48 results about "Total delay" patented technology

The invention relates to the technical field of chip design, and provides a critical path screening method based on a chip time sequence report, which comprises the following steps: collecting chip time sequence report data, screening out first N critical paths from the data based on time sequence index data, and establishing a path ID-delay type-scene three-dimensional data model; and calculating the delay ratio of the unit delay to the interconnection line delay in each critical path. Performing single-type delay, type relevance and RC condition influence comparison on different scenes to obtain delay characteristic data. The invention discloses a system for executing the method, which can avoid full data redundancy and improve the analysis efficiency by screening the first N critical paths. And the delay change rule in different scenes is quantified. The delay characteristic data reflects the actual influence of the key path delay on the time sequence, so that a designer can quickly position the delay bottleneck of the key path, and a basis and a reference are provided for the targeted optimization of the total delay of the chip in the later period.

The invention provides a scene port entering and leaving aircraft joint optimization scheduling method. The method comprises the following steps: aiming at aircrafts which take off and land on a plurality of parallel runways in an airport, establishing a mixed integer programming model for a scene port entering and leaving aircraft IASP; setting a target function and a constraint condition of an IASTP problem by taking minimization of the total delay duration of the port entering and leaving aircrafts as a target; and based on the constraint conditions, solving a target function of the IASTP problem by adopting a heuristic algorithm based on VNS, and obtaining a comprehensive scheduling scheme of runway and sliding path distribution, take-off and landing sequence and time of the port entering and leaving aircraft. According to the method, actual operation constraints of various scenes are considered, runway distribution and sorting, taxiing path selection and taxiway scheduling of the port entering and leaving aircrafts, and a deducing sorting scheduling scheme of the port leaving aircrafts are planned and optimized as a whole, the take-off and landing delay time of the port entering and leaving aircrafts is shortened as much as possible, the hub airport operation efficiency is improved, and the airport landing time is shortened. And decision support is provided for efficient scheduling of aircrafts.

The invention discloses an aircraft remote control delay compensation response method and system, and the method comprises the steps: obtaining airborne data, and constructing a multi-source data set; calculating bidirectional transmission delay based on a bidirectional delay estimation algorithm, and calculating initial total delay; the initial total delay is dynamically calibrated by using a self-adaptive delay calibration algorithm, the confidence coefficient is evaluated, and the delay precision is improved; deducing a flight state in a delay time period by adopting a delay deduction hybrid model, and dynamically adjusting parameters along with load; according to the deduction result and the original instruction, generating a compensation instruction containing constraints by using a model prediction control algorithm; and executing the instruction after onboard verification, comparing the actual state with the expected state, and feeding back a deviation value to optimize the weight of the next-round model so as to form a closed-loop lifting mechanism. According to the method, the problems of incomplete delay composition analysis, poor environmental adaptability, lack of constraint collaboration of compensation instructions, no closed-loop optimization mechanism and the like in the existing aircraft remote control delay compensation are solved.

The invention provides an energy storage equipment phase synchronization control method and an energy storage system, relates to the technical field of energy storage equipment, and aims to solve the problem of phase tracking lag of slave machines caused by communication link delay when multiple machines are connected in parallel. The energy storage device phase synchronization control method comprises the steps that a first synchronization frame is received from a first energy storage device, and the first synchronization frame comprises a first voltage phase; a second synchronization frame is received from the first energy storage device, the second synchronization frame comprises a first time difference, and the first time difference is the difference value between the sending completion time and the sending start time of the first synchronization frame; calculating a second time difference based on a first reception time of the first synchronization frame and a second reception time of the second synchronization frame; and performing phase synchronization based on the first voltage phase, the first time difference and the second time difference. According to the phase synchronization control method, the communication processing total delay of the whole link is actively calculated, then the real-time phase of the host at the current moment is dynamically predicted, and finally accurate synchronization without lag errors is achieved.

The invention relates to the technical field of intelligent manufacturing, and provides a steel member production scheduling optimization method and device and a computer readable storage medium, and the method is realized through the following steps: a user sets a scheduling date range and screens orders; dynamically adjusting the branch priority and the machine capacity; setting optimization weights of the total tardiness time and the total delay rate; a simulated annealing algorithm is adopted to globally optimize a steel structure function unit machining sequence, a greedy algorithm is combined to allocate production line resources for component groups of the same process, and a process-level sub-algorithm is nested to solve the time sequence coupling problem of part and main body machining. The problems of neat delivery, cross-production-line resource scheduling and the like in steel member production are innovatively solved.

A method for edge cache replacement based on deep reinforcement learning is provided, including: constructing a system network model; obtaining a caching state of an MEC server in the system network model; calculating a total delay for all users to obtain cached contents based on a total delay for a single user to obtain a cached content; constructing an optimization objective function based on the total delay for all users to obtain the cached contents; formulating a Markov decision process according to the optimization objective function; and replacing the cached content of the MEC server using a dynamic content replacement algorithm based on deep reinforcement learning according to the Markov decision process. According to a condition of a cache space of the MEC server, the system network model can obtain a minimum average delay for users to obtain contents and find a most suitable cache replacement policy.

The present application belongs to the technical field of mobile edge computing microservice, and particularly relates to an edge computing microservice deployment and task scheduling method based on microcell architecture in a 5G and Internet of Vehicles scenario.The method comprises the following steps: firstly, describing an edge computing network structure based on microcells in a 5G scenario; on this basis, systematically modeling the microservice deployment and task scheduling problem, with the optimization target being to minimize the delay of all users, which is mainly manifested as processing data upload delay; then, decomposing and completely solving the sub-problems to transform the original problem into a linear integer programming problem; and using an L2Box-ADMM algorithm to solve the linear integer programming problem.Test results show that, compared with other microservice deployment and task scheduling algorithms, the algorithm of the present application can find a microservice deployment and task scheduling strategy that satisfies the resource constraint condition and has smaller total delay, and can reduce the gap with the optimal solution by 35%.

The invention discloses a real-time evaluation method and device for a secondary reciprocity network, equipment and a storage medium, and relates to the technical field of automatic testing. The secondary reciprocity network comprises a central switch and at least one lower computer connected with the central switch, the lower computer comprises a controller, a backplane switch and at least one resource card which are connected with one another, the method comprises the following steps: obtaining a first delay, a second delay and a third delay, the first delay is the delay of a network card corresponding to the controller or the resource card, and the third delay is the delay of a network card corresponding to the controller or the resource card; the second delay is related delay of the switch, and the third delay is software delay; determining fourth time delay based on the first time delay and the second time delay, wherein the fourth time delay is processing time delay of the resource card; and determining the total delay of the secondary reciprocity network based on a first preset formula, the first delay, the second delay, the third delay and the fourth delay. Therefore, the problem that the real-time performance of the secondary reciprocity network architecture is not easy to evaluate is solved, and accurate evaluation of the real-time performance of the secondary reciprocity network is realized.

This invention provides a scheduling method for additive manufacturing workshops based on safety reinforcement learning, relating to the field of deep learning technology. The method includes: determining a workshop state vector S based on workshop simulation environment parameters; where T represents the current time, L represents the number of tasks being processed in the current batch, Tard represents the total delay time of all tasks, C represents the total completion time of completed tasks, and Index represents the task currently being scheduled; using the DQN algorithm, combined with the workshop state vector S and a reward function, determining the priority of tasks to be scheduled, and determining the batch of tasks to be scheduled based on the priority; using an improved A3C algorithm for machine selection, allocating the tasks to be scheduled in different batches to target machines; the improved A3C algorithm is an A3C algorithm incorporating a safety shield mechanism. By comprehensively considering task urgency, processing time, and machine load, the method dynamically optimizes production scheduling, improving scheduling efficiency and resource utilization, and achieving multi-objective balance.

The invention relates to the technical field of computers, in particular to a multi-agent cooperative communication and scheduling method based on deep reinforcement learning, and the method comprises the following steps: S1, constructing a multi-agent system architecture; s2, designing a deep reinforcement learning framework; step S3, introducing a GOLSC algorithm; s4, designing a scheduling rule; step S41, static distribution rules; step S42, dynamically scheduling the rule; and S5, intelligent agent collaboration and optimization are carried out. According to the invention, different types of dynamic events are divided into three types, so that the GOLSC algorithm can adopt different communication link construction strategies for different types of dynamic events to generate specific links with pertinence. After a GOLSC algorithm is introduced into a task scheduling model, numerical experiments are carried out on a large number of examples in different production environments, changes of the total delay rate and the total delay time are researched, and the effectiveness, adaptability and superiority of the algorithm model in the environments are further verified.

The application discloses a task scheduling method and device based on a distributed large language model, terminal equipment and a storage medium. The method comprises the following steps: obtaining communication data of each device node in a multi-layer network of the distributed large language model, a to-be-scheduled task, a task feature of the to-be-scheduled task, and real-time monitoring data of each device node; then, according to the communication data, the to-be-scheduled task, the task feature of the to-be-scheduled task, and the real-time monitoring data of each device node, performing model segmentation and task scheduling on the multi-layer network with the minimum total delay of the multi-layer network as the target, obtaining a target device node corresponding to each to-be-scheduled task, and distributing each to-be-scheduled task to the corresponding target device node for scheduling. Through implementation of the application, resource management of the multi-layer network in the large language model can be realized, the performance of the network is improved, and the delay is reduced.

The present application discloses a method for correcting pulse distortion in a multi-level phase-shifted all-digital transmitter, which relates to the field of all-digital transmitters. The method comprises: determining a relationship between a total delay error and a phase-shift control word; determining an integer multiple error relationship between the total delay error and the phase-shift control word based on the relationship between the total delay error and the phase-shift control word; calculating a pre-processed phase-shift control word based on the integer multiple error relationship between the total delay error and the phase-shift control word; calculating a compensation control word based on the total duty cycle variation error and the pre-processed phase-shift control word; controlling the delay of a carrier signal based on the compensation control word to obtain a carrier signal with a duty cycle variation error; generating a correction carrier signal based on the carrier signal with the duty cycle variation error; delaying the correction carrier signal based on the pre-processed phase-shift control word, and amplifying and synthesizing the output signal. The present application can implement adaptive correction processing for pulse waveform distortion and improve the linear performance of ADTx.

The invention discloses an order type task scheduling optimization method and system, and relates to the technical field of task scheduling and control optimization, and the method comprises the steps: constructing an order type task scheduling control model; by constructing a dual-objective function of total delay time minimization and overall execution efficiency maximization, global optimization of task resource allocation is achieved, it is clear that task execution time resources do not exceed the maximum processing duration, and the situation that due to excessive optimization, resources are occupied by a single task for a long time, and the task execution efficiency is improved is prevented. Two objective functions of total delay time and average processing efficiency are constructed, the total delay time objective function can reflect the influence of the task queuing length on the execution efficiency, a penalty term is introduced into a scheme violating constraints, the evaluation weight of the scheme is reduced, it is ensured that the generated scheduling scheme meets both the optimization objective and the actual constraint condition, and the scheduling efficiency is improved. The frontier solution set is generated through iterative solution, conversion of task planning from static rules to dynamic optimization is achieved, and an efficient and reliable solution is provided for an intelligent task management system.

The embodiment of the invention relates to an information processing method and device, equipment and a medium. The method comprises the steps of obtaining first task information of a to-be-executed data production task and a planned execution moment of the data production task; generating first estimation information corresponding to the data production task based on the first task information; the first pre-estimation information at least comprises a first pre-estimation duration required by the target cluster to execute the data production task; obtaining target reference information, and estimating a total delay duration corresponding to the data production task based on the target reference information; the target reference information comprises one or more of resource information of the target cluster, second task information of an upstream task on which the data production task depends, and fault information of the target cluster; and determining an estimated completion moment of the data production task based on the planned execution moment, the first estimated duration and the total delay duration. According to the embodiment of the invention, the accuracy of the estimated completion time of the finally obtained data production task can be fully guaranteed.

The invention relates to the technical field of computers and data processing, discloses a streaming transmission and low-delay decoding method based on a cloud game, and aims to solve the problems of high transmission delay, low coding and decoding efficiency and split interaction response in the prior art. The method comprises the following steps: extracting dynamic characteristics of a game picture, dynamically adjusting a coding rate and a resolution ratio through a reinforcement learning model based on network state parameters and the dynamic characteristics, generating a current frame prediction result by using an AI prediction model, and preferentially transmitting a key frame patch, decoding is accelerated through a special hardware decoding chip, asynchronous rapid decoding is adopted for key frame patches, and frames and user input events are decoded synchronously to control the end-to-end total delay to be smaller than or equal to 50 ms. According to the technical scheme, the loss rate and the average transmission delay of the key picture area can be remarkably reduced, the decoding delay is reduced, it is ensured that the total delay is stabilized within 50 ms, and the interaction synchronism and the operation response accuracy of the high-speed dynamic game are improved.

The invention provides a flight delay recovery method and device, computer equipment and a storage medium, and belongs to the field of aviation operation and maintaining.The method comprises the steps that the minimum total delay economic loss, the total delay duration and the delay duration standard deviation serve as optimization objectives; establishing an optimization model by taking aircraft resource allocation, unit task connection, passenger travel guarantee, ground guarantee resource collaboration and airport time slot capacity limitation as constraint conditions; a Harris eagle optimization algorithm is used as a basic algorithm, and a dynamic balance pool mechanism and a transverse crossing mechanism are introduced for improvement; and carrying out optimization solution on the optimization model by utilizing an improved Harris eagle optimization algorithm to generate a flight recovery scheme. In this way, a mathematical model which takes a plurality of key indexes as optimization targets and comprehensively considers multi-dimensional operation rule constraints is established, and complex scenes and requirements of flight recovery can be described more comprehensively and accurately.

The invention discloses a material cross-domain distribution method and device, and the method comprises the steps: building a material cross-domain distribution multi-target optimization model under a comprehensive constraint condition with the minimum material cross-domain distribution total delay time as a first optimization target and the minimum scheduling cost from a material support point to a material demand point as a second optimization target; mapping the material cross-domain distribution multi-objective optimization model by using a Logistic chaotic function to generate an initialized population, and fusing a variable neighborhood search operator into an MOEA / D algorithm to obtain an optimized MOEA / D algorithm; solving the material cross-domain distribution multi-target optimization model based on an optimized MOEA / D algorithm to obtain a material cross-domain distribution multi-target Pareto frontier solution set; therefore, the material cross-domain distribution scheme is determined based on the preset selection criterion according to the Pareto frontier solution set, the task reliability of mixed material cross-domain distribution in the whole period can be effectively improved, and the cost-effectiveness ratio of mixed material cross-domain distribution in the whole period can also be improved.

This invention discloses a chip prototype verification method, apparatus, product, equipment, and medium, relating to the field of circuit technology. This invention is applied to a verification system containing main and sub-verification boards. The sub-verification board is equipped with a first delay counter, and the main verification board is equipped with a second delay counter and an interrupt generation module. The method includes: obtaining the first delay value of the valid data signal and the original interrupt signal from the sub-verification board using the first delay counter; sending the service data, the two signals, and the first delay value to the main verification board; writing the service data into an external memory; obtaining the second delay value of the two signals received by the main verification board using the second delay counter; if the total delay value exceeds a preset clock cycle threshold, after all service data is written to the external memory, the interrupt generation module generates a target interrupt signal based on the first delay value and sends it to the main control unit; the main control unit reads the data from the external memory to complete the prototype verification. This method can accurately calculate inter-board delays, avoid timing offsets, and achieve accurate prototype correction.

The invention discloses a data processing method, device and equipment, and relates to the technical field of computers, which comprises the following steps of: simultaneously carrying out erasure code coding calculation and cyclic redundancy check calculation on a data block in a continuous time period when original data is loaded to a processor cache, so that multiple calculation operations on the same data are completed in a cache period, and the data processing efficiency is improved. The time for waiting for data loading of the processor and the memory bandwidth occupation are reduced, the cache utilization rate is improved, the total delay of data processing is reduced, and the input / output path is shortened. Therefore, the technical problems of repeated data loading and frequent swap-in and swap-out of the cache caused by multiple serial calculations are solved, and the technical effect of improving the data processing efficiency and the throughput capacity is achieved.

A method for estimating latency in a network distributed system with at least one sensor, a control unit, and an actuator for actuating on a technical system includes (i) determining a sensor latency between the sensor and the control unit based on sensor time information, (ii) estimating an actuator latency between the control unit and the actuator, (iii) providing multiple control functions each concerning a different estimated total latency, wherein the estimated total latency includes the sensor latency, the actuator latency and a control latency, (iv) providing a latency correction term based on a comparison between the estimated total latency and a measured total latency, (v) calculating a corrected total latency by using (adding) the latency correction term, available at the time of the estimation, to the total latency, (vi) selecting and executing a control function from the multiple control functions for which the corrected total latency lies within a latency range of this control function and calculating a control input from the selected control function, (vii) transmitting the control input to the actuator via the network, and (viii) applying, by the actuator, the control input to the technical system.

The application discloses a dense false target generation method based on segmentation reconstruction, which is applied to an FPGA provided with an IIR filter, a feedback branch of the IIR filter is provided with a register, and a forward branch of the IIR filter is connected with a RAM, and the method comprises the following steps: saving signals collected by a DRFM into the RAM; according to a minimum segmentation length, signal segments at each moment are sequentially obtained from the DRFM, and after register delay and accumulation, corresponding accumulated values at each moment are obtained; after the obtained signal segments reach a given false target number M, signal segments before M moments at each moment are sequentially obtained from a starting position of the external RAM according to the minimum segmentation length, and the corresponding accumulated values at each moment are subtracted from corresponding signal segment data obtained from the external RAM, and the corresponding accumulated values at each moment are taken as data of signal segments at each moment of the dense false target signal. The application overcomes the problem that the segmentation reconstruction method consumes too much storage resource when the total delay length is large.

The application discloses a multi-user task offloading calculation method, system and device and a storage medium, belongs to the wireless communication technical field, and comprises the following steps: calculating the channel transmission rate of user task offloading to a small base station and the channel transmission rate of user task being forwarded to a macro base station through the small base station; calculating the transmission delay of user task offloading to the small base station and the transmission delay of user task being forwarded to the macro base station through the small base station according to the two channel transmission rates; calculating the processing delay of user task calculation at the small base station and the macro base station; inputting the two transmission delays and the two processing delays into a task offloading and calculation resource joint allocation model based on delay minimization which is constructed, and obtaining the optimal allocation scheme of MEC calculation resources in the small base station and the macro base station by solving; and based on the optimal allocation scheme, user task is offloaded to the small base station and the macro base station for calculation; the application reduces the total delay of user task processing through joint optimization of task offloading and calculation resource allocation.

The application provides a multi-task edge computing method for an Internet of Things, and belongs to the technical field of edge computing, and comprises the following steps: collecting task state information of to-be-processed tasks generated by a task collector of a monitoring area of the Internet of Things and a transmission queue and a computing queue reported by an edge server; inputting the task state information into an intelligent agent to output a scheduling decision of the to-be-processed tasks; determining a task that needs to be unloaded and a target server for unloading according to the scheduling decision, and creating a virtual task in a computing queue of the target server; determining an expected arrival order of the task that needs to be unloaded in the target server according to a generation time of the task that needs to be unloaded and a waiting time of the virtual task, calculating a total delay and a total energy consumption, updating the intelligent agent based on queue perception TD3, and obtaining an optimal scheduling decision. The application solves the problem that, in the prior art, the influence of transmission delay of task unloading between servers on the order of a computing queue is ignored, resulting in inaccurate task scheduling.

The present disclosure relates to INL detection and calibration for phase interpolators. An apparatus includes control logic coupled to a phase detector circuit and an adjustable delay circuit. The control logic is configured to obtain a state of a first phase of an output signal of a phase interpolator relative to a second phase of a reference signal, and adjust a delay of the reference signal until the second phase matches the first phase. The control logic is further configured to measure a total delay of the reference signal when the second phase matches the first phase, and determine an integral nonlinearity of the phase interpolator at a first code based on the total delay. The control logic can further calibrate the first code of the phase interpolator based at least in part on the integral nonlinearity.

The invention discloses a flexible job shop scheduling method oriented to date of delivery constraints. The method is oriented to date of delivery constraints, takes total tardiness and maximum completion time into account, establishes a model comprising process, machine and sequence constraints, and expresses scheduling as Markov decision; constructing a delivery time perception heterogeneous graph composed of process and machine nodes, and explicitly injecting semantics such as urgency degree, residual processing time, queue and predicted idle time in node and edge features by combining three relations of process sequence, process-machine feasibility and same-machine time sequence; tardiness perception graph attention network coding is adopted, a single actor-double commentator structure is matched, and a decision is made in a feasible action set through mask normalization and temperature sampling; the rewards and the event advance are aligned and calculated according to increments, and PPO + GAE is used for stable optimization in the training stage. The method is stable in performance in the aspects of reducing the total tardiness and controlling the maximum completion time, convergence is faster, good generalization is achieved, and the method is suitable for engineering deployment and online application.

The embodiment of the invention provides a TCP transmission implementation method and device, computing equipment and a storage medium. The transmission method comprises the steps that the duration of a TCP window switching timer is set as TCP end-to-end total delay; after the data sender sends the TCP packet, the data sender does not need to wait for an acknowledgement (ACK) of the data receiver to the sent TCP packet, and continues to send the TCP packet to be sent; when the duration that the data receiving party does not receive the TCP packet needing to be received reaches the duration of the TCP window switching timer, the data receiving party sends a NACK message to require retransmission of the TCP packet; and when the data sender receives the NACK message before the TCP window switching timer is overtime, the data sender sends the TCP packet required to be retransmitted by the NACK message. According to the TCP transmission technical scheme, TCP transmission is achieved on a deterministic network, the received TCP packet does not need to be confirmed through frequent ACK confirmation messages of a TCP layer, the influence of the frequent ACK confirmation messages on the network bandwidth and the CPU load is reduced, and the network transmission rate is increased.

The invention discloses a method and system for conducting self-adaptive sampling in SPI communication, and belongs to the field of digital communication.The method comprises the steps that an SPI host sends a reading command capable of reading parameters to an SPI slave, and when the last data bit of the reading command is sent, a starting identification signal is generated; a first MISO signal returned by the SPI slave is received, timing is started when the trigger edge of the start identification signal is detected based on the automatic detection module, timing is stopped when the first expected jump edge in the first MISO signal is detected, so that total delay time is obtained, and delay compensation time is calculated; and taking the original sampling edge delay compensation time of the SPI clock as an optimal sampling edge, and sampling a second MISO signal returned by the SPI slave when the optimal sampling edge is effective. According to the method, the received data sampling points can be automatically adjusted in different application scenes, the SPI communication rate and robustness are improved, the application range is wide, and portability is high.

The invention provides a low-delay high-definition panoramic multi-video stream fusion method and device and a medium, and belongs to the technical field of video transmission. The method comprises the following steps: collecting video data, extracting key frames through a semantic compression strategy, and maintaining a local data queue; constructing a transmission time delay model at an edge side, introducing a time delay deviation index to evaluate the transmission consistency of different video streams, constructing a decoding packet loss probability model, and establishing a relationship between a compression ratio and a packet loss probability; constructing an optimization problem aiming at minimizing the weighted sum of the total time delay and the time delay deviation, and combining the bandwidth resource constraint and the long-term packet loss rate constraint; the optimization problem is converted into a real-time optimization target; carrying out edge bandwidth resource allocation by adopting an SAC algorithm; and dynamically adjusting an end-side video compression ratio based on a bandwidth-oriented UCB algorithm, and dynamically selecting an adaptive scene according to an edge-side allocation bandwidth. According to the invention, the balance between low time delay and low packet loss is realized, and the stability and impression quality of panoramic multi-video stream fusion are improved.

A spatially unrolled time domain (TD) architecture that includes an input and weight register having i inputs and j weights, where i corresponds with a number of delay lines for i neurons, and j corresponds with a number of processing elements (PEs) for each delay line of the i delay lines. An enable control register sends a global input pulse to i neurons, and each delay line of the i delay lines includes the corresponding j PEs for that delay line. Each PE includes a digital-to-time converter (DTC) that accepts a digital input and weight and generates a relative delay, each time delay within a given delay line contributing to an overall delay for the given delay line. i time-to-digital converters (TDCs). A readout register receives digital outputs from each of the i TDCs, and serially outputs a signal from each of the i delay lines based on the overall time delay for each of the i delay lines.

The invention relates to a burr filtering circuit with equal rising edge and falling edge transmission delays, and belongs to the technical field of circuits. According to the burr filtering circuit, two stages of delay circuits are connected in series, and related parameters of the first-stage delay circuit and the second-stage delay circuit are the same, so that no matter whether an input signal is changed from low to high (rising edge) or from high to low (falling edge), the total delay is not changed and is equal to the sum of discharge time and charge time of RC circuits in the two stages of delay circuits. In addition, the original duty ratio of the input signal can be ensured while the burr signal is filtered out. In addition, the burr filtering circuit can also avoid output signal mistaken overturning caused by power supply voltage jump.