Diesel engine starting performance detection system based on data analysis

Abstract

The invention belongs to the field of diesel engine detection, relates to a data analysis technology, and aims to solve the problem that a starting performance test result in the prior art cannot exclude external environment interference, in particular to a diesel engine starting performance detection system based on data analysis, which comprises a performance detection platform, the performance detection platform is in communication connection with a starting test module, an adaptation analysis module, a preheating analysis module and a database; the starting test module is used for testing and analyzing the starting performance of the diesel engine. The diesel engine is marked as a test object, and test environment parameters are configured for the test object. According to the invention, the starting performance of the diesel engine can be tested and analyzed, after testing environment parameters are configured for the diesel engine, the starting performance of the diesel engine is fed back according to testing coefficients, and differentiation marking is carried out on the starting performance; and the starting adaptability of the diesel engine in different test environments is evaluated through the marked abnormal coefficient, so that the accuracy of a test result is improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of diesel engine detection, and relates to a data analysis technique, in particular to a diesel engine starting performance detection system based on data analysis. BACKGROUND

[0002] The starting performance of a diesel engine is an important indicator for measuring its performance, and the starting speed is a key parameter, because the starting speed of the diesel engine is directly related to whether it can start rapidly and reliably and enter a normal working state, and the starting speed not only reflects the starting ability of the diesel engine, but also indirectly reflects its overall performance and health state.

[0003] The diesel engine starting performance detection system in the prior art cannot configure test environment parameters for the diesel engine, so that the starting performance test result of the diesel engine cannot exclude the interference of an external environment, the adaptability of the starting performance under different test environments cannot be effectively evaluated, and the cold starting performance of the diesel engine cannot be detected, and meanwhile, the prior art cannot make optimization decision analysis combined with test data of the diesel engine, and the efficiency is low when optimizing the diesel engine with abnormal performance.

[0004] In view of the above technical problems, the present application provides a solution. SUMMARY

[0005] The present application aims to provide a diesel engine starting performance detection system based on data analysis, which can solve the problem that the starting performance test result in the prior art cannot exclude the interference of an external environment. The present application aims to provide a diesel engine starting performance detection system based on data analysis, which can solve the problem that the starting performance test result in the prior art cannot exclude the interference of an external environment.

[0006] The present application can be achieved by the following technical scheme. A diesel engine starting performance detection system based on data analysis comprises a performance detection platform, which is communicatively connected with a starting test module, an adaptability analysis module, a preheating analysis module and a database. The starting test module is used for testing and analyzing the starting performance of the diesel engine: the diesel engine is marked as a test object, test environment parameters of the test object are configured, the test object is started under the corresponding test environment, and speed difference data SC, torque data ZZ and noise data ZS of the test object during the starting test are obtained, the speed difference data SC, the torque data ZZ and the noise data ZS are numerically calculated to obtain a test coefficient CS of the test object under the corresponding test environment; the corresponding test environment is marked as a normal environment or an abnormal environment through the test coefficient CS; after the test object completes the starting test under all test environments, a ratio of the number of abnormal environments to the total number of test environments is marked as an abnormal coefficient, and whether the overall starting performance test result of the test object meets the requirements is determined through the abnormal coefficient; The adaptation analysis module is used for analyzing the running adaptability of the diesel engine: when the overall starting performance test result of the test object does not meet the requirements, whether the overall starting performance abnormality of the test object and the environmental adaptability, the test fatigue degree are related is analyzed in sequence; The preheating analysis module is used for analyzing the preheating parameters of the test object.

[0007] Further, the specific process of configuring test environment parameters for the test object includes: randomly selecting a plurality of temperature values in the temperature range of the running environment of the test object as test temperature values, setting the temperature value of the test environment as the test temperature value, then placing the test object in the test environment and standing for L1 minutes, obtaining the surface temperature value of the test object and marking it as the actual temperature value.

[0008] Further, the process of obtaining the speed difference data SC includes: marking the speed value of the test object at the ignition moment as the ignition value, calling the standard speed range of the test object at the ignition moment, marking the average value of the maximum value and the minimum value of the standard speed range as the standard speed value, and marking the absolute value of the difference between the ignition value and the standard speed value as the speed difference data SC of the test object during the starting test; the torque data ZZ is the torque value of the test object at the ignition moment; the noise data ZS is the maximum noise decibel value generated by the test object during the test.

[0009] Further, the specific process of marking the test environment as a normal environment or an abnormal environment includes: obtaining the test threshold CSmax of the test object through the database, comparing the test coefficient CS of the test object with the test threshold CSmax: if the test coefficient CS is less than the test threshold CSmax, it is determined that the starting performance of the test object under the corresponding test environment meets the requirements, and the test environment is marked as a normal environment; if the test coefficient CS is greater than or equal to the test threshold CSmax, it is determined that the starting performance of the test object under the corresponding test environment does not meet the requirements, and the test environment is marked as an abnormal environment.

[0010] Further, the specific process of determining whether the overall starting performance test result of the test object meets the requirements comprises: obtaining an abnormal threshold value from the database, comparing the abnormal coefficient with the abnormal threshold value, if the abnormal coefficient is less than the abnormal threshold value, determining that the overall starting performance test result of the test object meets the requirements, if the abnormal coefficient is greater than or equal to the abnormal threshold value, determining that the overall starting performance test result of the test object does not meet the requirements, generating an adaptive analysis signal and sending the adaptive analysis signal to the adaptive analysis module through the performance detection platform.

[0011] Further, the specific process of analyzing whether the overall starting performance abnormality of the test object is related to environmental adaptability comprises: marking the average value of the maximum value and the minimum value of the test object operating environment temperature range as a standard temperature value, marking the absolute value of the difference between the test temperature value of the test environment and the standard temperature value as the temperature deviation value of the test environment, arranging the test environment according to the temperature deviation value from small to large to obtain a temperature deviation sequence, arranging the test environment according to the test coefficient CS value from small to large to obtain a test sequence, marking the absolute value of the difference between the sequence number of the test environment in the temperature deviation sequence and the sequence number in the test sequence as the temperature adaptation value of the test environment, summing and averaging the temperature adaptation values of all test environments to obtain the environmental adaptation coefficient of the test object, obtaining the environmental adaptation threshold value from the database, comparing the environmental adaptation coefficient with the environmental adaptation threshold value, if the environmental adaptation coefficient is less than the environmental adaptation threshold value, determining that the overall starting performance abnormality of the test object is related to environmental adaptability, generating a preheating analysis signal and sending the preheating analysis signal to the preheating analysis module through the performance detection platform, if the environmental adaptation coefficient is greater than or equal to the environmental adaptation threshold value, determining that the overall starting performance abnormality of the test object is not related to environmental adaptability.

[0012] Further, the specific process of analyzing whether the overall starting performance abnormality of the test object is related to the test fatigue degree comprises: arranging the test environment according to the starting test process execution time from early to late to obtain an execution sequence, marking the absolute value of the difference between the sequence number of the test environment in the execution sequence and the sequence number in the test sequence as a continuous adaptation value, summing and averaging the continuous adaptation values of all test environments to obtain the continuous adaptation coefficient of the test object, obtaining the continuous adaptation threshold value from the database, comparing the continuous adaptation coefficient with the continuous adaptation threshold value, if the continuous adaptation coefficient is less than the continuous adaptation threshold value, determining that the overall starting performance abnormality of the test object is related to the test fatigue degree, generating a fatigue optimization signal and sending the fatigue optimization signal to the mobile terminal of the management personnel through the performance detection platform, if the continuous adaptation coefficient is greater than or equal to the continuous adaptation threshold value, determining that the overall starting performance abnormality of the test object is not related to the test fatigue degree, generating a performance abnormality signal and sending the performance abnormality signal to the mobile terminal of the management personnel through the performance detection platform.

[0013] Furthermore, the specific process of the preheating analysis module analyzing the preheating parameters of the test object includes: the maximum and minimum values ​​of the actual temperature of the test object before starting the test under all test environments constitute the preheating target range, the preheating target range is marked as the preheating parameters of the test object, and the preheating parameters of the test object are sent to the mobile terminal of the management personnel through the performance testing platform.

[0014] The present invention has the following beneficial effects: 1. The starting test module can test and analyze the starting performance of diesel engines. After configuring the test environment parameters for the diesel engine, the various parameters of the diesel engine in the starting performance test process at different test temperatures are statistically analyzed and calculated to obtain test coefficients. Then, the starting performance of the diesel engine is fed back based on the test coefficients, and it is differentiated and marked. The abnormal coefficients after marking are used to evaluate the starting adaptability of the diesel engine under different test environments, thereby improving the accuracy of the test results. 2. The adaptability analysis module can analyze the operational adaptability of diesel engines. It analyzes and calculates the environmental adaptability coefficient and continuous adaptability coefficient from the perspectives of environmental adaptability and test fatigue adaptability, thereby extracting the test abnormality characteristics of diesel engines with abnormal overall starting performance, and then generating targeted optimization processing signals to improve the efficiency of return to the factory and optimization. 3. The preheating analysis module can analyze the preheating parameters of the test object. Based on the actual temperature value of the diesel engine before the start-up test, the preheating parameters are generated. When the environmental adaptability is abnormal, the starting performance of the diesel engine during the adaptation process can be improved by preheating control, simplifying and optimizing the processing procedures, and ensuring that the diesel engine can start normally in abnormal environments. Attached Figure Description

[0015] 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 of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] like Figure 1 As shown, a diesel engine starting performance testing system based on data analysis includes a performance testing platform, which is communicatively connected to a starting test module, an adaptation analysis module, a preheating analysis module, and a database.

[0019] The starting test module is used to test and analyze the starting performance of diesel engines: the diesel engine is marked as the test object, and the test environment parameters are configured for the test object: several temperature values ​​are randomly selected from the operating temperature range of the test object as the test temperature values, the temperature values ​​of the test environment are set as the test temperature values, and then the test object is placed in the test environment and left to stand for L1 minutes. The surface temperature value of the test object is obtained and marked as the actual temperature value. The starting test is performed on the test object, and the speed difference data SC, torque data ZZ and noise data ZS of the test object during the starting test are obtained. The process of acquiring speed difference data SC includes: marking the speed value of the test object at the ignition moment as the ignition value; retrieving the standard speed range of the test object at the ignition moment; marking the average of the maximum and minimum values ​​of the standard speed range as the standard speed value; and marking the absolute value of the difference between the ignition value and the standard speed value as the speed difference data SC of the test object during the starting test. Torque data ZZ is the torque value of the test object at the ignition moment; and noise data ZS is the maximum decibel level of noise generated by the test object during the test. Through formula The test coefficient CS of the test object under the corresponding test environment is obtained; where b1, b2, and b3 are proportional coefficients, and b1>b2>b3>1; the test threshold CSmax of the test object is obtained from the database, and the test coefficient CS of the test object is compared with the test threshold CSmax: if the test coefficient CS is less than the test threshold CSmax, the start-up performance of the test object under the corresponding test environment is determined to meet the requirements, and the test environment is marked as a normal environment; if the test coefficient CS is greater than or equal to the test threshold CSmax, the start-up performance of the test object under the corresponding test environment is determined to not meet the requirements, and the test environment is marked as an abnormal environment; After the test object completes all starting tests under all test environments, the ratio of the number of abnormal environments to the total number of test environments is marked as the abnormality coefficient. An abnormality threshold is obtained from the database, and the abnormality coefficient is compared with the abnormality threshold: if the abnormality coefficient is less than the abnormality threshold, the overall starting performance test result of the test object is deemed to meet the requirements; if the abnormality coefficient is greater than or equal to the abnormality threshold, the overall starting performance test result of the test object is deemed to not meet the requirements. An adaptation analysis signal is generated and sent to the adaptation analysis module through the performance testing platform. The starting performance of the diesel engine is tested and analyzed. After configuring the test environment parameters for the diesel engine, the parameters of each parameter during the starting performance test process at different test temperatures are statistically analyzed and calculated to obtain test coefficients. The starting performance of the diesel engine is then fed back based on the test coefficients, and differentiated markings are applied. The starting adaptability of the diesel engine under different test environments is evaluated using the marked abnormality coefficients, improving the accuracy of the test results.

[0020] The adaptation analysis module is used to analyze the operational adaptability of diesel engines: the average of the maximum and minimum values ​​of the operating environment temperature range of the test object is marked as the standard temperature value; the absolute value of the difference between the test temperature value and the standard temperature value is marked as the temperature deviation value of the test environment; the test environments are arranged in ascending order of temperature deviation value to obtain the temperature deviation sequence; the test environments are arranged in ascending order of test coefficient CS value to obtain the test sequence; the absolute value of the difference between the sequence number of the test environment in the temperature deviation sequence and the sequence number in the test sequence is marked as the temperature adaptation value of the test environment; the summation and average of the temperature adaptation values ​​of all test environments is taken to obtain the environmental adaptation coefficient of the test object; and the environmental adaptation threshold is obtained from the database.

[0021] The environmental adaptability coefficient is compared with the environmental adaptability threshold: if the environmental adaptability coefficient is less than the environmental adaptability threshold, it is determined that the overall start-up performance abnormality of the test object is related to environmental adaptability, a preheating analysis signal is generated and sent to the preheating analysis module through the performance testing platform; if the environmental adaptability coefficient is greater than or equal to the environmental adaptability threshold, it is determined that the overall start-up performance abnormality of the test object is unrelated to environmental adaptability. The test environments are arranged in order of priority from the start-up test process execution time to obtain the execution sequence. The absolute value of the difference between the sequence number of the test environment in the execution sequence and the sequence number in the test sequence is marked as the continuous adaptability value. The continuous adaptability values ​​of all test environments are summed and averaged to obtain the continuous adaptability coefficient of the test object. The continuous adaptability threshold is obtained through the database.

[0022] The continuous adaptation coefficient is compared with the continuous adaptation threshold: if the continuous adaptation coefficient is less than the continuous adaptation threshold, it is determined that the overall starting performance of the test object is abnormal and related to the test fatigue level. A fatigue optimization signal is generated and sent to the mobile terminal of the management personnel through the performance testing platform; if the continuous adaptation coefficient is greater than or equal to the continuous adaptation threshold, it is determined that the overall starting performance of the test object is abnormal and unrelated to the test fatigue level. A performance abnormality signal is generated and sent to the mobile terminal of the management personnel through the performance testing platform.

[0023] The preheating analysis module is used to analyze the preheating parameters of the test object: the maximum and minimum values ​​of the actual temperature of the test object before starting the test under all test environments constitute the preheating target range, the preheating target range is marked as the preheating parameters of the test object, and the preheating parameters of the test object are sent to the mobile terminal of the management personnel through the performance testing platform.

[0024] A data analysis-based diesel engine starting performance testing system, during operation, marks the diesel engine as the test object, configures the test environment parameters for the test object, performs a starting test on the test object, and acquires speed difference data (SC), torque data (ZZ), and noise data (ZS) during the starting test. The system then calculates the test coefficient (CS) from the speed difference data (SC), torque data (ZZ), and noise data (ZS). The test environment is marked as normal or abnormal using the test coefficient (CS). The ratio of the number of abnormal environments to the total number of test environments is marked as the abnormality coefficient. The system uses the abnormality coefficient to determine whether the overall starting performance of the test object meets the requirements. If the requirements are not met, the system analyzes the diesel engine's operational adaptability and determines whether the abnormal overall starting performance is related to environmental adaptability or test fatigue. Based on the determination results, a corresponding optimization processing signal is generated.

[0025] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

[0026] The above formulas are all derived from software simulations using a large amount of data, and are selected to be close to the true values. The coefficients in the formulas are set by those skilled in the art based on the actual situation; for example: formula Multiple sets of sample data were collected by a person skilled in the art, and corresponding test coefficients were set for each set of sample data. The set test coefficients and the collected sample data were substituted into the formulas, and any three formulas constituted a system of three linear equations. The calculated coefficients were filtered and the average value was taken, and the values ​​of b1, b2 and b3 were 3.62, 2.83 and 2.21, respectively. The magnitude of the coefficient is a specific value obtained by quantifying each parameter to facilitate subsequent comparison. The magnitude of the coefficient depends on the amount of sample data and the test coefficient initially set by those skilled in the art for each set of sample data. As long as it does not affect the proportional relationship between the parameter and the quantified value, such as the test coefficient being proportional to the value of the speed difference data.

[0027] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0028] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A diesel engine starting performance testing system based on data analysis, characterized in that, It includes a performance testing platform, which is communicatively connected to a startup test module, an adaptation analysis module, a preheating analysis module, and a database; The starting test module is used to test and analyze the starting performance of a diesel engine: The diesel engine is marked as the test object; test environment parameters are configured for the test object; a starting test is performed on the test object under the corresponding test environment, and the speed difference data SC, torque data ZZ, and noise data ZS are obtained during the starting test; the speed difference data SC, torque data ZZ, and noise data ZS are numerically calculated to obtain the test coefficient CS for the starting test of the test object under the corresponding test environment; the corresponding test environment is marked as a normal environment or an abnormal environment based on the test coefficient CS; after the test object completes the starting test under all test environments, the ratio of the number of abnormal environments to the total number of test environments is marked as the abnormality coefficient; the overall starting performance test results of the test object are judged based on the abnormality coefficient to determine whether they meet the requirements. The adaptation analysis module is used to analyze the operational adaptability of the diesel engine: when the overall starting performance test results of the test object do not meet the requirements, it sequentially analyzes whether the abnormal overall starting performance of the test object is related to environmental adaptability and test fatigue level; The preheating analysis module is used to analyze the preheating parameters of the test object.

2. The diesel engine starting performance testing system based on data analysis according to claim 1, characterized in that, The specific process of configuring the test environment parameters for the test object includes: randomly selecting several temperature values ​​from the operating environment temperature range of the test object as test temperature values, setting the temperature value of the test environment as the test temperature value, then placing the test object in the test environment and letting it stand for L1 minutes, obtaining the surface temperature value of the test object and marking it as the actual temperature value.

3. The diesel engine starting performance testing system based on data analysis according to claim 2, characterized in that, The process of acquiring speed difference data SC includes: marking the speed value of the test object at the ignition moment as the ignition value; retrieving the standard speed range of the test object at the ignition moment; marking the average of the maximum and minimum values ​​of the standard speed range as the standard speed value; and marking the absolute value of the difference between the ignition value and the standard speed value as the speed difference data SC of the test object during the starting test. Torque data ZZ is the torque value of the test object at the ignition moment. Noise data ZS is the maximum decibel noise generated by the test object during the test.

4. The diesel engine starting performance testing system based on data analysis according to claim 3, characterized in that, The specific process of marking a test environment as a normal or abnormal environment includes: obtaining the test threshold CSmax of the test object from the database, comparing the test coefficient CS of the test object with the test threshold CSmax: if the test coefficient CS is less than the test threshold CSmax, it is determined that the startup performance of the test object in the corresponding test environment meets the requirements, and the test environment is marked as a normal environment; if the test coefficient CS is greater than or equal to the test threshold CSmax, it is determined that the startup performance of the test object in the corresponding test environment does not meet the requirements, and the test environment is marked as an abnormal environment.

5. The diesel engine starting performance testing system based on data analysis according to claim 4, characterized in that, The specific process for determining whether the overall starting performance test results of the test object meet the requirements includes: obtaining the abnormal threshold from the database, comparing the abnormal coefficient with the abnormal threshold; if the abnormal coefficient is less than the abnormal threshold, the overall starting performance test results of the test object are determined to meet the requirements; if the abnormal coefficient is greater than or equal to the abnormal threshold, the overall starting performance test results of the test object are determined to not meet the requirements; generating an adaptive analysis signal and sending the adaptive analysis signal to the adaptive analysis module through the performance testing platform.

6. The diesel engine starting performance testing system based on data analysis according to claim 5, characterized in that, The specific process for analyzing whether the overall starting performance abnormality of the test object is related to its environmental adaptability includes: marking the average of the maximum and minimum values ​​of the operating environment temperature range of the test object as the standard temperature value; marking the absolute value of the difference between the test temperature value and the standard temperature value as the temperature deviation value of the test environment; arranging the test environments in ascending order of temperature deviation value to obtain a temperature deviation sequence; arranging the test environments in ascending order of test coefficient CS value to obtain a test sequence; marking the absolute value of the difference between the sequence number of the test environment in the temperature deviation sequence and the sequence number in the test sequence as the test environment temperature adaptability value; summing and averaging the temperature adaptability values ​​of all test environments to obtain the environmental adaptability coefficient of the test object; obtaining the environmental adaptability threshold from the database; and comparing the environmental adaptability coefficient with the environmental adaptability threshold: if the environmental adaptability coefficient is less than the environmental adaptability threshold, it is determined that the overall starting performance abnormality of the test object is related to environmental adaptability, and a preheating analysis signal is generated and sent to the preheating analysis module through the performance testing platform; if the environmental adaptability coefficient is greater than or equal to the environmental adaptability threshold, it is determined that the overall starting performance abnormality of the test object is not related to environmental adaptability.

7. A diesel engine starting performance testing system based on data analysis according to claim 6, characterized in that, The specific process for analyzing whether the overall startup performance anomaly of the test object is related to the test fatigue level includes: arranging the test environments in order of priority from start to finish according to the execution time of the startup test process to obtain an execution sequence; marking the absolute value of the difference between the sequence number of the test environment in the execution sequence and the sequence number in the test sequence as the continuous fitness value; summing and averaging the continuous fitness values ​​of all test environments to obtain the continuous fitness coefficient of the test object; obtaining the continuous fitness threshold from the database; and comparing the continuous fitness coefficient with the continuous fitness threshold: if the continuous fitness coefficient is less than the continuous fitness threshold, it is determined that the overall startup performance anomaly of the test object is related to the test fatigue level, a fatigue optimization signal is generated, and the fatigue optimization signal is sent to the mobile terminal of the management personnel through the performance detection platform; if the continuous fitness coefficient is greater than or equal to the continuous fitness threshold, it is determined that the overall startup performance anomaly of the test object is not related to the test fatigue level, a performance anomaly signal is generated, and the performance anomaly signal is sent to the mobile terminal of the management personnel through the performance detection platform.

8. The diesel engine starting performance testing system based on data analysis according to claim 7, characterized in that, The specific process of the preheating analysis module to analyze the preheating parameters of the test object includes: the maximum and minimum values ​​of the actual temperature of the test object before starting the test under all test environments constitute the preheating target range, the preheating target range is marked as the preheating parameters of the test object, and the preheating parameters of the test object are sent to the mobile terminal of the management personnel through the performance testing platform.

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