipment; m is the number of devices comprising sub-devices; SDi represents the i-th child device; n is the number of sub-components that a certain sub-device contains; pa represents the a-th sub-component; r is the number of sensors that a certain sub-component contains; vo represents the o-th sensor; xo is data collected by the o-th sensor.
In the present embodiment of the present invention,
device layer: d= (motor, speed reducer, grinding roller);
sub-equipment layer: SD 1= (system data, free end, drive end, winding);
SD 2= (reducer bearing, reducer input shaft, thrust bearing, bull gear);
SD 3= (left grinding roller, right grinding roller);
sub-component layer: p1= (data sensor);
p2= (bearing temperature rise sensor, bearing vibration sensor);
p3= (bearing temperature rise sensor; bearing vibration sensor);
p4= (winding temperature rise sensor);
p5= (bearing shell temperature rise sensor, lubricating oil temperature sensor);
p6= (bearing temperature rise sensor, bearing vibration sensor);
p7= (bearing vibration sensor);
p8= (bearing vibration sensor);
p9= (bearing vibration sensor);
p10= (bearing vibration sensor);
sensor layer: v1= (data sensor); v2= (bearing temperature rise sensor); v3= (bearing vibration sensor); v4= (bearing temperature rise sensor); v5= (bearing vibration sensor); v6= (winding temperature rise sensor); v7= (bearing shell temperature rise sensor); v8= (lubrication oil temperature sensor); v9= (bearing temperature rise sensor); v10= (bearing vibration sensor); v11= (bearing vibration sensor); v12= (bearing vibration sensor); v13= (bearing vibration sensor); v14= (bearing vibration sensor).
S2: acquiring real-time original data of equipment under an operation condition through a sensor layer, and quantizing the input original data by utilizing a quantization function input in advance in the sensor layer; the quantization is to quantize the input original data to be in the range of [0,1 ];
the data which is not in an order of magnitude originally is quantized to the range of [0,1] through quantization processing, so that the comparison of the data is facilitated.
Preferably, the raw data are data taken by a sensor under the operating condition of the equipment; the real-time raw data includes: voltage, current, power, flow, bearing temperature rise, bearing vibration, winding temperature rise, lubrication oil temperature, pressure data, etc., are included within the scope of the present invention as long as the raw data can be collected by providing a sensor.
In this embodiment, the raw data is composed of data collected by all the sensors V1 to V14.
Preferably, as shown in fig. 2, the quantization function is:
y＝0，＞F；
wherein: x is the data collected by a certain sensor; w is the early warning threshold of x; a is the alarm threshold of x; f is the fault threshold of x.
In the embodiment, the acquired data acquired by all the sensors including V1 to V14 are quantized one by one in the quantization function to obtain 14 quantized data in the range of [0,1 ];
preferably, the early warning threshold, the alarm threshold and the fault threshold are obtained according to statistics and experience of historical operation data of the equipment, if the average value is E and the variance is sigma obtained by counting the historical data of a certain state variable in a certain period of time, the early warning threshold of the state variable is E+3 x sigma, the alarm threshold is E+6 x sigma, and the fault threshold is a mandatory value specified by industry standards.
S3: inputting quantized data into a sub-component layer, screening out minimum quantized data corresponding to each sub-component in the equipment by utilizing a minimum value principle input in the sub-component layer in advance, and inputting the screened minimum quantized data corresponding to each sub-component into the sub-equipment layer;
aiming at a plurality of sub-components comprising a plurality of sensors, screening out minimum quantized sensor data corresponding to each sub-component by adopting a minimum value principle one by one for each sub-component, and taking the quantized value of the sensor as the quantized value of the sub-component to which the sensor belongs; but only comprises a plurality of sub-components of one sensor, and directly reserves the quantized data corresponding to the acquired data of the sensor.
Preferably, the minimum value principles input in advance in the device layer, the sub-device layer and the sub-component layer are respectively:
sub-component layer: sx (Pa) =minimum [ Sx (V1), sx (V2), sx (V3) & Sx (Vr) ];
sub-equipment layer: sx (SDi) =minimum [ Sx (P1), sx (P2), sx (P3)..sx (Pn) ];
device layer: sx (D) =minimum [ Sx (SD 1), sx (SD 2), sx (SD 3) & Sx (SDm) ];
wherein: minimum is a screening Minimum function; sx (Vr) is a value obtained by quantifying original data collected by an (r) th sensor, and r is the number of sensors contained in an (a) th sub-component; sx (Pa) is the minimum quantization value corresponding to the a-th sub-component; sx (Pn) is the minimum quantized value corresponding to the nth sub-component, and n is the number of sub-components contained in the ith sub-device; sx (SDi) is a minimum quantization value corresponding to the ith sub-device; sx (SDm) is the minimum quantized value corresponding to the mth sub-device, and m is the number of sub-devices contained in the device; sx (D) is the minimum quantization value corresponding to the device.
The state index of the sub-component with the worst state is used as the state index of the sub-equipment, and the state index of the sub-equipment with the worst state is used as the state index of the equipment.
In this embodiment, for P2, P3, P5 and P6 comprising a plurality of sensors,
p2= (bearing temperature rise sensor, bearing vibration sensor), comparing the quantized data of the bearing temperature rise sensor and the bearing vibration sensor, selecting smaller data;
p3= (bearing temperature rise sensor; bearing vibration sensor), comparing the quantized data of the bearing temperature rise sensor and the bearing vibration sensor, selecting smaller data;
p5= (bearing bush temperature rise sensor, lubricating oil temperature sensor), comparing the quantized data of the bearing bush temperature rise sensor and the lubricating oil temperature sensor, and selecting smaller data;
p6= (bearing temperature rise sensor, bearing vibration sensor), comparing the quantized data of the bearing temperature rise sensor and the bearing vibration sensor, selecting smaller data;
other sub-components P1, P4, P7, P8, P9 and P10 containing only one sensor directly retain quantized data corresponding to the acquired data of the corresponding sensor.
S4: screening out the minimum quantized data corresponding to each piece of equipment by utilizing a minimum value principle input in advance in the piece of equipment layer, and inputting the screened minimum quantized data corresponding to each piece of equipment into the equipment layer;
aiming at a plurality of pieces of sub-equipment comprising a plurality of sub-components, screening out the minimum quantized data corresponding to each piece of sub-equipment by adopting a minimum value principle one by one; and a plurality of sub-devices which only comprise one sub-component directly reserve the quantized data corresponding to the sub-component.
In the present embodiment, for the sub-devices SD1, SD2 and SD3 including a plurality of sub-components,
SD 1= (system data, free end, drive end, winding), comparing the system data, free end, drive end and the quantized data corresponding to the winding, selecting the smaller data;
SD 2= (speed reducer bearing, speed reducer input shaft, thrust bearing, large ring gear), comparing the quantized data corresponding to the speed reducer bearing, speed reducer input shaft, thrust bearing and large ring gear, selecting smaller data;
SD 3= (left grinding roller, right grinding roller), comparing quantized data corresponding to the left grinding roller and the right grinding roller, and selecting smaller data.
S5: screening out minimum quantized data corresponding to the equipment by utilizing a minimum value principle input in the equipment layer in advance; and judging the minimum quantized data corresponding to the equipment by utilizing a judging function input in advance by the equipment layer, outputting a characteristic value, and judging whether the equipment is in a normal state, an early warning state, an alarm state or a fault state under the operating condition according to the characteristic value.
Aiming at equipment comprising a plurality of sub-equipment, screening out minimum quantized data corresponding to the equipment by adopting a minimum value principle; and then judging in the minimum quantized data carried into a judging function, and outputting a characteristic value.
In this embodiment, for a device D comprising a plurality of sub-devices,
d= (motor, speed reducer, grinding roller), comparing the quantized data corresponding to the motor, speed reducer and grinding roller, and selecting smaller data.
Preferably, the judging function is:
wherein: sx (D) is the minimum quantization value corresponding to the device.
In this embodiment, the selected smaller data is brought into the decision function to obtain the characteristic value, so as to obtain whether the device D is in a normal state, an early warning state, an alarm state or a fault state.
Preferably, the segment values 1.0, 0.9 and 0.7 in the judging function are respectively obtained by carrying the early warning threshold W, the warning threshold a and the fault threshold F into the quantization function in S2.
The embodiment also provides a system for evaluating the equipment state under the operation condition, which comprises a processor and a storage, wherein the storage stores an equipment state evaluation program under the operation condition, and the steps of the method are executed when the processor runs the equipment state evaluation program under the operation condition.
The present embodiment also proposes a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the method described above.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the invention, and all equivalent structural changes made by the description of the present invention and the accompanying drawings or direct/indirect application in other related technical fields are included in the scope of the invention.
Claims (9)
1. The equipment state evaluation method under the operating condition is characterized by comprising the following steps of:
s1: constructing an equipment hierarchy model based on equipment to be evaluated and sub-equipment, sub-components and sensors contained in the equipment to be evaluated; the equipment hierarchy model comprises an equipment layer, a sub-component layer and a sensor layer;
s2: acquiring real-time original data of equipment under an operation condition through a sensor layer, and quantizing the original data by utilizing a quantization function input in advance in the sensor layer; the quantization is to quantize the original data all within the range of [0,1 ];
s3: inputting quantized data into a sub-component layer, screening out minimum quantized data corresponding to each sub-component in the equipment by utilizing a minimum value principle input in the sub-component layer in advance, and inputting the screened minimum quantized data corresponding to each sub-component into the sub-equipment layer;
s4: screening out the minimum quantized data corresponding to each piece of equipment by utilizing a minimum value principle input in advance in the piece of equipment layer, and inputting the screened minimum quantized data corresponding to each piece of equipment into the equipment layer;
s5: screening out minimum quantized data corresponding to the equipment by utilizing a minimum value principle input in the equipment layer in advance; judging the minimum quantized data corresponding to the equipment by utilizing a judging function input in advance by the equipment layer, outputting a characteristic value, and judging whether the equipment is in a normal state, an early warning state, an alarm state or a fault state under the operating condition according to the characteristic value;
the minimum value principles input in advance in the equipment layer, the sub-equipment layer and the sub-component layer are respectively as follows:
sub-component layer: sx (Pa) =minimum [ Sx (V1), sx (V2), sx (V3) … Sx (Vr) ];
sub-equipment layer: sx (SDi) =minimum [ Sx (P1), sx (P2), sx (P3) … Sx (Pn) ];
device layer: sx (D) =minimum [ Sx (SD 1), sx (SD 2), sx (SD 3) … Sx (SDm) ];
wherein: minimum is a screening Minimum function; sx (Vr) is a value obtained by quantifying original data collected by an (r) th sensor, and r is the number of sensors contained in an (a) th sub-component; sx (Pa) is the minimum quantization value corresponding to the a-th sub-component; sx (Pn) is the minimum quantized value corresponding to the nth sub-component, and n is the number of sub-components contained in the ith sub-device; sx (SDi) is a minimum quantization value corresponding to the ith sub-device; sx (SDm) is the minimum quantized value corresponding to the mth sub-device, and m is the number of sub-devices contained in the device; sx (D) is the minimum quantization value corresponding to the device.
2. The method for evaluating a device state under an operating condition according to claim 1, wherein in S1, the device hierarchy model is:
device layer: d= (SD 1, SD2, SD3, … SDm);
sub-equipment layer: sdi= (P1, P2, P3, … Pn);
sub-component layer: pa= (V1, V2, V3, … Vr);
sensor layer: vo= (xo);
wherein: d represents equipment; m is the number of devices comprising sub-devices; SDi represents the i-th child device; n is the number of sub-components that a certain sub-device contains; pa represents the a-th sub-component; r is the number of sensors that a certain sub-component contains; vo represents the o-th sensor; xo is data collected by the o-th sensor.
3. The method for evaluating the state of equipment under the operating condition of claim 1, wherein in S2, the real-time raw data is data taken by a sensor under the operating condition of the equipment; the raw data includes: voltage, current, power, flow, bearing temperature rise, bearing vibration, winding temperature rise, lubrication oil temperature, and pressure data.
4. The method for evaluating a state of an apparatus under an operating condition according to claim 1, wherein in S2, the quantization function is:
y＝0，>F；
wherein: x is the data collected by a certain sensor; w is the early warning threshold of x; a is the alarm threshold of x; f is the fault threshold of x.
5. The method for evaluating the state of equipment under the operating condition of claim 4, wherein the early warning threshold, the alarm threshold and the fault threshold are obtained according to historical operating data statistics and experience of the equipment.
6. The method for evaluating a state of an apparatus under an operating condition according to claim 4, wherein in S5, the determination function is:
wherein: sx (D) is the minimum quantization value corresponding to the device.
7. The method for evaluating the state of equipment under the operating condition of claim 1, wherein the segment values 1.0, 0.9 and 0.7 in the judging function are respectively obtained by carrying an early warning threshold W, an alarm threshold a and a fault threshold F into the quantizing function in S2.
8. An operating condition device state evaluation system comprising a processor and a memory, wherein the memory stores an operating condition device state evaluation program, and wherein the steps of the method of any one of claims 1 to 7 are performed when the processor runs the operating condition device state evaluation program.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910971512.5A CN110765604B (en) | 2019-10-14 | 2019-10-14 | Method and system for evaluating equipment state under operation condition and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910971512.5A CN110765604B (en) | 2019-10-14 | 2019-10-14 | Method and system for evaluating equipment state under operation condition and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110765604A CN110765604A (en) | 2020-02-07 |
| CN110765604B true CN110765604B (en) | 2023-05-12 |
Family
ID=69331985
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910971512.5A Active CN110765604B (en) | 2019-10-14 | 2019-10-14 | Method and system for evaluating equipment state under operation condition and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110765604B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104574213A (en) * | 2015-01-14 | 2015-04-29 | 国家电网公司 | Evaluation method based on electric car charging equipment performance evaluation system |
| CN105117980A (en) * | 2015-08-24 | 2015-12-02 | 云南电网有限责任公司 | Power grid equipment state automatic evaluation method |
| EP3110166A1 (en) * | 2015-06-26 | 2016-12-28 | Airbus Operations GmbH | Mobile monitoring device and method of collecting sensor measurement data |
| CN207182403U (en) * | 2017-04-11 | 2018-04-03 | 广西电网有限责任公司电力科学研究院 | A kind of distribution net equipment state evaluation system management platform |
| CN108508786A (en) * | 2018-03-05 | 2018-09-07 | 昆明理工大学 | A kind of conduit running condition detection and assessment system and method |
| WO2019141411A1 (en) * | 2018-01-19 | 2019-07-25 | Robert Bosch Gmbh | Vehicle failure warning system and corresponding vehicle failure warning method |
-
2019
- 2019-10-14 CN CN201910971512.5A patent/CN110765604B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104574213A (en) * | 2015-01-14 | 2015-04-29 | 国家电网公司 | Evaluation method based on electric car charging equipment performance evaluation system |
| EP3110166A1 (en) * | 2015-06-26 | 2016-12-28 | Airbus Operations GmbH | Mobile monitoring device and method of collecting sensor measurement data |
| CN105117980A (en) * | 2015-08-24 | 2015-12-02 | 云南电网有限责任公司 | Power grid equipment state automatic evaluation method |
| CN207182403U (en) * | 2017-04-11 | 2018-04-03 | 广西电网有限责任公司电力科学研究院 | A kind of distribution net equipment state evaluation system management platform |
| WO2019141411A1 (en) * | 2018-01-19 | 2019-07-25 | Robert Bosch Gmbh | Vehicle failure warning system and corresponding vehicle failure warning method |
| CN108508786A (en) * | 2018-03-05 | 2018-09-07 | 昆明理工大学 | A kind of conduit running condition detection and assessment system and method |
Non-Patent Citations (3)
| Title |
|---|
| ZHAO Xusheng.Research on comprehensive early-warning technology of coal and gas outburst.《 Procedia Engineering》.2011,第26卷第2376-2382页. * |
| 尹凯 ; 笃峻 ; 葛立青 ; .关键绩效指标在变电站设备在线监测中的应用.电力系统保护与控制.2015,(第04期),第71-76页. * |
| 颜冰 ; 钱国超 ; 王科 ; 邹德旭 ; 徐肖伟 ; 陈俊生 ; .高压并联电抗器绝缘状态评估方法.高压电器.2018,(第08期),第237-242页. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110765604A (en) | 2020-02-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Saidi et al. | An integrated wind turbine failures prognostic approach implementing Kalman smoother with confidence bounds | |
| EP1902293B1 (en) | Interface module of an electric motor for calculating the service life of a bearing | |
| US20120035885A1 (en) | Method and apparatus for monitoring and analyzing vibrations in rotary machines | |
| DE102013102625B4 (en) | Device for monitoring the operation of a system asset and system with such a device | |
| DE102020100591A1 (en) | ERROR DETECTING DEVICE FOR DETECTING A PROBLEM WITH A PART OF A MACHINE | |
| US11544554B2 (en) | Additional learning method for deterioration diagnosis system | |
| Ekwaro-Osire et al. | Probabilistic prognostics and health management of energy systems | |
| CN113468721B (en) | Method for predicting residual life of gears and bearings in gear reduction box | |
| CN110823561B (en) | Method for monitoring fatigue life of key part of rolling mill transmission shaft system under unsteady state load in real time based on material model library | |
| DE102019205833A1 (en) | Machine health monitoring of rotating machinery | |
| Madhusudana et al. | Use of discrete wavelet features and support vector machine for fault diagnosis of face milling tool | |
| CN116861798B (en) | Online real-time residual life prediction method for vacuum dry pump based on XGBoost algorithm | |
| CN110765604B (en) | Method and system for evaluating equipment state under operation condition and storage medium | |
| CN115371988A (en) | Engineering machinery fault diagnosis method and system based on multi-feature fusion | |
| Gorjian et al. | Remaining useful life prediction of rotating equipment using covariate-based hazard models–Industry applications | |
| CN112069738B (en) | Electric steering engine residual life prediction method and system based on DBN and multilayer fuzzy LSTM | |
| Stefaniak et al. | Diagnostic features modeling for decision boundaries calculation for maintenance of gearboxes used in belt conveyor system | |
| DE102010005525A1 (en) | Method for condition monitoring of a machine and monitoring device therefor | |
| CN113642618B (en) | Method and equipment for training screw device state prediction model | |
| Jegadeeshwaran et al. | Method and apparatus for fault diagnosis of automobile brake system using vibration signals | |
| EP2894789A1 (en) | System and method of data compression | |
| CN113723732A (en) | State determination method and system for centrifugal pump | |
| Mehta et al. | Application of multi-scale fuzzy entropy for roller bearing fault detection and fault classification based on VPMCD | |
| Tajiani et al. | RUL prediction of bearings using empirical wavelet transform and Bayesian approach | |
| Liao et al. | Machine anomaly detection and diagnosis incorporating operational data applied to feed axis health monitoring |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20231214 Address after: Room 101-223, Building 1, Building 1, Changsha Otto Machinery Co., Ltd., No. 13 Huanlian Road, Changsha High tech Development Zone, Changsha City, Hunan Province, 410000 Patentee after: HUNAN VTALL INFORMATION TECHNOLOGY CO.,LTD. Address before: 410000 floor 44, shijixincheng, Xiangshang, middle Kaiyuan Road, Changsha County, Changsha City, Hunan Province Patentee before: YINHE ELECTRIC CO.,LTD. |
|
| TR01 | Transfer of patent right |