A coke oven electric locomotive running distance error monitoring method and system

Abstract

The present application relates to the technical field of distance error monitoring, and particularly relates to a coke oven electric locomotive running distance error monitoring method and system, which comprises the following steps: obtaining first running distance measurement data and second running distance measurement data of the coke oven electric locomotive; obtaining the contact state between the coke oven electric locomotive and the track, and generating a count compensation coefficient based on the contact state; compensating and correcting the second running distance measurement data based on the count compensation coefficient to obtain third running distance measurement data; real-time conversion and comparison of the first running distance measurement data and the third running distance measurement data; and triggering a running distance deviation alarm in response to the comparison result exceeding a preset error threshold. Through the present application, the long-term stable operation of the coke dry quenching electric locomotive can be ensured, and the maintenance cost and downtime risk can be reduced.

Description

Technical Field

[0001] This invention relates to the technical field of distance error monitoring, and in particular to a method and system for monitoring the travel distance error of a coke oven locomotive. Background Technology

[0002] The dry quenching coke locomotive is mainly responsible for transporting coke cans filled with red coke to the dry quenching furnace area and transporting empty coke cans back to the coke oven. The accuracy of its travel distance measurement directly determines the accuracy of vehicle positioning, which in turn affects the dry quenching coke production efficiency and operational safety.

[0003] Existing methods for monitoring the travel distance error of coke oven locomotives mostly rely on a dual-encoder system consisting of a positioning encoder and a detection encoder. The positioning anomaly is determined by comparing the distance measurements from both. However, the measurement accuracy of the detection encoder is heavily dependent on the physical contact between its counting wheel and the track. Under conditions such as rain, snow, vibration, or uneven track, the counting wheel may slip, bounce, or experience insufficient contact pressure. This causes measurement errors within the detection encoder itself, making the data from the detection encoder used as a comparison benchmark unreliable and thus affecting the accuracy of the entire dual-encoder error monitoring system. Summary of the Invention

[0004] This invention provides a method and system for monitoring the travel distance error of coke oven locomotives, which can effectively solve the problems in the background art.

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

[0006] A method for monitoring the travel distance error of a coke oven locomotive includes:

[0007] Acquire the first and second travel distance measurement data of the coke oven locomotive;

[0008] The contact state between the coke oven locomotive and the track is obtained, and a counting compensation coefficient is generated based on the contact state.

[0009] Based on the counting compensation coefficient, the second walking distance measurement data is compensated and corrected to obtain the third walking distance measurement data;

[0010] The first walking distance measurement data and the third walking distance measurement data are converted and compared in real time;

[0011] If the comparison result exceeds the preset error threshold, a travel distance deviation alarm is triggered.

[0012] Furthermore, the first traversing distance measurement data is collected by a positioning encoder; the second traversing distance measurement data is collected by a detection encoder.

[0013] The positioning encoder is installed on the running wheel axle of the coke oven locomotive, and the detection encoder is installed on the independent counting wheel. The independent counting wheel is pressed against the track by a spring buffer device, and a vibration sensor and a pressure sensor are installed on the independent counting wheel.

[0014] Further, the contact state between the coke oven locomotive and the track is obtained, and a counting compensation coefficient is generated based on the contact state, including:

[0015] Within a preset distance from which the coke oven locomotive begins to travel, real-time contact status data between the independent counting wheels and the track are collected multiple times at a preset frequency;

[0016] Based on preset contact state data, the deviation of multiple sets of real-time contact state data is calculated respectively, and the multiple deviations are summarized in time sequence to obtain a state deviation sequence.

[0017] The state deviation sequence is evaluated in two dimensions to obtain the time series fluctuation index and the statistical anomaly index;

[0018] The time series fluctuation index and the statistical anomaly index are input into a preset count compensation correction model to obtain the count compensation coefficient.

[0019] Furthermore, the contact state data includes vibration data and pressure data.

[0020] Furthermore, the preset contact state data is contact state data collected under ideal environmental conditions; the ideal environmental conditions include a smooth track, no rain or snow interference, and stable operation of the locomotive.

[0021] Further, based on the aforementioned counting compensation coefficient, the second traversal ranging data is compensated and corrected to obtain the third traversal ranging data, including:

[0022] The obtained counting compensation coefficients are correlated with the second walking distance measurement data;

[0023] The compensation algorithm is determined based on the properties of the counting compensation coefficient and the characteristics of the second-travel distance measurement data;

[0024] The associated counting compensation coefficient and the second travel distance measurement data are substituted into the determined compensation algorithm for calculation;

[0025] The calculated third travel distance measurement data is verified.

[0026] Furthermore, the first walking distance measurement data and the third walking distance measurement data are converted and compared in real time, including:

[0027] The first and third travel distance measurement data are uniformly converted into the same length unit, a fixed time base is determined, and the travel distance measurement data is converted into the travel distance within that time period using this time base as the unit.

[0028] Based on the relationship between the actual operating speed of the electric locomotive and time, a linear conversion model is constructed;

[0029] After completing the real-time conversion, the conversion results of the first walking distance measurement data and the third walking distance measurement data are compared at the same time point.

[0030] Furthermore, the linear conversion model calculates that the travel distance of the locomotive when it is running at a constant speed is equal to the speed multiplied by the time; when the locomotive is running at a non-uniform speed, the running process is divided into multiple segments, and the movement is approximately uniform within each segment. The travel distance of each segment is calculated separately and then summed to obtain the travel distance of the entire process.

[0031] Furthermore, the factors influencing the setting of the preset error threshold include the locomotive's own performance, track conditions, coke weight, and environmental conditions.

[0032] On the other hand, the present invention also provides a coke oven locomotive travel distance error monitoring system, comprising:

[0033] The travel distance measurement data acquisition module acquires the first travel distance measurement data and the second travel distance measurement data of the coke oven locomotive;

[0034] The contact state acquisition and compensation coefficient generation module acquires the contact state between the coke oven locomotive and the track, and generates a counting compensation coefficient based on the contact state.

[0035] The ranging data compensation and correction module compensates and corrects the second walking ranging data based on the counting compensation coefficient to obtain the third walking ranging data.

[0036] The data conversion and real-time comparison module performs real-time conversion and comparison between the first walking distance measurement data and the third walking distance measurement data;

[0037] The deviation alarm trigger module triggers a travel distance deviation alarm in response to the comparison result exceeding the preset error threshold.

[0038] The technical solution of this invention achieves the following technical effects: By acquiring the contact state between the locomotive and the track and generating a counting compensation coefficient, the second travel distance measurement data is compensated and corrected, reducing measurement errors caused by slippage, bouncing, or insufficient contact pressure, and improving the reliability of the third travel distance measurement data; after compensation and correction, the more accurate third travel distance measurement data is compared with the first travel distance measurement data, which can accurately determine whether the positioning is abnormal and improve the accuracy of travel distance error monitoring; by improving the accuracy of distance measurement data and error monitoring, the vehicle can be accurately aligned, reducing production delays and safety accident risks caused by misalignment, and improving the efficiency and safety of dry quenching production; this method acquires the contact state between the locomotive and the track in real time. The system automatically adapts to changes in the contact state between the counting wheel and the track under different working conditions, generating a counting compensation coefficient to correct the distance measurement data. This eliminates the need for frequent manual intervention and allows for accurate monitoring of travel distance errors under various conditions. Throughout the entire locomotive operation, it continuously and promptly detects travel distance deviations. If the comparison result exceeds a preset error threshold, a travel distance deviation alarm is immediately triggered, enabling operators to take timely measures to prevent more serious problems caused by the accumulation of deviations and improve the controllability of the entire production process. Through the compensation and correction mechanism, the system improves data accuracy and system reliability, reduces misjudgments and system failures caused by measurement errors, ensures the long-term stable operation of the dry quenching coke locomotive, and reduces maintenance costs and downtime risks.

[0039] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a schematic diagram of the process of the present invention;

[0042] Figure 2 This is a structural diagram of the coke oven locomotive travel distance error monitoring system. Detailed Implementation

[0043] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0044] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0045] like Figure 1 As shown, the present invention provides a method for monitoring the travel distance error of a coke oven locomotive, which specifically includes the following steps:

[0046] S1. Obtain the first and second travel distance measurement data of the coke oven locomotive;

[0047] S2. Obtain the contact state between the coke oven locomotive and the track, and generate a counting compensation coefficient based on the contact state;

[0048] S3. Based on the counting compensation coefficient, the second walking distance measurement data is compensated and corrected to obtain the third walking distance measurement data;

[0049] S4. Perform real-time conversion and comparison between the first walking distance measurement data and the third walking distance measurement data;

[0050] S5. In response to the comparison result exceeding the preset error threshold, a travel distance deviation alarm is triggered.

[0051] In this embodiment, by acquiring the contact state between the locomotive and the track and generating a counting compensation coefficient, the second travel distance measurement data is compensated and corrected, reducing measurement errors caused by slippage, bouncing, or insufficient contact pressure, and improving the reliability of the third travel distance measurement data. After compensation and correction, the more accurate third travel distance measurement data is compared with the first travel distance measurement data, which can accurately determine whether the positioning is abnormal and improve the accuracy of travel distance error monitoring. By improving the accuracy of distance measurement data and error monitoring, the vehicle can be accurately aligned, reducing production delays and safety accident risks caused by misalignment, and improving the efficiency and safety of dry quenching production. This method acquires the contact state between the locomotive and the track in real time and, based on... This generated counting compensation coefficient corrects the distance measurement data and can automatically adapt to changes in the contact state between the counting wheel and the track under different working conditions, eliminating the need for frequent manual intervention and adjustment. It can accurately monitor the travel distance error under different working conditions; throughout the entire locomotive operation, it can continuously and promptly detect travel distance deviations; once the comparison result exceeds the preset error threshold, it immediately triggers a travel distance deviation alarm, enabling operators to take timely measures to avoid more serious problems caused by the accumulation of deviations, thereby improving the controllability of the entire production process; through the compensation correction mechanism, it improves the accuracy of data and the reliability of the system, reduces misjudgments and system failures caused by measurement errors, ensures the long-term stable operation of the dry quenching coke locomotive, and reduces maintenance costs and downtime risks.

[0052] In some embodiments of the present invention, for step S1, the first travel distance measurement data and the second travel distance measurement data of the coke oven locomotive are obtained;

[0053] The first travel distance measurement data is collected by a positioning encoder. The positioning encoder is directly installed on the travel wheel axle of the coke oven locomotive. Because the travel wheel axle is directly related to the actual travel of the locomotive, its rotation can accurately reflect the travel distance of the locomotive. During installation, ensure that the encoder is firmly connected to the wheel axle to avoid data deviation due to looseness. The positioning encoder records the number of rotations of the travel wheel axle through its internal counting device. Combined with the pre-set travel wheel circumference parameter, the first travel distance measurement data can be obtained by multiplication. This data serves as a basic reference and can accurately reflect the actual travel distance of the locomotive.

[0054] The second travel distance measurement data is collected by a detection encoder. The detection encoder is installed on an independent counting wheel, which is pressed firmly onto the track by a spring buffer device. The independent counting wheel is protected from interference from vibrations of other parts of the locomotive, and the spring buffer device ensures that the counting wheel and the track maintain appropriate contact pressure at all times, reducing slippage. At the same time, vibration sensors and pressure sensors are installed on the independent counting wheel. The vibration sensor can monitor the vibration of the counting wheel in real time, and the pressure sensor can obtain the pressure value between the counting wheel and the track in real time. The detection encoder records the number of rotations of the independent counting wheel, and combines it with the circumference of the counting wheel to obtain preliminary distance measurement data. The data collected by the vibration sensor and pressure sensor are also transmitted.

[0055] In this embodiment, by acquiring the first and second travel distance measurement data of the coke oven locomotive, the accuracy and reliability of distance measurement can be effectively improved. The first travel distance measurement data is collected by a positioning encoder, which is directly installed on the travel wheel axle. Since the travel wheel axle is directly related to the actual travel of the locomotive, its rotation can accurately reflect the travel distance of the locomotive. During installation, it is ensured that the encoder is firmly connected to the wheel axle to avoid data deviation caused by loosening. The encoder records the number of rotations of the wheel axle and combines it with the circumference parameter of the travel wheel to obtain the first travel distance measurement data through multiplication. The first travel distance measurement data can accurately reflect the actual travel distance of the locomotive. The second travel distance measurement data is collected by a detection encoder, which is installed on a separate... The counting wheel is pressed firmly onto the track by a spring buffer device, which avoids interference from vibrations of other parts of the locomotive and ensures that the wheel maintains appropriate contact pressure with the track, reducing slippage. Vibration and pressure sensors are installed on the counting wheel to monitor vibration and pressure values ​​in real time and transmit data. The encoder records the number of rotations of the wheel and calculates preliminary distance measurement data by combining the wheel's circumference. The data from the vibration and pressure sensors can effectively supplement the distance measurement results, further ensuring the accuracy and stability of the distance measurement data. By combining the first and second travel distance measurement data, the measurement accuracy of the locomotive's travel distance can be effectively improved, errors can be reduced, and the reliability of the system can be enhanced.

[0056] In a specific implementation, as one example, for step S2, the contact state between the coke oven locomotive and the track is obtained, and a counting compensation coefficient is generated based on the contact state;

[0057] Within a preset distance at which the coke oven locomotive begins to travel—a distance determined after extensive experimentation and verification using actual operational data—the contact between the locomotive and the track during the initial startup phase can be comprehensively reflected. Real-time contact status data between the independent counting wheels and the track is collected multiple times at a preset frequency. The collected contact status data includes vibration and pressure data. Vibration data reflects the vibration of the counting wheels during travel due to track unevenness, locomotive vibration, and other factors. Pressure data reflects the magnitude of the contact pressure between the counting wheels and the track. Through high-frequency acquisition, detailed and accurate information on changes in the contact status can be obtained.

[0058] Based on the preset contact state data, which is collected under ideal environmental conditions, the ideal environmental conditions refer to conditions such as a smooth track, no rain or snow interference, and stable locomotive operation. Under ideal environmental conditions, vibration and pressure data collected by the same vibration and pressure sensors are used as standard references. The deviation between multiple sets of real-time contact state data and preset contact state data is calculated. The multiple deviations are summarized in chronological order to obtain the state deviation sequence.

[0059] A two-dimensional evaluation is performed on the state deviation sequence. The first dimension is the temporal volatility index, which represents the degree of fluctuation of the state deviation sequence over time. By calculating the rate of change of deviation between adjacent time points and performing statistical analysis on the rate of change of the entire sequence, an index that reflects the magnitude of the fluctuation of the contact state over time is obtained. If the deviation changes drastically between adjacent time points, it indicates that the contact state has changed significantly in a short period of time, and the temporal volatility index will be high; conversely, if the change is gradual, the temporal volatility index will be low. The second dimension is the statistical anomaly index, which is used to analyze the anomalies in the data of the state deviation sequence from a statistical perspective. By setting reasonable statistical intervals and judgment criteria, the number and degree of data points with deviations exceeding the normal range are statistically analyzed, and then the statistical anomaly index is calculated. If there are many anomalous data points with large deviations in the sequence, the statistical anomaly index will be high.

[0060] The calculated temporal fluctuation index and statistical anomaly index are input into the preset counting compensation correction model. The counting compensation correction model is established based on a large amount of experimental data and actual operation cases, and comprehensively considers the impact of temporal fluctuation and statistical anomaly on the measurement error of the detection encoder. The model internally uses complex algorithms and parameter settings to convert the temporal fluctuation index and statistical anomaly index into specific counting compensation coefficients. When both the temporal fluctuation index and statistical anomaly index are high, it indicates that the contact condition is poor and the detection encoder may have a large measurement error. The model will output a large counting compensation coefficient to correct the second travel distance data. Conversely, when both indices are low, the output counting compensation coefficient is smaller.

[0061] In this embodiment, by acquiring the contact state between the coke oven locomotive and the track, the ranging accuracy can be effectively optimized. Within a preset distance at the start of the locomotive's movement, vibration and pressure data between the independently counting wheels and the track are collected at high frequency to record the changes in the contact state in detail. The collected data can reflect the contact situation between the locomotive and the track at the initial stage of startup, and can reveal the fluctuation of the contact state when the track is uneven or the locomotive vibrates. Using the preset contact state data as a benchmark, the deviation between the real-time contact state data and the standard data is calculated to obtain the state deviation sequence, which is then further evaluated in two dimensions. The time-series fluctuation index reflects the contact... The temporal fluctuation index measures the degree of contact state fluctuation over time, while the statistical anomaly index reveals abnormal fluctuations in the contact state through statistical analysis of deviation anomalies. These two indices provide a basis for the subsequent generation of the counting compensation coefficient. If the temporal fluctuation index and the statistical anomaly index are high, it indicates that the contact state is unstable and the measurement error of the encoder may be large. The model will output a larger counting compensation coefficient to correct the second travel distance measurement data. Conversely, if the two indices are low, the output compensation coefficient will be smaller. This step can dynamically adjust the distance measurement data according to the changes in the contact state, ensuring the accuracy and stability of the measurement results under different conditions and improving the measurement accuracy of the locomotive's travel distance.

[0062] In some embodiments of the present invention, for step S3, the second walking distance measurement data is compensated and corrected based on the counting compensation coefficient to obtain the third walking distance measurement data;

[0063] The obtained counting compensation coefficient is correlated with the second travel distance measurement data. Since the counting compensation coefficient is generated under a specific contact state, and the second travel distance measurement data is also collected during the operation of the same or similar locomotives, it is necessary to ensure that the two are corresponding in time and space so as to accurately perform compensation correction. The data can be matched according to the timestamps of the collected contact state data and the second travel distance measurement data.

[0064] Based on the nature of the counting compensation coefficient and the characteristics of the second travel distance measurement data, the compensation algorithm is determined. If the counting compensation coefficient is a proportionality coefficient, representing the proportional relationship between the measurement error and the true value, a multiplicative compensation algorithm can be used, i.e., third travel distance measurement data = second travel distance measurement data × (1 + counting compensation coefficient) or third travel distance measurement data = second travel distance measurement data × (1 - counting compensation coefficient), with the specific positive or negative sign determined according to the error direction. If the counting compensation coefficient is a fixed deviation value, an additive compensation algorithm is used, i.e., third travel distance measurement data = second travel distance measurement data + counting compensation coefficient or third travel distance measurement data = second travel distance measurement data - counting compensation coefficient.

[0065] The associated counting compensation coefficient and the second travel distance measurement data are substituted into the determined compensation algorithm for calculation;

[0066] Verify the calculated third travel distance data to check if it is within a reasonable range. If abnormal data is found, it may be due to inaccurate generation of the counting compensation coefficient or improper selection of the compensation algorithm. In this case, the contact state data can be re-analyzed, the counting compensation coefficient can be adjusted, or a more suitable compensation algorithm can be selected. The compensation calculation can be performed again until reasonable third travel distance data is obtained.

[0067] In this embodiment, the second travel distance measurement data is compensated and corrected using a counting compensation coefficient to obtain the third travel distance measurement data. This ensures the temporal and spatial correspondence between the counting compensation coefficient and the second travel distance measurement data, avoiding data inconsistencies due to time differences or different acquisition conditions. Matching timestamps accurately correlates the two, ensuring the accuracy of the compensation calculation. A suitable compensation algorithm is selected based on the characteristics of the counting compensation coefficient and the nature of the second travel distance measurement data. The third travel distance measurement data is obtained by substituting both into the compensation algorithm. After calculation, data verification is performed to ensure it is within a reasonable range. If data anomalies are found, the contact state data needs to be re-analyzed and the compensation coefficient or compensation algorithm adjusted until a reasonable result is obtained. This step ensures that the distance measurement data can be accurately corrected during operation, improving the accuracy of the measurement results. Through a reasonable compensation algorithm and verification mechanism, errors caused by inaccurate counting compensation coefficients or improper compensation methods are avoided, improving the stability of the system in practical applications.

[0068] In some embodiments of the present invention, for step S4, the first walking distance measurement data and the third walking distance measurement data are converted and compared in real time;

[0069] Unify data units and benchmarks; convert the first and third travel distance measurement data into the same length unit to ensure data comparability; at the same time, determine a fixed time benchmark, and use this time benchmark as the unit to convert the travel distance measurement data into the travel distance within that time period to eliminate data differences caused by time factors.

[0070] Based on the relationship between the actual operating speed and time of the locomotive, a linear conversion model is constructed. Assuming that the locomotive runs at a constant speed and the travel distance is equal to the speed multiplied by the time, the locomotive speed information is acquired in real time and combined with a unified time reference to convert the first and third travel distance measurement data into the theoretical travel distance within the same time period. If the locomotive does not run at a constant speed, a piecewise linear interpolation method is used to divide the running process into multiple segments. Within each segment, the locomotive is approximated as moving at a constant speed. The travel distance of each segment is calculated separately and then summed to obtain the travel distance of the entire process, thus realizing the real-time conversion between the two types of data.

[0071] After real-time conversion is completed, the conversion results of the first walking distance measurement data and the third walking distance measurement data are compared at the same time point. By setting a data buffer, the conversion data within a certain period of time is stored. The difference between the two conversion results is calculated using a comparison algorithm, and it is determined whether the difference exceeds the preset error threshold.

[0072] In this embodiment, by converting and comparing the first and third travel distance measurement data in real time, the consistency of the two types of data under the same time reference can be ensured. By unifying the data units and references, differences caused by different units or time references are eliminated. By converting the two sets of data into the same length unit and setting a fixed time reference, the travel distance of the locomotive within the same time period can be accurately reflected. A linear conversion model is established using the relationship between the actual operating speed of the locomotive and time, and the two sets of data are converted into theoretical travel distances according to the speed information of the locomotive. Under non-uniform speed operation, the travel distance of each segment is calculated using piecewise linear interpolation, and the cumulative travel distance of the entire process is finally obtained. After the real-time conversion is completed, by comparing the conversion results of the two datasets at the same time node, the differences between the two can be clearly understood. By setting a data buffer to store the conversion results within a certain period of time and applying a comparison algorithm to calculate the difference, it is possible to effectively determine whether the difference exceeds the preset error threshold, thereby realizing real-time monitoring and adjustment of data accuracy and ensuring the accuracy of the locomotive's operating status.

[0073] In some embodiments of the present invention, for step S5, in response to the comparison result exceeding a preset error threshold, a walking distance deviation alarm is triggered;

[0074] Setting a reasonable error threshold, the factors influencing the setting of the preset error threshold include:

[0075] The performance of the locomotive itself varies. Different models and specifications of dry quenching coke locomotives have differences in their mechanical structure, transmission system, and control system, which will affect the accuracy and stability of the travel distance measurement. The accuracy of the transmission device will also affect the accuracy of the travel distance. Factors such as gear ratio error and chain slack may cause the actual travel distance to be inconsistent with the theoretical value. Therefore, it is necessary to determine a reasonable error range based on the performance of the locomotive itself as a preset error threshold.

[0076] Track conditions, such as the flatness, straightness, and gauge of the track, have a significant impact on the measurement of the locomotive's travel distance. If the track is uneven, curved, or has a gauge deviation, the locomotive will experience bumps and swaying during operation, causing unstable contact between the counting wheels and the track, which in turn affects the accuracy of the distance measurement. The actual condition of the track is an important reference factor for setting the preset error threshold.

[0077] The weight of the coke can, especially when full of red-hot coke, differs significantly from that of an empty one. This difference affects the locomotive's running resistance and acceleration, thus impacting the distance measurement. A heavy coke can makes starting and braking more difficult, and the acceleration changes during operation are more complex, potentially leading to larger fluctuations in the distance measurement data. Conversely, an empty coke can makes the locomotive run more easily, resulting in relatively stable distance measurement data. Therefore, variations in the weight of the coke can must be taken into account when setting a preset error threshold.

[0078] Environmental conditions, such as rain, snow, vibration, and temperature, can affect locomotives and ranging equipment to varying degrees. Rain and snow may cause slippage between the counting wheels and the track, or water accumulation, affecting measurement accuracy. Vibration can lead to loosening of internal components and signal interference, resulting in inaccurate ranging data. Temperature changes may cause thermal expansion and contraction of the ranging equipment, affecting its performance and measurement accuracy. Therefore, it is necessary to set a reasonable preset error threshold based on the actual operating environment to adapt to measurement needs under different conditions.

[0079] Establish a real-time monitoring and judgment mechanism; continuously monitor the comparison results in real time during the data comparison process; use hardware circuits or software algorithms to compare the difference obtained from the comparison with the preset error threshold in real time; when the comparison difference is greater than or equal to the preset error threshold, it is determined that there is a deviation in the travel distance.

[0080] Once a deviation in travel distance is detected, the alarm device is immediately triggered. The alarm device can take various forms, such as an audible and visual alarm that emits a loud sound and bright light to attract the operator's attention; it can also send alarm information to the operator's mobile terminal, such as a mobile phone or tablet, and notify them in a timely manner via SMS, APP push, etc. At the same time, the alarm information is displayed on the monitoring system's display interface with eye-catching colors or icons, making it convenient for the operator to quickly locate the problem.

[0081] In this embodiment, by setting a reasonable error threshold and triggering a travel distance deviation alarm based on the comparison results, the accuracy of locomotive travel distance monitoring can be improved. By considering the performance differences of the locomotives themselves, it can be ensured that the error threshold reflects the performance characteristics of different locomotive models in different working environments, thereby ensuring measurement accuracy. The influence of track conditions on distance measurement accuracy is also taken into consideration, solving the interference caused by uneven, curved, or gauge deviations in the track, making the travel distance data more accurate and reliable. The fluctuations in locomotive resistance and acceleration caused by changes in coke tank weight are further incorporated into the error threshold setting, ensuring the stability of measurement data under different load conditions. The influence of external factors such as environmental conditions, such as rain, snow, vibration, and temperature changes, on the distance measuring equipment is also considered when setting the error threshold, thereby ensuring that the distance measuring system can maintain good working condition in various environments. By constructing a real-time monitoring and judgment mechanism, the comparison results can be continuously monitored and compared with the preset error threshold in real time. Once the difference exceeds the threshold, the alarm system is immediately triggered, ensuring that operators can respond quickly and solve problems in a timely manner. This can reduce production safety hazards caused by travel distance deviation and ensure the stability of dry quenching production efficiency.

[0082] Based on the same inventive concept as the coke oven locomotive travel distance error monitoring method in the foregoing embodiments, the present invention also provides a coke oven locomotive travel distance error monitoring system, such as... Figure 2 As shown, the system includes:

[0083] The travel distance measurement data acquisition module acquires the first travel distance measurement data and the second travel distance measurement data of the coke oven locomotive;

[0084] The contact state acquisition and compensation coefficient generation module acquires the contact state between the coke oven locomotive and the track, and generates a counting compensation coefficient based on the contact state.

[0085] The ranging data compensation and correction module compensates and corrects the second walking ranging data based on the counting compensation coefficient to obtain the third walking ranging data.

[0086] The data conversion and real-time comparison module performs real-time conversion and comparison between the first walking distance measurement data and the third walking distance measurement data;

[0087] The deviation alarm trigger module triggers a travel distance deviation alarm in response to the comparison result exceeding the preset error threshold.

[0088] The system described above in this invention can effectively realize the method for monitoring the travel distance error of coke oven locomotives, and the technical effects it can achieve are as described in the above embodiments, which will not be repeated here.

[0089] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely exemplary illustrations of the application as defined herein, and are to be considered as covering any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Thus, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A method for monitoring the travel distance error of a coke oven locomotive, characterized in that, include: Acquire the first and second travel distance measurement data of the coke oven locomotive; The first travel distance measurement data is collected by a positioning encoder; the second travel distance measurement data is collected by a detection encoder; the positioning encoder is installed on the travel wheel axle of the coke oven locomotive, the detection encoder is installed on an independent counting wheel, the independent counting wheel is pressed against the track by a spring buffer device, and a vibration sensor and a pressure sensor are provided on the independent counting wheel; The process of acquiring the contact state between the coke oven locomotive and the track, and generating a counting compensation coefficient based on the contact state, includes: collecting real-time contact state data between the independent counting wheels and the track multiple times at a preset frequency within a preset distance from which the coke oven locomotive begins to travel; calculating the deviation of multiple sets of real-time contact state data based on the preset contact state data, and summarizing the multiple deviations in time series to obtain a state deviation sequence; performing a two-dimensional evaluation on the state deviation sequence to obtain a time series fluctuation index and a statistical anomaly index; and inputting the time series fluctuation index and the statistical anomaly index into a preset counting compensation correction model to obtain the counting compensation coefficient. Based on the counting compensation coefficient, the second walking distance measurement data is compensated and corrected to obtain the third walking distance measurement data; The first walking distance measurement data and the third walking distance measurement data are converted and compared in real time; If the comparison result exceeds the preset error threshold, a travel distance deviation alarm is triggered.

2. The method for monitoring the travel distance error of a coke oven locomotive according to claim 1, characterized in that, The contact status data includes vibration data and pressure data.

3. The method for monitoring the travel distance error of coke oven locomotives according to claim 1, characterized in that, The preset contact state data is contact state data collected under ideal environmental conditions; the ideal environmental conditions include a smooth track, no rain or snow interference, and stable operation of the locomotive.

4. The method for monitoring the travel distance error of a coke oven locomotive according to claim 1, characterized in that, Based on the aforementioned counting compensation coefficient, the second traversal ranging data is compensated and corrected to obtain the third traversal ranging data, including: The obtained counting compensation coefficients are correlated with the second walking distance measurement data; The compensation algorithm is determined based on the properties of the counting compensation coefficient and the characteristics of the second-travel distance measurement data; The associated counting compensation coefficient and the second travel distance measurement data are substituted into the determined compensation algorithm for calculation; The calculated third travel distance measurement data is verified.

5. The method for monitoring the travel distance error of a coke oven locomotive according to claim 1, characterized in that, Real-time conversion and comparison of the first and third walking distance measurement data includes: The first and third travel distance measurement data are uniformly converted into the same length unit, a fixed time base is determined, and the travel distance measurement data is converted into the travel distance within that time period using this time base as the unit. Based on the relationship between the actual operating speed of the electric locomotive and time, a linear conversion model is constructed; After completing the real-time conversion, the conversion results of the first walking distance measurement data and the third walking distance measurement data are compared at the same time point.

6. The method for monitoring the travel distance error of a coke oven locomotive according to claim 5, characterized in that, The linear conversion model calculates that the travel distance of the locomotive when it is running at a constant speed is equal to the speed multiplied by the time. When the locomotive is running at a non-uniform speed, the running process is divided into multiple segments. Within each segment, the locomotive moves at approximately a constant speed. The travel distance of each segment is calculated separately and then summed to obtain the travel distance of the entire process.

7. The method for monitoring the travel distance error of a coke oven locomotive according to claim 1, characterized in that, The factors influencing the setting of the preset error threshold include the locomotive's own performance, track conditions, coke weight, and environmental conditions.

8. A coke oven locomotive travel distance error monitoring system, wherein the system is applied to the coke oven locomotive travel distance error monitoring method as described in claim 1, characterized in that, The system includes: The travel distance measurement data acquisition module acquires the first travel distance measurement data and the second travel distance measurement data of the coke oven locomotive; The contact state acquisition and compensation coefficient generation module acquires the contact state between the coke oven locomotive and the track, and generates a counting compensation coefficient based on the contact state. The ranging data compensation and correction module compensates and corrects the second walking ranging data based on the counting compensation coefficient to obtain the third walking ranging data. The data conversion and real-time comparison module performs real-time conversion and comparison between the first walking distance measurement data and the third walking distance measurement data; The deviation alarm trigger module triggers a travel distance deviation alarm in response to the comparison result exceeding the preset error threshold.

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