### Apache Airflow version

main (development)

### What happened

Airflow has `job_heartbeat_sec` (default 5) that was updated to 50 seconds in our environment. This caused 2 instances of triggerer process running for HA to keep updating triggerer_id since below query takes current time minus 30 seconds to query against the latest_heartbeat. This causes alive_triggerer_ids to return empty list since job_heartbeat_sec is more than 50 seconds and the current trigger running this query assigns the triggers to itself. This keeps happening moving triggers from one instance to another.

https://github.com/apache/airflow/blob/62a534dbc7fa8ddb4c249ade85c558b64d1630dd/airflow/models/trigger.py#L216-L223

### What you think should happen instead

The heartbeat calculation should have a value based on job_heartbeat_sec rather than 30 seconds hardcoded so that queries to check triggerer processes alive are adjusted as per user settings.

### How to reproduce

1. Change job_heartbeat_sec to 50 in airflow.cfg
2. Run 2 instances of triggerer.
3. Make an operator that uses `FileTrigger` with the file being absent or any other long running task.
4. Check triggerer_id for the trigger which keeps changing. 

### Operating System

Ubuntu

### Versions of Apache Airflow Providers

_No response_

### Deployment

Virtualenv installation

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""
        Alternative constructor that creates a trigger row based directly
        off of a Trigger object.
        """
        classpath, kwargs = trigger.serialize()
        return cls(classpath=classpath, kwargs=kwargs)
    @classmethod
    @internal_api_call
    @provide_session
    def bulk_fetch(cls, ids: Iterable[int], session: Session = NEW_SESSION) -> dict[int, Trigger]:
        """
        Fetches all the Triggers by ID and returns a dict mapping
        ID -> Trigger instance.
        """
        query = (
            session.query(cls)
            .filter(cls.id.in_(ids))
            .options(
                joinedload("task_instance"),
                joinedload("task_instance.trigger"),
                joinedload("task_instance.trigger.triggerer_job"),
            )
        )
        return {obj.id: obj for obj in query}
    @classmethod
    @internal_api_call
    @provide_session
    def clean_unused(cls, session: Session = NEW_SESSION) -> None: