A vehicle-mounted compressor equipment status assessment system based on data analysis

Abstract

The present invention discloses a vehicle-mounted compressor equipment status assessment system based on data analysis, relates to the technical field of vehicle-mounted compressor status assessment, and solves the technical problem in the prior art that the vehicle-mounted compressor cannot be subjected to performance impact analysis during actual operation and cannot be subjected to risk possibility assessment. Specifically, a performance impact analysis unit analyzes the performance impact of the vehicle-mounted compressor, sets the vehicle-mounted compressor as an analysis subject, obtains real-time performance parameters during the operation of the analysis subject, and the number of performance parameters is not unique, obtains the span value ratio and duration value ratio of the analysis subject in the real-time operation period, obtains high-impact parameters and low-impact parameters according to parameter comparison; obtains high-impact information and low-impact information, generates a high-impact signal or a low-impact signal according to information comparison, and sends it to a status assessment center.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle-mounted compressor status assessment, and in particular to a vehicle-mounted compressor equipment status assessment system based on data analysis. Background Art

[0002] The on-board compressor is the core component of the vehicle air-conditioning system and plays a vital role. The on-board compressor is driven by the power of the engine to suck in the low-temperature and low-pressure gaseous refrigerant, compress it into a high-temperature and high-pressure gaseous refrigerant, and then transport it to the condenser. In the condenser, the high-temperature and high-pressure gaseous refrigerant is cooled by heat dissipation and becomes a high-temperature and high-pressure liquid refrigerant. Then, the liquid refrigerant is reduced in pressure and temperature by the expansion valve and becomes a low-temperature and low-pressure liquid refrigerant and enters the evaporator. In the evaporator, the low-temperature and low-pressure liquid refrigerant absorbs the heat in the car and becomes a low-temperature and low-pressure gaseous refrigerant, which is sucked in by the compressor again. This cycle repeats to achieve cooling of the air in the car.

[0003] However, in the prior art, it is impossible to analyze the degree of impact on the performance of the vehicle-mounted compressor during actual operation, and it is impossible to assess the possibility of risks, so that it is impossible to infer the equipment status of the vehicle-mounted compressor through data collection. In addition, it is impossible to analyze the detectability of the vehicle-mounted compressor monitoring, resulting in an inability to ensure that the vehicle-mounted compressor can accurately collect monitoring data in real time.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to solve the above-mentioned problems and to propose a vehicle-mounted compressor equipment status assessment system based on data analysis.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] A vehicle-mounted compressor equipment status assessment system based on data analysis includes a status assessment center, the status assessment center is communicatively connected to a performance impact degree analysis unit, a risk possibility assessment unit, and a detectability analysis unit;

[0008] The performance impact degree analysis unit analyzes the performance impact degree of the vehicle compressor, sets the vehicle compressor as the analysis subject, obtains the real-time performance parameters of the analysis subject during operation, and the number of performance parameters is not unique, obtains the span value ratio and duration value ratio of the analysis subject in the real-time operation period, and obtains high-impact parameters and low-impact parameters according to parameter comparison; obtains high-impact information and low-impact information, generates a high-impact signal or a low-impact signal according to information comparison, and sends it to the status assessment center;

[0009] The risk possibility assessment unit conducts risk possibility assessment on the analysis subject, collects risk impact data and risk floating data, generates a high possibility signal or a low possibility signal based on data analysis, and sends it to the status assessment center;

[0010] The detectability analysis unit performs detectability analysis on the analysis subject, collects high detectability data and low detectability data, generates a detectability qualified signal or a detectability unqualified signal according to data comparison, and sends it to the status assessment center;

[0011] The unprovoked risk assessment unit performs an unprovoked risk assessment on the analysis subject, collects unprovoked detection information, and substitutes it into the formula to obtain the unprovoked risk assessment coefficient of the analysis subject during the unprovoked period, generates an unprovoked inefficiency signal or an unprovoked high efficiency signal based on the comparison of the unprovoked risk assessment coefficient, and sends it to the status assessment center.

[0012] As a preferred embodiment of the present invention, the span value ratio is obtained by collecting the non-intersection span value of the active control value range of the performance parameter of the analysis subject and the preset control value range during the real-time operation period, the span value of the corresponding parameter peak floating suppression speed during the parameter floating start control and the parameter floating control period when the performance parameter is passively controlled, and calculating the span value ratio according to the ratio;

[0013] The duration value ratio is obtained by comparing the interval between adjacent demand controls after the performance parameters of the analysis subject are regulated during the historical operation period with the duration of the numerical fluctuation after the regulation is completed, and the duration value ratio is calculated based on the ratio.

[0014] As a preferred embodiment of the present invention, if the span value ratio exceeds the span numerical ratio threshold, or the duration value ratio exceeds the duration numerical ratio threshold, then the corresponding performance parameter of the analysis subject is determined to be set as a high-impact parameter; if the span value ratio does not exceed the span numerical ratio threshold, and the duration value ratio does not exceed the duration numerical ratio threshold, then the corresponding performance parameter of the analysis subject is determined to be set as a low-impact parameter.

[0015] As a preferred embodiment of the present invention, the high impact information and the low impact information are respectively the accumulated value of the non-range excess of the high impact parameters in the real-time performance parameters of the analysis subject during the real-time operation period and the critical value of the corresponding parameter threshold range, and the numerical deviation between the numerical floating span of the low impact parameters of the real-time performance parameters of the analysis subject during the real-time operation period and the maximum range span value of the corresponding parameter threshold range.

[0016] As a preferred embodiment of the present invention, if the high-impact information exceeds the excess cumulative value threshold, or the low-impact information exceeds the numerical deviation threshold, a high-impact signal is generated; if the high-impact information does not exceed the excess cumulative value threshold, and the low-impact information does not exceed the numerical deviation threshold, a low-impact signal is generated.

[0017] As a preferred implementation manner of the present invention, the risk impact data and the risk floating data are respectively the ratio of the real-time floating quantity of the floating influencing factors of the high-impact parameters during the real-time operation of the analysis subject to the corresponding non-floating quantity of the influencing factors of the non-floating factors, and the real-time floating stage of the floating influencing factors of the low-impact parameters during the real-time operation of the analysis subject and the numerical synchronous growth span value of the current operating period of the low-impact parameters.

[0018] As a preferred embodiment of the present invention, if the risk impact data exceeds the factor quantity ratio threshold, or the risk floating data exceeds the numerical synchronous growth span value threshold, a high possibility signal is generated; if the risk impact data does not exceed the factor quantity ratio threshold, and the risk floating data does not exceed the numerical synchronous growth span value threshold, a low possibility signal is generated.

[0019] As a preferred embodiment of the present invention, the high detectable data and the low detectable data are respectively the proportion of the number of real-time value floating collection times of the sensor in the number of high-impact parameter value floating times within the current buffering time, and the maximum reciprocating span value of the low-impact parameter value collection deviation when the low-impact parameter value floats with any span during the operation of the analysis subject;

[0020] If the high detectable data exceeds the threshold of the proportion of the number of floating acquisitions, and the low detectable data does not exceed the maximum reciprocating span value threshold, a detectability qualified signal is generated; if the high detectable data does not exceed the threshold of the proportion of the number of floating acquisitions, or the low detectable data exceeds the maximum reciprocating span value threshold, a detectability unqualified signal is generated.

[0021] As a preferred embodiment of the present invention, the unexplained detection information includes the deviation value of the success rate of numerical floating control of high-impact parameters and low-impact parameters corresponding to the same control scheme within the unexplained period, the suppression growth amount of the numerical floating speed of the floating influencing factors of the corresponding performance parameters during the floating control of the performance parameters within the unexplained period, and the average value of the continuous increase rate of the delay frequency of any type of data collection of the performance parameters of the analysis subject within the unexplained period; and the corresponding labels CGP, YZZ and CZV are set.

[0022] As a preferred embodiment of the present invention, the formula is:

[0023] , where ghj1, ghj2 and ghjk3 are the preset proportional coefficients corresponding to the floating control success rate deviation value, the floating speed suppression growth amount and the continuous increase speed mean value, respectively, and e is a natural constant, and α is an error correction factor with a value of 0.98;

[0024] If the unexcused risk assessment coefficient P of the analysis subject during the unexcused period exceeds the unexcused risk assessment coefficient threshold, an unexcused inefficient signal is generated; if the unexcused risk assessment coefficient P of the analysis subject during the unexcused period does not exceed the unexcused risk assessment coefficient threshold, an unexcused efficient signal is generated.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] 1. In the present invention, the performance impact of the vehicle compressor is analyzed, and the performance parameters of the vehicle compressor and the historical operation process are synchronously analyzed to infer whether the performance impact of the vehicle compressor meets the actual operation requirements, so as to avoid the decrease in the fault tolerance of the vehicle compressor due to excessive performance impact, and fail to ensure trouble-free operation at every moment in the real-time operation stage, thereby reducing the operation adaptability of the vehicle compressor;

[0027] Conduct a risk possibility assessment on the analysis subject, infer whether there are risks in the current operation of the analysis subject based on the possibility analysis of the performance parameters of the analysis subject, and infer the possibility of risk in the current operation of the analysis subject based on data processing analysis, so as to control the operation of the analysis subject in advance.

[0028] 2. In the present invention, a detectability analysis is performed on the analysis subject, and the detectability analysis is used to infer whether the real-time detection efficiency during the operation of the analysis subject meets the actual needs, so as to avoid the failure to detect the operation risk of the analysis subject in time, resulting in low accuracy of the state assessment of the analysis subject, and the inability to timely control the equipment, thereby reducing the operation efficiency of the analysis subject;

[0029] Conduct an unprovoked risk assessment on the analysis subject, collect and analyze real-time data based on the time periods when the analysis subject is operating without cause, and infer the current operation stability and safety of the analysis subject, so as to avoid the analysis subject running in the unprovoked period. The operating efficiency is reduced, resulting in an increased risk of failure and even the risk of terminating operation due to failure; at the same time, it can also improve the accuracy of equipment status assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0031] Figure 1 This is a principle block diagram of Embodiment 1 of the present invention;

[0032] Figure 2 This is a principle block diagram of the second embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0035] Embodiment 1

[0036] See also Figure 1 As shown, a vehicle-mounted compressor equipment status assessment system based on data analysis includes a status assessment center, which is communicatively connected to a performance impact degree analysis unit, a risk possibility assessment unit, and a detectability analysis unit; wherein the status assessment center is bidirectionally connected to the performance impact degree analysis unit, the risk possibility assessment unit, and the detectability analysis unit;

[0037] The status assessment center generates a performance impact analysis signal and sends the performance impact analysis signal to the performance impact analysis unit. After receiving the performance impact analysis signal, the performance impact analysis unit analyzes the performance impact of the vehicle compressor, and synchronously analyzes the performance parameters of the vehicle compressor and the historical operation process to infer whether the performance impact of the vehicle compressor meets the actual operation requirements, so as to avoid the fault tolerance rate of the vehicle compressor being reduced due to excessive performance impact, and fail to guarantee trouble-free operation at every moment in the real-time operation stage, thereby reducing the operation adaptability of the vehicle compressor;

[0038] The on-board compressor is set as the analysis subject, and the real-time performance parameters of the analysis subject during operation are obtained, and the number of performance parameters is not unique, specifically, the performance parameters of the on-board compressor in the prior art when it is used, such as cooling capacity, power, exhaust volume and other parameters; the real-time operation time period and historical operation time period of the analysis subject are collected and analyzed, and the non-intersection span value of the active control value range and the preset control value range of the performance parameter of the analysis subject in the real-time operation period, the span value of the corresponding parameter peak floating suppression speed during the passive control of the performance parameter and the control period of the parameter floating are obtained, and the span value ratio is obtained according to the ratio calculation; at the same time, the adjacent demand control interval length and the value floating duration after the completion of the control of the performance parameter of the analysis subject in the historical operation period are obtained, and the duration value ratio is calculated according to the ratio;

[0039] The non-intersection span value of the active control value range of the performance parameters of the analysis subject in the real-time operation period and the preset control value range, the span ratio of the parameter floating start control and the parameter peak floating suppression speed span value during the parameter floating control period when the performance parameters are passively controlled, and the duration ratio of the adjacent demand control interval after the performance parameters of the analysis subject in the historical operation period are completed and the duration of the value floating after the completion of the control are compared with the span value ratio threshold and the duration value ratio threshold respectively:

[0040] If the span value ratio exceeds the span value ratio threshold, or the duration value ratio exceeds the duration value ratio threshold, the corresponding performance parameter of the analysis subject is determined to be set as a high-impact parameter; if the span value ratio does not exceed the span value ratio threshold, and the duration value ratio does not exceed the duration value ratio threshold, the corresponding performance parameter of the analysis subject is determined to be set as a low-impact parameter;

[0041] The accumulated value of the excess amount outside the range between the high-impact parameters of the real-time performance parameters of the analysis subject in the real-time operation period and the critical value of the corresponding parameter threshold range is collected, and the numerical deviation between the numerical floating span of the low-impact parameters of the real-time performance parameters of the analysis subject in the real-time operation period and the maximum range span value of the corresponding parameter threshold range is obtained at the same time, wherein the accumulated value of the excess amount outside the range is expressed as the accumulated value of the excess value between the value not within the threshold range and the critical value, and the maximum critical value is used if the range is exceeded, and the minimum critical value is used if the range is not exceeded; and the accumulated value of the excess amount outside the range between the high-impact parameters of the real-time performance parameters of the analysis subject in the real-time operation period and the critical value of the corresponding parameter threshold range, and the numerical deviation between the numerical floating span of the low-impact parameters of the real-time performance parameters of the analysis subject in the real-time operation period and the maximum range span value of the corresponding parameter threshold range are marked as high-impact information and low-impact information, respectively, and compared with the accumulated value threshold and the numerical deviation threshold, respectively:

[0042] If the accumulated value of the non-range excess of the high-impact parameter of the real-time performance parameter of the analysis subject during the real-time operation period and the critical value of the corresponding parameter threshold range exceeds the accumulated value threshold, or the value deviation of the floating span of the low-impact parameter of the real-time performance parameter of the analysis subject during the real-time operation period and the maximum span value of the corresponding parameter threshold range exceeds the value deviation threshold, then the real-time performance impact degree analysis is determined to be abnormal, a high-degree impact signal is generated and sent to the status assessment center, and the status assessment center monitors the corresponding high-impact parameters and low-impact parameters and controls them in advance;

[0043] If the accumulated value of the non-range excess amount between the high-impact parameter of the real-time performance parameter of the analysis subject and the critical value of the corresponding parameter threshold range during the real-time operation period does not exceed the accumulated value threshold, and the value deviation between the floating span of the low-impact parameter value of the real-time performance parameter of the analysis subject and the maximum span value of the corresponding parameter threshold range during the real-time operation period does not exceed the value deviation threshold, then it is determined that the real-time performance impact degree analysis is normal, a low-impact signal is generated and sent to the status assessment center;

[0044] After receiving the low-level impact signal, the status assessment center generates a risk possibility assessment signal and sends the risk possibility assessment signal to the risk possibility assessment unit. After receiving the risk possibility assessment signal, the risk possibility assessment unit conducts a risk possibility assessment on the analysis subject, and infers whether there is a risk in the current operation of the analysis subject based on the performance parameter possibility analysis of the analysis subject, and infers the risk possibility of the current operation of the analysis subject based on the data processing analysis, so as to control the operation of the analysis subject in advance;

[0045] The ratio of the real-time floating number of floating influencing factors of high-impact parameters to the non-floating number of influencing factors of corresponding non-floating influencing factors is obtained during the real-time operation of the analysis subject, where the floating influencing factors are factors that affect the numerical values ​​of the high-impact parameters of the analysis subject, such as environmental parameters, etc.; at the same time, the real-time floating stage of the floating influencing factors of low-impact parameters during the real-time operation of the analysis subject and the numerical synchronization growth span value of the low-impact parameters in the current operation period are obtained, and the ratio of the real-time floating number of floating influencing factors of high-impact parameters during the real-time operation of the analysis subject to the non-floating number of influencing factors of corresponding non-floating influencing factors, and the real-time floating stage of the floating influencing factors of low-impact parameters during the real-time operation of the analysis subject and the numerical synchronization growth span value of the low-impact parameters in the current operation period are marked as risk impact data and risk floating data, respectively, and compared with the factor quantity ratio threshold and the numerical synchronization growth span threshold, respectively:

[0046] If the ratio of the real-time floating quantity of the floating influencing factors of the high-impact parameters to the corresponding non-floating quantity of the influencing factors of the non-floating influencing factors during the real-time operation of the analysis subject exceeds the factor quantity ratio threshold, or the numerical synchronization growth span value of the real-time floating stage of the floating influencing factors of the low-impact parameters during the real-time operation of the analysis subject and the current operation period of the low-impact parameters exceeds the numerical synchronization growth span value threshold, then the risk possibility assessment of the analysis subject is determined to be abnormal, a high possibility signal is generated and sent to the status assessment center. After receiving the high possibility signal, the status assessment center monitors the corresponding floating influencing factors while monitoring the performance parameters of the analysis subject, and makes timely adjustments when monitoring the floating;

[0047] If the ratio of the real-time floating quantity of the floating influencing factors of the high-impact parameters to the corresponding non-floating quantity of the influencing factors of the non-floating factors during the real-time operation of the analysis subject does not exceed the factor quantity ratio threshold, and the real-time floating phase of the floating influencing factors of the low-impact parameters during the real-time operation of the analysis subject and the numerical synchronization growth span value of the current operation period of the low-impact parameters do not exceed the numerical synchronization growth span value threshold, then it is determined that the risk possibility assessment of the analysis subject is normal, a low possibility signal is generated and sent to the status assessment center;

[0048] After receiving the low-likelihood signal, the status assessment center generates a detectability analysis signal and sends the detectability analysis signal to the detectability analysis unit. After receiving the detectability analysis signal, the detectability analysis unit performs detectability analysis on the analysis subject, and infers whether the real-time detection efficiency during the operation of the analysis subject meets the actual needs through the detectability analysis, so as to avoid the failure to detect the operation risk of the analysis subject in time, resulting in low accuracy of the status assessment of the analysis subject, and the inability to adjust the equipment in time, which reduces the operation efficiency of the analysis subject.

[0049] The buffering time between the floating influencing factor value floating moment and the high-impact parameter value floating moment of the high-impact parameter during the operation of the analysis subject is obtained, and the proportion of the sensor's real-time floating value collection times in the high-impact parameter value floating times within the current buffer time is obtained according to the corresponding buffer time, and the proportion of the sensor's real-time floating value collection times in the high-impact parameter value floating times within the current buffer time is marked as high detectable data. At the same time, the maximum reciprocating span value of the low-impact parameter value collection deviation when the low-impact parameter value floats with any span during the operation of the analysis subject is obtained, and the maximum reciprocating span value of the low-impact parameter value collection deviation when the low-impact parameter value floats with any span during the operation of the analysis subject is marked as low detectable data, and compared with the value floating collection times proportion threshold and the maximum reciprocating span value threshold respectively:

[0050] If the proportion of the number of real-time value floating collection times by the sensor in the number of high-impact parameter value floating times within the current buffering time exceeds the threshold of the number of value floating collection times, and the maximum reciprocating span value of the low-impact parameter value collection deviation when the low-impact parameter value floats in any span during the operation of the analysis subject does not exceed the maximum reciprocating span value threshold, then the detectability analysis of the current operation of the analysis subject is determined to be qualified, and a detectability qualified signal is generated and sent to the status assessment center; after receiving the signal, the status assessment center conducts continuous monitoring with the currently set data collection cycle and the set data error;

[0051] If the proportion of the number of real-time value floating collection times by the sensor in the number of high-impact parameter value floating times within the current buffering time does not exceed the value floating collection times proportion threshold, or the maximum reciprocating span value of the low-impact parameter value collection deviation exceeds the maximum reciprocating span value threshold when the low-impact parameter value floats in any span during the operation of the analysis subject, then the detectability analysis of the current operation of the analysis subject is determined to be unqualified, and a detectability unqualified signal is generated and sent to the status assessment center. After receiving the signal, the status assessment center monitors the operation status of the real-time analysis subject and adjusts the data collection cycle and the set data error. That is, if there is a delay or deviation in the parameter monitoring corresponding to the operation status, the data collection cycle and the set data error are adjusted;

[0052] Embodiment 2

[0053] In the previous embodiment, the historical operation and real-time operation of the vehicle compressor are monitored in real time, and the equipment status is evaluated according to the parameter influence. On the basis of the previous embodiment, this embodiment performs an unprovoked risk assessment on the vehicle compressor. Please refer to Figure 2 As shown, the status assessment center is communicatively connected with the unprovoked risk assessment unit;

[0054] The status assessment center generates an unprovoked risk assessment signal and sends it to the unprovoked risk assessment unit. After receiving the unprovoked risk assessment signal, the unprovoked risk assessment unit conducts an unprovoked risk assessment on the analysis subject, collects and analyzes real-time data based on the unprovoked operation period of the analysis subject, and infers the operation stability and safety of the current analysis subject, so as to avoid the analysis subject running in the unprovoked period with a decrease in operating efficiency, resulting in an increase in the risk of failure and even the risk of terminating the operation due to failure; at the same time, it can also improve the accuracy of equipment status assessment;

[0055] According to the equipment failure moment of the analysis subject, the operation time period is divided into a failure period and a fault-free period, and the deviation value of the floating control success rate of the high-impact parameter and the low-impact parameter corresponding to the same control scheme in the fault-free period is obtained. At the same time, the floating speed suppression growth amount of the floating influencing factor corresponding to the performance parameter in the performance parameter floating control process in the fault-free period is obtained, and the deviation value of the floating control success rate of the high-impact parameter and the low-impact parameter corresponding to the same control scheme in the fault-free period and the floating speed suppression growth amount of the floating influencing factor corresponding to the performance parameter in the performance parameter floating control process in the fault-free period are marked as CGP and YZZ respectively;

[0056] Obtain the average value of the continuous increase rate of any type of data collection delay frequency of the performance parameter of the analysis subject during the no-cause period, and mark the average value of the continuous increase rate of any type of data collection delay frequency of the performance parameter of the analysis subject during the no-cause period as CZV;

[0057] The above collected data are uniformly marked as unprovoked detection information, and substituted into the formula to obtain the unprovoked risk assessment coefficient P of the analysis subject during the unprovoked period, where the formula is:

[0058] , where ghj1, ghj2 and ghjk3 are the preset proportional coefficients corresponding to the floating control success rate deviation value, the floating speed suppression growth amount and the continuous increase speed mean value, respectively, and e is a natural constant, and α is an error correction factor with a value of 0.98;

[0059] Compare the unexcused risk assessment coefficient P of the analysis subject during the unexcused period with the unexcused risk assessment coefficient threshold:

[0060] If the unexcused risk assessment coefficient P of the analysis subject during the unexcused period exceeds the unexcused risk assessment coefficient threshold, the unexcused risk assessment of the analysis subject during the unexcused period is determined to be abnormal, and an unexcused inefficiency signal is generated and sent to the status assessment center. The status assessment center continuously analyzes and monitors the unexcused risk assessment coefficient of the analysis subject during the remaining time of the current operation, and performs equipment maintenance on the analysis subject when the coefficient fluctuation span is too large or the current operation is completed;

[0061] If the unexcused risk assessment coefficient P of the analysis subject during the unexcused period does not exceed the unexcused risk assessment coefficient threshold, it is determined that the unexcused risk assessment of the analysis subject during the unexcused period is normal, and an unexcused high-efficiency signal is generated and sent to the status assessment center;

[0062] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by technicians in this field according to actual conditions;

[0063] When the present invention is in use, the performance impact degree analysis unit obtains the span value ratio and the duration value ratio of the analysis subject within the real-time operation period, and obtains high impact parameters and low impact parameters according to parameter comparison; obtains high impact information and low impact information, generates a high degree of impact signal or a low degree of impact signal according to information comparison, and sends it to the status assessment center; the risk possibility assessment unit collects risk impact data and risk floating data, generates a high possibility signal or a low possibility signal according to data analysis, and sends it to the status assessment center; the detectability analysis unit collects high detectable data and low detectable data, generates a detectability qualified signal or a detectability unqualified signal according to data comparison, and sends it to the status assessment center; the unwarranted risk assessment unit collects unwarranted detection information, and substitutes it into the formula to obtain the unwarranted risk assessment coefficient of the analysis subject within the unwarranted period, generates an unwarranted inefficiency signal or an unwarranted high efficiency signal according to the comparison of the unwarranted risk assessment coefficient, and sends it to the status assessment center.

[0064] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A vehicle-mounted compressor equipment status assessment system based on data analysis, characterized in that: It includes a status assessment center, which is communicatively connected to a performance impact degree analysis unit, a risk possibility assessment unit, and a detectability analysis unit; The performance impact degree analysis unit analyzes the performance impact degree of the vehicle compressor, sets the vehicle compressor as the analysis subject, obtains the real-time performance parameters of the analysis subject during operation, and the number of performance parameters is not unique, obtains the span value ratio and duration value ratio of the analysis subject in the real-time operation period, and obtains high-impact parameters and low-impact parameters according to parameter comparison; obtains high-impact information and low-impact information, generates a high-impact signal or a low-impact signal according to information comparison, and sends it to the status assessment center; The risk possibility assessment unit conducts risk possibility assessment on the analysis subject, collects risk impact data and risk floating data, generates a high possibility signal or a low possibility signal based on data analysis, and sends it to the status assessment center; The detectability analysis unit performs detectability analysis on the analysis subject, collects high detectability data and low detectability data, generates a detectability qualified signal or a detectability unqualified signal according to data comparison, and sends it to the status assessment center; The unprovoked risk assessment unit performs an unprovoked risk assessment on the analysis subject, collects unprovoked detection information, and substitutes it into the formula to obtain the unprovoked risk assessment coefficient of the analysis subject during the unprovoked period, generates an unprovoked low efficiency signal or an unprovoked high efficiency signal according to the comparison of the unprovoked risk assessment coefficient, and sends it to the status assessment center; The span value ratio is obtained by collecting the non-intersection span value of the active control value range of the performance parameter of the analysis subject in the real-time operation period and the preset control value range, and the span value of the corresponding parameter peak floating suppression speed during the parameter floating start control and parameter floating control period when the performance parameter is passively controlled, and calculating the span value ratio according to the ratio; The duration value ratio is obtained by calculating the duration of the adjacent demand regulation interval after the performance parameters of the analysis subject are regulated in the historical operation period and the duration of the value fluctuation after the regulation is completed, and the duration value ratio is obtained based on the ratio. If the span value ratio exceeds the span value ratio threshold, or the duration value ratio exceeds the duration value ratio threshold, the corresponding performance parameter of the analysis subject is determined to be set as a high-impact parameter; if the span value ratio does not exceed the span value ratio threshold, and the duration value ratio does not exceed the duration value ratio threshold, the corresponding performance parameter of the analysis subject is determined to be set as a low-impact parameter; The high impact information and the low impact information are respectively the accumulated value of the non-range excess of the high impact parameter in the real-time performance parameters of the analysis subject during the real-time operation period and the critical value of the corresponding parameter threshold range, and the numerical deviation of the floating span of the low impact parameter value in the real-time performance parameters of the analysis subject during the real-time operation period and the maximum span value of the corresponding parameter threshold range; If the high-impact information exceeds the excess cumulative value threshold, or the low-impact information exceeds the numerical deviation threshold, a high-impact signal is generated; If the high-impact information does not exceed the excess cumulative value threshold, and the low-impact information does not exceed the numerical deviation threshold, a low-impact signal is generated; The risk impact data and risk floating data are respectively the ratio of the real-time floating quantity of the floating influencing factors of the high-impact parameters in the real-time operation of the analysis subject to the corresponding non-floating quantity of the influencing factors of the non-floating factors, and the synchronous growth span value of the real-time floating stage of the floating influencing factors of the low-impact parameters in the real-time operation of the analysis subject and the current operation period of the low-impact parameters; If the risk impact data exceeds the factor quantity ratio threshold, or the risk floating data exceeds the numerical synchronous growth span value threshold, a high possibility signal is generated; if the risk impact data does not exceed the factor quantity ratio threshold, and the risk floating data does not exceed the numerical synchronous growth span value threshold, a low possibility signal is generated; The high detectable data and low detectable data are respectively the proportion of the number of real-time value floating collection times of the sensor in the number of high-impact parameter value floating times within the current buffering time, and the maximum reciprocating span value of the low-impact parameter value collection deviation when the low-impact parameter value floats in any span during the operation of the analysis subject; If the high detectable data exceeds the threshold of the proportion of the number of floating acquisitions, and the low detectable data does not exceed the maximum reciprocating span value threshold, a detectability qualified signal is generated; if the high detectable data does not exceed the threshold of the proportion of the number of floating acquisitions, or the low detectable data exceeds the maximum reciprocating span value threshold, a detectability unqualified signal is generated; The unprovoked detection information includes the deviation value of the success rate of the numerical floating control of high-impact parameters and low-impact parameters corresponding to the same control scheme during the unprovoked period, the suppression growth amount of the numerical floating speed of the floating influencing factors of the corresponding performance parameters during the floating control process of the performance parameters during the unprovoked period, and the continuous increase speed average of the delay frequency of any type of data collection of the performance parameters of the analysis subject during the unprovoked period; and the corresponding labels CGP, YZZ and CZV are set; The formula is , where ghj1, ghj2 and ghjk3 are the preset proportional coefficients corresponding to the floating control success rate deviation value, the floating speed suppression growth amount and the continuous increase speed mean value, respectively, and e is a natural constant, and α is an error correction factor with a value of 0.98; If the unexcused risk assessment coefficient P of the analysis subject during the unexcused period exceeds the unexcused risk assessment coefficient threshold, an unexcused inefficient signal is generated; if the unexcused risk assessment coefficient P of the analysis subject during the unexcused period does not exceed the unexcused risk assessment coefficient threshold, an unexcused efficient signal is generated.

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