CN104133468B - Fault diagnosis method for crushing and screening process - Google Patents
Fault diagnosis method for crushing and screening process Download PDFInfo
- Publication number
- CN104133468B CN104133468B CN201410371534.5A CN201410371534A CN104133468B CN 104133468 B CN104133468 B CN 104133468B CN 201410371534 A CN201410371534 A CN 201410371534A CN 104133468 B CN104133468 B CN 104133468B
- Authority
- CN
- China
- Prior art keywords
- cur
- array
- current value
- equipment
- score
- 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
Landscapes
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The invention discloses a fault diagnosis method for a crushing and screening process, which correctly and timely infers the reason causing the fault by analyzing and extracting the characteristics of production data obtained in an industrial process so as to shorten the time for fault stop processing, even avoid the fault by predicting in advance and ensure the continuous, efficient and stable operation of the crushing and screening process.
Description
Technical field
The present invention relates to select the monitoring of smelting procedure fault and diagnostic techniques field, the fault particularly relating to a kind of crushing and screening flow process is examined
Disconnected method.
Background technology
Crushing and screening working condition is complicated and changeable, unexpected incidents are many, working strength is big, and particularly ore properties change is often
Often bring a lot of beyond thought difficulty to production;As caused rainy season a large amount of sludges in crushing and screening production procedure to pile up, lead
Cause the serious production such as the blanking funnel blockade of material transferring equipment, screen plugging, feed port blocking, belt conveyer overload
Fault happens occasionally, and once finds not in time, will lead to large area, stop even personal injury for a long time.
In consideration of it, actual production needs the fault in production such as monitoring and diagnosis putty, belt overload or sieve breakage, and then
The problem of production procedure is positioned, in order to production operation personnel take measures in time, avoid problem worse, generation
Bigger economic loss.
But, prior art the most too relies on workman's experience and continual patrolling and examining realize, i.e. add ore dressing
The human cost of factory, also the easy inertia because of workman and experience difference cause the unusual fluctuations even fault of production procedure.Cause
This reason diagnosing the generation of broken sieving circuit fault promptly and accurately, to producing and operation important in inhibiting.
Summary of the invention
It is an object of the invention to provide the method for diagnosing faults of a kind of crushing and screening flow process, by production obtained to industrial process
The analysis of data and feature extraction, infer the reason of causing trouble the most timely, in the hope of shortening what scram processed
Time, avoid the generation of fault even with look-ahead, it is ensured that the fortune that crushing and screening flow process is lasting, efficient, stable
OK.
It is an object of the invention to be achieved through the following technical solutions:
A kind of method for diagnosing faults of crushing and screening flow process, the method includes:
Set up an electric current input array according to the current value of each equipment in the automated system got in real time, and rejecting should
Exceptional value in array;
By the size of the variable quantity of current value each in this array in a period of time Yu threshold value, determine per unit electricity
Stream variation tendency;Utilize variance analysis, determine each device current value wave stability within a period of time in this array
Situation;Size according to current value each in this array Yu load threshold value judges whether corresponding device is in the shape that normally works
State;
Judge rock feeder in described automated system to ore deposit frequency values current time with on once change the time after
Whether exceed to the ore deposit delay adjustments time;
The most then according to wave stability feelings within a period of time of per unit curent change trend, each current value
Whether condition and each equipment are in normal operating conditions to determine per unit steady operation scope, and according to stable state work
Make some skew monitoring result and the Failure Diagnostic Code Table A pre-build, the reason that tracing trouble occurs;
Otherwise, according to per unit curent change trend and the Failure Diagnostic Code table B that pre-builds, tracing trouble is sent out
Raw reason.
As seen from the above technical solution provided by the invention, this crushing and screening flow process method for diagnosing faults can be the most timely
The reason inferring causing trouble, in the hope of shortening the time that scram processes, avoid even with look-ahead therefore
The generation of barrier, it is ensured that the operation that crushing and screening flow process is lasting, efficient, stable.
Accompanying drawing explanation
In order to be illustrated more clearly that the technical scheme of the embodiment of the present invention, required use in embodiment being described below
Accompanying drawing is briefly described, it should be apparent that, the accompanying drawing in describing below is only some embodiments of the present invention, for
From the point of view of those of ordinary skill in the art, on the premise of not paying creative work, it is also possible to obtain according to these accompanying drawings
Other accompanying drawings.
The flow chart of the method for diagnosing faults of a kind of crushing and screening flow process that Fig. 1 provides for the embodiment of the present invention one.
Fig. 2 is a kind of crushing circuit screening fault diagnosis algorithm structural representation that the embodiment of the present invention two provides;
Fig. 3 is the crushing and screening process flow diagram that the embodiment of the present invention two provides;
Fig. 4 is the schematic diagram carrying out on-line fault diagnosis according to real-time production data that the embodiment of the present invention two provides.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clearly and completely
Describe, it is clear that described embodiment is only a part of embodiment of the present invention rather than whole embodiments.Based on
Embodiments of the invention, it is every other that those of ordinary skill in the art are obtained under not making creative work premise
Embodiment, broadly falls into protection scope of the present invention.
Embodiment one
The flow chart of the method for diagnosing faults of a kind of crushing and screening flow process that Fig. 1 provides for the embodiment of the present invention one.Such as Fig. 1 institute
Showing, the method mainly comprises the steps:
In the automated system that step 11, basis get in real time, the current value of each equipment sets up an electric current input array,
And reject the exceptional value in this array.
In the embodiment of the present invention, the equipment in automated system specifically includes that rock feeder, vibrosieve, on-the-sieve material transmission
Belt conveyer and undersize material feed belt transporter.
Described exceptional value typically refers to current value and more than or equal to N (such as, 1.2) times of this equipment rated current or is less than
Equal to no-load current S (such as, 0.8) times.
Step 12, size by the variable quantity of current value each in this array in a period of time Yu threshold value, determine each
The curent change trend of equipment;Utilize variance analysis, determine that in this array, the fluctuation within a period of time of each current value is steady
Qualitative situation;Size according to current value each in this array Yu load threshold value judges whether corresponding device is in normal work
Make state.
This step needs to carry out electric current each in array judgement or the calculating of above-mentioned three types;Specifically, equipment
Curent change trend specifically include that trend is above-mentioned, trend declines and Trend Stationary;Wave stability situation is mainly wrapped
Include: fluctuate bigger than normal, fluctuate less than normal normal with fluctuation;Duty specifically includes that load is bigger than normal, load is less than normal and load
Normally.
Step 13, judge rock feeder in described automated system to ore deposit frequency values current time with on once change
Whether the time is after exceeding to the ore deposit delay adjustments time;The most then proceed to step 14;Otherwise, step 15 is proceeded to.
Step 14, according to wave stability feelings within a period of time of per unit curent change trend, each current value
Whether condition and each equipment are in normal operating conditions to determine per unit steady operation scope, and according to stable state work
Make some skew monitoring result and the Failure Diagnostic Code Table A pre-build, the reason that tracing trouble occurs.
This step determines per unit steady operation scope according to the result of step 12, and then combines the event pre-build
Barrier diagnostic rule Table A, the reason that tracing trouble occurs.
Step 15, according to the variation tendency of per unit electric current and the Failure Diagnostic Code table B that pre-builds, diagnosis therefore
The reason that barrier occurs.
The crushing and screening flow process method for diagnosing faults that the embodiment of the present invention provides can infer causing trouble the most timely
Reason, in the hope of shortening the time that scram processes, avoids the generation of fault even with look-ahead, it is ensured that broken
The operation that broken sieving circuit is lasting, efficient, stable.
Embodiment two
For the ease of understanding the present invention, the present invention will be further described for 2-4 below in conjunction with the accompanying drawings.
As in figure 2 it is shown, the invention mainly comprises the following steps:
The current value of each equipment in step 21, the automated system got in real time.
In the embodiment of the present invention, computer ethernet communication interface can be passed through, with OPC (a kind of Microsoft that utilizes
COM/DCOM technology reaches the agreement of Automated condtrol) mode and ore dressing plant automated system (DCS) realize producing
Data real-time, interactive.
The data obtained in real time specifically include that the current value Cur_feed={cf of rock feeder1,cf2,cf3,…,cfnAnd give ore deposit frequency
Rate value Freq={freq1,freq2,freq3,…,freqn, the current value of each vibrosieve
Cur_screen={cs1,cs2,cs3,…,csn, on-the-sieve material feed belt transporter current value cb1, undersize material transmits skin
Band transporter current value cb2;Sampling period may be configured as 1 second.
Step 22, set up an electric current input array, and reject the exceptional value in this array.
In the embodiment of the present invention, set up an electric current input array according to current value accessed in step 21:
Cur []={ Cur_feed, Cur_screen, cb1,cb2}
={ cf1,cf2,cf3,…,cfn,cs1,cs2,cs3,…,csn,cb1,cb2};
Afterwards, current value per unit in this array is judged, if the current value of a certain equipment of current time is more than
N (such as, 1.2) times equal to this equipment rated current or S (such as, 0.8) times less than or equal to no-load current, then
Determine that it is exceptional value;Again using the current value of upper this equipment of moment as the effective current value of current time, and write should
In array.
Step 23, size by the variable quantity of current value each in this array in a period of time Yu threshold value, determine each
The curent change trend of equipment.
Specifically, any appliance is calculated in this array at the current value Cur [i] of ttThe current value with the t-1 moment
Cur[i]t-1Between variable quantity e [i]t:
e[i]t=Cur [i]t-Cur[i]t-1;
By this variable quantity e [i]tCompare with variable quantity threshold value, it is judged that this variable quantity e [i]tThe interval fallen into, and calculate this change
Change amount e [i]tCurrent time change score Score [i]t:
Wherein, error_hh Yu error_h is ascending threshold high limit, and error_hh > error_h;Error_l with
Error_ll is falling-threshold value lower bound, and error_l > error_ll;
According to sliding window width h, by adding up from this variable score in t-h+1 moment to t, added up
Score Score_total [i]t:
Score_total[i]t=Score [i]t+Score[i]t-1+…+Score[i]t-h+1;
According to cumulative score result, it is judged that the variation tendency of this electric current:
Wherein, ScoremaxAscendant trend for pre-setting judges score threshold, ScoreminScore is judged for downward trend
Threshold value.
Repeat the above steps, until obtaining all devices curent change trend in array.
Step 24, utilize variance analysis, determine each device current value wave stability within a period of time in this array
Situation.
According to sliding window width h, will stop to t from the t-h moment, any appliance electric current in each sampling period
The variable quantity composition array of value Cur [i]:
{Cur[i]t-Cur[i]t-1,Cur[i]t-1-Cur[i]t-2,…,Cur[i]t-h+1-Cur[i]t-h};
And calculate the variances sigma [i] of this arrayt;
By calculated variances sigma [i]tCompare with carrying out the threshold value that obtains of variance study from historical data, it is judged that variable
Fluctuation situation:
Wherein, σmaxFor fluctuation high limit, σminFor fluctuation lower bound.
Repeat the above steps, until obtaining the wave stability situation of array all devices current value.
Step 25, size according to current value each in this array Yu load threshold value judge whether corresponding device is in normally
Duty.
Utilize threshold value to judge any appliance current value Cur [i] in ttThe no work model exceeded when equipment normally produces
Enclose:
Wherein, Cur [i]maxLimit for normal workload height, Cur [i]minFor normal workload load lower bound.
It is emphasized that the sequencing that can not differentiate between execution between above-mentioned steps 23-step 25.
Step 26, judge rock feeder in described automated system to ore deposit frequency values current time with on once change
Whether the time is after exceeding to the ore deposit delay adjustments time;The most then proceed to step 27;Otherwise, step 28 is proceeded to.
Step 27, according to wave stability feelings within a period of time of per unit curent change trend, each current value
Whether condition and each equipment are in normal operating conditions to determine per unit steady operation scope, and according to stable state work
Make some skew monitoring result and the Failure Diagnostic Code Table A pre-build, the reason that tracing trouble occurs.
In the embodiment of the present invention, first, determining per unit steady operation scope, it specifically includes that
If the curent change trend of a certain equipment is that Trend Stationary, its wave stability situation within a period of time are for fluctuating
Normal and duty is the normal state of load, then the steady operation point extraction enumerator of its correspondence adds 1;Otherwise, it is right
The steady operation point answered extracts enumerator clear 0;And when when changing to ore deposit frequency of arbitrary rock feeder, its correspondence steady
Enumerator the most clear 0 is extracted in state operating point;
When the steady operation point extraction enumerator of this equipment reaches setting value count_k, calculate from t-count_k+1
Moment rises, and stops to t, and meansigma methods Ave_Cur [i] of the current value Cur [i] of this equipment currently gives ore deposit frequency as this equipment
Steady operation point under rate;
And determine calculating steady operation scope:
If currently giving under the frequency of ore deposit, when the most not calculating steady operation point Ave_Cur [i], then with Cur [i]maxAs surely
State work high limit initial value, Cur [i]minAs steady operation lower bound initial value.
By above-mentioned steps, complete the steady operation range computation of all devices in array.
Then, offset monitoring result according to steady operation point, the reason that tracing trouble occurs.
Wherein, steady operation point skew monitoring result specifically includes that 1) operating point situation about slowly offseting: if a certain equipment
Curent change trend be Trend Stationary, and be continued above steady operation scope arrive set time, then judge this equipment
Operating point slowly offsets;Otherwise, it is determined that equipment operating point is normal;2) situation that operating point offsets rapidly, if a certain equipment
Curent change trend be that trend rises or trend declines, and exceed steady operation scope, then judge that this equipment operating point is fast
Speed skew;Otherwise, it is determined that equipment operating point is normal.
According to this equipment steady operation point drift condition, in conjunction with the Failure Diagnostic Code Table A pre-build, tracing trouble is sent out
Raw reason.
Exemplary, Failure Diagnostic Code Table A is as shown in table 1, can set up in conjunction with site technique flow process:
Table 1 Failure Diagnostic Code Table A
Step 28, according to the variation tendency of per unit electric current and the Failure Diagnostic Code table B that pre-builds, diagnosis therefore
The reason that barrier occurs.
Exemplary, table B is as shown in table 2 for Failure Diagnostic Code:
Table 2 Failure Diagnostic Code table B
Exemplary, in order to further illustrate the present invention, below using the crushing and screening process of certain gold mine as objective for implementation.
Technological process is as it is shown on figure 3, wherein, if n=3.Concrete steps include:
Step 1: read online data.Read one group of crushing and screening process real time data by OPC mode, delay including 3
Rush ore storage bin material place value Lv={4.7,5.5,3.6}, the current value Cur_feed={17.8 of corresponding 3 rock feeders, 16.5,17.2}
With to ore deposit frequency value F req={32.5,28.5,27}, the current value Cur_screen={23.6 of vibrosieve, 29.5,30.1}, sieve
Upper material transfer belt transporter current value cb1=222, undersize material feed belt transporter current value cb2=191, sampling
Cycle is 1 second.
Step 2: set up input array.The current value of above-mentioned all devices read is formed an electric current input array:
Cur []={ 17.8,16.5,17.2,23.6,29.5,30.1,222,191}.
Step 3: rejecting abnormalities value.Each variable in traversal array Cur [], as a example by the 4th variable, when this variable
When corresponding equipment runs, it is judged that at current time, whether this device current 23.6 exceedes the working range of equipment (wherein
The rated current of equipment is 57, and no-load current is 16).23.6 be both not greater than rated current 1.2 times are found by calculating
68.4, the most not less than 0.8 times 12.8 of no-load current;Therefore present current value is virtual value not rejecting.Other are become
After amount carries out same judgement process, find all in effective range, it is not necessary to reject.
Step 4: to each variable in array Cur [], is changed trend abstraction and judges.As a example by the 4th variable,
Current time value 23.6 is-1.8 with the difference of a upper moment value 25.1.Compare by itself and variable change are arranged threshold value
Relatively:
Understand, must being divided into "-2 " of this variable current time variation tendency.According to default sliding window width 4, to
The score "-2 " of variation tendency score " 0 ", "-1 ", "-1 " and the current time in front 3 sampling periods known is carried out
Cumulative, the variation tendency obtaining current this variable of moment accumulates to be divided into "-4 ", judges score less than the downward trend preset
Threshold value "-3 ", therefore judge that this variable is as " trend decline ".Similarly, the tendency judgement of its dependent variable is completed, it is determined that knot
Fruit is followed successively by and { rises, steadily, steadily, decline, steadily, steadily, steadily, steadily }.
Step 5: utilize variance analysis, carries out wave stability judgement to each variable in array Cur [].With the 4th
As a example by variable, according to sliding window width 4, calculate the variable quantity of this variable interior of the most adjacent 2 sampling periods, it is assumed that successively
For-1.8 ,-0.6 ,-0.6 ,-0.2, composition array-1.8 ,-0.6 ,-0.6 ,-0.2}, and the variance calculating this array is
0.6928.Compare by it is arranged threshold value with fluctuation change
Can determine whether that this variable is in " fluctuation is normal " state.Similarly, the wave stability completing its dependent variable judges,
Result of determination is followed successively by { normal, normally, normally, normally, normally, normally, normally, normal }.
Step 6: machine utilization scope judges.Each variable in traversal array Cur [], as a example by the 4th variable, when
Vibration equipment sieve corresponding to this variable is currently running, and current moment current value is 23.6.By by itself and machine utilization scope
Arrange threshold value to compare:
In the range of can determine whether that this variable belongs to " load is normal ".Similarly, the load range completing its dependent variable judges,
Result of determination is followed successively by { normal, normally, normally, normally, normally, normally, normally, normal }.
Step 7: known current sampling period and the last time changing the moment to ore deposit frequency prolong to ore deposit after exceeding
Time set 30 seconds time, jump to step 8.
Step 8: calculate equipment steady operation scope.As a example by the 4th variable, this change in current sample period as previously mentioned
Amount is in " Trend Stationary ", " fluctuation is normal " and " load is normal " state, then steady operation point extraction enumerator adds
1.Assume that this counter reaches setting value 60 already, the 4th variable when arriving setting value by computing counter
Meansigma methods in 60 sampling periods, currently gives the steady operation point under the frequency of ore deposit, it is assumed that result of calculation is as this variable
26.4.It follows that calculate steady operation scope, wherein, steady operation scope height limits:
Min ((1+10%) × 26.4,34.0)=29.1;
Steady operation scope lower bound:
Max ((1-10%) × 26.4,17.4)=23.8;
Similarly, the steady operation range computation of its dependent variable is completed.Final calculation result: all variable steady operation models
Enclosing high limit to be followed successively by: { 17.5,18.2,17.9,29.1,30.8,31.3,241,202, }, steady operation scope lower bound is followed successively by:
{14.3,14.9,14.6,23.8,25.2,25.6,197,165}。
Step 9: offset monitoring result according to steady operation point, the reason that tracing trouble occurs.Calculating knot according to step 8
Really, only the 1st variable and the 4th variable be not within the scope of steady operation.Wherein, the 1st variable is higher than " stable state work
Make scope ", and it is in " trend rising " state, belong to operating point " positive deviation " through judgement;4th variable is less than
" steady operation scope ", and be in " trend decline " state, through judging to belong to operating point " negative bias from ".Other become
Amount is in " operating point is normal " state.To sum up, all variable steady operation points skew monitoring result is followed successively by: { positively biased
From, normally, normally, negative bias from, normally, normally, normally, normal }.Monitoring result is offset according to steady operation point,
Rock feeder " positive deviation ", vibrosieve " negative bias from ", the reason that search location fault occurs in Table 1 is: under rock feeder
Funnel blocks.Crushing and screening flow process fault diagnosis terminates.
The effect of on-line fault diagnosis is carried out as shown in Figure 4, at the 23rd sample point, rock feeder according to real-time production data
Electric current exceedes steady operation range limit, is simultaneously in trend propradation, i.e. this variable and there occurs positive deviation;Similar
Ground, vibrosieve electric current is less than steady operation range lower limit, and the trend that is simultaneously in declines state, i.e. this variable and there occurs negative bias
From.Offseting monitoring result according to steady operation point, the reason that search location fault occurs in Failure Diagnostic Code Table A is:
Rock feeder blanking funnel blockade.Operator, according to the fail result of this method diagnosis, stopped rock feeder, effectively immediately
Avoid the generation of production accident.
This fault diagnosis result complies fully with on-the-spot actual production abnormal conditions, simultaneously because as early as possible be found that batcher
The fault of blanking funnel blockade, shorten the time of parking handling failure, it is to avoid the extension of production accident, to production
Operate helpful.
The crushing and screening flow process method for diagnosing faults that the present invention provides, has the advantage that
1, by the feature extraction of crushing and screening flow process creation data and analysis, it is achieved that in production process, such as feed bin is deposited
The funnel diagnosis producing abnormal monitoring and fault such as stifled under material deficiency, Vibration Screen hole plug, rock feeder, it is ensured that flow
Under journey abnormal conditions, production capacity is recovered as soon as possible.
2, the unusual service condition monitoring on the screening efficiency significant feed preparation unit size of impact is achieved, it is ensured that qualified screening product
Yield.
3, diagnosis real-time is high, by fault degradation trend is carried out extraction and analysis, and the anticipation of fault in production of having practised, greatly
Reduce greatly and artificial patrol and examine intensity.
Through the above description of the embodiments, those skilled in the art it can be understood that to above-described embodiment permissible
Realized by software, it is also possible to the mode adding necessary general hardware platform by software realizes.Based on such reason
Solving, the technical scheme of above-described embodiment can embody with the form of software product, and this software product can be stored in one
In individual non-volatile memory medium (can be CD-ROM, USB flash disk, portable hard drive etc.), including some instructions with so that
One computer equipment (can be personal computer, server, or the network equipment etc.) performs the present invention, and each is implemented
Method described in example.
The above, the only present invention preferably detailed description of the invention, but protection scope of the present invention is not limited thereto,
Any those familiar with the art in the technical scope of present disclosure, the change that can readily occur in or replace
Change, all should contain within protection scope of the present invention.Therefore, protection scope of the present invention should be with claims
Protection domain is as the criterion.
Claims (8)
1. the method for diagnosing faults of a crushing and screening flow process, it is characterised in that the method includes:
Set up an electric current input array according to the current value of each equipment in the automated system got in real time, and rejecting should
Exceptional value in array;
By the size of the variable quantity of current value each in this array in a period of time Yu threshold value, determine per unit electricity
Stream variation tendency;Utilize variance analysis, determine each device current value wave stability within a period of time in this array
Situation;Size according to current value each in this array Yu load threshold value judges whether corresponding device is in the shape that normally works
State;
Judge rock feeder in described automated system to ore deposit frequency values current time with on once change the time after
Whether exceed to the ore deposit delay adjustments time;
The most then according to wave stability feelings within a period of time of per unit curent change trend, each current value
Whether condition and each equipment are in normal operating conditions to determine per unit steady operation scope, and according to stable state work
Make some skew monitoring result and the Failure Diagnostic Code Table A pre-build, the reason that tracing trouble occurs;
Otherwise, according to per unit curent change trend and the Failure Diagnostic Code table B that pre-builds, tracing trouble is sent out
Raw reason.
Method the most according to claim 1, it is characterised in that described establishment one electric current input array includes:
Obtain the current value Cur_feed={cf of each rock feeder in automated system in real time1,cf2,cf3,…,cfn, Mei Yizhen
The current value Cur_screen={cs of dynamic sieve1,cs2,cs3,…,csn, on-the-sieve material feed belt transporter current value cb1, sieve
Lower material transfer belt transporter current value cb2;
According to each current value got set up one electric current input array:
Method the most according to claim 1 and 2, it is characterised in that the exceptional value in this array of described rejecting includes:
Current value per unit in this array is judged, if the current value of a certain equipment of current time is more than or equal to being somebody's turn to do
N times of equipment rated current or less than or equal to S times of no-load current, then determine that it is exceptional value;
Using the current value of upper this equipment of moment as the effective current value of current time, and write in this array.
Method the most according to claim 1, it is characterised in that described by electricity each in this array in a period of time
The variable quantity of flow valuve and the size of threshold value, determine that per unit curent change trend includes:
Calculate in this array any appliance at the current value Cur [i] of ttThe current value Cur [i] with the t-1 momentt-1Between
Variable quantity e [i]t:
e[i]t=Cur [i]t-Cur[i]t-1;
By this variable quantity e [i]tCompare with variable quantity threshold value, it is judged that this variable quantity e [i]tThe interval fallen into, and calculate this change
Change amount e [i]tCurrent time change score Score [i]t:
Wherein, error_hh Yu error_h is ascending threshold high limit, and error_hh > error_h;Error_l with
Error_ll is falling-threshold value lower bound, and error_l > error_ll;
According to sliding window width h, will add up from the change score in t-h+1 moment to t, obtain adding up
Divide Score_total [i]t:
Score_total[i]t=Score [i]t+Score[i]t-1+…+Score[i]t-h+1;
According to cumulative score result, it is judged that the variation tendency of this electric current:
Wherein, ScoremaxAscendant trend for pre-setting judges score threshold, ScoreminScore is judged for downward trend
Threshold value.
Method the most according to claim 1, it is characterised in that described utilize variance analysis, determines in this array every
One device current value wave stability situation within a period of time includes:
According to sliding window width h, will stop to t from the t-h moment, any appliance electric current in each sampling period
The variable quantity composition array of value Cur [i]:
{Cur[i]t-Cur[i]t-1,Cur[i]t-1-Cur[i]t-2,…,Cur[i]t-h+1-Cur[i]t-h};
And calculate the variances sigma [i] of this arrayt;
By calculated variances sigma [i]tCompare with carrying out the threshold value that obtains of variance study from historical data, it is judged that variable
Fluctuation situation:
Wherein, σmaxFor fluctuation high limit, σminFor fluctuation lower bound.
Method the most according to claim 1, it is characterised in that described according to current value each in this array and load
The size of threshold value judges whether corresponding device is in normal operating conditions and includes:
Wherein, Cur [i]maxLimit for normal workload height, Cur [i]minFor normal workload load lower bound, Cur [i] is
This array any appliance is at the current value of t.
7. according to the method described in claim 1,4,5 or 6, it is characterised in that described determine per unit stable state work
Include as scope:
If the curent change trend of a certain equipment is that Trend Stationary, its wave stability situation within a period of time are for fluctuating
Normal and duty is the normal state of load, then the steady operation point extraction enumerator of its correspondence adds 1;Otherwise, it is right
The steady operation point answered extracts enumerator clear 0;And when when changing to ore deposit frequency of arbitrary rock feeder, its correspondence steady
Enumerator the most clear 0 is extracted in state operating point;
When the steady operation point extraction enumerator of this equipment reaches setting value count_k, calculate from t-count_k+1
Moment rises, and stops to t, and meansigma methods Ave_Cur [i] of the current value Cur [i] of this equipment currently gives ore deposit frequency as this equipment
Steady operation point under rate;
And determine calculating steady operation scope:
If currently giving under the frequency of ore deposit, when the most not calculating steady operation point Ave_Cur [i], then with Cur [i]maxAs surely
State work high limit initial value, Cur [i]minAs steady operation lower bound initial value.
Method the most according to claim 7, it is characterised in that described according to steady operation point skew monitoring result with
And the Failure Diagnostic Code Table A pre-build, the reason that tracing trouble occurs includes:
The situation that operating point slowly offsets: if the curent change trend of a certain equipment is Trend Stationary, and be continued above stable state
Working range arrives the time set, then judge that this equipment operating point slowly offsets;Otherwise, it is determined that equipment operating point is just
Often;
The situation that operating point offsets rapidly: rise or trend decline if the curent change trend of a certain equipment is trend, and super
Cross steady operation scope, then judge that this equipment operating point offsets rapidly;Otherwise, it is determined that equipment operating point is normal;
According to this equipment steady operation point drift condition, in conjunction with the Failure Diagnostic Code Table A pre-build, tracing trouble is sent out
Raw reason.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410371534.5A CN104133468B (en) | 2014-07-30 | 2014-07-30 | Fault diagnosis method for crushing and screening process |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410371534.5A CN104133468B (en) | 2014-07-30 | 2014-07-30 | Fault diagnosis method for crushing and screening process |
Publications (2)
Publication Number | Publication Date |
---|---|
CN104133468A CN104133468A (en) | 2014-11-05 |
CN104133468B true CN104133468B (en) | 2016-12-07 |
Family
ID=51806187
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201410371534.5A Active CN104133468B (en) | 2014-07-30 | 2014-07-30 | Fault diagnosis method for crushing and screening process |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN104133468B (en) |
Families Citing this family (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107942994B (en) * | 2017-11-07 | 2019-06-28 | 湖南捷能高新技术有限公司 | A kind of satellite temperature control system method for diagnosing faults based on temperature curve feature |
CN110274841B (en) * | 2018-03-15 | 2021-12-24 | 中冶长天国际工程有限责任公司 | Diagnosis method and device for screening process in sintered fuel grain size composition detection system |
CN110270397B (en) * | 2018-03-15 | 2021-04-20 | 中冶长天国际工程有限责任公司 | Four-roller crusher early warning method and system |
CN115055265A (en) * | 2022-06-30 | 2022-09-16 | 中钢石家庄工程设计研究院有限公司 | Large-scale iron ore deposit underground mining selects to select fills integration system |
CN116679669B (en) * | 2023-06-07 | 2024-03-26 | 矿冶科技集团有限公司 | Screening system fault diagnosis method and system |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101839957B (en) * | 2010-05-08 | 2011-12-07 | 中国矿业大学 | Method for diagnosing main circuit fault of power converter of switched reluctance motor |
CN102728432A (en) * | 2011-04-06 | 2012-10-17 | 中冶长天国际工程有限责任公司 | Method and system for maintenance early-warning of single-roller crusher |
CN103529343A (en) * | 2013-03-27 | 2014-01-22 | Tcl集团股份有限公司 | Intelligent diagnosing method and system of electrical device |
-
2014
- 2014-07-30 CN CN201410371534.5A patent/CN104133468B/en active Active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101839957B (en) * | 2010-05-08 | 2011-12-07 | 中国矿业大学 | Method for diagnosing main circuit fault of power converter of switched reluctance motor |
CN102728432A (en) * | 2011-04-06 | 2012-10-17 | 中冶长天国际工程有限责任公司 | Method and system for maintenance early-warning of single-roller crusher |
CN103529343A (en) * | 2013-03-27 | 2014-01-22 | Tcl集团股份有限公司 | Intelligent diagnosing method and system of electrical device |
Also Published As
Publication number | Publication date |
---|---|
CN104133468A (en) | 2014-11-05 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN104133468B (en) | Fault diagnosis method for crushing and screening process | |
CN115130702B (en) | Textile machine fault prediction system based on big data analysis | |
WO2017197873A1 (en) | System and method for diagnosing failure of belt-type conveyor | |
CN106919141A (en) | Preventive maintenance management system, unit control apparatus, preventive maintenance management method | |
CN102223264B (en) | Alarm processing method and alarm processing system for monitoring system | |
CN107247849A (en) | Optimize the maintaining method and system of mechanical system based on proportional hazards model | |
CN101183260A (en) | Mineral concentration full flow process automatic control method | |
CN103698698A (en) | Diagnostic method of electrical life of high-voltage circuit breaker based on fuzzy theory | |
CN113762604B (en) | Industrial Internet big data service system | |
CN115358626A (en) | Safety inspection early warning system for mineral processing production equipment | |
CN104880488B (en) | Cutting breaking automatic testing method based on amperometry | |
CN104820884A (en) | Power network dispatching real-time data inspection method combined with characteristics of power system | |
CN102615709A (en) | Concrete slump monitoring device and method | |
CN102226898A (en) | Method and device for controlling monitoring data to be put in storage in online monitoring system | |
CN104361088A (en) | Congestion data processing method based on real-time weight analysis in SCADA (supervisory control and data acquisition) system | |
CN105043770A (en) | Wind turbine generator abnormal vibration judging method and apparatus thereof | |
CN102981096B (en) | A kind of data grid fault identification method of decomposing based on WAMS sequential | |
CN110472851A (en) | A kind of power distribution network risk hidden danger dynamic evaluation model building method neural network based | |
CN104242453A (en) | Voltage alarm method used for buses of main electric network | |
CN116104576A (en) | Remote monitoring system for operation of mining face of quartz stone | |
CN103475698A (en) | Multi-channel water conservancy system and control method | |
CN113285654B (en) | Oil field petrochemical servo motor system based on fluid pressure actuating mechanism | |
CN109976294B (en) | Intelligent parking method and system | |
CN116720853B (en) | Comprehensive monitoring method and system for safety performance of ultra-thick oil petroleum drilling and production equipment | |
CN106950946A (en) | A kind of hydrometallurgy exception control method based on optimization principles |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
C14 | Grant of patent or utility model | ||
GR01 | Patent grant |