Mining electric shovel working device structure welding seam health monitoring and evaluating method based on intelligent bearing

Abstract

The invention discloses a mining electric shovel working device structure welding seam health monitoring and evaluation method based on an intelligent bearing, and the method comprises the following steps: 1, constructing a stress prediction model: constructing a structure stress rapid prediction model for an electric shovel working device based on a reduced-order modeling method; 2, the working state of an electric shovel working device is obtained, specifically, a first intelligent bearing is installed at a top pulley of the mining electric shovel, and a second intelligent bearing is installed at a second pushing shaft; the length Lh of the steel wire rope, the lifting operation load Fh, the extension length Lp of the bucket rod and the pushing operation load FP are obtained through data obtained by the first intelligent bearing and the second intelligent bearing in real time; step 3, stress prediction: inputting the length Lh of the steel wire rope, the lifting operation load Fh, the extension length Lp of the bucket rod and the pushing operation load FP into the structure stress rapid prediction model to obtain the structure stress of the key site; step 4, fatigue analysis; and step 5, health assessment. Therefore, the fatigue damage of the structural weld joint of the mining electric shovel working device can be monitored in the whole process.

Description

Technical Field

[0001] The invention discloses a method for health monitoring and evaluation of a weld structure of a mining electric shovel working device based on an intelligent bearing, and relates to the field of health monitoring of structural parts of a mining electric shovel working device. Background Art

[0002] Electric mining shovels are the main mining equipment in large open-pit mines. However, electric mining shovels need to face heavy-load working conditions and harsh environmental conditions during actual operation, and even some drivers' illegal operations, which can lead to abnormal cracking of the structural welds of the electric shovel working device, causing serious safety accidents and economic losses. Therefore, it is of great significance to conduct health monitoring of the structural welds of the electric mining shovel working device.

[0003] In the process of health monitoring of the welds of the working device structure of the mining shovel, it is particularly important to identify the changes in the load and stress of the working device. Most of the previous stress monitoring methods use strain gauges to obtain load data at limited points, which faces certain challenges. On the one hand, the strain gauge is easily disturbed when obtaining load data, making it difficult to achieve long-term monitoring; on the other hand, the strain gauge can only monitor the stress state of a limited number of monitoring points, with a small monitoring range, and cannot achieve global monitoring. Summary of the invention

[0004] The present invention proposes a method for monitoring and evaluating the health of the structural welds of the working device of a mining electric shovel based on intelligent bearings. The method can identify the changes in the load and stress of the working device during the operation of the electric shovel, and realize the full monitoring of fatigue damage of the structural parts. By establishing a finite element model and using the order reduction algorithm, a rapid prediction model of the structural stress of the key points in the weld area of ​​the working device of the electric shovel is obtained. Intelligent bearings are installed at the top pulley of the boom and the thrust gearbox, and the speed parameters of the intelligent bearings are used to determine the working posture of the working device of the electric shovel; the load parameters of the intelligent bearings are used to determine the load state of the working device. The working posture and load state of the working device of the electric shovel are imported into the rapid prediction model of structural stress, and the real-time changes in the structural stress of the key points in the weld area are obtained, which are used for fatigue analysis, and then the health assessment of the weld is performed.

[0005] In order to achieve the above technical objectives, the present invention will adopt the following technical solutions:

[0006] A method for monitoring and evaluating the health of a weld structure of a mining electric shovel working device based on an intelligent bearing comprises the following steps:

[0007] Step 1: Construct a stress prediction model:

[0008] Based on the reduced-order modeling method, a rapid structural stress prediction model is constructed for the electric shovel working device;

[0009] The structural stress rapid prediction model can predict the structural stress of the key point P at all structural welds of the electric shovel working device by inputting the parameters representing the working state of the electric shovel working device;

[0010] Step 2: Get the working status of the shovel working device:

[0011] A first intelligent bearing is installed at the top pulley of the mining electric shovel, and a second intelligent bearing is installed at the push second shaft;

[0012] The parameters that characterize the working state of the electric shovel working device include the wire rope length L of the electric shovel working device h , lifting load F h , arm extension length L p And the pushing load F P ;

[0013] The speed S of the top pulley is obtained in real time through the first intelligent bearing h and the real-time load F1 at the top pulley, so as to calculate the wire rope length L of the shovel working device at any time. h , lifting load F h ;

[0014] The speed S of the second push shaft is obtained in real time through the second intelligent bearing P and the real-time load F2 at the two axes of push, so as to calculate the arm extension length L of the electric shovel working device at any time. p , Pushing load F P ;

[0015] Step 3: Stress prediction:

[0016] The length of the wire rope L at any time obtained in step 2 h , lifting load F h , arm extension length L p And the pushing load F P Combined in order into the input vector {L h ,L p ,F h ,F P};

[0017] The obtained input vector {L h ,L p ,F h ,F P} Input the structural stress rapid prediction model constructed in step 1 to predict the key points P = {P1, P2, ..., P i ,...,P n} to predict the structural stress and obtain the predicted stress values ​​of key points at all structural welds Where: n represents the total number of all key points at the weld of the shovel working device structure, and the value is a positive integer;

[0018] Step 4: Fatigue analysis:

[0019] Based on the key point P at any structural weld of the shovel working device obtained in step 3 i The predicted stress Calculate the key point P at the corresponding structural weld i Total fatigue damage D, total fatigue life T and remaining fatigue life T re ;

[0020] Step 5: Health Assessment:

[0021] Based on the key point P of any structural weld obtained in step 4 i Total fatigue damage D, total fatigue life T and remaining fatigue life T re , evaluate the health status of the shovel's working device and give corresponding usage recommendations.

[0022] Preferably, in step 2, the length L of the wire rope at any time h , the calculation formula is as follows:

[0023]

[0024] Where: L h0 is the initial value of the wire rope length; R h is the pulley radius; S h is the rotation speed of the top pulley, which is obtained in real time through the first intelligent bearing;

[0025] The lifting load at any time is calculated as follows:

[0026] F h =T h ×F1;

[0027] Where: F1 is the real-time load at the top pulley, which is obtained in real time through the first smart bearing; T h is the transformation matrix of the real-time load at the top pulley;

[0028] The arm extension length L at any time p , the calculation formula is as follows:

[0029]

[0030] Where: L p0 is the initial value of the arm length; R P S is the transmission ratio between the push shaft and the bucket arm;P To push the second axis speed, it is acquired in real time through the second smart bearing;

[0031] The push load at any time is calculated as follows:

[0032] F p =T p ×F2;

[0033] Where: F2 is the real-time load at the push-pull second axis, which is obtained in real time through the second smart bearing; T p It is the transformation matrix of the real-time load F2 at the pushing and pressing axis.

[0034] Preferably, in step 4, any key point P i The total fatigue damage is obtained by the following steps:

[0035] Step 4.1, a SN curve group of structural stress of a given electric shovel structure weld is composed of a plurality of SN curves with different stress ratios;

[0036] Step 4.2: Obtain any key point P of the shovel working device through step 3 i Time-varying stress It is expressed as:

[0037] In the formula, Represents the key point P i Predicted stress value at time t1;

[0038] Step 4.3: Use the real-time rain flow counting method based on the key point P obtained in step 2 i Time-varying stress Get the key point P i The stress amplitude S of the structural stress at a , stress ratio S r and stress cycle number n j ;

[0039] Step 4.4: According to the stress ratio S r and the weld SN curve set given in step 4.1, interpolate to determine the stress ratio S r The weld SN curve below;

[0040] Step 4.5: Based on the stress ratio S determined in step 4.4 r The SN curve of the weld under the above conditions is used to obtain the stress amplitude S a The corresponding number of cycles N j ;

[0041] Step 4.6: Calculate any key point P i Fatigue damage:

[0042] Step 4.7: According to the Miner criterion, determine any key point P i The total fatigue damage is:

[0043] Preferably, in step 4, any key point P i The total fatigue life T is calculated by the following formula:

[0044]

[0045] Where: D represents any key point P i Total damage; T run Indicates the elapsed operating time of the shovel working device.

[0046] Preferably, in step 4, any key point P i The remaining fatigue life is calculated by the following formula:

[0047] T re =TT run ;

[0048] Where: T represents any key point P i Total fatigue life; T run Indicates the elapsed operating time of the shovel working device.

[0049] Preferably, in step 5, for any key point P i The total fatigue damage of the system is pre-set with two fatigue damage thresholds, corresponding to the first fatigue damage threshold D max1 , the second fatigue damage threshold D max2 ;

[0050] For any key point P i The remaining fatigue life of the vehicle is preset with a threshold value T0 for the next maintenance time;

[0051] When any key point P of the shovel working device i The total fatigue damage satisfies D<D max1 When working, keep the shovel working device in normal use and perform regular maintenance;

[0052] When any key point P of the shovel working device i The total fatigue damage satisfies D max1 <D<D max2 When , it means that the key point P i It is a dangerous point and needs to be carefully observed and maintained on schedule;

[0053] When any key point P of the shovel working device i The total fatigue damage satisfies D>D max2 And the key point Pi The remaining fatigue life satisfies T re >T0, indicating that the key point P i It is a dangerous point and needs to be carefully observed and maintained on schedule;

[0054] When any key point P of the shovel working device i The total fatigue damage satisfies D>D max2 And the key point P i The remaining fatigue life satisfies T re When <T0, the shovel working device is stopped and a prompt is given to i Carry out structural reinforcement.

[0055] Preferably, in step 5, for any key point P i , the corresponding reinforcement times k are preset, and after each structural reinforcement treatment, the fatigue total damage of the corresponding key point is reset, and the structural component scrap evaluation index X is given for the corresponding key point i ;

[0056] Calculate any key point P i The evaluation index of structural parts scrapping is calculated as follows:

[0057] Calculate the scrap evaluation index of the entire structural parts of the electric shovel working device. The calculation formula is:

[0058] Determine whether the overall scrap evaluation index of the structural parts of the electric shovel working device has reached the preset value X 报废 , if the judgment result shows that X>X 报废 , prompting that the electric shovel working device has reached the scrap standard.

[0059] Preferably, the reinforcement times k is 3.

[0060] Preferably, in step 1, the structural stress rapid prediction model is constructed in the following manner:

[0061] Step 1.1, establish the finite element model of the electric shovel working device;

[0062] Step 1.2: According to theoretical analysis and field measurement results, determine the working posture L of the electric shovel working device = {L h ,L p}、Working load F={F h ,F p} value range;

[0063] Step 1.3: Within the range of the working posture L and the working load F of the electric shovel working device, take N values ​​for combination design to form an array M = {M1, M2, ..., M S,...,M N}; Any array in array M N represents the total number of elements included in the array M;

[0064] Step 1.4: Using the finite element model of the electric shovel working device, according to the array M constructed in step 1.3, complete the electric shovel working device in each working condition C = {C1, C2, ..., Cl, ..., C L}Analysis under C l represents the lth working condition among all working conditions C of the electric shovel working device, and L represents the total number of all working conditions of the electric shovel working device;

[0065] Step 1.5: According to the finite element analysis results and the statistical data of structural weld damage, determine the key points P = {P1, P2, ..., P i ,...,P n};

[0066] Step 1.6: Extract and calculate the structural stress of key points under each working condition

[0067] Step 1.7: Use the three-dimensional simulation reduction algorithm to build a rapid prediction model for structural stress, and use the array M built in step 1.3 and the structural stress of key points under each working condition extracted in step 1.6 The constructed rapid structural stress prediction model is trained to obtain a trained rapid structural stress prediction model.

[0068] Based on the above technical objectives, the present invention has the following advantages over the prior art:

[0069] The present invention installs intelligent bearings at the top pulley and the push shaft, combines the stress prediction model, identifies the changes in the working device force and stress during the operation of the electric shovel, realizes the prediction of fatigue and damage of structural parts, meets the requirements of structural parts maintenance according to the situation, and fully guarantees the safe operation of the electric shovel. The main advantages are:

[0070] 1. Compared with the traditional method of collecting load data through strain gauges, the present invention can reduce the impact of various interferences through intelligent bearings and achieve long-term monitoring.

[0071] 2. Compared with reading motor parameters and obtaining torque load through PLC, the present invention can obtain the detailed six-component force state of the load at the structural bearing through the intelligent bearing, and the structural load state is more accurate.

[0072] 3. The speed information can also be obtained through the intelligent bearing. After calibration, the working posture of the working device can be determined, avoiding the need to install additional displacement sensors, inclination sensors, etc.

[0073] 4. Compared with the traditional stress monitoring of limited key points through strain gauges, the present invention combines intelligent bearings with stress prediction models to monitor the entire area of ​​the structure, including the weld area, which can increase the monitoring range and obtain a more accurate stress state. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 It is the intelligent bearing distribution for electric shovel operation described in the present invention;

[0075] Figure 2 It is a flow chart of the method for monitoring and evaluating the health of the weld structure of the mining electric shovel working device based on the intelligent bearing described in the present invention.

[0076] In the figure: 1-top pulley; 2-speed reducer; 3-first smart bearing; 4-second smart bearing. DETAILED DESCRIPTION

[0077] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means any limitation to the present invention and its application or use. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Unless otherwise specified, the relative arrangement, expressions and numerical values ​​of the components and steps described in these embodiments do not limit the scope of the present invention. The techniques, methods and equipment known to ordinary technicians in the relevant fields may not be discussed in detail, but in appropriate cases, the techniques, methods and equipment should be regarded as part of the specification. In all examples shown and discussed here, any specific value should be interpreted as merely exemplary, rather than as a limitation. Therefore, other examples of the exemplary embodiments may have different values.

[0078] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations).

[0079] like Figure 2 As shown, the method for monitoring and evaluating the health of the weld of the mining electric shovel working device structure based on the intelligent bearing of the present invention comprises the following steps:

[0080] Step 1: Construct a stress prediction model:

[0081] Based on the reduced-order modeling method, a rapid structural stress prediction model is constructed for the electric shovel working device;

[0082] The structural stress rapid prediction model can predict the structural stress of the key point P at all structural welds of the electric shovel working device by inputting the parameters representing the working state of the electric shovel working device; the structural stress rapid prediction model is specifically constructed in the following way:

[0083] Step 1.1, establish the finite element model of the electric shovel working device;

[0084] Step 1.2: According to theoretical analysis and field measurement results, determine the working posture L of the electric shovel working device = {L h ,L p}、Working load F={F h ,F p} value range;

[0085] Step 1.3: Within the range of the working posture L and the working load F of the electric shovel working device, take N values ​​for combination design to form an array M = {M1, M2, ..., M S ,...,M N}; Any array in array M N represents the total number of elements included in the array M;

[0086] Step 1.4: Using the finite element model of the electric shovel working device, according to the array M constructed in step 1.3, complete the electric shovel working device in each working condition C = {C1, C2, ..., Cl, ..., C L}Analysis under C l represents the lth working condition among all working conditions C of the electric shovel working device, and L represents the total number of all working conditions of the electric shovel working device;

[0087] Step 1.5: According to the finite element analysis results and the statistical data of structural weld damage, determine the key points P = {P1, P2, ..., P i ,...,P n};

[0088] Step 1.6: Extract and calculate the structural stress of key points under each working condition

[0089] Step 1.7: Use the reduced-order modeling method to build a rapid prediction model for structural stress, and use the array M built in step 1.3 and the structural stress of key points under each working condition extracted in step 1.6 The constructed rapid structural stress prediction model is trained to obtain a trained rapid structural stress prediction model.

[0090] Step 2: Get the working status of the shovel working device:

[0091] Step 2.1: Determine the working posture of the electric shovel working device:

[0092] Step 2.1.1, install the first intelligent bearing 3 at the top pulley 1 of the electric shovel; install the second intelligent bearing 4 at the push shaft (the position connected to the power output end of the reducer 2), and press Figure 1 The posture shown is calibrated to obtain the wire rope length L in this posture h0 (The point of intersection between the wire rope and the top pulley 1 of the electric shovel is marked as A, the point of connection between the wire rope and the bucket is marked as B, and the length of the wire rope is L h0 That is, the length between the cutting point A and the connection point B) and the stick extension length L p0 (The pushing and pressing two axes are marked as position C, and the stick extension length is L p0 That is, the length between the part C and the connection point B), and this is used as the initial value for calculation. In other words, in the initial state, the arm is in the horizontal direction (that is, Figure 1 The wire rope is parallel to the left and right direction, while the wire rope is parallel to the vertical direction (i.e. Figure 1 The arrangement is in the up and down direction.

[0093] Step 2.1.2: When the electric shovel is operating, the real-time speed S of the top pulley can be obtained through the first intelligent bearing 3. h . For the pulley speed S h Integrate and obtain the change in the length of the wire rope based on the motion relationship between the pulley and the wire rope, and then add it to the initial value of the wire rope length L h0 Add them together to get the length L of the wire rope at any time. h The specific calculation formula is as follows:

[0094]

[0095] Where: R h is the pulley radius.

[0096] Step 2.1.3: When the electric shovel is operating, the real-time speed S of the push shaft can be obtained through the second intelligent bearing 4. P . For the speed of the two-axis pusher S P Integrate, and according to the motion relationship between the two pushing axes and the bucket arm, multiply by the corresponding transmission ratio to get the change in the bucket arm extension length, and then add it to the initial value of the bucket arm length L.p0 Add them together to get the extension length L of the arm at any time. p The specific calculation formula is as follows:

[0097]

[0098] Where: R P It is the transmission ratio between the pushing shaft and the bucket arm.

[0099] Step 2.1.4: The electric shovel working device is driven by the lifting and pushing mechanisms to obtain the lifting wire rope length L at any time. h And the stick extension length L p After that, the working posture L of the electric shovel working device at that moment can be determined.

[0100] Step 2.2: Determine the working load of the shovel working device:

[0101] Step 2.2.1: When the electric shovel is operating, the real-time load F1 at the top pulley can be obtained through the first smart bearing 3. This load is a universal vector force with 6 components. h , the lifting load of the working device can be obtained. The specific formula is as follows: F h =T h ×F1.

[0102] Step 2.2.2: When the electric shovel is operating, the real-time load F2 at the push axis can be obtained through the second intelligent bearing 4. This load is a universal vector force with 6 components. p , the pushing load of the working device can be obtained. The specific formula is as follows: F p =T p ×F2.

[0103] Step 2.2.3: The shovel working device is driven by the lifting and pushing mechanisms to obtain the lifting load F at any time. h And the pushing load F p After that, the working load F of the electric shovel working device at that moment can be determined.

[0104] Step 3: Stress prediction:

[0105] Step 3.1: Using the first and second smart bearings, the working posture and working load of the electric shovel working device obtained in real time in step 2 are sequentially combined into an input vector {L h ,L p ,F h ,F P}, import the structural stress rapid prediction model constructed in step 1.

[0106] Step 3.2: Use the structural stress rapid prediction model to predict the key points P = {P1, P2, ..., P i ,...,P n} to predict the structural stress and obtain the predicted stress values ​​of key points at all structural welds Wherein: n represents the total number of all key points at the weld of the electric shovel working device structure, and its value is a positive integer.

[0107] Step 4: Fatigue analysis:

[0108] Based on the key point P at any structural weld of the shovel working device obtained in step 3 i The predicted stress S Pi , calculate the key point P at the corresponding structural weld i Total fatigue damage D, total fatigue life T and remaining fatigue life T re ;

[0109] First, taking the key point P1 as an example, its total fatigue damage D, total fatigue life T and remaining fatigue life T are given. re The calculation process.

[0110] Step 4.1, a SN curve group of structural stress of a given electric shovel structure weld is composed of a plurality of SN curves with different stress ratios;

[0111] Step 4.2: Through step 3, obtain the stress of any key point P1 of the shovel working device changing with time It is expressed as:

[0112] In the formula, It represents the predicted stress value of the key point P1 at time t1;

[0113] Step 4.3: Use the real-time rain flow counting method to calculate the stress of the key point P1 obtained in step 2 over time. Get the stress amplitude S of the structural stress at the key point P1 a , stress ratio S r and stress cycle number n j ;

[0114] Step 4.4: According to the stress ratio S r and the weld SN curve set given in step 4.1, interpolate to determine the stress ratio S r The weld SN curve below;

[0115] Step 4.5: Based on the stress ratio S determined in step 4.4 r The SN curve of the weld under the above conditions is used to obtain the stress amplitude S a The corresponding number of cycles N j;

[0116] Step 4.6, calculate the fatigue damage of key point P1:

[0117] Step 4.7: According to the Miner criterion, the total fatigue damage of the key point P1 is determined as:

[0118] Step 4.8: The total fatigue life T of the key point P1 is calculated by the following formula:

[0119]

[0120] Where: D represents the total fatigue damage of the key point P1 calculated in step 4.7; T run Indicates the elapsed operating time of the shovel working device.

[0121] Step 4.9: The remaining fatigue life of the key point P1 is calculated by the following formula:

[0122] T re =TT run ;

[0123] Where: T represents the total fatigue life of the key point P1 calculated in step 4.8; T run Indicates the elapsed operating time of the shovel working device.

[0124] Repeat the above steps 4.1 to 4.9 to calculate the total fatigue damage of all key points of the shovel working device. Total fatigue life Remaining fatigue life All confirmed.

[0125] Step 5: Health Assessment:

[0126] Step 5.1: Taking a key point as an example, based on the fatigue analysis results of the electric shovel working device obtained in step 4, evaluate its structural health status and generate usage recommendations suitable for this electric shovel.

[0127] Specifically, for any key point P i The total fatigue damage of the system is pre-set with two fatigue damage thresholds, corresponding to the first fatigue damage threshold D max1 , the second fatigue damage threshold D max2 ; For any key point P i The remaining fatigue life of the shovel is determined by a preset threshold value T0 for the next maintenance time. The health status of the shovel working device is divided into four levels, and indicator lights of different colors are used to indicate the status.

[0128] When any key point P of the shovel working device i The total fatigue damage satisfies D<Dmax1 When the shovel is running normally, the working device of the shovel should be maintained regularly and the green indicator light should be triggered, indicating that the working device of the shovel is in good health.

[0129] When any key point P of the shovel working device i The total fatigue damage satisfies D max1 <D<D max2 When , it means that the key point P i It is a dangerous point and needs to be carefully observed and maintained regularly; and the yellow indicator light will be triggered.

[0130] When any key point P of the shovel working device i The total fatigue damage satisfies D>D max2 And the key point P i The remaining fatigue life satisfies T re >T0, indicating that the key point P i It is a dangerous point and needs to be carefully observed and maintained on schedule, and the orange indicator light will be triggered.

[0131] When any key point P of the shovel working device i The total fatigue damage satisfies D>D max2 And the key point P i The remaining fatigue life satisfies T re When <T0, the shovel working device is stopped and a prompt is given to i Perform structural reinforcement and trigger the red indicator light.

[0132] Step 5.2: For any key point P i , the corresponding reinforcement times k are preset, and after each structural reinforcement treatment, the total fatigue damage of the corresponding key points is reset. The value of the reinforcement times k is 3.

[0133] In the specific implementation process, after the first structural reinforcement, the total fatigue damage of the key point is reset to D 加固1 ; After the second structural reinforcement, the total fatigue damage of this key point is reset to D 加固2 ; After the third structural reinforcement, the total fatigue damage of this key point is reset to D 加固3 .

[0134] Step 5.3: For any key point P i , according to each structural reinforcement treatment, the scrap evaluation index X of the given structural parts is i In other words, for a certain key point, the initial value of the structural component scrap evaluation index is 0, the given structural component scrap evaluation index after the first structural reinforcement treatment is marked as X1, the given structural component scrap evaluation index after the second structural reinforcement treatment is marked as X2, and the given structural component scrap evaluation index after the third structural reinforcement treatment is marked as X3... Then the key point Pi The evaluation index of the structural parts scrapping is calculated as follows:

[0135] Step 5.4: Calculate the overall scrap evaluation index of the structural parts of the electric shovel working device. The calculation formula is: And judge whether the overall scrap evaluation index of the structural parts of the electric shovel working device reaches the preset value X 报废 , if the judgment result shows that X>X 报废 , prompting that the electric shovel working device has reached the scrap standard.

Claims

1. A method for monitoring and evaluating the health of welds in a mining electric shovel working device structure based on intelligent bearings, characterized in that: The steps include: Step 1: Construct a stress prediction model: Based on the reduced-order modeling method, a rapid structural stress prediction model is constructed for the electric shovel working device; The structural stress rapid prediction model can predict the structural stress of the key point P at all structural welds of the electric shovel working device by inputting the parameters representing the working state of the electric shovel working device; Step 2: Get the working status of the shovel working device: A first intelligent bearing is installed at the top pulley of the mining electric shovel, and a second intelligent bearing is installed at the push second shaft; The parameters that characterize the working state of the electric shovel working device include the wire rope length L of the electric shovel working device h , lifting load F h , arm extension length L p And the pushing load F P ; The speed S of the top pulley is obtained in real time through the first intelligent bearing h and the real-time load F1 at the top pulley, so as to calculate the wire rope length L of the shovel working device at any time. h , lifting load F h ; The speed S of the second push shaft is obtained in real time through the second intelligent bearing P and the real-time load F2 at the two axes of push, so as to calculate the arm extension length L of the electric shovel working device at any time. p , Pushing load F P ; Step 3: Stress prediction: The length of the wire rope L at any time obtained in step 2 h , lifting load F h , arm extension length L p And the pushing load F P Combined in order into the input vector {L h ,L p ,F h ,F P }; The obtained input vector {L h ,L p ,F h ,F P } Input the structural stress rapid prediction model constructed in step 1 to predict the key points P = {P1, P2, ..., P i ,...,P n } to predict the structural stress and obtain the predicted stress value S={S P1 ,S P2 ,...,S Pi ,...,S Pn }, where: n represents the total number of all key points at the weld of the electric shovel working device structure, and the value is a positive integer; Step 4: Fatigue analysis: Based on the key point P at any structural weld of the shovel working device obtained in step 3 i The predicted stress Calculate the key point P at the corresponding structural weld i Total fatigue damage D, total fatigue life T and remaining fatigue life T re ; Step 5: Health Assessment: Based on the key point P of any structural weld obtained in step 4 i Total fatigue damage D, total fatigue life T and remaining fatigue life T re , evaluate the health status of the shovel's working device and give corresponding usage recommendations.

2. The method for monitoring and evaluating the health of weld seams of a mining electric shovel working device structure based on intelligent bearings according to claim 1 is characterized in that: In step 2, the length of the wire rope at any time is L h , the calculation formula is as follows: Where: L h0 is the initial value of the wire rope length; R h is the pulley radius; S h is the rotation speed of the top pulley, which is obtained in real time through the first intelligent bearing; The lifting load at any time is calculated as follows: F h =T h ×F1; Where: F1 is the real-time load at the top pulley, which is obtained in real time through the first smart bearing; T h is the transformation matrix of the real-time load at the top pulley; The arm extension length L at any time p , the calculation formula is as follows: Where: L p0 is the initial value of the arm length; R P S is the transmission ratio between the push shaft and the bucket arm; P To push the second axis speed, Real-time acquisition through the second intelligent bearing; The push load at any time is calculated as follows: F p =T p ×F2; Where: F2 is the real-time load at the push-pull second axis, which is obtained in real time through the second smart bearing; T p It is the transformation matrix of the real-time load F2 at the pushing and pressing axis.

3. According to claim 1, the method for monitoring and evaluating the health of the weld seam of the working device structure of a mining electric shovel based on intelligent bearings, It is characterized in that In step 4, any key point P i The total fatigue damage is obtained by the following steps: Step 4.1, a SN curve group of structural stress of a given electric shovel structure weld is composed of a plurality of SN curves with different stress ratios; Step 4.2: Obtain any key point P of the shovel working device through step 3 i Time-varying stress It is expressed as: In the formula, Represents the key point P i Predicted stress value at time t1; Step 4.3: Use the real-time rain flow counting method based on the key point P obtained in step 2 i Time-varying stress Get the key point P i The stress amplitude S of the structural stress at a , stress ratio S r and stress cycle number n j ; Step 4.4: According to the stress ratio S r and the weld SN curve set given in step 4.1, interpolate to determine the stress ratio S r The weld SN curve below; Step 4.5: Based on the stress ratio S determined in step 4.4 r The SN curve of the weld under the above conditions is used to obtain the stress amplitude S a The corresponding number of cycles N j ; Step 4.6: Calculate any key point P i Fatigue damage: Step 4.7: According to the Miner criterion, determine any key point P i The total fatigue damage is:

4. The method for monitoring and evaluating the health of welds of a mining electric shovel working device structure based on intelligent bearings according to claim 3 is characterized in that: In step 4, any key point P i The total fatigue life T is calculated by the following formula: Where: D represents any key point P i Total damage; T run Indicates the elapsed operating time of the shovel working device.

5. The method for monitoring and evaluating the health of welds of a mining electric shovel working device structure based on intelligent bearings according to claim 4 is characterized in that: In step 4, any key point P i The remaining fatigue life is calculated by the following formula: T re =T-T run ; Where: T represents any key point P i Total fatigue life; T run Indicates the elapsed operating time of the shovel working device.

6. The method for monitoring and evaluating the health of the weld seam of the working device of a mining electric shovel based on intelligent bearings according to claim 1, It is characterized in that In step 5, for any key point P i The total fatigue damage of the system is pre-set with two fatigue damage thresholds, corresponding to the first fatigue damage threshold D max1 , the second fatigue damage threshold D max2 ; For any key point P i The remaining fatigue life of the vehicle is preset with a threshold value T0 for the next maintenance time; When any key point P of the shovel working device i The total fatigue damage satisfies D<D max1 When working, keep the shovel working device in normal use and perform regular maintenance; When any key point P of the shovel working device i The total fatigue damage satisfies D max1 <D<D max2 When , it means that the key point P i It is a dangerous point and needs to be carefully observed and maintained on schedule; When any key point P of the shovel working device i The total fatigue damage satisfies D>D max2 And the key point P i The remaining fatigue life satisfies T re >T0, indicating that the key point P i It is a dangerous point and needs to be carefully observed and maintained on schedule; When any key point P of the shovel working device i The total fatigue damage satisfies D>D max2 And the key point P i The remaining fatigue life satisfies T re When <T0, the shovel working device is stopped and a prompt is given to i Carry out structural reinforcement.

7. The method for monitoring and evaluating the health of welds of a mining electric shovel working device structure based on intelligent bearings according to claim 6 is characterized in that: In step 5, for any key point P i , the corresponding reinforcement times k are preset, and after each structural reinforcement treatment, the fatigue total damage of the corresponding key point is reset, and the structural component scrap evaluation index X is given for the corresponding key point i ; Calculate any key point P i The evaluation index of structural parts scrapping is calculated as follows: Calculate the scrap evaluation index of the entire structural parts of the electric shovel working device. The calculation formula is: Determine whether the overall scrap evaluation index of the structural parts of the electric shovel working device has reached the preset value X 报废 , if the judgment result shows that X>X 报废 , prompting that the electric shovel working device has reached the scrap standard.

8. The method for monitoring and evaluating the health of welds of a mining electric shovel working device structure based on intelligent bearings according to claim 7 is characterized in that: The value of reinforcement times k is 3.

9. The method for monitoring and evaluating the health of welds of a mining electric shovel working device structure based on intelligent bearings according to claim 1 is characterized in that: In step 1, the structural stress rapid prediction model is constructed in the following way: Step 1.1, establish the finite element model of the electric shovel working device; Step 1.2: According to theoretical analysis and field measurement results, determine the working posture L of the electric shovel working device = {L h ,L p }、Working load F={F h ,F p } value range; Step 1.3: Within the range of the working posture L and the working load F of the electric shovel working device, take N values ​​for combination design to form an array M = {M1, M2, ..., M S ,...,M N }; Any array in array M N represents the total number of elements included in the array M; Step 1.4: Using the finite element model of the electric shovel working device, according to the array M constructed in step 1.3, complete the electric shovel working device in each working condition C = {C1, C2, ..., Cl, ..., C L }Analysis under C l represents the lth working condition among all working conditions C of the electric shovel working device, and L represents the total number of all working conditions of the electric shovel working device; Step 1.5: According to the finite element analysis results and the statistical data of structural weld damage, determine the key points P = {P1, P2, ..., P i ,...,P n }; Step 1.6: Extract and calculate the structural stress of key points under each working condition Step 1.7: Use the reduced-order modeling method to build a rapid prediction model for structural stress, and use the array M built in step 1.3 and the structural stress of key points under each working condition extracted in step 1.6 The constructed rapid structural stress prediction model is trained to obtain a trained rapid structural stress prediction model.

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