A shield machine cutter state electric control evaluation system and method

Abstract

The application discloses a kind of shield machine cutter state electric control evaluation system and method, it is related to shield machine cutter evaluation technical field, the collaborative work of the state evaluation module of scraper, tearing knife and roller cutter is achieved, the overall monitoring and comprehensive evaluation of the running state of cutter core component are realized;Through the use of historical data, real-time data acquisition and dynamic analysis, and the evaluation index generated by multi-module cooperation, the system can accurately reflect the overall operation state of the cutter, timely detect abnormal problems, effectively improve the construction efficiency and operation safety of the shield machine;In addition, the system uses flexible parameter adjustment mechanism and multi-dimensional data fusion technology, not only suitable for different geological conditions and construction needs, but also provides maintenance suggestions to operators in time through early warning function, reduces the risk of failure and construction cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of shield machine cutter evaluation, in particular to a shield machine cutter state electric control evaluation system and method. BACKGROUND

[0002] As the core equipment of tunnel construction, the cutter of the shield machine bears the key task of breaking rocks, cutting soil and cleaning impurities. The three cutters on the cutter, namely the rolling cutter, the scraping cutter and the tearing cutter, each play a different role and adapt to various complex geological conditions through division of labor. However, under the long-time high-load working state of the shield machine, the cutters of the cutter will gradually appear problems such as wear and tear and abnormal stress, directly affecting the construction efficiency and equipment safety. Especially the scraping cutter and the tearing cutter, as they mainly function in cleaning soil, sand and gravel and stone blocks, they are usually located at the edge of the cutter, and their state is difficult to monitor directly.

[0003] In the prior art, the monitoring of the state of the cutter of the shield machine is often limited to a single dimension, such as periodically stopping the machine to detect the wear of the cutters or relying on a single sensor to collect running data. These methods have problems such as detection lag, one-sided data or difficulty in real-time monitoring of the overall health status of the cutter. In addition, different types of cutters (such as rolling cutters, tearing cutters and scraping cutters) have their own operating characteristics and wear laws, and the scraping cutters and the tearing cutters are difficult to install reliable sensors for real-time monitoring due to their dispersed working positions and complex usage. In the process of long-time continuous work of the shield machine, the running state and wear of the scraping cutters and the tearing cutters cannot be known in real time, which may lead to excessive wear or damage of the cutters not being discovered in time, thereby affecting the overall running state of the cutter.

[0004] Therefore, there is an urgent need for an electric control evaluation system and method that can comprehensively monitor and evaluate the state of the cutter of the shield machine to realize accurate judgment and dynamic management of the running state of the cutter and ensure the safety and efficiency of the shield construction. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a shield machine cutter state electric control evaluation system and method, which solves the problems in the background art.

[0006] To achieve the above purpose, the present application realizes the following technical scheme: a shield machine cutter state electric control evaluation system, comprising:

[0007] a scraping cutter and tearing cutter state evaluation module for evaluating the scraping cutters and the tearing cutters on the cutter and determining the state evaluation coefficient of the scraping cutters and the tearing cutters on the cutter as a whole;

[0008] The rolling cutter state evaluation module is configured to evaluate the rolling cutters on the cutter head and determine a state evaluation coefficient of the rolling cutters on the cutter head as a whole.

[0009] The cutter head evaluation module is configured to evaluate the state of the cutter head according to the state evaluation coefficients of the scraping and tearing cutters and the state evaluation coefficient of the rolling cutters on the cutter head as a whole, determine a cutter head evaluation index, and determine the current running state of the cutter head according to the cutter head evaluation index.

[0010] As a further scheme of the present application, the scraping and tearing cutter state evaluation module comprises a historical data storage unit, a reference data determination unit, and a scraping and tearing cutter state evaluation unit.

[0011] The historical data storage unit is configured to store scraping and tearing cutter usage duration data, store the duration of each past usage of the scraping cutter through a scraping cutter usage data set, and store the duration of each past usage of the tearing cutter through a tearing cutter usage data set.

[0012] The reference data determination unit is configured to determine a scraping cutter reference usage duration and a tearing cutter reference usage duration according to the scraping cutter usage data set and the tearing cutter usage data set in the historical data storage unit, respectively.

[0013] The scraping and tearing cutter state evaluation unit is configured to obtain the scraping cutter reference usage duration and the tearing cutter reference usage duration, comprehensively evaluate the scraping and tearing cutters on the cutter head according to the scraping cutter reference usage duration and the tearing cutter reference usage duration, respectively, and determine a state evaluation coefficient of the scraping and tearing cutters on the cutter head as a whole.

[0014] The rolling cutter state evaluation module comprises a rolling cutter data acquisition unit, a data analysis unit, and a rolling cutter state evaluation unit.

[0015] The rolling cutter data acquisition unit is configured to acquire working data of each rolling cutter during work, and the working data comprises rolling cutter rotation data, rolling cutter radius data, rolling cutter temperature data, and rolling cutter stress data.

[0016] The data analysis unit is configured to analyze and determine the real-time index condition of each rolling cutter according to the rolling cutter rotation data, the rolling cutter radius data, the rolling cutter temperature data, and the rolling cutter stress data in the working data, and determine an index coefficient of the real-time index condition of each rolling cutter. The real-time index condition comprises a rotation condition index, a wear condition index, a temperature condition index, and a stress condition index.

[0017] The rolling cutter state evaluation unit is configured to evaluate the running state of each rolling cutter according to the index coefficient of the real-time index condition of each rolling cutter, and further determine a state evaluation coefficient of the rolling cutters on the cutter head as a whole.

[0018] The cutter head evaluation module comprises a cutter head evaluation unit and a warning unit.

[0019] The cutter head evaluation unit is configured to evaluate the state of the cutter head according to the state evaluation coefficient of the overall scraper and tearing knife on the cutter head and the state evaluation coefficient of the overall hob on the cutter head, and determine a cutter head evaluation index;

[0020] The early warning unit is configured to determine the current running state of the cutter head according to the cutter head evaluation index.

[0021] As a further aspect of the present application, the specific way of determining the reference use time length of the scraper and the reference use time length of the tearing knife respectively according to the scraper use data set and the tearing knife use data set in the historical data storage unit is that:

[0022] AS1: Obtain the scraper use data set and the tearing knife use data set, and from the current time, extract scrapers use data and tearing knives use data from the scraper use data set and the tearing knife use data set respectively, wherein, is a preset value;

[0023] AS2: Mark each data in the extracted scrapers use data and tearing knives use data as and respectively, wherein, , represents the th scraper use data in the scrapers use data, represents the th tearing knife use data in the tearing knives use data;

[0024] AS3: Then calculate the average value of the scrapers use data and the tearing knives use data respectively, and mark them as and respectively.

[0025] AS4: Calculate the dispersion value of the scrapers use data by the following formula:

[0026]

[0027] Calculate the dispersion value of the tearing knives use data by the following formula:

[0028]

[0029] AS5: Obtain the dispersion value Discrete values With threshold Comparison:

[0030] like ,Will Average of scraper usage data The scraper's reference usage time is used as a standard, and the scraper's reference usage time is marked as... ;

[0031] like ,according to The results Sort the data from largest to smallest, and select the first value each time. Eliminate, and leave the remaining Recalculate its discrete values ​​until the discrete values ​​are reached. , obtain exclusion Number of ,like ,calculate indivual The average value is used as the reference usage time for the scraper, and the reference usage time for the scraper is marked as... ;like ,calculate indivual The average value is used as the reference usage time for the scraper, and the reference usage time for the scraper is marked as... ;in, .

[0032] As a further aspect of the present invention, it also includes:

[0033] AS6: Obtaining Discrete Values Discrete values With threshold Comparison:

[0034] like ,Will Average data of individual ripper usage The ripper's baseline usage time was used as the reference duration; and the ripper's baseline usage time was marked as... ;

[0035] like ,according to The results Sort the data from largest to smallest, and select the first value each time. Eliminate the remaining ones Recalculate its discrete values ​​until the discrete values ​​are reached. , obtain exclusion Number of ,like ,calculate indivual The average value is used as the reference usage time for the scraper, and the reference usage time for the scraper is marked as... ;like ,calculate indivual The average value is used as the reference usage time for the scraper, and the reference usage time for the scraper is marked as... ;in, .

[0036] As a further aspect of the present invention: the specific method for comprehensively evaluating the scraper and ripper on the cutter disc based on the scraper's reference usage time and the ripper's reference usage time, and determining the overall state evaluation coefficient of the scraper and ripper on the cutter disc, is as follows:

[0037] BS1: Determine the number of scrapers and rippers installed on the cutter head, and mark the scrapers and rippers on the cutter head as follows: and ,in, , z represents the total number of scrapers on the cutter head, and s represents the total number of tearing blades on the cutter head;

[0038] BS2: Next, determine each scraper The duration of use after installation on the cutter head, and marked as such. At the same time, obtain the baseline usage time of the scraper. The following formula is used to calculate the value of each scraper. Usage percentage:

[0039]

[0040] Get each scraper The usage ratio is used to evaluate all scrapers on the cutter head using the following formula to determine the overall condition evaluation coefficient of the scrapers:

[0041]

[0042] in, For the first The weight of each scraper, and satisfying ;

[0043] BS3: Next, determine each tearing blade. The duration of use after installation on the cutter head, and marked as such. Simultaneously, obtain the baseline usage time of the ripper. Each tearing blade is calculated using the following formula. Usage percentage:

[0044]

[0045] Get each ripper The usage ratio is used to evaluate all the ripping blades on the cutter head using the following formula to determine the overall condition evaluation coefficient of the ripping blades:

[0046]

[0047] in, For the first The weight of each scraper, and satisfying .

[0048] As a further aspect of the present invention: the specific method for analyzing and judging the current real-time performance of each hob based on the hob rotation data, hob radius data, hob temperature data, and hob stress data in the working data, and determining the index coefficient of each hob's real-time performance is as follows:

[0049] CS1: Randomly select a hob from the cutter head as the target hob;

[0050] CS2: The index coefficient of the target hob rotation index is determined by the following formula:

[0051]

[0052] in, The index coefficient is represented as an indicator of the rotation status. This represents the current angular velocity of the hob rotation. Expressed as theoretical angular velocity of rotation;

[0053] CS3: The index coefficient of the target hob wear condition index is determined by the following formula:

[0054]

[0055] in, The index coefficient is represented as an indicator of wear and tear. This represents the current radius of the hob. This represents the initial radius of the hob. This represents the minimum radius of the hob. When it is lower than the minimum radius of the hob, it indicates that the hob is severely worn and needs to be replaced.

[0056] CS4: The index coefficients for the target hob temperature condition are determined using the following function:

[0057]

[0058] in, The index coefficient is represented as an indicator of temperature conditions. This represents the current temperature of the hob. This is indicated as the upper limit of the safe temperature. This represents the maximum operating temperature of the hob.

[0059] CS5: The index coefficients of the target hob stress condition index are determined using the following function:

[0060]

[0061] in, The index coefficients are shown as indicators of stress conditions. This represents the actual force applied to the hob. Indicated as the safe stress range, This is expressed as the ultimate stress value;

[0062] CS6: Repeat steps CS2-CS5, treating each hob on the cutter head as a target hob, and determine the index coefficients for the real-time performance of the target hob.

[0063] As a further aspect of the present invention: the specific method for evaluating the operating status of each hob based on the index coefficients of each hob's real-time index conditions, and thus determining the overall state evaluation coefficient of the hobs on the cutter head, is as follows:

[0064] DS1: The evaluation value for each hob's operating state is determined using the following formula:

[0065]

[0066] in, Represented as the first Evaluation values ​​of the hob's operating status. y represents the total number of hobs on the cutter head;

[0067] DS2: Next, obtain the evaluation values ​​of y hob running states, and determine the overall state evaluation coefficient of the hobs on the cutter head using the following formula:

[0068]

[0069] in, It represents the overall state evaluation coefficient of the hobbing cutter on the cutter head.

[0070] As a further aspect of the present invention: the specific method for evaluating the cutter head condition based on the overall condition evaluation coefficients of the scraper and tearing blades on the cutter head and the overall condition evaluation coefficients of the rolling cutter on the cutter head, and determining the cutter head evaluation index, is as follows:

[0071] The tool turret evaluation index is determined using the following formula:

[0072]

[0073] wherein, is expressed as a cutter evaluation index, , and is a weight factor.

[0074] As a further aspect of the present application: the specific way of judging the current running state of the cutter according to the cutter evaluation index is:

[0075] If , it indicates that the current running state of the cutter is not good, and an alarm is sent to the subsequent monitoring display terminal; wherein, is a preset value;

[0076] If , it indicates that the current running state of the cutter tends to be normal, and no processing is done.

[0077] A shield machine cutter state electric control evaluation method, comprising:

[0078] Step one: evaluate the scrapers and tearing knives on the cutter to determine the overall state evaluation coefficient of the scrapers and tearing knives on the cutter;

[0079] Step two: evaluate the rolling knives on the cutter to determine the overall state evaluation coefficient of the rolling knives on the cutter;

[0080] Step three: evaluate the cutter state according to the overall state evaluation coefficient of the scrapers and tearing knives on the cutter and the overall state evaluation coefficient of the rolling knives on the cutter, determine the cutter evaluation index, and judge the current running state of the cutter according to the cutter evaluation index.

[0081] The present application provides a shield machine cutter state electric control evaluation system and method. Compared with the prior art, the following beneficial effects are possessed:

[0082] The shield machine cutter state electric control evaluation system and method provided by the present application realizes comprehensive monitoring and comprehensive evaluation of the running state of the core components of the cutter through the collaborative work of the scraper, tearing knife and rolling knife state evaluation module; through the use of historical data, real-time data acquisition and dynamic analysis, and the evaluation index generated by multi-module collaboration, the system can accurately reflect the overall running state of the cutter, timely discover abnormal problems, and effectively improve the construction efficiency and running safety of the shield machine.

[0083] In addition, the system adopts a flexible parameter adjustment mechanism and multi-dimensional data fusion technology, which is not only suitable for different geological conditions and construction needs, but also provides maintenance suggestions to the operator in time through the early warning function, reduces the risk of failure and construction cost. Overall, the present application significantly improves the scientificity, reliability and intelligent level of the running state evaluation of the cutter of the shield machine, and provides strong support for the safety and efficiency of shield construction. Attached Figure Description

[0084] The invention will now be further described with reference to the accompanying drawings.

[0085] Fig. 1 This is a structural framework diagram of a shield tunneling machine cutterhead condition electrical control evaluation system according to the present invention;

[0086] Fig. 2 This is a flowchart illustrating the steps of an electronic control evaluation method for the cutterhead status of a tunnel boring machine according to the present invention. Detailed Implementation

[0087] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0088] Example 1

[0089] Please see Figs. 1-2 The present invention provides a shield tunneling machine cutterhead condition electrical control evaluation system, comprising:

[0090] The scraper and ripper condition assessment module is used to assess the scraper and ripper on the cutter head and determine the overall condition assessment coefficient of the scraper and ripper on the cutter head. The scraper and ripper condition assessment module includes a historical data storage unit, a baseline data determination unit, and a scraper and ripper condition assessment unit.

[0091] The historical data storage unit is used to store the usage duration data of the scraper and the ripper. The scraper usage dataset stores the duration of each past scraper usage; the ripper usage dataset stores the duration of each past ripper usage.

[0092] Specifically, the storage of the duration of each past use of the scraper and the storage of the duration of each past use of the tearing blade are as follows: the storage of the duration of each past use of the scraper represents the usage time of the scraper on the blade disc from when it is in good condition to when it is scrapped; the storage of the duration of each past use of the tearing blade represents the usage time of the tearing blade on the blade disc from when it is in good condition to when it is scrapped.

[0093] It should be noted that, for a typical tunnel boring machine (TBM), the cutterhead is generally equipped with roller cutters, tearing cutters, and scrapers. The roller cutters are mainly used to break up rocks, the tearing cutters are used to scrape sand into small pieces, and the scrapers are used to scrape off soil and gravel. The three types of blades have different heights and work together in a coordinated manner. The time spent using the scraper and the time spent using the tearing cutter mentioned above represent the time the TBM is in the process of excavation.

[0094] The baseline data determination unit is used to determine the baseline usage time of the scraper and the baseline usage time of the ripper based on the scraper usage dataset and the ripper usage dataset in the historical data storage unit, respectively.

[0095] The specific method for determining the baseline usage time of the scraper and the baseline usage time of the ripper based on the scraper usage dataset and the ripper usage dataset in the historical data storage unit is as follows:

[0096] AS1: Obtain the scraper usage dataset and the ripper usage dataset, and starting from the current moment, extract data from both datasets respectively. Data on scraper usage and Data on the use of individual rippers, among which... These are preset values, specifically determined by professional personnel. In this embodiment, It is 60;

[0097] AS2: Extraction Data on scraper usage and Each data point in the data for each ripper is labeled as follows: and ,in, , Represented as The first scraper usage data Data on scraper usage. Represented as The first data in the ripper usage data Data on the use of individual rippers;

[0098] AS3: Then calculate separately Data on scraper usage and The average value of the data used by each ripper is denoted as follows: and ;

[0099] AS4: Calculated using the following formula Each scraper uses discrete values ​​of data. :

[0100]

[0101] Calculated using the following formula Each ripper uses discrete values ​​of data. :

[0102]

[0103] AS5: Obtaining Discrete Values Discrete values With threshold Comparison:

[0104] like ,Will Average data of scraper usage The scraper's reference usage time is used as a standard, and the scraper's reference usage time is marked as... , where the threshold Determined by professional staff;

[0105] like ,according to The results Sort the data from largest to smallest, and select the first value each time. Eliminate, and leave the remaining Recalculate its discrete values ​​until the discrete values ​​are reached. , obtain exclusion Number of ,like ,calculate indivual The average value is used as the reference usage time for the scraper, and the reference usage time for the scraper is marked as... ;like ,calculate indivual The average value is used as the reference usage time for the scraper, and the reference usage time for the scraper is marked as... ;in, ;

[0106] AS6: Obtaining Discrete Values Discrete values With threshold Comparison:

[0107] like ,Will Average data of ripper usage The ripper's baseline usage time was used as the reference duration; and the ripper's baseline usage time was marked as... Among them, the threshold It shall be determined by professional staff;

[0108] like ,according to The results Sort the data from largest to smallest, and select the first value each time. Eliminate the remaining ones Recalculate its discrete values ​​until the discrete values ​​are reached. , obtain exclusion Number of ,like ,calculate The average value of the first K values is taken as the reference service time of the scraper, and the reference service time of the scraper is marked as Tscraper. If Tscraper , the average value of the first K values is taken as the reference service time of the scraper, and the reference service time of the scraper is marked as Tscraper. ; The average value of the first K values is taken as the reference service time of the scraper, and the reference service time of the scraper is marked as Tscraper. ; ;

[0109] The scraper and the tearing knife state evaluation unit is used to obtain the reference service time of the scraper and the reference service time of the tearing knife, and to comprehensively evaluate the scraper and the tearing knife on the cutter head according to the reference service time of the scraper and the reference service time of the tearing knife, and to determine the state evaluation coefficient of the overall scraper and tearing knife on the cutter head.

[0110] The specific way of comprehensively evaluating the scraper and the tearing knife on the cutter head according to the reference service time of the scraper and the reference service time of the tearing knife, and determining the state evaluation coefficient of the overall scraper and tearing knife on the cutter head is as follows:

[0111] BS1: Determine the number of scrapers and tearing knives installed on the cutter head, and mark the scrapers and tearing knives on the cutter head as S1 and S2 respectively, wherein S1 represents the number of scrapers, and S2 represents the number of tearing knives. , , wherein z represents the total number of scrapers on the cutter head, and s represents the total number of tearing knives on the cutter head. ,

[0112] BS2: Then determine the service time of each scraper S1 installed on the cutter head, and mark it as T1. At the same time, obtain the reference service time of the scraper Tscraper, and calculate the service proportion of each scraper S1 by the following formula:

[0113]

[0114] Obtain the service proportion of each scraper S1, and evaluate all scrapers on the cutter head by the following formula to determine the state evaluation coefficient of the overall scraper:

[0115]

[0116] , wherein w1 represents the weight of the first scraper S1, and the specific parameter value is determined by professional staff according to the installation position of the scraper (such as near the center or the edge) or the actual work load distribution, and satisfies w1 ;

[0117] ​​​​​​​​BS3: Next, determine each tearing blade. The duration of use after installation on the cutter head, and marked as such. Simultaneously, obtain the baseline usage time of the ripper. Each tearing blade is calculated using the following formula. Usage percentage:

[0118]

[0119] Get each tearing blade The usage ratio is used to evaluate all the ripping blades on the cutter head using the following formula to determine the overall condition evaluation coefficient of the ripping blades:

[0120]

[0121] in, For the first The weight of each scraper, and the specific parameter values, are determined by professional personnel based on the scraper's installation location (e.g., near the center or edge) or the actual workload distribution, and must meet the following requirements. ;

[0122] By statistically analyzing and storing historical usage data of the scraper and ripper, and combining this with the calculation of dynamic benchmark usage time, the module accurately assesses the condition of the tools. Through the calculation of discrete values ​​and the elimination of outlier data, this module effectively reduces the interference of outlier data on the assessment results, ensuring the stability and reliability of the assessment. In addition, the module introduces the concept of scraper and ripper weights, and combines the tool installation position and actual workload to further improve the accuracy and adaptability of the assessment results. Finally, this module can generate an overall condition assessment coefficient for the scraper and ripper on the cutterhead, laying the foundation for the overall condition assessment of the cutterhead, effectively improving the monitoring capability of tool condition and reducing construction risks.

[0123] The hob condition assessment module is used to assess the hobs on the cutter head and determine the overall condition assessment coefficient of the hobs on the cutter head. The hob condition assessment module includes a hob data acquisition unit, a data analysis unit, and a hob condition assessment unit.

[0124] The hob data acquisition unit is used to collect the working data of each hob during operation. The working data includes hob rotation data, hob radius data, hob temperature data, and hob stress data.

[0125] Specifically, for the collection of the cutter self-rotation data, a rotation sensor is installed in the bearing of the cutter for monitoring the self-rotation condition of the cutter; at the same time, a protective groove or a sealed cavity is arranged on the surface of the cutter head, and the sensor is embedded in the groove or the cavity to avoid direct exposure to the high-pressure, impact and wear environment; for the collection of the cutter stress data, a stress sensor is embedded in the cutter fixing seat for sensing the stress condition of the cutter; for the collection of the cutter temperature data, a temperature sensor is arranged in the bearing lubricating cavity of the cutter to indirectly judge the temperature of the cutter by monitoring the temperature change of the bearing; for the collection of the cutter radius data, a high-precision displacement sensor (such as a linear displacement sensor or an eddy current displacement sensor) is arranged near the cutter, the probe of the displacement sensor is in contact with the outer edge of the cutter, and the displacement of the sensor probe reflects the change of the radius as the cutter wears;

[0126] a data analysis unit configured to analyze and determine the real-time index condition of each cutter according to the cutter self-rotation data, the cutter radius data, the cutter temperature data and the cutter stress data in the working data, and determine the index coefficient of the real-time index condition of each cutter; wherein the real-time index condition includes a self-rotation condition index, a wear condition index, a temperature condition index and a stress condition index;

[0127] The specific manner of analyzing and determining the real-time index condition of each cutter according to the cutter self-rotation data, the cutter radius data, the cutter temperature data and the cutter stress data in the working data, and determining the index coefficient of the real-time index condition of each cutter is as follows:

[0128] CS1: any cutter selected from the cutter head is taken as a target cutter;

[0129] CS2: the index coefficient of the self-rotation condition index of the target cutter is determined by the following formula:

[0130]

[0131] wherein, represents the index coefficient of the self-rotation condition index, represents the current cutter rotation angular velocity, represents the theoretical rotation angular velocity, and the specific parameter value is determined by professional staff according to past data and experience;

[0132] CS3: the index coefficient of the wear condition index of the target cutter is determined by the following formula:

[0133]

[0134] wherein, represents the index coefficient of the wear condition index, represents the current radius of the cutter, represents the initial radius of the cutter, represents the minimum radius of the cutter, and when it is lower than the minimum radius of the cutter, it indicates that the cutter is severely worn and needs to be replaced;

[0135] CS4: The index coefficient of the target cutter temperature condition index is determined by the following function:

[0136]

[0137] wherein, represents the index coefficient of the temperature condition index, represents the current temperature of the cutter, represents the upper limit of the safety temperature, i.e. the optimal temperature range allowed by the cutter, represents the extreme working temperature of the cutter, and The specific parameter values of and are determined by professional staff according to experience;

[0138] CS5: The index coefficient of the target cutter stress condition index is determined by the following function:

[0139]

[0140] wherein, represents the index coefficient of the stress condition index, represents the actual stress of the cutter, represents the safety stress range, i.e. the maximum working load allowed by the design of the cutter, represents the extreme stress value; and The specific parameter values of and are determined by professional staff according to experience;

[0141] CS6: Repeat steps CS2-CS5, and determine the index coefficient of the real-time index condition of the target cutter for each cutter on the cutter head;

[0142] The cutter state evaluation unit is used to evaluate the running state of each cutter according to the index coefficient of the real-time index condition of each cutter, and further determine the state evaluation coefficient of the overall cutter on the cutter head;

[0143] The specific way of evaluating the running state of each cutter according to the index coefficient of the real-time index condition of each cutter, and further determining the state evaluation coefficient of the overall cutter on the cutter head is:

[0144] DS1: The evaluation value of the running state of each cutter is determined by the following formula:

[0145]

[0146] wherein, evaluation value of the i-th cutter running state, y represents the total number of cutters on the cutter head;

[0147] It should be noted that the coefficients in the formula are index coefficients of the real-time index situation of the i-th cutter, and the values of the coefficients in the formula are different for different i-th cutters;

[0148] DS2: Then, the evaluation values of the running states of the y cutters are obtained, and the state evaluation coefficient of the cutters on the cutter head as a whole is determined by the following formula:

[0149]

[0150] wherein, represents the state evaluation coefficient of the cutters on the cutter head as a whole;

[0151] Based on the four core indexes of cutter rotation, wear, temperature and stress, the data is collected in real time by embedded sensors to comprehensively monitor the running state of each cutter. The sensor layout and protection design avoid the direct impact of harsh environments on the monitoring equipment, improving the durability and data collection accuracy of the system. The multi-dimensional analysis method in the module can dynamically evaluate the state of each cutter according to real-time data, and generate a state evaluation coefficient of the cutters on the cutter head as a whole by integrating the running indexes of individual cutters;

[0152] The cutter head evaluation module is configured to evaluate the state of the cutter head according to the state evaluation coefficient of the scrapers and tear cutters on the cutter head as a whole and the state evaluation coefficient of the cutters on the cutter head as a whole, determine a cutter head evaluation index, and determine the current running state of the cutter head according to the cutter head evaluation index. The cutter head evaluation module includes a cutter head evaluation unit and a warning unit.

[0153] The cutter head evaluation unit is configured to evaluate the state of the cutter head according to the state evaluation coefficient of the scrapers and tear cutters on the cutter head as a whole and the state evaluation coefficient of the cutters on the cutter head as a whole, and determine a cutter head evaluation index.

[0154] The specific way of evaluating the state of the cutter head according to the state evaluation coefficient of the scrapers and tear cutters on the cutter head as a whole and the state evaluation coefficient of the cutters on the cutter head as a whole, and determining a cutter head evaluation index is as follows:

[0155] ​​​​​​​​​​​The cutter head evaluation index is determined by the following formula:

[0156]

[0157] wherein, represents the cutter head evaluation index, , and is a weight factor;

[0158] The early warning unit determines the current running state of the cutter head according to the cutter head evaluation index.

[0159] The specific way of determining the current running state of the cutter head according to the cutter head evaluation index is:

[0160] If , it indicates that the current running state of the cutter head is not good, and an alarm is sent to the subsequent monitoring display terminal; wherein, is a preset value, and the specific parameter is determined by professional staff according to a large number of experiments;

[0161] If , it indicates that the current running state of the cutter head tends to be normal, and no treatment is needed.

[0162] The overall running state of the cutter head is comprehensively evaluated by combining the state evaluation coefficients of the scrapers and the tearing knives and the overall state evaluation coefficient of the rolling cutter to generate a unified cutter head evaluation index. This module can adapt to different construction scenes and the characteristics of cutter head design through flexible adjustment of the weight factor, which provides a guarantee for the accuracy of the evaluation result. At the same time, this module has a built-in early warning function, which can timely send an alarm to the operator when the running state is abnormal through dynamic judgment of the evaluation index, so as to ensure that maintenance measures can be taken quickly when the cutter head state is not good, reducing construction delay and fault risk. Overall, this module significantly improves the safety and running efficiency of the cutter head of the shield tunneling machine through integrated analysis of multiple evaluation results and dynamic early warning of abnormal states.

[0163] Embodiment Two

[0164] In the specific implementation process of this embodiment, on the basis of Embodiment One and different from Embodiment One, this embodiment further provides a method for electrically controlling and evaluating the state of a cutter head of a shield tunneling machine. The method is realized in the following way:

[0165] Step One: Evaluate the scrapers and the tearing knives on the cutter head to determine the overall state evaluation coefficient of the scrapers and the tearing knives on the cutter head.

[0166] Step Two: Evaluate the rolling cutter on the cutter head to determine the overall state evaluation coefficient of the rolling cutter on the cutter head.

[0167] Step three: evaluating the state of the cutter head according to the state evaluation coefficient of the whole scraping knife and tearing knife on the cutter head and the state evaluation coefficient of the whole hob on the cutter head, determining the cutter head evaluation index, and judging the current running state of the cutter head according to the cutter head evaluation index.

[0168] Embodiment three

[0169] In the specific implementation process of this embodiment, all the implementation processes described above are included.

[0170] Some data in the above formula are dimensionless for numerical calculation, and the contents not described in detail in the specification all belong to the prior art known to those skilled in the art.

[0171] The above embodiments are only used to illustrate the technical method of the present application but not limit the present application. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical method of the present application.

Claims

1. A shield tunneling machine cutterhead condition electrical control evaluation system, characterized in that, include: The scraper and ripper condition assessment module is used to assess the scrapers and rippers on the cutter head and determine the overall condition assessment coefficient of the scrapers and rippers on the cutter head. The scraper and ripper condition assessment module includes a historical data storage unit, a baseline data determination unit, and a scraper and ripper condition assessment unit. The historical data storage unit is used to store the usage duration data of the scraper and the ripper. The scraper usage dataset stores the duration of each past scraper usage; the ripper usage dataset stores the duration of each past ripper usage. The baseline data determination unit is used to determine the baseline usage time of the scraper and the baseline usage time of the ripper based on the scraper usage dataset and the ripper usage dataset in the historical data storage unit, respectively. The scraper and ripper condition assessment unit is used to obtain the baseline usage time of the scraper and the baseline usage time of the ripper, and to comprehensively assess the scraper and ripper on the cutter head based on the baseline usage time of the scraper and the baseline usage time of the ripper, and to determine the overall condition assessment coefficient of the scraper and ripper on the cutter head. The hob condition assessment module is used to assess the hobs on the cutter head and determine the overall condition assessment coefficient of the hobs on the cutter head. The hob condition assessment module includes a hob data acquisition unit, a data analysis unit, and a hob condition assessment unit. The hob data acquisition unit is used to collect the working data of each hob during operation. The working data includes hob rotation data, hob radius data, hob temperature data, and hob stress data. The data analysis unit is used to analyze and judge the current real-time index status of each hob based on the hob rotation data, hob radius data, hob temperature data and hob stress data in the working data, and to determine the index coefficient of each hob's real-time index status; among which, the real-time index status includes rotation index, wear index, temperature index and stress index. The hob condition assessment unit is used to assess the operating status of each hob based on the index coefficients of each hob's real-time index conditions, and then determine the overall condition assessment coefficient of the hobs on the cutter head. The cutter head evaluation module is used to evaluate the state of the cutter head based on the overall state evaluation coefficients of the scraper and tearing blades on the cutter head and the overall state evaluation coefficients of the hobbing blades on the cutter head, determine the cutter head evaluation index, and judge the current operating state of the cutter head based on the cutter head evaluation index; The cutterhead evaluation module includes a cutterhead evaluation unit and an early warning unit; The cutter head evaluation unit is used to evaluate the condition of the cutter head based on the overall condition evaluation coefficients of the scraper and tearing blades on the cutter head and the overall condition evaluation coefficients of the hobbing blades on the cutter head, and to determine the cutter head evaluation index. The early warning unit determines the current operating status of the cutterhead based on the cutterhead evaluation indicators.

2. The shield machine cutterhead status electrical control evaluation system according to claim 1, characterized in that, The specific method for determining the baseline usage time of the scraper and the baseline usage time of the ripper based on the scraper usage dataset and the ripper usage dataset in the historical data storage unit is as follows: AS1: Obtain the scraper usage dataset and the ripper usage dataset, and starting from the current moment, extract data from both datasets respectively. Data on scraper usage and Data on the use of individual rippers, among which... This is the default value; AS2: Extraction Data on scraper usage and Each data point in the data for each ripper is labeled as follows: and ,in, , Represented as The first scraper usage data Data on scraper usage. Represented as The first data in the ripper usage data Data on the use of individual rippers; AS3: Then calculate separately Data on scraper usage and The average value of the data used by each ripper is denoted as follows: and ; AS4: Calculated using the following formula Each scraper uses discrete values ​​of data. : ； Calculated using the following formula Each ripper uses discrete values ​​of data. : ； AS5: Obtaining Discrete Values Discrete values With threshold Comparison: like ,Will Average data of scraper usage The scraper's reference usage time is used as a standard, and the scraper's reference usage time is marked as... ; like ,according to The results Sort the data from largest to smallest, and select the first value each time. Eliminate, and leave the remaining Recalculate its discrete values ​​until the discrete values ​​are reached. , obtain exclusion Number of ,like ,calculate indivual The average value is used as the reference usage time for the scraper, and the reference usage time for the scraper is marked as... ;like ,calculate indivual The average value is used as the reference usage time for the scraper, and the reference usage time for the scraper is marked as... ;in, .

3. The shield machine cutterhead status electrical control evaluation system according to claim 2, characterized in that, Also includes: AS6: Obtaining Discrete Values Discrete values With threshold Comparison: like ,Will Average data of ripper usage The ripper's baseline usage time was used as the reference duration; and the ripper's baseline usage time was marked as... ; like ,according to The results Sort the data from largest to smallest, and select the first value each time. Eliminate, and leave the remaining Recalculate its discrete values ​​until the discrete values ​​are reached. , obtain exclusion Number of ,like ,calculate indivual The average value is used as the reference usage time for the scraper, and the reference usage time for the scraper is marked as... ;like ,calculate indivual The average value is used as the reference usage time for the scraper, and the reference usage time for the scraper is marked as... ;in, .

4. The shield machine cutterhead status electrical control evaluation system according to claim 3, characterized in that, The specific method for comprehensively evaluating the scraper and ripper on the cutter disc based on the reference usage time of the scraper and the reference usage time of the ripper is as follows: BS1: Determine the number of scrapers and rippers installed on the cutter head, and mark the scrapers and rippers on the cutter head as follows: and ,in, , z represents the total number of scrapers on the cutter head, and s represents the total number of tearing blades on the cutter head; BS2: Next, determine each scraper The duration of use after installation on the cutter head, and marked as such. At the same time, obtain the baseline usage time of the scraper. The following formula is used to calculate the value of each scraper. Usage percentage: ； Get each scraper The usage ratio is used to evaluate all scrapers on the cutter head using the following formula to determine the overall condition evaluation coefficient of the scrapers: ； in, For the first The weight of each scraper, and satisfying ; BS3: Next, determine each tearing blade. The duration of use after installation on the cutter head, and marked as such. Simultaneously, obtain the baseline usage time of the ripper. Each tearing blade is calculated using the following formula. Usage percentage: ； Get each tearing blade The usage ratio is used to evaluate all the ripping blades on the cutter head using the following formula to determine the overall condition evaluation coefficient of the ripping blades: ； in, For the first The weight of each scraper, and satisfying .

5. The shield machine cutterhead status electrical control evaluation system according to claim 4, characterized in that, The specific method for analyzing and judging the current real-time performance of each hob based on the hob rotation data, hob radius data, hob temperature data, and hob stress data in the working data, and determining the index coefficient of each hob's real-time performance, is as follows: CS1: Randomly select a hob from the cutter head as the target hob; CS2: The index coefficient of the target hob rotation index is determined by the following formula: ； in, The index coefficient is represented as an indicator of the rotation status. This represents the current angular velocity of the hob rotation. Expressed as theoretical angular velocity of rotation; CS3: The index coefficient of the target hob wear condition index is determined by the following formula: ； in, The index coefficient is represented as an indicator of wear and tear. This represents the current radius of the hob. This represents the initial radius of the hob. This represents the minimum radius of the hob. When it is lower than the minimum radius of the hob, it indicates that the hob is severely worn and needs to be replaced. CS4: The index coefficients for the target hob temperature condition are determined using the following function: ； in, The index coefficient is represented as an indicator of temperature conditions. This represents the current temperature of the hob. This is indicated as the upper limit of the safe temperature. This represents the maximum operating temperature of the hob. CS5: The index coefficients of the target hob stress condition index are determined using the following function: ； in, The index coefficients are shown as indicators of stress conditions. This represents the actual force applied to the hob. Indicated as the safe stress range, This is expressed as the ultimate stress value; CS6: Repeat steps CS2-CS5, treating each hob on the cutter head as a target hob, and determine the index coefficients for the real-time performance of the target hob.

6. The shield machine cutterhead status electrical control evaluation system according to claim 5, characterized in that, The specific method for evaluating the operating status of each hob based on the index coefficients of each hob's real-time index conditions, and then determining the overall status evaluation coefficient of the hobs on the cutter head, is as follows: DS1: The evaluation value for each hob's operating state is determined using the following formula: ； in, Represented as the first Evaluation values ​​of the hob's operating status. y represents the total number of hobs on the cutter head; DS2: Next, obtain the evaluation values ​​of y hob running states, and determine the overall state evaluation coefficient of the hobs on the cutter head using the following formula: ； in, It represents the overall state evaluation coefficient of the hobbing cutter on the cutter head.

7. The shield machine cutterhead status electrical control evaluation system according to claim 6, characterized in that, The specific method for evaluating the cutter head condition and determining the cutter head evaluation index based on the overall condition evaluation coefficients of the scraper and tearing blades on the cutter head and the overall condition evaluation coefficients of the hobbing cutter on the cutter head is as follows: The tool turret evaluation index is determined using the following formula: ； in, This is represented as a toolbox evaluation index. , and This is the weighting factor.

8. The shield machine cutterhead status electrical control evaluation system according to claim 7, characterized in that, The specific method for determining the current operating status of the cutter head based on the cutter head evaluation indicators is as follows: like This indicates that the cutterhead is not operating properly, and an alarm is sent to the subsequent monitoring display terminal; among them, This is the default value; like This indicates that the cutter head is currently operating normally and no further action is required.

9. A method for evaluating the electrical control status of a tunnel boring machine (TBM) cutterhead, wherein the method is applied to the TBM cutterhead electrical control evaluation system according to any one of claims 1-8, characterized in that, include: Step 1: Evaluate the scraper and ripper on the cutter head and determine the overall condition evaluation coefficient of the scraper and ripper on the cutter head; Step 2: Evaluate the hobs on the cutter head and determine the overall state evaluation coefficient of the hobs on the cutter head; Step 3: Evaluate the condition of the cutter head based on the overall condition evaluation coefficients of the scraper and tearing blades on the cutter head and the overall condition evaluation coefficients of the rolling cutter on the cutter head, determine the cutter head evaluation index, and judge the current operating condition of the cutter head based on the cutter head evaluation index.

Images