A fault analysis method and system of a hydraulic anchor rod drill rig for coal mines

Abstract

The application discloses a kind of hydraulic anchor rod drill rig's fault analysis method and system for coal mine, it is related to mining machinery equipment technical field, comprising: at least one fault perception unit is arranged in drill rig and the data acquisition of fault perception unit is carried out;Establish drill rig environment benchmark model, calculate the actual response coefficient of fault perception unit;According to the acquisition data of each sensor of at least one historical hydraulic fault of drill rig, the historical response coefficient of fault perception unit in historical hydraulic fault is calculated;According to historical response coefficient, the identification rule of historical hydraulic fault is constructed;The actual fault that exists in drill rig is identified using the identification rule of historical hydraulic fault.Through establishing drill rig environment benchmark model, calculating the actual response coefficient of fault perception unit and constructing the identification rule of historical hydraulic fault, the influence of different temperature and hydraulic pressure on sound frequency is comprehensively considered, and multiple faults existing in parallel can be determined.

Description

Technical Field

[0001] This invention relates to the field of mining machinery and equipment technology, specifically to a fault analysis method and system for a hydraulic anchor bolt drilling rig used in coal mines. Background Technology

[0002] Hydraulic anchor drilling rigs are industrial equipment primarily used in support engineering for coal mine roadways and tunnels. Powered by a hydraulic system, they perform drilling operations to install anchor bolts and reinforce the roadway. They offer advantages such as safety, explosion-proof design, ease of operation, and labor-saving features.

[0003] Although the failure rate of hydraulic anchor drilling rigs is low, there is still a certain failure rate. There are various types of failures in hydraulic anchor drilling rigs, but the most critical ones are related to the hydraulic system. However, there are many types of failures in the hydraulic system, and multiple failures may occur simultaneously. In addition, due to different parameter settings for the drilling rig, the parameters are affected by failures in different ways, which will hinder the accurate identification of failures. Summary of the Invention

[0004] To solve the above-mentioned technical problems, a fault analysis method and system for a hydraulic anchor bolt drilling rig used in coal mines is provided. This technical solution solves the problems mentioned in the background technology.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A fault analysis method for a hydraulic anchor bolt drilling rig used in coal mines includes:

[0007] At least one fault sensing unit is installed inside the drilling rig, and data from the fault sensing unit is collected. The fault sensing unit is a temperature sensor, a sound sensor, or a pressure sensor.

[0008] Establish a drilling rig environment benchmark model, and calculate the actual response coefficient of the fault sensing unit based on the drilling rig environment benchmark model;

[0009] Based on the sensor data collected from at least one historical hydraulic fault of the drilling rig, the historical response coefficient of the fault sensing unit in the historical hydraulic fault is calculated.

[0010] Based on historical response coefficients, identification rules for historical hydraulic faults are constructed;

[0011] By using historical hydraulic fault identification rules, the actual faults existing in the drilling rig can be identified.

[0012] Preferably, the step of installing at least one fault sensing unit inside the drilling rig and collecting data from the fault sensing unit includes the following steps:

[0013] Temperature sensor array, sound sensor array, and pressure sensor array are installed inside the drilling rig, with the same number of each type of sensor.

[0014] A temperature feature set C is established based on the temperature sensor array. The temperature feature set C is derived from... , ..., Composition, where n is the number of temperature sensors, where This represents the data collected by the i-th temperature sensor, where i is the subscript;

[0015] A sound frequency set D is established based on the sound sensor array. The sound frequency set D is derived from... , ..., Composition, in which This represents the data collected by the i-th sound sensor;

[0016] A load sensing set E is established based on the pressure sensor array. The load sensing set E is composed of... , ..., Composition, in which The data corresponds to the data collected by the i-th pressure sensor;

[0017] Temperature sensors, sound sensors, and pressure sensors with the same number are placed in the same location.

[0018] Preferably, the establishment of the drilling rig environmental benchmark model includes the following steps:

[0019] Pair the data collected by the fault sensing units with the same number in the temperature feature set, sound frequency set, and load sensing set to form at least one initial coordinate. The data in the initial coordinate are in the order of data collected by the temperature sensor, pressure sensor, and sound sensor.

[0020] The ternary coordinates are obtained by taking the average of at least one initial coordinate.

[0021] Obtain at least one baseline condition indicating that the drilling rig is operating normally;

[0022] The ternary coordinates obtained under the baseline conditions will be used as the baseline ternary coordinates;

[0023] A benchmark fitting function is obtained by fitting a benchmark ternary coordinate system for at least one benchmark condition. The independent variable of the benchmark fitting function is the data collected by the temperature sensor and the pressure sensor, and the dependent variable is the data collected by the sound sensor. The benchmark fitting function is used as the benchmark model of the drilling rig environment.

[0024] Preferably, the step of calculating the actual response coefficient of the fault perception unit based on the drilling rig environmental benchmark model includes the following steps:

[0025] During the actual operation of the drilling rig, at least one initial coordinate is obtained as the actual initial coordinate, and the data in the actual initial coordinate are recorded as the first actual value, the second actual value, and the third actual value in sequence.

[0026] Substitute the first and second actual values ​​into the benchmark fitting function to obtain the actual reference value, and subtract the third actual value from the actual reference value to obtain the actual difference value.

[0027] The first actual value, the second actual value, and the actual difference value are paired and fitted to obtain the actual response function, where the first actual value and the second actual value are independent variables, and the actual difference value is the dependent variable.

[0028] Plot the actual response function in the coordinate system to obtain the actual response surface, and take at least one actual point uniformly on the actual response surface;

[0029] The actual response coefficients are obtained by taking the average slope of the actual response surface at at least one actual point.

[0030] Preferably, the calculation of the historical response coefficients of the fault sensing unit in historical hydraulic faults includes the following steps:

[0031] Under the condition of historical hydraulic failure, at least one initial coordinate is obtained as the historical initial coordinate, and the data in the historical initial coordinate is recorded as the first historical value, the second historical value and the third historical value in sequence.

[0032] Substitute the first and second historical values ​​into the benchmark fitting function to obtain the historical reference value, and subtract the third historical value from the historical reference value to obtain the historical difference value.

[0033] The first historical value, the second historical value, and the historical difference value are paired and fitted to obtain the historical response function, where the first historical value and the second historical value are independent variables, and the historical difference value is the dependent variable.

[0034] Plot the historical response function in the coordinate system to obtain the historical response surface, and take at least one historical point uniformly on the historical response surface;

[0035] The historical response coefficients are obtained by averaging the slopes of the historical response surface at at least one historical point.

[0036] Preferably, the step of constructing the identification rules for historical hydraulic faults based on historical response coefficients includes the following steps:

[0037] Based on the drilling rig environmental benchmark model and benchmark conditions, the fluctuation range of historical response coefficients is formed;

[0038] A recognition interval for the historical response coefficient is formed, with the historical response coefficient as the midpoint. The length of the recognition interval is equal to twice the fluctuation range of the historical response coefficient. The recognition interval is matched to the historical hydraulic fault that generated the historical response coefficient.

[0039] At least one identification point is uniformly selected in the identification interval to form at least one combination of identification points, such that the identification points in the combination of identification points belong to different identification intervals.

[0040] Based on experience, set the allowable error for fault analysis;

[0041] If the difference between the cumulative value of the identification points in the identification point combination and the actual response coefficient is less than the allowable error, then the historical hydraulic faults corresponding to the identification intervals containing the identification points in the identification point combination will be considered as suspected hydraulic faults.

[0042] Preferably, the process of determining the fluctuation range of historical response coefficients based on the drilling rig environmental benchmark model and benchmark conditions includes the following steps:

[0043] Under the baseline conditions, at least one initial coordinate obtained will be used as the baseline initial coordinate;

[0044] The data in the initial coordinate system are recorded in sequence as the first reference value, the second reference value, and the third reference value;

[0045] Substitute the first and second benchmark values ​​into the benchmark fitting function to obtain the benchmark reference value. Subtract the third benchmark value from the benchmark reference value to obtain the benchmark difference value.

[0046] The first benchmark value, the second benchmark value, and the benchmark difference value are paired and fitted to obtain the benchmark response function, where the first benchmark value and the second benchmark value are independent variables, and the benchmark difference value is the dependent variable.

[0047] The average of the absolute values ​​of the maximum and minimum values ​​of the derivative of the baseline response function is used as the floating value for the baseline case.

[0048] The average of the fluctuation values ​​of at least one baseline case is used to obtain the fluctuation range of the historical response coefficient.

[0049] Preferably, the process of identifying actual faults in the drilling rig using historical hydraulic fault identification rules includes the following steps:

[0050] When a suspected hydraulic fault is identified, the operating parameters of the drilling rig are changed to obtain at least one actual operating parameter.

[0051] Given the actual operating parameters, the actual response coefficient is used to identify the suspected hydraulic faults corresponding to the actual response coefficients using the historical hydraulic fault identification rules. The suspected hydraulic faults corresponding to the same actual response coefficient are then aggregated to form a set of suspected hydraulic faults.

[0052] The intersection of the suspected hydraulic fault sets is used to obtain the actual fault set. The elements in the actual fault set are taken as the actual faults existing in the drilling rig.

[0053] A fault analysis system for a hydraulic anchor bolt drilling rig used in coal mines, used to implement the aforementioned fault analysis method for the hydraulic anchor bolt drilling rig used in coal mines, includes:

[0054] The data acquisition module is equipped with at least one fault sensing unit inside the drilling rig and performs data acquisition from the fault sensing unit. The fault sensing unit is a temperature sensor, a sound sensor, or a pressure sensor.

[0055] The data processing module establishes a drilling rig environment benchmark model, calculates the actual response coefficient of the fault sensing unit based on the drilling rig environment benchmark model, and calculates the historical response coefficient of the fault sensing unit in the historical hydraulic fault based on the sensor data collected by each sensor of at least one historical hydraulic fault of the drilling rig.

[0056] A rule-building module, which constructs identification rules for historical hydraulic faults based on historical response coefficients;

[0057] The fault identification module uses historical hydraulic fault identification rules to identify the actual faults existing in the drilling rig.

[0058] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0059] By establishing a benchmark model of the drilling rig environment, calculating the actual response coefficient of the fault perception unit, and constructing identification rules for historical hydraulic faults, the actual response coefficient and historical response coefficient are generated by collecting temperature, sound, and hydraulic data and integrating the effects of different temperatures and hydraulic pressures on sound frequencies. Based on the historical response coefficient, fault identification rules are generated, and then the fault identification results of the actual response coefficient under various conditions are combined to determine the actual faults existing in the drilling rig. Thus, multiple faults existing in parallel can be identified, and errors caused by the influence of faults on different operating parameters can be avoided, thereby enabling accurate fault identification. Attached Figure Description

[0060] Figure 1 This is a flowchart illustrating the fault analysis method for the hydraulic anchor bolt drilling rig used in coal mines according to the present invention.

[0061] Figure 2This is a schematic diagram illustrating the process of installing at least one fault sensing unit inside the drilling rig and collecting data from the fault sensing unit according to the present invention.

[0062] Figure 3 This is a schematic diagram of the process for establishing the drilling rig environmental benchmark model according to the present invention;

[0063] Figure 4 This is a flowchart illustrating the process of calculating the actual response coefficient of the fault sensing unit based on the drilling rig environmental benchmark model of the present invention.

[0064] Figure 5 This is a schematic diagram of the process for calculating the historical response coefficients of the fault sensing unit in historical hydraulic faults according to the present invention.

[0065] Figure 6 This is a flowchart illustrating the process of constructing historical hydraulic fault identification rules based on historical response coefficients according to the present invention.

[0066] Figure 7 This is a flowchart illustrating the process of generating the fluctuation range of historical response coefficients based on the drilling rig environmental benchmark model and benchmark conditions according to the present invention.

[0067] Figure 8 This is a schematic diagram illustrating the process of identifying actual faults in a drilling rig using historical hydraulic fault identification rules, as described in this invention. Detailed Implementation

[0068] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0069] Reference Figure 1 As shown, a fault analysis method for a hydraulic anchor bolt drilling rig used in coal mines includes:

[0070] At least one fault sensing unit is installed inside the drilling rig, and data from the fault sensing unit is collected. The fault sensing unit is a temperature sensor, a sound sensor, or a pressure sensor.

[0071] Establish a drilling rig environment benchmark model, and calculate the actual response coefficient of the fault sensing unit based on the drilling rig environment benchmark model;

[0072] Based on the sensor data collected from at least one historical hydraulic fault of the drilling rig, the historical response coefficient of the fault sensing unit in the historical hydraulic fault is calculated.

[0073] Based on historical response coefficients, identification rules for historical hydraulic faults are constructed;

[0074] By using historical hydraulic fault identification rules, the actual faults existing in the drilling rig can be identified.

[0075] The main purpose of this solution is to analyze the faults in the hydraulic system of a hydraulic anchor bolt drilling rig. The analysis primarily uses the vibration frequency of sound to identify faults. Since the hydraulic anchor bolt drilling rig operates using hydraulic pressure, any abnormality in the hydraulic system will cause changes in vibration, which can be used to identify the fault. However, it is important to note that different operating environments of the hydraulic anchor bolt drilling rig, such as varying ambient temperatures and different hydraulic pressure outputs depending on the specific operational requirements, will affect the sound. Therefore, these factors need to be taken into account, and corresponding steps are included in the subsequent steps to address these issues.

[0076] Reference Figure 2 As shown, installing at least one fault detection unit inside the drilling rig and collecting data from the fault detection unit includes the following steps:

[0077] Temperature sensor array, sound sensor array, and pressure sensor array are installed inside the drilling rig, with the same number of each type of sensor.

[0078] A temperature feature set C is established based on the temperature sensor array. The temperature feature set C consists of , ..., n, where n is the number of temperature sensors, and represents the data collected by the i-th temperature sensor, where i is the subscript.

[0079] A sound frequency set D is established based on the sound sensor array. The sound frequency set D is composed of , ..., , where represents the data collected by the i-th sound sensor.

[0080] A load sensing set E is established based on the pressure sensor array. The load sensing set E is composed of, ..., where corresponds to the data collected by the i-th pressure sensor.

[0081] Temperature sensors, sound sensors, and pressure sensors with the same number are placed in the same location.

[0082] Here, data is collected. Temperature sensors, sound sensors, or pressure sensors are collectively referred to as fault sensing units. The purpose of numbering is to ensure that temperature sensors, sound sensors, or pressure sensors with the same number are in the same location, so that their data collection conditions are consistent. Therefore, they can be combined for analysis. Otherwise, combining data from different locations for analysis can easily lead to analysis errors.

[0083] Reference Figure 3 As shown, establishing the drilling rig environmental benchmark model includes the following steps:

[0084] Pair the data collected by the fault sensing units with the same number in the temperature feature set, sound frequency set, and load sensing set to form at least one initial coordinate. The data in the initial coordinate are in the order of data collected by the temperature sensor, pressure sensor, and sound sensor.

[0085] The ternary coordinates are obtained by taking the average of at least one initial coordinate.

[0086] Obtain at least one baseline condition indicating that the drilling rig is operating normally;

[0087] The ternary coordinates obtained under the baseline conditions will be used as the baseline ternary coordinates;

[0088] A benchmark fitting function is obtained by fitting a benchmark ternary coordinate system for at least one benchmark condition. The independent variable of the benchmark fitting function is the data collected by the temperature sensor and the pressure sensor, and the dependent variable is the data collected by the sound sensor. The benchmark fitting function is used as the benchmark model of the drilling rig environment.

[0089] The benchmark fitting function outputs the sound frequency. Its main purpose is to predict the sound frequency under different temperature and pressure conditions during normal operation. This allows for comparison with data collected under different temperature and pressure conditions. Thus, the influence of different factors in the conditions can be avoided during the comparison, and only the sound frequency is considered, resulting in more accurate identification.

[0090] Reference Figure 4 As shown, the calculation of the actual response coefficient of the fault sensing unit based on the drilling rig environment benchmark model includes the following steps:

[0091] During the actual operation of the drilling rig, at least one initial coordinate is obtained as the actual initial coordinate, and the data in the actual initial coordinate are recorded as the first actual value, the second actual value, and the third actual value in sequence.

[0092] Substitute the first and second actual values ​​into the benchmark fitting function to obtain the actual reference value, and subtract the third actual value from the actual reference value to obtain the actual difference value.

[0093] The first actual value, the second actual value, and the actual difference value are paired and fitted to obtain the actual response function, where the first actual value and the second actual value are independent variables, and the actual difference value is the dependent variable.

[0094] Plot the actual response function in the coordinate system to obtain the actual response surface, and take at least one actual point uniformly on the actual response surface;

[0095] The actual response coefficients are obtained by taking the average slope of the actual response surface at at least one actual point.

[0096] The actual response coefficient is mainly generated by the surface formed by the actual difference value. Assuming that there are no faults in the actual operation, the actual difference value should be very close to the value predicted by the benchmark fitting function. Since the benchmark fitting function is a bivariate function and its graph is a surface, the generated actual response surface must be almost planar. Conversely, when there are more faults, the deviation between the actual response coefficient and the value predicted by the benchmark fitting function will change with the temperature and pressure. Therefore, the average slope of the tangent plane at at least one actual point can be used as the actual response coefficient, which can reflect the abnormality of the sound frequency. The calculation principle of the historical response coefficient is consistent with that of the actual response coefficient.

[0097] Reference Figure 5 As shown, the calculation of the historical response coefficients of the fault sensing unit in historical hydraulic faults includes the following steps:

[0098] Under the condition of historical hydraulic failure, at least one initial coordinate is obtained as the historical initial coordinate, and the data in the historical initial coordinate is recorded as the first historical value, the second historical value and the third historical value in sequence.

[0099] Substitute the first and second historical values ​​into the benchmark fitting function to obtain the historical reference value, and subtract the third historical value from the historical reference value to obtain the historical difference value.

[0100] The first historical value, the second historical value, and the historical difference value are paired and fitted to obtain the historical response function, where the first historical value and the second historical value are independent variables, and the historical difference value is the dependent variable.

[0101] Plot the historical response function in the coordinate system to obtain the historical response surface, and take at least one historical point uniformly on the historical response surface;

[0102] The historical response coefficients are obtained by averaging the slopes of the historical response surface at at least one historical point.

[0103] Reference Figure 6 As shown, the steps for constructing identification rules for historical hydraulic faults based on historical response coefficients are as follows:

[0104] Based on the drilling rig environmental benchmark model and benchmark conditions, the fluctuation range of historical response coefficients is formed;

[0105] A recognition interval for the historical response coefficient is formed, with the historical response coefficient as the midpoint. The length of the recognition interval is equal to twice the fluctuation range of the historical response coefficient. The recognition interval is matched to the historical hydraulic fault that generated the historical response coefficient.

[0106] At least one identification point is uniformly selected in the identification interval to form at least one combination of identification points, such that the identification points in the combination of identification points belong to different identification intervals.

[0107] Based on experience, set the allowable error for fault analysis;

[0108] If the difference between the cumulative value of the identification points in the identification point combination and the actual response coefficient is less than the allowable error, then the historical hydraulic faults corresponding to the identification intervals containing the identification points in the identification point combination will be considered as suspected hydraulic faults.

[0109] At least one historical hydraulic fault encompasses all past faults of the drilling rig. Each fault is different, leading to different historical response coefficients. However, due to fluctuations during fault occurrence, the actual response coefficient resulting from a fault related to a historical hydraulic fault may differ from the historical response coefficient corresponding to that fault. Therefore, it is necessary to establish an identification interval for historical response coefficients to identify the historical hydraulic faults corresponding to those coefficients. Furthermore, multiple faults may exist concurrently, meaning the actual response coefficient may correspond to at least one historical hydraulic fault. Therefore, this fault is decomposed using an exhaustive comparison method. When the difference between the cumulative value of the identification points in the identification point combination and the actual response coefficient is less than the allowable error, it indicates that the common effect of the historical hydraulic faults corresponding to the identification interval containing the identification points in the identification point combination is consistent with the actual response coefficient. Therefore, these are suspected faults requiring further screening.

[0110] Reference Figure 7 As shown, based on the drilling rig environmental benchmark model and benchmark conditions, the fluctuation range of historical response coefficients includes the following steps:

[0111] Under the baseline conditions, at least one initial coordinate obtained will be used as the baseline initial coordinate;

[0112] The data in the initial coordinate system are recorded in sequence as the first reference value, the second reference value, and the third reference value;

[0113] Substitute the first and second benchmark values ​​into the benchmark fitting function to obtain the benchmark reference value. Subtract the third benchmark value from the benchmark reference value to obtain the benchmark difference value.

[0114] The first benchmark value, the second benchmark value, and the benchmark difference value are paired and fitted to obtain the benchmark response function, where the first benchmark value and the second benchmark value are independent variables, and the benchmark difference value is the dependent variable.

[0115] The average of the absolute values ​​of the maximum and minimum values ​​of the derivative of the baseline response function is used as the floating value for the baseline case.

[0116] The average of the fluctuation values ​​of at least one baseline case is used to obtain the fluctuation range of the historical response coefficient.

[0117] Historical response coefficients are used to identify historical hydraulic faults corresponding to historical response coefficients. In reality, when historical hydraulic faults occur, the resulting response coefficients will deviate from the historical response coefficients. Therefore, it is necessary to determine the magnitude of this deviation. Response coefficients with a difference from the historical response coefficient less than this deviation are identified as historical hydraulic faults corresponding to the historical response coefficients. The fluctuation range is obtained based on the fluctuation situation in the baseline conditions. The baseline conditions are all normal operating conditions, so the fluctuation situation in them is also normal. In addition, to avoid the abnormal influence of a single case, the average value of the fluctuation value of at least one baseline condition is taken.

[0118] Reference Figure 8 As shown, the identification of actual faults in the drilling rig using historical hydraulic fault identification rules includes the following steps:

[0119] When a suspected hydraulic fault is identified, the operating parameters of the drilling rig are changed to obtain at least one actual operating parameter.

[0120] Given the actual operating parameters, the actual response coefficient is used to identify the suspected hydraulic faults corresponding to the actual response coefficients using the historical hydraulic fault identification rules. The suspected hydraulic faults corresponding to the same actual response coefficient are then aggregated to form a set of suspected hydraulic faults.

[0121] The intersection of the suspected hydraulic fault sets is used to obtain the actual fault set. The elements in the actual fault set are taken as the actual faults existing in the drilling rig.

[0122] Because the identification rules of historical hydraulic faults are used, multiple suspected hydraulic faults corresponding to the actual response coefficients can be identified. However, these are not necessarily actual faults. In actual use, the operating parameters of the drilling rig can be adjusted. Therefore, multiple operating conditions can be obtained by adjusting the hydraulic system. Under different operating conditions, the corresponding actual response coefficients can be obtained. Using the identification rules of historical hydraulic faults, the set of suspected hydraulic faults corresponding to the actual response coefficients can be identified. It is easy to know that the actual fault must appear in all the suspected hydraulic fault sets corresponding to the actual response coefficients, that is, it must appear in their intersection. Therefore, when the number of actual response coefficients is large enough, the faults contained in their intersection can almost be identified as actual faults. Fault handling according to the elements in their intersection can definitely solve all actual faults. However, some non-existent faults may need to be handled, but their number is very small and the operation time is short. Therefore, it will not have a significant impact on the processing.

[0123] A fault analysis system for a hydraulic anchor bolt drilling rig used in coal mines, used to implement the aforementioned fault analysis method for the hydraulic anchor bolt drilling rig used in coal mines, includes:

[0124] The data acquisition module is equipped with at least one fault sensing unit inside the drilling rig and performs data acquisition from the fault sensing unit. The fault sensing unit is a temperature sensor, a sound sensor, or a pressure sensor.

[0125] The data processing module establishes a drilling rig environment benchmark model, calculates the actual response coefficient of the fault sensing unit based on the drilling rig environment benchmark model, and calculates the historical response coefficient of the fault sensing unit in the historical hydraulic fault based on the sensor data collected by each sensor of at least one historical hydraulic fault of the drilling rig.

[0126] A rule-building module, which constructs identification rules for historical hydraulic faults based on historical response coefficients;

[0127] The fault identification module uses historical hydraulic fault identification rules to identify the actual faults existing in the drilling rig.

[0128] Furthermore, this solution also proposes a storage medium on which a computer-readable program is stored, which, when invoked, executes the aforementioned fault analysis method for hydraulic anchor drilling rigs used in coal mines.

[0129] It is understandable that the storage medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid-state drive (SSD).

[0130] In summary, the advantages of this invention are as follows: by establishing a benchmark model of the drilling rig environment, calculating the actual response coefficient of the fault perception unit, and constructing identification rules for historical hydraulic faults, the actual response coefficient and historical response coefficient are generated by collecting temperature, sound, and hydraulic data and integrating the effects of different temperatures and hydraulic pressures on sound frequencies. Based on the historical response coefficient, fault identification rules are generated, and then the fault identification results of the actual response coefficients under various conditions are combined to determine the actual faults existing in the drilling rig. Thus, multiple faults existing in parallel can be identified, and errors caused by the influence of faults on different operating parameters can be avoided, thereby enabling accurate fault identification.

[0131] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A fault analysis method for a hydraulic anchor bolt drilling rig used in coal mines, characterized in that, include: At least one fault sensing unit is installed inside the drilling rig, and data from the fault sensing unit is collected. The fault sensing unit is a temperature sensor, a sound sensor, or a pressure sensor. Establish a drilling rig environment benchmark model, and calculate the actual response coefficient of the fault sensing unit based on the drilling rig environment benchmark model; Based on the sensor data collected from at least one historical hydraulic fault of the drilling rig, the historical response coefficient of the fault sensing unit in the historical hydraulic fault is calculated. Based on historical response coefficients, identification rules for historical hydraulic faults are constructed; By using historical hydraulic fault identification rules, the actual faults existing in the drilling rig can be identified; The process of constructing identification rules for historical hydraulic faults based on historical response coefficients includes the following steps: Based on the drilling rig environmental benchmark model and benchmark conditions, the fluctuation range of historical response coefficients is formed; A recognition interval for the historical response coefficient is formed, with the historical response coefficient as the midpoint. The length of the recognition interval is equal to twice the fluctuation range of the historical response coefficient. The recognition interval is matched to the historical hydraulic fault that generated the historical response coefficient. At least one identification point is uniformly selected in the identification interval to form at least one combination of identification points, such that the identification points in the combination of identification points belong to different identification intervals. Based on experience, set the allowable error for fault analysis; If the difference between the cumulative value of the identification points in the identification point combination and the actual response coefficient is less than the allowable error, then the historical hydraulic faults corresponding to the identification intervals containing the identification points in the identification point combination will be considered as suspected hydraulic faults.

2. The fault analysis method for a hydraulic anchor bolt drilling rig used in coal mines according to claim 1, characterized in that, The process of installing at least one fault detection unit inside the drilling rig and collecting data from the fault detection unit includes the following steps: Temperature sensor array, sound sensor array, and pressure sensor array are installed inside the drilling rig, with the same number of each type of sensor. A temperature feature set C is established based on the temperature sensor array. The temperature feature set C is derived from... , ..., Composition, where n is the number of temperature sensors, where This represents the data collected by the i-th temperature sensor, where i is the subscript; A sound frequency set D is established based on the sound sensor array. The sound frequency set D is derived from... , ..., Composition, in which This represents the data collected by the i-th sound sensor; A load sensing set E is established based on the pressure sensor array. The load sensing set E is composed of... , ..., Composition, in which The data corresponds to the data collected by the i-th pressure sensor; Temperature sensors, sound sensors, and pressure sensors with the same number are placed in the same location.

3. The fault analysis method for a hydraulic anchor bolt drilling rig used in coal mines according to claim 2, characterized in that, The establishment of the drilling rig environmental benchmark model includes the following steps: Pair the data collected by the fault sensing units with the same number in the temperature feature set, sound frequency set, and load sensing set to form at least one initial coordinate. The data in the initial coordinate are in the order of data collected by the temperature sensor, pressure sensor, and sound sensor. The ternary coordinates are obtained by taking the average of at least one initial coordinate. Obtain at least one baseline condition indicating that the drilling rig is operating normally; The ternary coordinates obtained under the baseline conditions will be used as the baseline ternary coordinates; A benchmark fitting function is obtained by fitting a benchmark ternary coordinate system for at least one benchmark condition. The independent variable of the benchmark fitting function is the data collected by the temperature sensor and the pressure sensor, and the dependent variable is the data collected by the sound sensor. The benchmark fitting function is used as the benchmark model of the drilling rig environment.

4. The fault analysis method for a hydraulic anchor bolt drilling rig used in coal mines according to claim 3, characterized in that, The calculation of the actual response coefficient of the fault sensing unit based on the drilling rig environment benchmark model includes the following steps: During the actual operation of the drilling rig, at least one initial coordinate is obtained as the actual initial coordinate, and the data in the actual initial coordinate are recorded as the first actual value, the second actual value, and the third actual value in sequence. Substitute the first and second actual values ​​into the benchmark fitting function to obtain the actual reference value, and subtract the third actual value from the actual reference value to obtain the actual difference value. The first actual value, the second actual value, and the actual difference value are paired and fitted to obtain the actual response function, where the first actual value and the second actual value are independent variables, and the actual difference value is the dependent variable. Plot the actual response function in the coordinate system to obtain the actual response surface, and take at least one actual point uniformly on the actual response surface; The actual response coefficients are obtained by taking the average slope of the actual response surface at at least one actual point.

5. The fault analysis method for a hydraulic anchor bolt drilling rig used in coal mines according to claim 4, characterized in that, The calculation of the historical response coefficients of the fault sensing unit in historical hydraulic faults includes the following steps: Under the condition of historical hydraulic failure, at least one initial coordinate is obtained as the historical initial coordinate, and the data in the historical initial coordinate is recorded as the first historical value, the second historical value and the third historical value in sequence. Substitute the first and second historical values ​​into the benchmark fitting function to obtain the historical reference value, and subtract the third historical value from the historical reference value to obtain the historical difference value. The first historical value, the second historical value, and the historical difference value are paired and fitted to obtain the historical response function, where the first historical value and the second historical value are independent variables, and the historical difference value is the dependent variable. Plot the historical response function in the coordinate system to obtain the historical response surface, and take at least one historical point uniformly on the historical response surface; The historical response coefficients are obtained by averaging the slopes of the historical response surface at at least one historical point.

6. The fault analysis method for a hydraulic anchor bolt drilling rig used in coal mines according to claim 5, characterized in that, The process of determining the fluctuation range of historical response coefficients based on the drilling rig environmental benchmark model and benchmark conditions includes the following steps: Under the baseline conditions, at least one initial coordinate obtained will be used as the baseline initial coordinate; The data in the initial coordinate system are recorded in sequence as the first reference value, the second reference value, and the third reference value; Substitute the first and second benchmark values ​​into the benchmark fitting function to obtain the benchmark reference value. Subtract the third benchmark value from the benchmark reference value to obtain the benchmark difference value. The first benchmark value, the second benchmark value, and the benchmark difference value are paired and fitted to obtain the benchmark response function, where the first benchmark value and the second benchmark value are independent variables, and the benchmark difference value is the dependent variable. The average of the absolute values ​​of the maximum and minimum values ​​of the derivative of the baseline response function is used as the floating value for the baseline case. The average of the fluctuation values ​​of at least one baseline case is used to obtain the fluctuation range of the historical response coefficient.

7. The fault analysis method for a hydraulic anchor bolt drilling rig used in coal mines according to claim 6, characterized in that, The process of identifying actual faults in the drilling rig using historical hydraulic fault identification rules includes the following steps: When a suspected hydraulic fault is identified, the operating parameters of the drilling rig are changed to obtain at least one actual operating parameter. Given the actual operating parameters, the actual response coefficient is used to identify the suspected hydraulic faults corresponding to the actual response coefficients using the historical hydraulic fault identification rules. The suspected hydraulic faults corresponding to the same actual response coefficient are then aggregated to form a set of suspected hydraulic faults. The intersection of the suspected hydraulic fault sets is used to obtain the actual fault set. The elements in the actual fault set are taken as the actual faults existing in the drilling rig.

8. A fault analysis system for a hydraulic anchor bolt drilling rig used in coal mines, used to implement the fault analysis method for a hydraulic anchor bolt drilling rig used in coal mines as described in any one of claims 1-7, characterized in that, include: The data acquisition module is equipped with at least one fault sensing unit inside the drilling rig and performs data acquisition from the fault sensing unit. The fault sensing unit is a temperature sensor, a sound sensor, or a pressure sensor. The data processing module establishes a drilling rig environment benchmark model, calculates the actual response coefficient of the fault sensing unit based on the drilling rig environment benchmark model, and calculates the historical response coefficient of the fault sensing unit in the historical hydraulic fault based on the sensor data collected by each sensor of at least one historical hydraulic fault of the drilling rig. A rule-building module, which constructs identification rules for historical hydraulic faults based on historical response coefficients; The fault identification module uses historical hydraulic fault identification rules to identify the actual faults existing in the drilling rig.

Images