Electromechanical equipment fault positioning and alarm protection device

Abstract

The invention discloses an electromechanical equipment fault positioning and alarm protection device, which comprises a master station, a plurality of slave stations subordinate to the master station, a plurality of computing units subordinate to each slave station, and one or more sensors subordinate to each computing unit, the sensors belonging to the same computing unit are used for detecting the same electromechanical device and generating first working parameter data, the corresponding computing unit receives the first working parameter data and converts the first working parameter data into second working parameter data, and the corresponding slave station receives the second working parameter data and converts the second working parameter data into third working parameter data. And the master station judges whether the electromechanical equipment breaks down or not according to the third working parameter data and preset fault data, and generates a mark number and fault type information of the electromechanical equipment which breaks down. Therefore, the method has the beneficial effects of enhanced data accuracy and fault prediction capability, flexible and extensible system architecture and the like.

Description

Technical Field

[0001] The present invention relates to the field of industrial informationization, and in particular to a mechanical and electrical equipment fault location and alarm protection device. Background Art

[0002] In modern factories, electromechanical equipment constitutes the core part of the production process. They are organized into a complex network structure based on specific production process requirements. This structure usually presents a tree-like topological feature, in which each branch represents a specific workflow or production line. Therefore, the electromechanical equipment in the same workflow is interdependent and closely connected. The operating status of one device directly affects the operation of its adjacent devices.

[0003] With the continuous improvement of the degree of industrial automation, the requirements for the stability and reliability of electromechanical equipment are also increasing. However, in actual operation, electromechanical equipment may fail due to multiple reasons such as material wear, environmental factors, design defects, etc. These failures may not only affect the function of a single device, but may also affect other equipment in the entire workflow through a chain reaction, resulting in a decrease in overall efficiency or even production interruption.

[0004] At present, although there are many solutions based on sensors and data acquisition systems that can provide a certain degree of fault warning, most solutions fail to fully consider the interaction between devices and their impact on system stability. When an abnormality is detected in a certain electromechanical equipment, it is difficult to quickly and accurately determine whether the abnormality is caused by a problem with the equipment itself or is affected by the failure of its upstream and downstream equipment. Therefore, how to effectively locate the source of the fault and take corresponding maintenance measures accordingly has become the key to improving production continuity and reducing downtime. Summary of the invention

[0005] The present invention aims to solve the technical problems in the above-mentioned technology at least to some extent.

[0006] To this end, the present invention discloses a mechanical and electrical equipment fault location and alarm protection device, comprising: a master station, the master station has multiple slave stations, each of the slave stations has multiple computing units, each of the computing units has one or more sensors, wherein:

[0007] The sensors belonging to the same computing unit are used to detect the same electromechanical equipment. When the sensor detects the electromechanical equipment and generates first working parameter data, the corresponding computing unit converts the first working parameter data into second working parameter data, and the corresponding slave station converts the second working parameter data into third working parameter data. The master station determines whether the electromechanical equipment fails based on the third working parameter data and preset fault data, and generates the label and fault type information of the faulty electromechanical equipment.

[0008] In addition, the electromechanical equipment fault location and alarm protection device disclosed in the present invention may also have the following additional technical features:

[0009] In one embodiment of the present invention, the sensor collects data of the corresponding electromechanical equipment at predetermined time intervals, and after collecting a plurality of the data each time, uses it as a round of data, and uses the round of data as the first working parameter data, and repeats this process over and over again.

[0010] In one embodiment of the present invention, the calculation unit is provided with a digital signal processor, and the digital signal processor is used to record the first working parameter data and calculate the mean value of the first working parameter data, specifically,

[0011]

[0012] X, X i and are respectively the first operating parameter data, the data points of the first operating parameter data and the mean of the first operating parameter data, and n is the number of data points of the first operating parameter data;

[0013] The second operating parameter data includes the first operating parameter data and an average value of the first operating parameter data.

[0014] In one embodiment of the present invention, the slave station is provided with another digital signal processor, which is used to record the second working parameter data of all the computing units and calculate the Pearson correlation coefficient of the second working parameter data of two adjacent computing units on the same link, specifically,

[0015]

[0016] X a , X ia and are respectively the first operating parameter data of one of the two adjacent computing units on the same link, a data point of the first operating parameter data, and a mean value of the first operating parameter data, X b, X ib and are respectively the first working parameter data of the other one of the two adjacent computing units on the same link, the data points of the first working parameter data and the mean value of the first working parameter data, and r is the Pearson correlation coefficient of the second working parameter data of the two adjacent computing units on the same link;

[0017] The third operating parameter data includes the second operating parameter data and the Pearson correlation coefficient.

[0018] In one embodiment of the present invention, the slave station is further provided with another digital signal processor, which is used to record the second operating parameter data of all the computing units and calculate the mutual information value of the second operating parameter data of two adjacent computing units on the same link, specifically,

[0019]

[0020] X a , X ia and are respectively the first operating parameter data of one of the two adjacent computing units on the same link, a data point of the first operating parameter data, and a mean value of the first operating parameter data, X b , X ib and are respectively the first operating parameter data, the data points of the first operating parameter data and the mean value of the first operating parameter data of the other one of the two adjacent computing units on the same link, p(x ia ,x ib ) are the joint probability distributions of the first operating parameter data of one of the two adjacent computing units on the same link and the first operating parameter data of the other, p(x ia ) and p(x ib ) are marginal probability distributions of the first operating parameter data of one of the two adjacent computing units on the same link and the first operating parameter data of the other one, respectively;

[0021] The third operating parameter data also includes the mutual information value.

[0022] In one embodiment of the present invention, the slave station is further provided with another digital signal processor, which is used to record the second operating parameter data of all the computing units and calculate the cross-correlation function value of the second operating parameter data of two adjacent computing units on the same link, specifically,

[0023] in,

[0024] X a , X ia and are respectively the first operating parameter data of one of the two adjacent computing units on the same link, a data point of the first operating parameter data, and a mean value of the first operating parameter data, X b , X ib and are respectively the first operating parameter data, the data points of the first operating parameter data and the mean value of the first operating parameter data of the other one of the two adjacent computing units on the same link, n is the number of data points of the first operating parameter data, τ is the time lag coefficient, is the cross-correlation function value;

[0025] The third operating parameter data also includes the cross-correlation function value.

[0026] In one embodiment of the present invention, the master station is provided with a microcontroller, and the microcontroller is used to determine whether the electromechanical device fails according to the third working parameter data, and generate the label and fault type information of the electromechanical device that fails, specifically,

[0027] When the first operating parameter data in the third operating parameter data matches the preset fault data, it indicates that the electromechanical equipment corresponding to the third operating parameter data is likely to fail;

[0028] When the Pearson correlation coefficient r=0, it indicates that the electromechanical device that may fail is on the same link and the adjacent electromechanical device has not failed, and the electromechanical device corresponding to the third working parameter data must have an independent failure. When the Pearson correlation coefficient r=1 or r=-1, it indicates that the electromechanical device that may fail is on the same link and the adjacent electromechanical device may also fail.

[0029] When the mutual information value I(X a ;X b )=0, it indicates that two electromechanical devices that may fail have independent failures. a ;X b ) = 1, it indicates that the faults between the two electromechanical devices that may fail affect each other;

[0030] When the cross-correlation function value When the time lag coefficient τ = 0, it reaches the maximum value, indicating that the two electromechanical devices that may fail synchronously affect each other and then both fail;

[0031] When the cross-correlation function value When the time lag coefficient τ=1 or τ=-1 reaches the maximum value, it indicates that the two electromechanical devices that may fail influence each other with a lag, and one of the two electromechanical devices that may fail must fail and affect the other.

[0032] In one embodiment of the present invention, when each of the computing units is subordinate to a plurality of the sensors, a sliding resistor is provided at the data output end of each of the sensors, and the other end of each of the sliding resistors is electrically connected to the computing unit.

[0033] In one embodiment of the present invention, the other end of the sliding resistor on each of the sensors is gathered into a node and electrically connected to the calculation unit.

[0034] In one embodiment of the present invention, another sliding resistor is further provided on the node, and the sliding resistor is electrically connected to the calculation unit.

[0035] The electromechanical equipment fault location and alarm protection device disclosed in the present invention has the following beneficial effects:

[0036] (1) Enhanced data accuracy and fault prediction capabilities. Multiple sensors are deployed to collect the working parameters of electromechanical equipment in real time. After multi-level processing by the computing unit and slave station, the master station finally performs comprehensive analysis. The multi-level data processing mechanism in this process can effectively filter out signal noise and ensure the high accuracy of the acquired data. In addition, the master station automatically identifies the identification of the electromechanical equipment and its fault type based on the third working parameter data, thereby achieving early warning of potential faults, supporting the implementation of preventive maintenance strategies, reducing unexpected downtime events, and ensuring the continuity and stability of the production process.

[0037] (2) The flexible and scalable system architecture adopts a modular design concept, allowing sensors, computing units, and slave stations to be added or removed according to actual needs to adapt to industrial application scenarios of different scales and complexities, with good flexibility and expansion capabilities.

[0038] Additional contents and advantages of the present invention will be given in the following description or may be understood through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The technical solutions and beneficial effects of the present invention will become apparent and easily understood from the following contents in conjunction with the accompanying drawings, wherein:

[0040] Figure 1 A circuit topology diagram of a device for locating faults and providing alarm protection for electromechanical equipment according to an embodiment of the present invention;

[0041] Figure 2 A circuit topology diagram of a device for locating faults and providing alarm protection for electromechanical equipment according to another embodiment of the present invention;

[0042] Figure 3 A circuit topology diagram of a device for locating faults and providing alarm protection for electromechanical equipment according to another embodiment of the present invention;

[0043] Figure 4 This is a circuit topology diagram of a device for locating faults and providing alarm protection for electromechanical equipment according to another embodiment of the present invention.

[0044] As shown in the figure:

[0045] 100-master station, 200-slave station, 300-computing unit, 400-sensor, 500-sliding resistor. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present invention will be described clearly and completely 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, rather than all the embodiments.

[0047] The following will describe the electromechanical equipment fault location and alarm protection device disclosed in the present invention with reference to the various accompanying drawings. Specifically, in a typical industrial environment, such as a large manufacturing plant, there are a variety of electromechanical equipment that need to be monitored and maintained, and the electromechanical equipment fault location and alarm protection device disclosed in the present invention can be used in this environment.

[0048] Embodiment 1

[0049] like Figure 1 As shown, a mechanical and electrical equipment fault location and alarm protection device includes: a master station 100, the master station 100 has multiple slave stations 200, each slave station 200 has multiple computing units 300, each computing unit 300 has one or more sensors 400, wherein:

[0050] The sensor 400 belonging to the same computing unit 300 is used to detect the same electromechanical device. When the sensor 400 detects the electromechanical device and generates first working parameter data, the corresponding computing unit 300 converts the first working parameter data into second working parameter data, and the corresponding slave station 200 converts the second working parameter data into third working parameter data. The master station 100 determines whether the electromechanical device fails based on the third working parameter data and the preset fault data, and generates the label and fault type information of the faulty electromechanical device.

[0051] In the embodiment of the present invention, the master station 100 is located in the control center, responsible for receiving data from all slave stations 200, and analyzing the data to determine whether a device fails. The master station 100 compares the third operating parameter data with the preset fault data. Once the third operating parameter data and the preset fault data match, the master station 100 automatically determines the number and fault type of the corresponding electromechanical device, and generates corresponding alarm information.

[0052] The master station 100 has a plurality of slave stations 200 under it, each of which is connected to a certain number of computing units 300, and the slave stations 200 convert the second working parameter data into the third working data through a complex data processing process;

[0053] Each slave station 200 manages a plurality of computing units 300, each computing unit 300 is directly connected to one or more sensors 400, and the computing unit 300 is mainly used to obtain first working parameter data from the sensor 400, and perform preliminary processing on the raw data to form second working parameter data;

[0054] The sensor 400 is installed at a key position of each electromechanical device and is responsible for regularly collecting various physical quantity data during the operation of the device.

[0055] Embodiment 2

[0056] In order to better explain the present invention, in one embodiment of the present invention, as Figure 1 As shown, the sensor 400 collects data of the corresponding electromechanical device at a predetermined time interval △t. After collecting n data each time, it is regarded as a round of data. For the convenience of understanding, this round of data can be recorded as a vector X = (X1, X2, ..., X n ), and use one round of data as the first working parameter data, and repeat this process over and over again.

[0057] The calculation unit 300 is provided with a digital signal processor, which is used to record the first working parameter data and calculate the mean value of the first working parameter data, specifically,

[0058] in,

[0059] X, X i and are respectively the first operating parameter data, the data points of the first operating parameter data and the mean of the first operating parameter data, and n is the number of data points of the first operating parameter data;

[0060] The second operating parameter data includes the first operating parameter data and the mean value of the first operating parameter data;

[0061] The slave station is provided with another three digital signal processors, wherein one digital signal processor is used to record the second working parameter data of all computing units and calculate the Pearson correlation coefficient of the second working parameter data of two adjacent computing units on the same link, specifically,

[0062] in,

[0063] X a , X ia and are respectively the first operating parameter data of one of two adjacent computing units on the same link, a data point of the first operating parameter data, and the mean value of the first operating parameter data, X b , X ib and are respectively the first working parameter data of the other of the two adjacent computing units on the same link, the data point of the first working parameter data and the mean value of the first working parameter data, and r is the Pearson correlation coefficient of the second working parameter data of the two adjacent computing units on the same link;

[0064] The third operating parameter data includes the second operating parameter data and the Pearson correlation coefficient.

[0065] Another digital signal processor is used to record the second working parameter data of all computing units and calculate the mutual information value of the second working parameter data of two adjacent computing units on the same link, specifically,

[0066] in,

[0067] X a , X ia and are respectively the first operating parameter data of one of two adjacent computing units on the same link, a data point of the first operating parameter data, and the mean value of the first operating parameter data, X b , X ib and are the first operating parameter data, the data point of the first operating parameter data and the mean value of the first operating parameter data of the other of the two adjacent computing units on the same link, respectively. ia ,x ib ) are the joint probability distributions of the first operating parameter data of one and the first operating parameter data of the other two computing units that are on the same link and adjacent to each other, p(x ia ) and p(x ib ) are marginal probability distributions of the first operating parameter data of one and the first operating parameter data of the other two computing units that are on the same link and adjacent to each other;

[0068] The third operating parameter data also includes a mutual information value.

[0069] The last digital signal processor is used to record the second working parameter data of all computing units and calculate the cross-correlation function value of the second working parameter data of two adjacent computing units on the same link, specifically,

[0070] in,

[0071] X a , X ia and are respectively the first operating parameter data of one of two adjacent computing units on the same link, a data point of the first operating parameter data, and the mean value of the first operating parameter data, X b , X ib and are respectively the first operating parameter data of the other of the two adjacent computing units on the same link, the data point of the first operating parameter data and the mean value of the first operating parameter data, n is the number of data points of the first operating parameter data, τ is the time lag coefficient, is the cross-correlation function value;

[0072] The third operating parameter data also includes a cross-correlation function value.

[0073] The master station is provided with a microcontroller, which is used to determine whether the electromechanical device fails according to the third working parameter data, and generate the label and fault type information of the electromechanical device that fails, specifically,

[0074] When the first operating parameter data in the third operating parameter data matches the preset fault data, it indicates that the electromechanical equipment corresponding to the third operating parameter data is likely to fail;

[0075] When the Pearson correlation coefficient r=0, it indicates that the electromechanical device that may fail is on the same link and the adjacent electromechanical device has not failed, and the electromechanical device corresponding to the third working parameter data must have an independent failure. When the Pearson correlation coefficient r=1 or r=-1, it indicates that the electromechanical device that may fail is on the same link and the adjacent electromechanical device may also fail.

[0076] When the mutual information value I(X a ;X b )=0, it indicates that two electromechanical devices that may fail have independent failures. a ;X b)=1, it indicates that the faults between the two electromechanical devices that may fail affect each other;

[0077] When the cross-correlation function value When the time lag coefficient τ = 0, it reaches the maximum value, indicating that the two electromechanical devices that may fail synchronously affect each other and then both fail;

[0078] When the cross-correlation function value When the time lag coefficient τ=1 or τ=-1 reaches the maximum value, it indicates that the two electromechanical devices that may fail influence each other with a lag, and one of the two electromechanical devices that may fail must fail and affect the other.

[0079] In the embodiment of the present invention, for example, two computing units 300 belonging to the same slave station 200, each computing unit 300 has a sensor 400 under it. For the convenience of explanation, during the computing process, a sensor 400 is marked as X. a , another sensor 400 is marked as X b , marked as X a The electromechanical device detected by the sensor 400 and the electromechanical device marked with X b The electromechanical devices detected by the sensor 400 are on the same link and adjacent to each other, assuming that the number is X a The data obtained by the sensor 400 is X a ={55,56,55,54,56,57,55,54,56,53}, denoted by X b The data obtained by the sensor 400 is X b ={55,54,53,53,52,55,54,53,53,52}, and assuming that the preset fault data is that the normal temperature value should be ≤55, from X a ={55,56,55,54,56,57,55,54,56,53}, we can see that the label is X a The temperature of the electromechanical device detected by the sensor 400 is abnormal for many times;

[0080] It should be noted that approximate values ​​are used in the following calculations due to the limitation of data accuracy;

[0081] Specifically, calculation So the Pearson correlation coefficient From this we can easily determine the label X a The electromechanical device detected by the sensor 400 and the electromechanical device marked with X b The electromechanical equipment detected by the sensor 400 may fail;

[0082] For the mutual information value I(X a ;X b )=0.7219, it indicates that the failures of two electromechanical devices that may fail affect each other;

[0083] For the cross-correlation function value For example, when τ = 0, the correlation function value , when τ=1, the correlation function value When τ = -1, the correlation function value The above results show that the a The electromechanical device detected by the sensor 400 and the electromechanical device marked with X b The electromechanical devices detected by the sensor 400 have very strong synchronous mutual influence and delayed mutual influence;

[0084] Therefore, according to the above data, it can be concluded that, first, the electromechanical device corresponding to the third working parameter data must have failed, and at the same time, the electromechanical device in the same link and adjacent to the electromechanical device that must have failed also has a failure, but the failure has not been discovered. At the same time, it can also be determined that the failure between the two electromechanical devices is caused by mutual influence, and the electromechanical device at the downstream position affects the electromechanical device at the upstream position. Therefore, when the master station 100 displays the number and fault information of the corresponding electromechanical device, the relevant staff needs to check the electromechanical device and the electromechanical devices in the same link and adjacent to it at the same time, and focus on checking the electromechanical device at the downstream position;

[0085] For other technical contents involved in this embodiment, please refer to the above embodiments, which will not be described in detail in this embodiment.

[0086] Embodiment 3

[0087] In order to better explain the present invention, in one embodiment of the present invention, as Figure 2 and Figure 3 As shown, when each computing unit is subordinate to a plurality of sensors 400, a sliding resistor 500 is respectively provided at the data output end of each sensor 400, and the other end of each sliding resistor 500 is electrically connected to the computing unit.

[0088] The other end of the sliding resistor 500 on each sensor 400 is gathered into a node and electrically connected to the calculation unit 300 .

[0089] like Figure 4 As shown, another sliding resistor 500 is also provided on the node, and the sliding resistor 500 is electrically connected to the calculation unit 300 .

[0090] In the embodiment of the present invention, a computing unit 300 is provided on an electromechanical device, and a computing unit 300 may be subordinate to a plurality of sensors 400, for example, four sensors 400. For the convenience of explanation, the four sensors 400 are respectively used to measure the temperature of the electromechanical device and are marked as T. a , used to measure the vibration of electromechanical equipment and marked as V a , used to measure the output power of electromechanical equipment and marked as U a , used to measure the output current of electromechanical equipment and marked as I a ;

[0091] In order to optimize the whole device, a sliding resistor 500 on the sensor 400 can be used to assign weights to it, that is, X a =T a ω a1 +V a ω a2 +U a ω a3 +I a ω a4 ;

[0092] In addition, the other end of the sliding resistor 500 on each sensor 400 is gathered into a sliding resistor 500 on a node, which can further optimize the entire device, and the calculation unit 300 can better receive the data of the sensor 400.

[0093] For other technical contents involved in this embodiment, please refer to the above embodiments, which will not be described in detail in this embodiment.

[0094] In summary, according to the electromechanical equipment fault location and alarm protection device disclosed in the present invention, on the one hand, the data accuracy and fault prediction capabilities are enhanced. By deploying multiple sensors to collect the working parameters of the electromechanical equipment in real time, and after multi-level processing by the computing unit and the slave station, the master station finally performs a comprehensive analysis. The multi-level data processing mechanism in this process can effectively filter out signal noise and ensure the high accuracy of the acquired data. In addition, the master station automatically identifies the identification of the electromechanical equipment and its fault type based on the third working parameter data, thereby achieving early warning of potential faults, supporting the implementation of preventive maintenance strategies, reducing unexpected downtime events, and ensuring the continuity and stability of the production process; on the other hand, the flexible and scalable system architecture adopts a modular design concept, allowing sensors, computing units and slave stations to be added or removed according to actual needs to adapt to industrial application scenarios of different scales and complexities, and has good flexibility and expansion capabilities.

[0095] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A mechanical and electrical equipment fault location and alarm protection device, characterized in that: include: A master station, the master station has multiple slave stations, each of the slave stations has multiple computing units, each of the computing units has one or more sensors, wherein: The sensor belonging to the same computing unit is used to detect the same electromechanical equipment and generate first working parameter data. The corresponding computing unit receives the first working parameter data and converts it into second working parameter data. The corresponding slave station receives the second working parameter data and converts it into third working parameter data. The master station determines whether the electromechanical equipment fails based on the third working parameter data and preset fault data, and generates the label and fault type information of the failed electromechanical equipment.

2. The electromechanical equipment fault location and alarm protection device according to claim 1, characterized in that: The sensor collects data of the corresponding electromechanical equipment at a predetermined time interval. After collecting a plurality of the data each time, the data is used as a round of data, and the round of data is used as the first working parameter data, and this is repeated.

3. The electromechanical equipment fault location and alarm protection device according to claim 2, characterized in that: The calculation unit is provided with a digital signal processor, and the digital signal processor is used to record the first working parameter data and calculate the mean value thereof, and the second working parameter data includes the first working parameter data and the mean value thereof.

4. The electromechanical equipment fault location and alarm protection device according to claim 3, characterized in that: The slave station is provided with another digital signal processor, which is used to record the second working parameter data of all the computing units and calculate the Pearson correlation coefficient of the second working parameter data of two adjacent computing units on the same link, and the third working parameter data includes the second working parameter data and the Pearson correlation coefficient.

5. The electromechanical equipment fault location and alarm protection device according to claim 4, characterized in that: The slave station is also provided with another digital signal processor, which is used to record the second working parameter data of all the computing units and calculate the mutual information value of the second working parameter data of two adjacent computing units on the same link, and the third working parameter data also includes the mutual information value.

6. The electromechanical equipment fault location and alarm protection device according to claim 5, characterized in that: The slave station is also provided with another digital signal processor, which is used to record the second operating parameter data of all the computing units and calculate the cross-correlation function value of the second operating parameter data of two adjacent computing units on the same link, and the third operating parameter data also includes the cross-correlation function value.

7. The electromechanical equipment fault location and alarm protection device according to claim 6, characterized in that: The master station is provided with a microcontroller, and the microcontroller is used to determine whether the electromechanical device fails according to the third working parameter data, and generate the label and fault type information of the electromechanical device that fails, specifically, When the first operating parameter data in the third operating parameter data matches the preset fault data, it indicates that the electromechanical equipment corresponding to the third operating parameter data is likely to fail; When the Pearson correlation coefficient is 0, it indicates that the electromechanical device that may fail is on the same link and the adjacent electromechanical device has not failed, and the electromechanical device corresponding to the third working parameter data must have an independent failure. When the Pearson correlation coefficient is 1 or -1, it indicates that the electromechanical device that may fail is on the same link and the adjacent electromechanical device may also fail. When the mutual information value is 0, it indicates that two electromechanical devices that may fail have independent failures, and when the mutual information value is 1, it indicates that the failures between the two electromechanical devices that may fail affect each other. When the cross-correlation function value reaches a maximum value when the time lag coefficient is 0, it indicates that two electromechanical devices that may fail synchronously affect each other and both fail; When the cross-correlation function value reaches the maximum value when the time lag coefficient is 1 or -1, it indicates that the two electromechanical devices that may fail affect each other with a lag, and one of the two electromechanical devices that may fail must fail and affect the other.

8. The electromechanical equipment fault location and alarm protection device according to claim 2, characterized in that: When each of the calculation units is subordinate to a plurality of the sensors, a sliding resistor is respectively provided at the data output end of each of the sensors, and the other end of each of the sliding resistors is electrically connected to the calculation unit.

9. The electromechanical equipment fault location and alarm protection device according to claim 8, characterized in that: The other end of the sliding resistor on each of the sensors is gathered into a node and electrically connected to the calculation unit.

10. The electromechanical equipment fault location and alarm protection device according to claim 9, characterized in that: Another sliding resistor is also arranged on the node, and the sliding resistor is electrically connected to the calculation unit.

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