CN112836359A - Safety evaluation method for power supply and distribution equipment of cigarette production enterprise - Google Patents
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- 238000011156 evaluation Methods 0.000 title claims abstract description 42
- 238000009826 distribution Methods 0.000 title claims abstract description 26
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 18
- 235000019504 cigarettes Nutrition 0.000 title claims abstract description 14
- 238000005070 sampling Methods 0.000 claims abstract description 64
- 230000015556 catabolic process Effects 0.000 claims abstract description 17
- 238000006731 degradation reaction Methods 0.000 claims abstract description 17
- 238000000034 method Methods 0.000 claims abstract description 13
- 238000012544 monitoring process Methods 0.000 claims abstract description 11
- 238000004364 calculation method Methods 0.000 claims description 14
- 238000010438 heat treatment Methods 0.000 claims description 14
- 238000009529 body temperature measurement Methods 0.000 claims description 8
- 230000002159 abnormal effect Effects 0.000 claims description 3
- 230000007547 defect Effects 0.000 abstract description 2
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- 238000010586 diagram Methods 0.000 description 3
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- G—PHYSICS
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- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- 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
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- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/04—Power grid distribution networks
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- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/12—Timing analysis or timing optimisation
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Abstract
The invention provides a safety evaluation method for power supply and distribution equipment of a cigarette production enterprise. The method comprises the steps of utilizing a primary alarm temperature sequence and a secondary alarm temperature sequence set by power supply equipment and a load current sequence of the equipment, utilizing a dynamic time warping algorithm to calculate the similarity of the temperature sequence and the current sequence, and determining an equipment degradation threshold value and a fault threshold value. And taking the equipment temperature sequence measured by the online temperature measuring system and the load current sequence of the power supply and distribution equipment, calculating a similarity value by using a dynamic time warping algorithm, and comparing the similarity value with a set threshold value to realize effective evaluation of the safety of the power supply and distribution equipment. The method provided by the application does not need to transform data with different sampling rates, different monitoring quantities of the power supply and distribution system are comprehensively utilized, the defect that the accuracy of a single data or single criterion evaluation result is low is overcome, the accuracy of equipment power supply safety evaluation is improved, and the method has a good effect on the safety evaluation of the power supply and distribution equipment of the cigarette enterprises which are greatly changed by a production plan.
Description
Technical Field
The invention belongs to the field of cigarettes, and particularly relates to a safety evaluation method for power supply and distribution equipment of a cigarette production enterprise.
Background
Cigarette production enterprises are generally divided into main production workshops such as sorting, threshing and redrying, shredding and rolling, and other auxiliary workshops and departments, and are influenced by production plan change and different operation time, and heating conditions caused by different loads borne by power supply and distribution equipment and cables in different time periods are different.
In order to monitor the heating condition of equipment in operation, a temperature online monitoring system is introduced to monitor the temperature change condition of key equipment and main connection points. When the load changes, the load current flowing through the equipment is different, and the temperature data measured by the temperature monitoring system is also different. If only certain monitoring data is used for safety evaluation of equipment, the influence of measurement errors on evaluation results cannot be avoided, the reliability of the results is not high, and the problem of data reprocessing caused by different sampling rates has to be faced when various monitoring data are used for evaluation.
Disclosure of Invention
In order to comprehensively utilize the monitoring data of different sampling rates, improve the accuracy of equipment safety evaluation and ensure the safety of equipment operation, it is necessary to provide a safety evaluation method for comprehensive temperature and load current to improve the reliability of equipment safety evaluation.
In order to realize the purpose, the invention is realized by adopting the following technical scheme: the method comprises the following steps: step 1, respectively calculating similarity values by using an equipment load current sampling sequence and a set primary alarm and secondary alarm temperature sampling sequence to serve as an equipment degradation threshold value and a fault threshold value;
step 2, taking a temperature measurement sequence of a temperature on-line monitoring system of the power supply equipment, then taking a load current sampling sequence corresponding to a time window with the same length at the moment, and carrying out similarity calculation on the temperature sequence and the current sequence by utilizing a dynamic time warping algorithm;
and 3, comparing the calculation result with a set threshold value, thereby realizing the safety evaluation of the power supply and distribution equipment.
Preferably, in the step 1, a primary alarm temperature sampling sequence with the length of 10 minutes and a 10-minute equipment load current value sampling sequence are taken, a similarity value is calculated by using a dynamic time warping algorithm, and the similarity value is used as an equipment degradation threshold value; and (3) taking a secondary alarm temperature sampling sequence with the length of 10 minutes and a 10-minute equipment load current value sampling sequence, calculating a similarity value by using a dynamic time warping algorithm, and taking the similarity value as an equipment fault threshold value.
Preferably, the device degradation threshold calculation method is as follows: s101: acquiring a 10-minute primary alarm temperature sampling sequence:
Tset1＝(t′1,t′2···t′m)
wherein, Tset1For a set primary alarm temperature sequence, t' is a temperature value
S102: acquiring a 10-minute device load current value:
I＝(i1,i2···in)
wherein, I is the actual load current sampling current sequence of the equipment, and I is the actual load current value of the equipment.
S103: and calculating the similarity by using a dynamic time warping algorithm:
D1＝DTW(Tset1,I)
wherein D is1DTW is a dynamic time warping algorithm for similarity values of two sequences. Will D1As a device degradation threshold.
Preferably, the method for calculating the device failure threshold value is as follows: s201: acquiring a secondary alarm temperature sampling sequence with the length of 10 minutes:
Tset2＝(t″1,t″2···t″m)
wherein, Tset2Setting a secondary alarm temperature sequence, wherein t' is a temperature value;
s202: acquiring a 10-minute device load current value:
I＝(i1,i2···in)
wherein, I is the actual load current sampling current sequence of the equipment, and I is the actual load current value of the equipment;
s203: and calculating the similarity by using a dynamic time warping algorithm:
D2＝DTW(Tset2,I)
wherein D is2DTW is a dynamic time warping algorithm for similarity values of two sequences. Will D2As a device failure threshold.
7. Preferably, the step 2 uses a dynamic time warping algorithm to perform a similarity calculation method of the temperature sequence and the current sequence as follows: s301: obtaining a temperature sampling sequence of the online temperature measuring system with the length of 10 minutes:
T＝(t1,t2···tm)
wherein T is a heating temperature sampling sequence of actual operation of the equipment, and T is a temperature value;
s302: acquiring a 10-minute device actual load current sampling sequence:
I＝(i1,i2···in)
wherein, I is the actual load current sampling current sequence of the equipment, and I is the actual load current value of the equipment;
s303, carrying out error compensation on the temperature sampling sequence of the online temperature measurement system:
t0＝t+λε
wherein, t0For the compensated temperature value, t is the temperature sampling value of the temperature measuring system, and lambda epsilon is the linear combination of various errors;
s304: calculating the similarity value of the actual operation heating temperature sampling sequence and the actual load current sampling sequence of the equipment by using a dynamic time warping algorithm:
D＝DTW(T0,I)
wherein D is the similarity value of two sequences, DTW is the dynamic time warping algorithm, T0Is an error compensated temperature sequence.
Preferably, the step 3 compares the calculation result with a set threshold, so as to implement the safety evaluation method of the power supply and distribution equipment as follows: s305: respectively reacting D with D1And D2Comparing, if:
D＜D1
the equipment safety evaluation result is as follows: the power supply equipment is in a normal operation state and does not need to be processed, if:
D1＜D＜D2
the equipment safety evaluation result is as follows: the abnormal heating condition has appeared in equipment or cable joint department, is in the degradation state, needs to strengthen and patrols and examines, and the check of stopping power after production, if:
D＞D2
the equipment safety evaluation result is as follows: the heating condition of the equipment or the cable joint is far beyond the normal operation state, and the equipment or the cable joint needs to be immediately switched to standby equipment.
The invention has the beneficial effects that:
data with different sampling rates do not need to be converted, different monitoring quantities of the power supply and distribution system are comprehensively utilized, the defect that the accuracy of a single data or single criterion evaluation result is low is overcome, the accuracy of equipment power supply safety evaluation is improved, and the method has a good effect on the safety evaluation of the power supply and distribution equipment of the cigarette enterprises which are greatly changed by production plans.
Drawings
Fig. 1 is a schematic flow chart of calculating the degradation threshold of the device according to the present invention.
Fig. 2 is a schematic flow chart of the calculation of the fault threshold of the device according to the invention.
FIG. 3 is a schematic diagram of a safety evaluation process of the inventive apparatus.
Detailed Description
Reference will now be made in detail to embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following examples do not represent all embodiments consistent with the present application, but are merely examples of systems and methods consistent with aspects of the present application, as detailed in the claims.
Respectively calculating similarity values by using the equipment load current sampling sequence and the set primary alarm and secondary alarm temperature sampling sequence to serve as an equipment degradation threshold value and a fault threshold value; taking a temperature measurement sequence of a temperature online monitoring system of the power supply equipment, then taking a load current sampling sequence corresponding to a time window with the same length at the moment, and carrying out similarity calculation on the temperature sequence and the current sequence by utilizing a dynamic time warping algorithm; and comparing the calculation result with a set threshold value, thereby realizing the safety evaluation of the power supply and distribution equipment.
And taking a primary alarm temperature sampling sequence with the length of 10 minutes and a 10-minute equipment load current value sampling sequence, calculating a similarity value by using a dynamic time warping algorithm, and taking the similarity value as an equipment degradation threshold value.
And (3) taking a secondary alarm temperature sampling sequence with the length of 10 minutes and a 10-minute equipment load current value sampling sequence, calculating a similarity value by using a dynamic time warping algorithm, and taking the similarity value as an equipment fault threshold value.
The method comprises the steps of taking a temperature measurement sequence of a temperature online monitoring system of certain power supply equipment or a cable, compensating errors caused by the accuracy of the measured equipment, the measurement system, the temperature measurement distance, background noise and environmental temperature change of the actually measured temperature sequence, then taking a load current sampling sequence corresponding to a time window with the same length at the moment, and calculating the similarity value of the temperature sampling sequence and the load current sampling sequence by utilizing a dynamic time warping algorithm.
And comparing the similarity value with the calculated threshold value, thereby completing the safety evaluation of the power supply and distribution equipment. Example 1:
s1: referring to fig. 1, a schematic diagram of a degradation threshold calculation flow of a power supply and distribution equipment safety evaluation method for performing similarity determination by using a dynamic time warping algorithm according to the present application is shown, including the following steps:
s101: acquiring a 10-minute primary alarm temperature sampling sequence:
Tset1＝(t′1,t′2···t′m)
wherein, Tset1For the set primary alarm temperature sequence, t' is a temperature value.
S102: acquiring a 10-minute device load current value:
I＝(i1,i2···in)
wherein, I is the actual load current sampling current sequence of the equipment, and I is the actual load current value of the equipment.
S103: and calculating the similarity by using a dynamic time warping algorithm:
D1＝DTW(Tset1,I)
wherein D is1DTW is a dynamic time warping algorithm for similarity values of two sequences. Will D1As a device degradation threshold.
S2: referring to fig. 2, a schematic diagram of a fault threshold calculation process of a power supply and distribution equipment safety evaluation method for performing similarity determination by using a dynamic time warping algorithm according to the present application is shown, which includes the following steps:
s201: acquiring a secondary alarm temperature sampling sequence with the length of 10 minutes:
Tset2＝(t″1,t″2···t″m)
wherein, Tset2And t' is a temperature value for the set secondary alarm temperature sequence.
S202: acquiring a 10-minute device load current value:
I＝(i1,i2···in)
wherein, I is the actual load current sampling current sequence of the equipment, and I is the actual load current value of the equipment.
S203: and calculating the similarity by using a dynamic time warping algorithm:
D2＝DTW(Tset2,I)
wherein D is2DTW is a dynamic time warping algorithm for similarity values of two sequences. Will D2As a device failure threshold.
S3: referring to fig. 3, a schematic flow chart of a power supply and distribution equipment safety evaluation method for similarity determination by using a dynamic time warping algorithm according to the present application includes the following steps:
8, S301: obtaining a temperature sampling sequence of the online temperature measuring system with the length of 10 minutes:
T＝(t1,t2···tm)
wherein T is a heating temperature sampling sequence of actual operation of the equipment, and T is a temperature value;
s302: acquiring a 10-minute device actual load current sampling sequence:
I＝(i1,i2···in)
wherein, I is the actual load current sampling current sequence of the equipment, and I is the actual load current value of the equipment;
s303, carrying out error compensation on the temperature sampling sequence of the online temperature measurement system:
t0＝t+λε
wherein, t0For the compensated temperature value, t is the temperature sampling value of the temperature measuring system, and lambda epsilon is the linear combination of various errors;
s304: calculating the similarity value of the actual operation heating temperature sampling sequence and the actual load current sampling sequence of the equipment by using a dynamic time warping algorithm:
D＝DTW(T0,I)
wherein D is the similarity value of two sequences, DTW is the dynamic time warping algorithm, T0Is an error compensated temperature sequence.
S304: respectively reacting D with D1And D2Comparing, if:
D＜D1
the equipment safety evaluation result is as follows: the power supply equipment is in a normal running state and does not need to be processed. If:
D1＜D＜D2
the equipment safety evaluation result is as follows: abnormal heating condition occurs at the joint of the equipment or the cable, the equipment or the cable is in a degradation state, the inspection needs to be enhanced, and the power failure inspection is carried out after the production is finished. If:
D＞D2
the equipment safety evaluation result is as follows: the heating condition of the equipment or the cable joint is far beyond the normal operation state, and the equipment or the cable joint needs to be immediately switched to standby equipment and processed.
The present invention is not limited to the above-described embodiments, and various modifications and variations of the present invention are intended to be included within the scope of the claims and the equivalent technical scope of the present invention without departing from the spirit and scope of the present invention.
Claims (6)
1. A safety evaluation method for power supply and distribution equipment of cigarette manufacturing enterprises is characterized by comprising the following steps: the method comprises the following steps: step 1, respectively calculating similarity values by using an equipment load current sampling sequence and a set primary alarm and secondary alarm temperature sampling sequence to serve as an equipment degradation threshold value and a fault threshold value;
step 2, taking a temperature measurement sequence of a temperature on-line monitoring system of the power supply equipment, carrying out error compensation on the actually measured temperature sequence, then taking a load current sampling sequence corresponding to a time window with the same length at the moment, and carrying out similarity calculation on the temperature sequence and the current sequence by utilizing a dynamic time warping algorithm;
and 3, comparing the calculation result with a set threshold value, thereby realizing the safety evaluation of the power supply and distribution equipment.
2. The safety evaluation method for the power supply and distribution equipment of the cigarette manufacturing enterprise according to claim 1, wherein the safety evaluation method comprises the following steps: step 1, taking a primary alarm temperature sampling sequence with the length of 10 minutes and a 10-minute equipment load current value sampling sequence, calculating a similarity value by using a dynamic time warping algorithm, and taking the similarity value as an equipment degradation threshold value; and (3) taking a secondary alarm temperature sampling sequence with the length of 10 minutes and a 10-minute equipment load current value sampling sequence, calculating a similarity value by using a dynamic time warping algorithm, and taking the similarity value as an equipment fault threshold value.
3. The safety evaluation method of the power supply and distribution equipment of the cigarette manufacturing enterprise according to claim 1 or 2, wherein: the device degradation threshold calculation method is as follows: s101: acquiring a 10-minute primary alarm temperature sampling sequence:
Tset1＝(t′1,t′2…t′m)
wherein, Tset1For a set primary alarm temperature sequence, t' is a temperature value
S102: acquiring a 10-minute device load current value:
I＝(i1,i2…in)
wherein, I is the actual load current sampling current sequence of the equipment, and I is the actual load current value of the equipment;
s103: and calculating the similarity by using a dynamic time warping algorithm:
D1＝DTW(Tset1,I)
wherein D is1For similarity values of two sequences, DTW is dynamic time warping algorithm, and D is1As a device degradation threshold.
4. The safety evaluation method of the power supply and distribution equipment of the cigarette manufacturing enterprise according to claim 3, characterized in that: the method for calculating the equipment fault threshold in the step 1 comprises the following steps: s201: acquiring a secondary alarm temperature sampling sequence with the length of 10 minutes:
Tset2＝(t″1,t″2…t″m)
wherein, Tset2Setting a secondary alarm temperature sequence, wherein t' is a temperature value;
s202: acquiring a 10-minute device load current value:
I＝(i1,i2…in)
wherein, I is the actual load current sampling current sequence of the equipment, and I is the actual load current value of the equipment;
s203: and calculating the similarity by using a dynamic time warping algorithm:
D2＝DTW(Tset2,I)
wherein D is2For similarity values of two sequences, DTW is dynamic time warping algorithm, and D is2As a device failure threshold.
5. The safety evaluation method of the power supply and distribution equipment of the cigarette manufacturing enterprise according to claim 4, wherein the safety evaluation method comprises the following steps: the step 2 of calculating the similarity between the temperature sequence and the current sequence by using the dynamic time warping algorithm comprises the following steps: s301: obtaining a temperature sampling sequence of the online temperature measuring system with the length of 10 minutes:
T＝(t1,t2…tm)
wherein T is a heating temperature sampling sequence of actual operation of the equipment, and T is a temperature value;
s302: acquiring a 10-minute device actual load current sampling sequence:
I＝(i1,i2…in)
wherein, I is the actual load current sampling current sequence of the equipment, and I is the actual load current value of the equipment;
s303, carrying out error compensation on the temperature sampling sequence of the online temperature measurement system:
t0＝t+λε
wherein, t0For the compensated temperature value, t is the temperature sampling value of the temperature measuring system, and lambda epsilon is the linear combination of various errors;
s304: calculating the similarity value of the actual operation heating temperature sampling sequence and the actual load current sampling sequence of the equipment by using a dynamic time warping algorithm:
D＝DTW(T0,I)
wherein D is the similarity value of two sequences, DTW is the dynamic time warping algorithm, T0For temperature sequences after error compensation。
6. The method for evaluating the safety of the power supply and distribution equipment of the cigarette manufacturing enterprise according to claim 4 or 5, wherein the method comprises the following steps: and 3, comparing the calculation result with a set threshold value, so as to realize the safety evaluation method of the power supply and distribution equipment, which comprises the following steps: s305: respectively reacting D with D1And D2Comparing, if:
D＜D1
the equipment safety evaluation result is as follows: the power supply equipment is in a normal operation state and does not need to be processed, if:
D1＜D＜D2
the equipment safety evaluation result is as follows: the abnormal heating condition has appeared in equipment or cable joint department, is in the degradation state, needs to strengthen and patrols and examines, and the check of stopping power after production, if:
D＞D2
the equipment safety evaluation result is as follows: the heating condition of the equipment or the cable joint is far beyond the normal operation state, and the equipment or the cable joint needs to be immediately switched to standby equipment.
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